Ebook Cancer epidemiology and prevention (4/E): Part 2

(BQ) Part 2 book “Cancer epidemiology and prevention” has contents: Stomach cancer, small intestine cancer, biliary tract cancer, liver cancer, hodgkin lymphoma, multiple myeloma, bone cancers, soft tissue sarcoma, endometrial cancer, ovarian cancer, bladder cancer,… and other contents.

 593 31 Stomach Cancer CATHERINE DE MARTEL AND JULIE PARSONNET OVERVIEW Stomach cancer is the fifth most common incident cancer worldwide and the third leading cause of cancer death Almost half of the world’s cases occur in Asia, with 42% in China alone Although the incidence and mortality from stomach cancer are decreasing, global disease burden remains high Moreover, the absolute number of cases continues to rise because of population aging Adenocarcinomas comprise over 90% of gastric malignancies The adenocarcinomas are further classified according to anatomic location (cardia vs non-​cardia), histology (e.g., intestinal or diffuse, signet ring or non-​signet ring) and most recently by molecular classification Adenocarcinomas in the stomach’s body and antrum are usually caused by chronic infection with Helicobacter pylori (H pylori); the incidence of these tumors is decreasing worldwide Cardia tumors have epidemiological characteristics more similar to those of esophageal adenocarcinoma; the incidence of these tumors is increasing, particularly in high-​income, Western countries New molecular classification systems have been proposed based on investigations of tumors in high-​income countries The Cancer Genome Atlas Program has identified four molecular subtypes: (1) tumors positive for Epstein-​Barr virus; (2) those marked by microsatellite instability; (3) genomically stable tumors; and (4) tumors with chromosomal instability and extensive somatic copy-​ number aberrations These subtypes have not yet been integrated into etiologic and descriptive studies The most promising public health strategy for preventing gastric cancer is the eradication of H pylori with antibiotics This approach is currently being tested in randomized clinical trials INTRODUCTION At the dawn of the twentieth century, stomach cancer represented an astonishing one-​third of all cancers, approximately 1% of hospital admissions, and 2% of all deaths investigated by necropsy (Fenwick and Fenwick, 1903) Although stomach cancer remained the leading cause of cancer death in the world until the mid-​twentieth century, overall, the rapid decline in stomach cancer throughout the last 100 years has been touted as an “unplanned triumph” (Howson et al., 1986) The term “unplanned” highlights the lack of directed intervention in preventing this disease; rather, stomach cancer’s decline parallels the improvements in nutrition, sanitation, and hygiene in the twentieth century This steady decrease in incidence over time provides insights into stomach cancer etiology, as well as directions for the ultimate elimination of stomach cancer as an important health problem worldwide Over 90% of stomach cancer cases are adenocarcinomas arising from the gastric glands (Coleman et  al., 1993; World Health Organization [WHO], 2010) Other histologic types of epithelial stomach cancer include adenosquamous carcinoma, carcinoma with lymphoid stroma (i.e., medullary carcinoma), hepatoid carcinoma, squamous cell carcinoma, and the small group of neuroendocrine neoplasms (WHO, 2010) Gastric cancers of non-​epithelial origin include lymphomas and mesenchymal tumors, such as leiomyoma, schwannoma, and Kaposi sarcoma in immunosuppressed patients (WHO, 2010) Secondary tumors are rare, the stomach being one of the five least common metastatic sites (Disibio and French, 2008) Because they represent the vast majority of gastric tumors, this chapter focuses on adenocarcinomas of the stomach, including cancers of both the gastric cardia (ICD-​O code 16.0) and non-​cardia (ICD-​O codes C16.1–​C16.6) (WHO, 2013) DISEASE BURDEN According to GLOBOCAN, an estimated 952,000 new cases of gastric cancer occurred worldwide in 2012 (Ferlay et al., 2013), making it the fifth most common cause of cancer worldwide (6.8% of all cancers) More than 70% of cases (677,000) occurred in less developed countries, with 553,000 cases occurring in Eastern Asia, and nearly half of the total number (405,000 cases or 42.5% of the total) in China alone Global incidence and death rates are shown in Figures 31–​1a and 31–​1b Europe contributed nearly 15% of the global burden (140,000 cases), and Latin America contributed a further 6% (61,000 cases) (Ferlay et al., 2013) Eastern Europe and the Andes are areas with particularly high risk In the United States, the American Cancer Society predicts that 26,370 new cases of stomach cancer (16,480 in men and 9890 in women) will be diagnosed in 2016 with 10,730 deaths (6540 men and 4190 women) (American Cancer Society, 2016) This places stomach cancer as the 15th most common malignancy, in terms of both incidence and mortality, in the United States Survival rates for stomach cancer are generally poor A  recent international comparison of survival in 279 population-​based cancer registries in 67 countries (Allemani et  al., 2015)  shows that the 5-​ year age standardized net survival from stomach cancer (i.e., the proportion of cancer patients who survive 5  years, after eliminating the background mortality due to other causes) ranges from 15% to 35% for adults Survival is considerably higher in Japan and South Korea (50%–​60%), where systematic screening allows the early detection and surgical treatment of tumors It is not known how much of the improvement in survival in these countries represents lead-​time bias, however Some studies suggest a 30%–​ 60% reduction in mortality with screening (Hamashima et al., 2013; Hamashima et al., 2015) The slope of improvement in mortality has remained relatively constant since the early 1970s, prior to the onset of widespread endoscopic and radiographic screening programs (Whitlock, 2012) Because of its high case-​fatality, gastric cancer accounts for a larger fraction of cancer deaths than incident cases globally (8.8% versus 6.8%) Despite its declining incidence, gastric cancer remains the third leading cause of cancer death worldwide (723,000 deaths estimated per annum), after lung and liver cancers (American Cancer Society, 2016; Ferlay et  al., 2013) The preceding estimates represent the figures for adenocarcinoma, the most common histological type of gastric cancer The worldwide total number of lymphomas of gastric origin in 2012 was estimated to be 18,000, or less than 2% the number of adenocarcinomas (Plummer et al., 2016) Other gastric histologic types are even less common CLASSIFICATION Epidemiologic studies over the last 50  years have classified gastric cancers according to several systems, beginning with histopathology 593 594 594 PART IV:  Cancers by Tissue of Origin > 15.4 9.7–15.4 6.6–9.7 4–6.6 13 7.2–13 5.5–7.2 3.6–5.5 < 3.6 No Data Not applicable Figure 31–​1b.  Estimated worldwide stomach cancer mortality rates per 100,000 in men for the year 2012 Source: GLOBOCAN 2012, IARC, WHO in the mid-​1960s, followed by anatomic location in the early 1990s Molecular classification systems have recently been proposed but have not yet been integrated into epidemiologic studies, nor are molecular markers available at this point from population-​ based tumor registries Gastric Anatomy and Function Grossly, the stomach has four anatomical regions: the cardia, the fundus, the body, and the pylorus, as shown in Figure 31–​2 The gastric cardia (also known as the gastroesophageal [GE] or esophagogastric junction [WHO,  2010]) is a narrow circular band, 1.5–​3  cm wide, located at the junction where the tubular esophagus joins the stomach The cardia’s proximal border can usually be seen on endoscopy, but the distal boundary is poorly defined (WHO, 2010) The fundus and body, the sections of the stomach that secrete acid, comprise the majority of the stomach The pylorus is the section of the stomach that transitions from stomach to the small bowel; the proximal portion of the pylorus located within the stomach and before the pyloric sphincter is known as the antrum All areas of the stomach are covered with mucus-​secreting foveolar and columnar epithelial cells lining the luminal surfaces and invaginations called gastric pits Midway down the pits are the gastric stem cells; at the base of the pits are the glands Secretory glands in the  59 595 Stomach Cancer CIN • Intestinal histology • TP53 mutation • RTK-RAS activation Cardia GE Junction Fundus EBV Body Pylorus • PIK3CA mutation • PD-L1/2 overexpression • EBV-CIMP • CDKN2A silencing • Immune cell signaling Antrum MSI • Hypermutation • Gastric-CIMP • MLH1 silencing • Mitotic pathways GS • Diffuse histology • CDH1, RHOA mutations • CLDN18–ARHGAP fusion • Cell adhesion Figure 31–​2.  Cancer Genome Atlas: key features of the four tumor types by gastric site MSI = microsatellite instability; EBV = Epstein Barr virus; CIN = chromosomal instability; GS = genomically stable Source: The Cancer Genome Atlas Research Network, Comprehensive molecular characterization of gastric adenocarcinoma Adapted from Nature 2014;513(7517):202–​209 body and fundus of the stomach produce hydrochloric acid and intrinsic factor (parietal cells), serotonin (enteroendocrine or Kulchitsky cells), and pepsinogen, leptin, and lipase (chief cells) Enteroendocrine cells in the gastric antrum secrete gastrin (G cells) and somatostatin (D cells) Cardiac and pyloric glands have neither parietal nor chief cells and largely secrete mucus The length of the cardiac mucosa increases with age and with central obesity, often developing histopathological signs of moderate to severe inflammation (Derakhshan et  al., 2015; Miao et al., 2014) When H. pylori infection occurs, it typically starts in the pylorus, extending to the body and fundus over time, causing infiltration of the mucosa with inflammatory cells—​a condition known as chronic, active gastritis (Correa and Piazuelo, 2008) Anatomic Subtypes In the United States, overall rates of stomach cancer have continued to decline over the last three decades from an age-​standardized rate of 11.7 per 100,000 in 1975 to 6.7 per 100,000 in 2013 However, in the 1990s, investigators noted strikingly different epidemiologic trends in the incidence rate of cardia versus non-​cardia tumors: gastric cardia cancer increased continuously beginning in the mid-​1970s, whereas the incidence of non-​cardia cancers sharply declined (Blot et al., 1993; Henson et al., 2004; Levi et al., 1990; Powell and McConkey, 1992; Wu et al., 2009) Since 1990, however, the age-​standardized incidence rate of cardia cancer—​unlike adenocarcinoma of the esophagus—​seems to have stabilized in the United States at approximately 2.1 per 100,000 (Figure 31–​3; Wu et al., 2009) In contrast, the incidence rate of non-​cardia cancer in the overall population has decreased progressively to 4.1 per 100,000, although incidence remains higher among Asians, blacks, and Hispanic whites (Devesa et al., 1998) Similar trends have been reported worldwide In some countries of Europe and the Americas, the incidence of cardia cancers now approximates or exceeds that of non-​cardia cancer among men (Derakhshan et al., 2016; WHO, 2010) Although the differentiation of anatomical subsite of gastric cancers has improved over time (Camargo et  al., 2011a), it can be difficult to determine the origin of large tumors that bridge the lower esophagus and upper stomach (Misumi et  al., 1989)  or that arise in the poorly defined distal boundary of the gastric cardia As of 2016, tumors registered with overlapping (ICD-​O C16.8) or unspecified (C16.9) anatomical subsites constitute nearly half (40%–​50%) of all stomach cancers in Japan, Korea, and the United States; 50%–​60% in the United Kingdom, Italy, and Australia; and up to 90% in Brazil (Machii and Saika, 2016) Histologic Subtypes As noted earlier, over 90% of stomach cancer cases are adenocarcinomas arising from the gastric glands (Coleman et al., 1993; WHO, 2010) Several histologic classification systems have been proposed for gastric adenocarcinoma Among these, the Laurén system has been the most influential Laurén Classification Described by Pekka Laurén in 1965, the Laurén classification divides gastric cancer into two histological types:  intestinal and diffuse (Laurén, 1965; Nevalainen, 2013) Intestinal-​type cancers form recognizable glands, whereas diffuse adenocarcinomas consist of poorly cohesive cells that infiltrate diffusely into the gastric wall with little or no gland formation (WHO, 2010) These two types are usually easy to distinguish under the microscope Moreover, since intestinal and diffuse tumors differ in their clinical, epidemiologic, and etiologic characteristics, the Laurén classification provides a useful framework for understanding pathology, epidemiology, and clinical treatment Because many of the seminal epidemiologic and clinical investigations of gastric adenocarcinoma have employed the Laurén classification 596 596 PART IV:  Cancers by Tissue of Origin Rate per 100,000 person-years 10 Diffuse 10 Intestinal 10 1 0.1 0.1 0.1 Other Types Anatomic site Cardia Specified Non-Cardia Overlapping and Non-Specified 0.01 0.01 0.01 1980 1990 2000 1980 1990 2000 Year of diagnosis 1980 1990 2000 Figure 31–​3.  Trends in stomach carcinoma incidence by histologic type and anatomic site (SEER 1978–​1983 to 2001–​2005) Source: Wu H et al., Cancer Epidemiol Biomarkers Prev 2009;18:1945–​1952 system, the terms “intestinal” and “diffuse” will be used frequently throughout this chapter The intestinal subtype historically represented the majority of gastric adenocarcinomas worldwide, and the decrease in this subtype has been the major contributor to the overall decline in stomach cancer (Figure 31–​3) In contrast to the decreasing incidence rate of the intestinal subtype, the incidence of diffuse gastric cancers has increased by over 400% (Henson et  al., 2004) Consequently, the proportion of gastric cancers contributed by the two subtypes has changed dramatically over time In the early 1970s, intestinal-​ type cancers represented over 90% of gastric adenocarcinomas in the United States; by 2000, this proportion had decreased by 50% Similar trends have been reported in Europe (Laurén and Nevalainen, 1993), Latin America (Rampazzo et  al., 2012), and Asia (Hajmanoochehri et al., 2013; Kaneko and Yoshimura, 2001), although one study from Sweden showed decreases in both tumor types (Ekstrom et al., 2000a) The Laurén classification has also proven useful in evaluating the natural history of gastric cancer and temporal trends in cancer incidence and precursor lesions, as discussed in the following (Lewin and Appelman, 1995; WHO, 2010) Perhaps because of its increased complexity, the WHO classification has been used less frequently in epidemiologic studies than the Laurén system Among the intestinal-​type tumors, tubular carcinomas are the most common, accounting for 56% of stomach tumors in some studies (Terada, 2016) Papillary carcinomas (13% of tumors) tend to occur in the proximal part of the stomach and to be more aggressive than other histologic types, with higher likelihood of metastasis and mortality Table 31–​1.  Comparison of Laurén and WHO Gastric Adenocarcinoma Classifications Laurén Classification Intestinal type Papillary adenocarcinoma Tubular adenocarcinoma Mucinous adenocarcinoma Diffuse type Signet ring cell carcinoma Other poorly cohesive carcinoma Not classified Rare adenocarcinomas including: Hepatoid adenocarcinoma Oncocytic adenocarcinoma Paneth cell carcinoma Gastric carcinoma with lymphoid stroma and others WHO Histologic Classification In 2010, the WHO devised a more granular classification for gastric cancer (Hu et al., 2012; WHO, 2010) (Table 31–​1) The intent of this new classification was to harmonize the histological typing of gastric cancers with that used for cancers of the small and large intestine WHO Classification (Hu et al., 2012)  597 Stomach Cancer Mucinous adenocarcinomas comprise approximately 10% of gastric adenocarcinomas, and can have features of both intestinal and diffuse-​ type malignancies Signet ring cell and other poorly cohesive carcinomas comprise the majority of diffuse types and tend to be highly invasive In their early stage, hereditary gastric malignancies usually manifest themselves as patchy intramucosal distributions of signet ring cells (Hu et al., 2012) Molecular Classifications In 2014, the Cancer Genome Atlas program (TCGA) tested 295 gastric cancer samples with array-​based analyses of somatic copy number, whole-​ exome sequencing, array-​ based DNA methylation profiling, messenger RNA sequencing, microRNA sequencing, reverse-​phase protein array, microsatellite instability testing, and, on a subset, low-​ pass whole genome sequencing (The Cancer Genome Atlas [TCGA] Research Network, 2014) These methods identified four molecular subtypes of gastric cancer: (1) tumors positive for Epstein-​Barr virus (EBV); (2) tumors marked by microsatellite instability (MSI); (3) genomically stable tumors (GS); and (4) tumors with chromosomal instability (CIN), characterized by the presence of extensive somatic copy-​ number aberrations (The Cancer Genome Atlas Research Network, 2014) (Figure 31–​2) The last of these subtypes comprised approximately half of the tested tumors, whereas the EBV tumors represented less than 10% Although TCGA found no prognostic significance associated with these categories in their small data set, they did identify statistical associations with gender (men were more likely to have EBV-​related tumors), anatomic subsite (CIN more likely in the cardia and EBV more likely in the body), Laurén classification (75% of GS were diffuse-​type), and age (GS tumors occurred at younger ages and MSI, older) Four subtypes with different nomenclature were also identified by the Asian Cancer Research Group (ACRG), based on gene expression profiles, and later were confirmed using the three other cohorts, including TCGA (Cristescu et al., 2015) These subtypes were labeled microsatellite instability (MSI), microsatellite stable-​epithelial to mesenchymal transition (MSS/​EMT), MSS/​tumor protein 53 (TP53) positive, and MSS/​TP53 negative Unlike the TCGA subtypes, the ACRG subtypes were clearly linked to prognosis Recurrence and survival were worst for the MSS/​EMT tumors, which typically displayed loss of e-​cadherin (CDH1) expression and diffuse, signet ring histopathology Prognosis was best for MSI tumors Other studies have categorized tumors based on mutations of single genes For example, germline mutations in CDH1 account for most familial gastric cancers More recently, tumors of the cardia and the gastroesophageal junction have been classified based on overexpression of the human epidermal growth factor (HER-​2) receptor (Gravalos and Jimeno, 2008) Because these more aggressive tumors may respond favorably to monoclonal antibody treatments, expression of HER-​2 may prove to be useful as a clinical marker (Bang et al., 2010) TUMOR GRADE AND STAGE The grading of gastric adenocarcinoma is based on the degree of differentiation (WHO, 2010) Well-​differentiated tumors have well-​ formed glands that often resemble metaplastic intestinal epithelium, whereas poorly differentiated tumors are composed of highly irregular glands that are recognized with difficulty, or single cells that remain isolated or are arranged in small or large clusters Moderately differentiated tumors display patterns intermediate between well and poorly differentiated TNM Staging The system most often used to stage stomach cancers in the United States is the American Joint Commission on Cancer (AJCC) TNM system The TNM staging considers the size and the extent of the primary 597 tumor (T), the involvement of regional lymph nodes (N), and presence or absence of distant metastasis (M) (Washington, 2010) The staging system used by the SEER program classifies cancer cases into three categories: localized, regional, and distant In the United States, 27% of stomach cancer cases reported to SEER registries between 2006 and 2012 were diagnosed when localized, 28% were regional, and 35% were distant The remaining 10% were classified as unknown stage at diagnosis (Howlader et al., 2015) Other classification systems for stomach cancer make the distinction between early disease (i.e., invasive cancer not extending beyond the submucosa) and advanced disease (i.e., invasion of the muscularis or beyond) This approach is commonly used in countries that employ routine endoscopic screening for gastric cancer PRECANCEROUS OR PRECURSOR LESIONS For nearly a century, it has been known that gastric cancers with the intestinal-​type histology typically originate from mucosa affected by chronic gastritis (Hartfall, 1936) It was not until the advent of modern endoscopy, however, that serial inspection of unautolyzed specimens clarified the temporal sequence of preneoplastic histopathology For intestinal-​type tumors, the neoplastic cascade begins with chronic gastritis, an inflammatory condition in which both acute and chronic inflammatory cells invade the mucosa, and mucosal cell turnover is accelerated In a subset of people, the chronic gastritis progresses to chronic atrophic gastritis with loss of gastric glands and diminished ability to produce gastric acid As the atrophic gastritis progresses to involve large areas of the stomach, the mucosa may develop islands of intestinal metaplasia in which the gastric mucosa recapitulates the morphologic appearance of intestinal mucosa These metaplastic zones can have different histologic morphologies termed “complete” (type I) or “incomplete” (types II and III), as discussed later, and can eventually extend to involve much of the stomach After many years, the mucosa in a subset of individuals progresses to low-​and then high-​ grade gastric epithelial dysplasia and ultimately to early and then invasive intestinal-​type cancer Preneoplasia Correa and colleagues (Correa, 2002; Correa et al., 1976; Correa and Yardley, 1992) have proposed a multistep premalignant process for the intestinal-​type gastric carcinoma, involving a sequence of histopathological changes in the mucosa from normal to non-​atrophic gastritis, multifocal atrophic gastritis, intestinal metaplasia, and dysplasia In high-​risk populations, chronic gastritis predominantly affects the antrum and is associated with multifocal atrophic gastritis and gland loss (Correa, 2002) The metaplastic process tends to begin at the antrum-​corpus junction, then enlarge and extend to the antrum and/​ or the corpus A patchy distribution of dysplastic foci may eventually appear within the area of intestinal metaplasia As mentioned, the two main types of intestinal metaplasia are “complete” (also called small intestinal type or type I) and “incomplete” (also called colonic type or types II and III) The epithelium in the complete type resembles the small intestinal phenotype, small intestine digestive enzymes are present, and only sialomucins are expressed In incomplete metaplasia, small intestine digestive enzymes are absent or only partially expressed, the epithelium resembles the colonic phenotype, and sulfomucins are expressed, either in combination with (type II) or without (type III) sialomucins (Camargo et  al., 2011a) Incomplete metaplasia is frequently associated with frank dysplasia and early carcinoma Controversies still exist regarding the utility of subtyping intestinal metaplasia as a marker of stomach cancer risk However, the results from prospective cohorts suggest that complete intestinal metaplasia occurs first and may transform over time into incomplete metaplasia, which has a much higher risk of malignant transformation (Camargo et al., 2014) Furthermore, the great majority of individuals with intestinal-​type gastric cancer have some evidence of metaplasia in surrounding tissue (Lauwers and Srivastava, 2007) 598 598 PART IV:  Cancers by Tissue of Origin Dysplasia (also called intraepithelial neoplasia), which arises in either native gastric or intestinalized gastric epithelia, is characterized by partial or complete loss of differentiation (IARC, 2010) The magnitude of risk of cancer for each of these precursor stages is difficult to measure, due to their patchy distribution, inconsistent terminology among pathologists, and the challenge of performing repeated endoscopy in large cohort studies To rectify some of these problems, several groups (e.g., Padova International Classification, Vienna classification, Paris endoscopic classification) (Rugge et al., 2000; Schlemper et al., 2000; The Paris Classification, 2003) have tried to eliminate inconsistencies and semantic misunderstandings across countries—​especially between Japan and Europe/​North America—​regarding the terminology for preneoplastic lesions and early invasive cancers (IARC, 2010; Stolte, 2003) Despite differences in nomenclature, however, it is clear that each step increases risk, even though only a minority of cases ultimately progress from preneoplasia to invasive cancer In a nationwide cohort study in the Netherlands, the annual incidence of gastric cancer was 0.10% for patients whose most severe premalignant lesion was chronic atrophic gastritis, 0.25% for those with intestinal metaplasia, 0.60% for those with mild-​to-​moderate dysplasia, and 6.0% for those with severe dysplasia (de Vries et al., 2008) A large study from China demonstrated a similar magnitude of increasing risk with advancing precancerous conditions: < 0.1% patients with atrophy gastritis, 2.7% with deep intestinal metaplasia, and 7% with moderate or severe dysplasia developed cancer over years (Camargo et al., 2011a) More recently, data from a low-​risk Swedish cohort of over 400,000 people indicated that, over 20 years, one of 256 individuals with normal gastric mucosa would develop cancer (standardized incidence ratio [SIR] = 1.0) compared to in 85 for gastritis (SIR = 1.8), in 50 for atrophic gastritis (SIR = 2.8), in 39 for intestinal metaplasia (SIR = 3.4), and in 19 for dysplasia (SIR = 6.5) (Song et al., 2015) Precursor lesions can be identified via endoscopy or by using serum markers for chronic atrophic gastritis Because gastric glands, and the chief cells in the glands, can be destroyed in atrophic gastritis, biomarkers for proteins produced by chief cells have been used to detect this damage The most studied of these proteins are pepsinogens I and II Both low pepsinogen I and a low ratio of pepsinogen I to pepsinogen II have been used clinically (Charvat et al., 2016; Yamaguchi et al., 2016), although the sensitivity and specificity for the detection of atrophic gastritis are modest (approximately 65% and 85%, respectively) (Huang et al., 2015) Given the low incidence of gastric cancer and its precursors, pepsinogen screening is not recommended in the United States or other low-​incidence countries due to the low predictive power of positive tests (PDQ® Screening and Prevention Editorial Board, 2016) No precursor lesions have yet been identified for diffuse cancer or the rarer subtypes of adenocarcinoma Chemotactism BMDC recruitment NFκB TNFα/SDF1 In 1975, Pelayo Correa proposed a model for intestinal-​type gastric carcinogenesis positing that gastric cancer arose from chronic gastritis and that subsequent steps in tumor progression were caused by other exposures or cofactors (Correa et  al., 1975) With the discovery of H. pylori in the 1980s and subsequent research confirming its central role in causing chronic gastritis, Correa revised his model to incorporate H. pylori infection as the initiating step in carcinogenesis (Correa, 2004) In this model, dietary factors—​including salt-​preserved foods, high fats, high nitrates, and decreased fruits and vegetables—​fostered subsequent tumor progression Bacterial overgrowth in the hypochlorhydric stomach was also thought to contribute to mutation and mucosal changes by inducing the formation of carcinogenic N-​nitroso compounds and free radicals Some of the stages of the Correa model have been confirmed experimentally, notably the role for salts in magnifying damage in H. pylori–​infected stomachs (D’Elia et al., 2014; Gaddy et  al., 2013) Molecular aspects of this model of tumor progression are also being elucidated For example, metaplasia associated with gastric overproduction of a trefoil protein normally found in the intestine (spasmolytic polypeptide) is a particularly strong marker for cancer risk A different model of tumor progression was proposed by Houghton et al (2004) These researchers showed experimentally that H. pylori–​ related tumors of the stomach derive from bone marrow–​derived stem cells, rather than resident peripheral stem cells or mucosal cells The bone marrow–​derived stem cells are recruited to the stomach by the chronic inflammatory process, fuse with gastric epithelial cells, and then replicate, regenerating the mucosal surface and replacing the original stem cells that were destroyed by chronic gastritis (Bessede et al., 2015) (Figure 31–​4) As with the Correa model, chronic inflammation due to H. pylori infection is the dominant factor in the carcinogenic process Some studies suggest that precursor lesions can be reversed or their progression aborted by eradication of Helicobacter pylori infection (Fukase et  al., 2008) Thus, several international guidelines recommend H.  pylori eradication for those with precancerous conditions and even early gastric cancer The latter are thought to be true malignancies that have not yet invaded the muscularis They can be cured by the combination of surgical excision and H.  pylori eradication (Malfertheiner et al., 2012; Rollan et al., 2014) No analogous tumor progression model has yet been identified for sporadic diffuse gastric cancers However, genome-​wide analysis studies (GWAS) have identified several germline mutations associated with hereditary diffuse gastric cancer (HDGC) Here, the initial stages of carcinogenesis are postulated to begin with germline GFP+BMDC Chronic infection with H pylori Inflammation and epithelial damages TUMOR PROGRESSION MODELS Homing and differentiation cell/cell fusion CD44 EMT affecting EMT confering differentiation CSC properties Altered Dysplasia during differentiation regenerative Composed at 22% of BMDC /metaplasia hyperplasia Composed of CD44+ cells with CSC properties Emergence of CD44high CSC and carcinoma Figure 31–​4.  Stem cell model of gastric carcinogenesis EMT = epithelial-​mesenchymal transition; CSC = cancer stem cells; BMDC = bone marrow-​derived cells Source: Bessede E et al., Helicobacter pylori infection and stem cells at the origin of gastric cancer Oncogene 2015;34(20):2547–​2555  59 Stomach Cancer mutations—​frameshifts, point mutations, or deletions—​that typically affect one of two genes:  CDH1 or, less commonly, CTNNA1 (alpha e-​catenin) (Caldas et  al., 1999; Majewski et  al., 2013) The loss of function of the second allele in HDGC patients—​either due to loss of heterozygosity or promoter hypermethylation—​may then lead to gastric cancer (Grady et al., 2000; Majewski et al., 2013) SURVIVAL Survival among patients with stomach cancer is still among the lowest of all cancer sites in most regions of the world (Allemani et al., 2015) Only cancers of the lung, liver, and pancreas have worse survival Five-​year net survival from stomach cancer diagnosed between 2005 and 2009 is generally in the range of 25% to 30% Five-​year relative survival is slightly better in some Western countries (i.e., up to 33% in Belgium and Austria) and in China (31%) and substantially better in Japan and Korea (58% and 54%, respectively) The success in these latter countries is due to the larger proportion of early-​stage, curable cancers diagnosed through the intensive screening for stomach cancer in these countries Between the periods 1995–​1999 and 2005–​2009, survival statistics have shown very large increases in South Korea (33% to 58%) and China (15% to 31%), but relative survival rose by less than 10% in most other locations (Allemani et al., 2015) Diagnosis at an early stage is critical for survival In stomach cancer patients in the United States diagnosed between 1992 and 1998, the overall relative survival at 5 years for all disease stages combined was 22% (Jemal et al., 2003) Stage-​specific survival was the highest for localized disease (59%), followed by regional disease (22%), and lowest for distant disease (2%) (Jemal et al., 2003) Between 2006 and 2012, the overall relative survival improved slightly to 30% Stage-​ specific survival had also improved since 1992–​1998, with 67%, 31%, and 5% observed for localized, regional, and distant disease, respectively (American Cancer Society, 2016) Survival is lower for patients with cancer of the cardia than for non-​cardia cancers, even in early stage disease (Amini et al., 2015) DESCRIPTIVE EPIDEMIOLOGY Traditionally, descriptive analyses of stomach cancer have classified gastric tumors as either a single entity or as cardia versus non-​cardia cancers Mortality data not capture either the anatomic location or the histologic characteristics of the tumor Even when tumors are subclassified as cardia or non-​cardia, tumor registration does not currently capture the heterogeneity that particularly affects cardia cancers These are thought to represent a mix of at least two etiologies: the first involves severe atrophic gastritis due to H. pylori, similar to the pathway for non-​cardia cancers; the second is thought to result from a transformation of squamous to columnar metaplasia due to the reflux of gastric contents, similar to the development of esophageal adenocarcinoma (Derakhshan et  al., 2008; Miao et  al., 2014) The former predominates in high-​risk populations where chronic infection is still common, such as Northwest Iran and central China The latter predominates in Western countries where central obesity and esophageal adenocarcinoma are common (Derakhshan et al., 2015) Cardia and non-​cardia cancers differ in their demographic, geographical, and temporal distributions The extent of these differences depends on the mix of the two etiologies of cardia cancer (H. pylori–​ related versus reflux-​related) in a given area We describe in the following the epidemiological features of the most frequent non-​cardia subsite, and highlight the differences with the cardia subsite at the end of each paragraph, when necessary Demographic Characteristics Stomach cancer is extremely rare before the age of 30 After this age, the age-​specific incidence rate of all subsites combined increases slowly until the age of 50 and then increases more sharply, with the highest incidence seen in the oldest age groups In the United 599 States, the median age at diagnosis is 69 for both sexes (Derakhshan et al., 2009; Sipponen and Correa, 2002) At all ages, men are twice as likely as women to develop non-​cardia stomach cancer and four times as likely to develop cardia cancer Interestingly, the male-​to-​ female ratio varies across countries, and is reported to be only 1.5 in Sub-​Saharan Africa This variation probably reflects differences in the prevalence of the main etiologic factors for cardia cancer, as mentioned earlier (Colquhoun et  al., 2015) Within each gender, African Americans and Asian Pacific Islanders have twice the incidence rate of overall stomach cancer than non-​Hispanic whites (Colquhoun et al., 2015) Within any country or population, non-​cardia gastric cancer is most often seen in lower socioeconomic groups and has been associated with risk factors that correlate with lower socioeconomic status (SES; i.e., lower income, educational level, and occupational standing, greater number of siblings, and crowding) These factors also correlate with H. pylori infection A large European multicenter study reported that adjustment for H. pylori infection eliminated the association between lower SES and non-​cardia gastric cancer (Nagel et al., 2007) Other factors, such as fruit and vegetable consumption, cigarette smoking, and physical activity, may also confound any observed association with SES Notably, although higher SES is inversely associated with non-​cardia gastric cancer, it is strongly associated with cardia gastric cancer and esophageal adenocarcinoma, especially in the middle-​and high-​income countries Geographic Variation A global map of male age-​ standardized incidence rates from GLOBOCAN 2012 shows that the highest rates of stomach cancers occur in Eastern and Southeastern Asia, Eastern Europe, and parts of Central and South America The map of female incidence rates is nearly identical except that, in any given country, the rates in women are approximately half those in men Internationally, the incidence of stomach cancer varies approximately 10-​fold among men, from more than 60 per 100,000 in Korea to less than per 100,000 in the United States, Sweden, or Kuwait (Forman et al., 2013) The extremely high incidence rates among men in Korea (62 per 100,000) and Japan (46 per 100,000) may partly reflect the intensive endoscopic surveillance conducted in these countries Screening detects even very small lesions that might not otherwise progress or be diagnosed Even excluding Korea and Japan, however, a four-​fold variation in male incidence persists, with rates over 20 per 100,000 in Belarus, Lithuania, the Russian Federation, and Costa Rica Within Europe, there is considerable variation between the countries at highest risk (generally in Eastern Europe) and those with the lowest risk (in Scandinavia, Switzerland, and the United Kingdom) In the United States, the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program (SEER), estimates a national standardized incidence rate for stomach cancers using nine population-​ based cancer registries (San Francisco–​Oakland, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle–​Puget Sound, Utah, and Atlanta) For the period 2008–​2012, annual incidence rates per 100,000 were 10.1 for men and 5.3 for women, for all races combined Age-​ standardized incidence rates per 100,000 were higher in blacks than in whites for both men (14.6 vs 9.2) and women (8.4 vs 4.5) (Howlader et al., 2015) In individual registries, age-​standardized incidence rates for white men range from 5.4 per 100,000 in Utah to 11.7 in Los Angeles, and those for white women range from 2.4 per 100,000 in Hawaii to 6.9 in Los Angeles Incidence rates of stomach cancer for black men range from 11.5 per 100,000 in Greater California to 19.1 in Louisiana, and for black women from 6.2 per 100,000 in Kentucky to 10.5 in Connecticut Male rates are approximately two-​fold higher than female rates across the registries for both blacks and whites On average, among the 18 SEER registries during the period 2008–​2012, black males had the highest incidence (14.6 per 100,000) followed by Asian or Pacific Islanders (14.5), Hispanic (14.2), American Indian/​ Alaska Native (12.3), and white men (9.2) Female rates showed a similar pattern, with the highest incidence among Asian or Pacific 60 600 PART IV:  Cancers by Tissue of Origin Islanders (8.8), followed by blacks and Hispanics (both 8.4), American Indians/​Alaska Natives (7.5), and whites (4.5) (Howlader et al., 2015) Migrant Studies Comparisons of cancer risk among people who migrate from a low-​ risk to a high-​risk population, or vice versa, can provide insights into the relative contributions of inherited versus acquired risk factors In a landmark study of Japanese migrants to Hawaii and their descendants (Kolonel et al., 1985), age-​adjusted incidence rates of stomach cancer in the 1970s were lower in Japanese-​born migrants to Hawaii (“Issei” or first generation) than among the Japanese in Japan The rates were even lower in the Hawaiian-​born Japanese (“Nisei” or second generation), although still higher than the Caucasian rates Migrants to Australia from seven European countries with higher stomach cancer rates than Australia (England, Scotland, Ireland, Poland, Yugoslavia, Greece, and Italy) showed a risk reduction with increased duration of residence in Australia (McMichael et  al., 1980) A  study of migrant populations within Italy (Fascioli et  al., 1995)  suggested that place of birth was a stronger predictor of stomach cancer risk than current place of residence Mortality data from several European countries also showed a closer relation of stomach cancer risk to county of birth than county of death (Coggon et al., 1990; Spallek et al., 2012), indicating the persistent significance of environmental factors in earlier life Collectively, these data suggest that environmental factors acting early in life have a crucial role in gastric carcinogenesis Temporal Trends Over the last half century, the overall incidence and death rates from stomach cancer have decreased steadily almost everywhere The database Cancer Incidence in Five Continents (CI5plus) contains updated annual incidence rates for 118 selected populations from 102 cancer registries through 2007 (Ferlay et al., 2013) A comparison over a 30-​ year period (1977–​2007) shows that, apart from year-​to-​year sporadic fluctuations, the trends of the decline of stomach cancer incidence are remarkably similar in men and in women, and in high-​risk countries such as Japan and low-​risk countries such as Denmark In the United States, incidence rates have decreased by more than 80% since 1950 (Siegel et al., 2016) The magnitude and consistency of this downward trend worldwide parallels the decrease in the prevalence of H. pylori Analysis of cancer registry data over time has provided an average estimated annual percentage change (EAPC) in gastric cancer incidence of  –​2.5% per annum (Bray et  al., 2012) The decrease in the incidence rate is outweighed, however, by the increase in the world’s population Thus, the absolute number of gastric cancer cases is expected to increase from 952,000 new cases in 2012 to 1,520,000 new cases by 2030 Mortality trends from GLOBOCAN (Ferlay et al., 2013) show that the decline in mortality is slightly greater and shows more variability across countries than incidence, suggesting that some improvement in survival has accompanied the reduction in the incidence rate A recent global overview of gastric mortality for the period 1980–​2010 demonstrated an average EAPC of –​3.7% in men in the European Union, –​ 2.7% in the United States, and  –​4.1% in Korea (Ferro et  al., 2014) The rate of decrease has slowed in the United States, France, and some other European countries In the United States, the EAPC decreased to  –​1.6 during the interval 2006–​2010 A  European study of birth cohort trends shows that the rate of decrease has diminished among cohorts born after the 1940s, particularly among women (Malvezzi et al., 2010) Incidence trends also vary by histological subtype and anatomic site, with widespread decreases in non-​cardia and intestinal cancers but increases in cardia and, less commonly, diffuse cancers (Kaneko and Yoshimura, 2001; Wu et  al., 2009) The SEER Program in the United States identified a strong decrease of the intestinal type in both sexes and all age groups, whereas the diffuse type—​particularly the signet ring cell type—​progressively increased (Henson et al., 2004) The increase in signet ring cell type has not been found in other populations, however (Chapelle et al., 2016; Kaneko and Yoshimura, 2001) A SEER study by Wu et al showed a 23% increase in cardia cancer (ICD code 16.0) from 1978–​1983 to 1996–​2000, whereas non-​ cardia cancer (ICD code 16.1–​6) and overlapping/​unspecified cancer of the stomach (ICD code 16.8–​9) decreased (Wu et al., 2009) (Figure 31–​ 2) Although the increase in cardia cancer may partly reflect improvements in gastric cancer subsite recording during the period, a true increase is likely and has been reported in other studies in the United States and Northern Europe, including the United Kingdom (Steevens et  al., 2010) Data from the nine oldest US SEER cancer registries (covering 10% of the population) showed that the incidence rates for cardia cancer significantly increased among whites from 1976 to 2007, but did not change among blacks or other races (Camargo et al., 2011a) This is consistent with white males having higher rates of cardia cancer than blacks, in contrast to the opposite pattern for gastric cancer overall ETIOLOGIC FACTORS The strongest risk factor for stomach cancer identified to date is chronic infection with the bacterium Helicobacter pylori (H. pylori) Because H. pylori infection was established as a risk factor for stomach cancer relatively recently (IARC, 1994), studies conducted earlier did not have information on H. pylori infection Some risk factors and protective factors, such as smoking and certain dietary components, may be correlated with H.  pylori infection, leading to confounding Alternatively, non–​H.  pylori risk factors and protective factors may modify the risk due to H. pylori infection, which is likely since only a small minority of people infected with H. pylori ever develop stomach cancer Hence, the most informative studies are those that collect information on both H. pylori and other putative risk factors Helicobacter pylori Historical Aspects Long before the discovery of H. pylori, gastric adenocarcinoma was known to arise within areas of gastritis The type of gastritis associated with cancer—​termed “chronic active gastritis” or “chronic type B gastritis” because of the presence of both lymphocytes and neutrophils—​ was extremely common in elderly populations and was thought to be a natural consequence of aging In detailed studies from Northern Europe and Latin America, the majority of individuals over the age of 50 years were found to have chronic type B gastritis (Correa et al., 1976; Siurala et al., 1985) H. pylori had been described almost a century (Kreinitz, 1906) before Marshall and Warren’s groundbreaking work (Warren and Marshall, 1983) However, with the rediscovery of H. pylori in the early 1980s, the idea that gastric inflammation preceded cancer took on new meaning Experimental ingestions and clinical trials of H. pylori eradication all demonstrated that H. pylori was the dominant cause of type B gastritis (Dixon et al., 1996), prompting reconsideration of traditional dietary and genetic theories of gastric carcinogenesis If H. pylori caused gastritis and gastritis was a precursor to malignancy in the majority of cases, H. pylori was likely to be a critical factor in carcinogenesis In 1994, an expert working group convened by the International Agency for Research on Cancer (IARC) classified infection with H pylori as carcinogenic to humans, based on its association with gastric adenocarcinoma and MALT lymphoma (IARC, 1994) This conclusion was upheld in 2009 by a second IARC working group (IARC, 2012a), with the added precision that H pylori was designated a cause of non-​cardia gastric carcinoma, the most common subtype globally It was recently estimated that 89% of non-​cardia gastric cancers worldwide, or 730,000 incident cases in 2012, were attributable to H pylori (Plummer et al., 2015) Evidence for Carcinogenicity Helicobacter pylori is a spiral Gram-​negative bacterium that colonizes the stomach Although most infections are asymptomatic, H.  pylori  601 Stomach Cancer is associated with chronic gastritis, peptic ulcer disease, gastric B-​ cell mucosa-​ associated lymphoid tissue (MALT) lymphoma, and gastric adenocarcinoma It is believed that H. pylori was once ubiquitous in humans, but that its prevalence has declined in successive birth cohorts, especially in Western Europe, North America, Oceania, and Japan, so that infection is now rare among children (Herrera and Parsonnet, 2009) The risk of H. pylori infection is associated with low socioeconomic status, particularly with overcrowding and poor sanitation (Palli et al., 1994; Rothenbacher et al., 1999) Thus the gradual disappearance of H. pylori in these regions may be largely a byproduct of economic development The widespread use of antibiotics and improvements in diet may also have played a role It is noteworthy that the reduction in H.  pylori prevalence matches the decline in gastric cancer incidence and mortality Almost all of the epidemiological evidence on the relationship between H. pylori and gastric cancer comes from serological assessment of anti–​H.  pylori immunoglobin G (IgG) antibodies It is now widely accepted that serological assessment of H. pylori infection has poor sensitivity in retrospective studies, so that case control studies systematically underestimate the strength of the association This is because atrophic gastritis, a precancerous lesion, reduces the burden of H.  pylori infection This in turn decreases titers of IgG antibody, potentially causing the H.  pylori infection to become serologically undetectable For this reason, the best evidence of H. pylori prevalence in relation to cancer comes from prospective studies The most comprehensive relative risk estimates for H pylori and gastric cancer come from a pooled analysis of 12 prospective studies, which included 762 cases of non-​cardia gastric cancer and 2250 controls The pooled odds ratio was 2.97 (95% CI = 2.34–​3.77) for H pylori infection (Forman and Helicobacter and Cancer Collaborative Group, 2001) The same study included 274 cases of cardia gastric cancer and 827 controls with an odds ratio of 0.99 (95% CI = 0.40–​ 1.77) for H pylori infection When the pooled analysis was restricted to cases occurring at least 10 years after the blood draw used for H pylori diagnosis, the odds ratio increased to 5.93 (95% CI = 3.41–​ 10.3) for non-​cardia cancer but decreased to 0.46 (95% CI = 0.23–​ 0.90) for cardia cancer This subgroup analysis underscores the much stronger relationship with non-cardia than cardia cancer and the need to account for the effect of premalignant disease on the detection of H pylori infection, even in prospective studies Further follow-​up of the individual studies contributing to this pooled analysis was reviewed in the IARC Monographs volume 100 part B, but did not substantively change the conclusions (IARC, 2012a) Although H.  pylori infection clearly increases risk for cancers of the gastric body and antrum, its relationship to cardia cancers has not been firmly established Some data suggest that these topographical subtypes may represent a mixture of two different tumors, resembling either non-​cardia adenocarcinoma (H. pylori induced) or esophageal adenocarcinoma (reflux induced) in their etiology In Western countries, tumors of the cardia occur more frequently in white males (Yang and Davis, 1988) and a large proportion occur in the setting of gastroesophageal reflux disease (GERD) Conversely, in high-​risk areas for H.  pylori and non-​cardia gastric cancers, most cancers of the cardia occur in H. pylori–​infected people, and may conceivably be related to H. pylori infection (Shakeri et al., 2015) Virulence Factors H.  pylori readily loses and acquires DNA fragments and undergoes various structural genetic changes such as point mutations and chromosomal rearrangements (Blaser and Berg, 2001) As a consequence, H.  pylori isolates have an extraordinary degree of genetic variability between and even within infected hosts, and this diversity may contribute to the clinical outcome of the infection (Aras et  al., 2002; Patra et al., 2012) A number of genetic factors associated with H.  pylori colonization (babA, sabA, alphAB, hopZ, and OipA) and virulence (cagA, vacA) have been identified (Keilberg and Ottemann, 2016)  (Figure 31–​ 5) The genetic marker that has attracted most attention in epidemiological studies is the presence of the cag pathogenicity island (PAI), a DNA sequence of 40 kbp present in 70% of H. pylori strains in Europe and North America, but ubiquitous in 601 Asia and most of Africa (Peek and Crabtree, 2006) PAI-​containing organisms cause greater inflammation and are more closely associated with intestinal-​type dysplasia and malignancy than are strains without the PAI (Parsonnet et al., 1997) In contrast, diffuse-​type cancers have similar associations with both PAI-​positive and PAI-​negative isolates Other polymorphic genes—​ such as the vacuolating cytotoxin and babA-​2 adherence gene—​have been linked to pathogenicity, but none as strongly as the PAI The PAI encodes for a type four secretion system that injects the cagA protein into the host cell, where it is phosphorylated and binds to the Shp-​2 tyrosine phosphatase (Stein et al., 2002; Yamazaki et al., 2003) The host cell consequently elongates and acquires a growth-​ factor-​like phenotype (Segal et al., 1997) The cagA protein is highly immunogenic, which allows serological detection of infection with CagA-​positive H.  pylori by the detection of anti-​cagA antibodies CagA-​positive strains are associated with higher risk of gastric cancer than cagA-​negative strains A  meta-​analysis of 16 cohort and case-​control studies including 778 cases of non-​cardia gastric cancer and 1409 matched controls found an elevated risk of cagA-​positive H. pylori infections, with an odds ratio of 2.01 (95% CI = 1.21–​3.32) for cagA-​positivity among all H.  pylori–​infected individuals (Shiota et al., 2010) The cag pathogenicity island is also associated with precancerous gastric lesions Plummer et al (2007) analyzed a cross-​sectional endoscopic survey of 2145 individuals from Venezuela, in which both the presence of H. pylori DNA and presence of the cagA gene were determined by polymerase chain reaction (PCR) on gastric biopsies Infection with cagA-​positive H. pylori strains but not cagA-​negative strains was associated with the severity of precancerous lesions Using individuals with normal gastric mucosa or superficial gastritis as controls, the OR for dysplasia was 15.5 (95% CI = 6.4–​37.2) for cagA-​positive H.  pylori compared with 0.90 (95% CI  =  0.37–​2.17) for cagA-​negative H. pylori González et al (2011) analyzed a follow-​ up study of 312 individuals from Spain with an average of 12.8 years of follow-​up between two endoscopies, also using PCR detection and genotyping of H. pylori The relative risk for progression of precancerous lesions was 2.28 (95% CI = 1.13–​4.58) for cagA-​positive strains compared with cagA-​negative strains Host Response and Other Interacting Factors The host also plays an important role in H. pylori outcome El-​Omar et al (2000) reported that H. pylori–​infected subjects who developed gastric cancer were more likely to have specific genotypes of interleukin (IL)-​1β or the IL-​1β receptor antagonist Interestingly, the higher risk genotypes of IL-​1β not only induce more inflammation than lower risk genotypes but also increase suppression of gastric acid secretion, supporting the pathogenic model devised by Correa Moreover, the IL-​1β genotype is not associated with cancer risk in the absence of infection A  subsequent study identified similar, though less strong, interactions between H.  pylori and TNF-​α (Machado et  al., 2003) Other putative host factors that are being explored include p53 polymorphisms and variants of the HLA genotype Environmental factors such as tobacco smoking, diet, and medications may also enhance or diminish H.  pylori’s deleterious effects, although relatively few of these studies have measured the effects of combined exposures Studies of dietary factors are particularly sparse A  prospective Scandinavian cohort demonstrated a protective association with ascorbic acid (vitamin C) and beta-​carotene in H. pylori–​infected subjects but not in uninfected subjects (Ekstrom et al., 2000b) A study by Correa and colleagues on gastric dysplasia and other preneoplastic conditions supported this finding They observed that both H. pylori eradication therapy and dietary antioxidants (ascorbic acid and beta-​carotene) prevented preneoplastic progression Combining antioxidants with H. pylori eradication therapy did not provide added benefit, however, suggesting that the benefit of antioxidants may be limited to infected hosts In animals, dietary salt magnifies H. pylori–​associated gastric carcinogenesis (Fox et al., 2003); this finding has not been substantiated in humans Non-​ dietary exposures that may alter H.  pylori outcome include aspirin and non-​steroidal anti-​inflammatory drugs (NSAIDs), which appear 602 602 HopZ/OipA AlpA/B VacA SabA BabA PART IV:  Cancers by Tissue of Origin α5 α5 β1 CagA β1 ? Lex Laminin Le b Abi Src Vacuolation P-CagA Shp2 IL8 ATP IL2 Apoptosis TNF Cell integrity Proliferation cell polarity Inflammation Figure 31–​5.  Adherence and virulence factors used by H. pylori to promote direct interactions with epithelial cells H. pylori possesses multiple adherence factors to attach to epithelial cells, including BabA, SabA, AlphA/​B, HopZ, and OipA Adherence is important for CagA delivery via the T4SS CagA is phosphorylated inside the host cell, and alters signaling pathways, leading to loss in cell integrity and alteration of cell proliferation and cell polarity, and induces inflammation Independent of attachment, VacA is secreted by H. pylori and can enter the cells via T5SS VacA leads to vacuolation and apoptosis of its host cells Source: Keilberg D, Ottemann KM How Helicobacter pylori senses, targets and interacts with the gastric epithelium Environ Microbiol 2016;18(3):791–​806 to protect against gastric cancer only in infected subjects (Zaridze et al., 1999) Smoking was associated with increased risk of stomach cancer in H. pylori–​infected subjects (OR = 2.2; 95% CI = 1.2–​4.2) in a nested case control study from Sweden, where cases and controls were tested by enzyme-​linked immunosorbent assay (ELISA) (Siman et al., 2001) Compared to nonsmokers, active smokers had significantly higher risk of colonization by cagA-​positive virulent strains and a non-​significant increase in bacterial load (Santibanez et al., 2015) In a population-​based case-​control study in Germany, the relative risk of gastric cancer was 2.6 (95% CI  =  1.2–​5.7) for nonsmoking subjects with CagA-​positive H.  pylori infections and 7.2 (95% CI  =  2.2–​23.6) for smoking subjects with CagA-​positive H. pylori infections, compared with subjects without these risk factors (Brenner et al., 2002) Hence, smoking could act indirectly on cancer risk by promoting the emergence of the more virulent strains in the gastric mucosa The age at which H. pylori infection is acquired may also modulate risk, since infection in high-​risk areas is usually acquired in childhood Only indirect data actually support this hypothesis, however (Blaser et al., 1995) Nevertheless, the theory remains popular, both because of its biological plausibility (increased duration of chronic inflammation increases the risk for genetic mutations to accumulate in gastric epithelium) and the epidemiological patterns of disease (cancer occurs more frequently in regions where childhood infection is common) Even among infected children, however, differences in gastric response to infection exist between high-​risk and low-​risk regions (Bedoya et al., 2003), suggesting that age at acquisition cannot explain important differences in clinical progression Epstein-​Barr Virus In 2014, The Cancer Genome Atlas Research Network recognized EBV-​associated gastric cancer (EBVaGC) as one of the four subtypes of a new molecular classification of gastric adenocarcinoma (The Cancer Genome Atlas Research Network, 2014) EBVaCG tumors are distinguished from the other subtypes by higher levels of DNA methylation in CpG islands of promoter regions and by distinctive genetic alterations The latter include a high frequency of mutations in PIK3CA and ARID1A, a mutation in BCOR, and amplification of PD-​ L1 and PD-​L2 (The Cancer Genome Atlas Research Network, 2014) In epidemiological studies, the established way to identify EBV in gastric tumors has been through detection of EBV-​encoded small RNAs (EBERs) or EBV DNA using in situ hybridization (ISH) (Fukayama and Ushiku, 2011; Hamilton-​Dutoit and Pallesen, 1994) Two meta-​analyses have now been published of gastric cancer studies that used ISH detection methods (Lee et al., 2009; Murphy et al., 2009) One of these was followed by a pooled analysis of over 5000 cancer cases from 15 populations (Camargo et al., 2011b) The pooled analysis detected EBV in malignant epithelial cells in 9% of all gastric cancers, although with high heterogeneity among the studies EBVaGC displays distinctive epidemiological and clinical features The proportion of EBV-​associated gastric cancer is higher at younger than at older cases, higher in men than in women (11% versus 5%, respectively), and slightly higher in American or Caucasian patients than in Asians (10% versus 8%, respectively) (Lee et al., 2009; Murphy et al., 2009) EBV-​related tumors also typically occur in the gastric body or cardia of the stomach, rather than in the antrum (Takada, 2000), and are common in gastric stumps following gastric resection A large multicenter case series examined the association of EBV status with survival after gastric cancer diagnosis, accounting for tumor stage and other prognostic factors, and found a lower mortality rate (Hazard Ratio [HR] = 0.72; 95% CI = 0.61–​0.86) (Camargo et al., 2014) A small percentage (probably less than 1%) of all gastric cancers are categorized histopathologically as lymphoepithelioma-​like carcinomas (LELC) These are epithelial tumors with intense lymphoid infiltration in the stroma, similar in appearance to nasopharyngeal carcinomas Between 80% and 100% of gastric LELC contain monoclonally integrated Epstein-​Barr virus (Burke et al., 1990; Herrmann and Niedobitek, 2003; Wu et al., 2000) Apart from these histopathological features and the consistent association with EBV, LELC resembles the conventional form of EBVaGC (Cheng et al., 2015) How and when EBV acts to induce malignant transformation remains largely unknown In the inflammatory mucosa, EBV is probably transferred from EBV-​infected B lymphocytes to gastric epithelial cells The viral genome is not integrated into the host genome but becomes circular and episomal within the cytoplasm of infected cells EBV uses the cellular machinery of the host cell to propagate its monoclonal viral genome, epigenetically silence viral and host genes, and control the behavior and microenvironment of the infected cell (Abe et al., 2015) EBV does not replicate in gastric tumors but does express latent genes according to specific latency patterns EBVaGC 1294 1294 multiple myeloma (MM) (cont.) World Health Organization (WHO), 798 definition and scope of the term, 797, 799 diagnosis, 797, 798, 798t environmental factors, 805–​7 future research, 808 host factors familial aggregation, 801, 803 genetic susceptibility, 803–​4 predisposing medical conditions, 804–​5 incidence and mortality demographic patterns, 799–​800, 799f–​801f trends, 800, 800f, 801f pathology, 797 prevention, 807–​8 prognostic factors, 801, 802t risk stratification, 801 stages of development, 798–​99 See also monoclonal gammopathy of undetermined significance survival, 800–​801 multiple primary cancer diagnosis, survival after, 1164 multiple primary cancer occurrence, 1162 methodologic issues in quantifying, 1156 in survivors of particular malignancies, 1156, 1157t, 1158–​62 time trends, 1162–​64 multiple primary cancers, 1155 See also cancer: prior; subsequent neoplasms (SN)/​second cancers classification, 1155–​56 descriptive epidemiology, 1156 future research, 1181 genetic testing in individuals with, 1178 multiple keratinocyte cancers, 1097 prevention and screening, 1180–​81 risk factors future research directions, 1179–​80 genetic susceptibility, 1173–​74, 1175t, 1176–​79 hematopoietic cell transplantation, 1171–​73 lifestyle and medical history, 1179–​80 radiotherapy, 1164–​69 systemic cancer therapy, 1169–​71 thyroid cancer and, 845–​46 multiple sclerosis (MS) and Hodgkin lymphoma, 759 multiple testing, 2, 59–​60 multiplicity, transparency, and reproducible research, 103 muscle-​invasive bladder cancer (MIBC), 985, 989, 990 mutagen sensitivity assay in bladder cancer, 989 mutations, genetic See also germline mutations; non-​synonymous mutations; point mutations; signature mutations; variants of unknown significance; specific genes acquired See somatic mutations activating (gain of function), 11, 527, 530, 534, 673, 720, 842, 854, 1019 MYC gene, 64, 424, 535, 673, 803, 890, 988t, 989t, 1133, 1134, 1178 mycophenolate mofetil, 423, 463 mycosis fungoides/​Sézary syndrome (MF/​SS), 774, 781 myelocytomatosis viral oncogene See MYC gene myelodysplastic/​myeloproliferative neoplasms (MDS/​MPN), 715, 736, 737 See also leukemia classification, 716, 719t, 720–​21, 721t Index myelodysplastic syndromes (MDS), 25, 715 See also acute myeloid leukemia; leukemia; myeloid neoplasms/​myeloid malignancies; therapy-​related MDS/​ AML age and, 724, 725f alcohol and, 733 autoimmune disorders and, 734 chemicals and, 730, 731 cigarette smoking and, 733 classification, 716, 720t, 720–​21 future directions, 736–​37 genetic risk factors, 735 incidence, 724, 725f infectious agents and, 734 radiation and, 728 severe congenital neutropenia and, 466 myeloid leukemia See acute myeloid leukemia; chronic myeloid leukemia myeloid neoplasms/​myeloid malignancies, 25 See also acute myeloid leukemia; myelodysplastic syndromes; myeloproliferative neoplasms (MPNs)/​ myeloproliferative disorders; therapy-​ related MDS/​AML in children, 1132–​33 cigarette smoking and, 261 classification, 1132 definition and scope of the term, 715 descriptive epidemiological patterns by WHO subtype, 722–​24 descriptive epidemiology, 1132 risk factors, 1133 environmental exposures, 1133 ionizing radiation, 1133 lifestyle, 1133 predisposition, 1132–​33 survival, 724, 726f, 1133 symptoms, clinical presentation, and diagnosis, 1132 treatment, 1133 myelokathexis See WHIM (warts, hypogammaglobulinemia, immunodeficiency, and myelokathexis) syndrome myeloma See multiple myeloma myeloma proteins, 804 myelopoiesis, transient abnormal, 1133 myeloproliferative neoplasms (MPNs)/​ myeloproliferative disorders, 25, 715 See also chronic myeloid leukemia; leukemia; myeloid neoplasms/​myeloid malignancies age and, 724, 725f classification, 716, 718t, 720–​21 future directions, 736, 737 incidence, 718–​19t, 724, 725f subsequent primary malignancies after, 1157t transformation to t-​AML, 732 N-​acetyltransferase2 (NAT2) phenotype, 988 naïve B cells See B cells/​B lymphocytes: naïve and memory naïve T cells See T cells/​T lymphocytes: naïve and memory nanoparticles, occupational exposure to, 286 nasal cavity cancer See also sinonasal cancer cigarette smoking and, 198 nasopharyngeal carcinoma (NPC), 489 descriptive epidemiology, 490 age-​specific incidence, 490, 491f demographic patterns, 490 geographic variation, 490, 492f disease burden, 489 etiologic factors, 498t alcohol, 495–​96 dietary consumption of salt-​preserved foods, 494–​95 evidence supporting the involvement of early-​life exposures, 499, 499b infections, 451, 490, 493–​94, 499 nitrosamines, 494, 495, 497, 499 occupational exposures, 496 tea and traditional herbal medicine, 496 tobacco and other smoke, 199, 495 future research directions, 498–​99 host factors, 498t DNA repair and tumor suppressor genes, 497–​98 familial aggregation, 496–​97 genome-​wide association studies (GWAS), 498 human leukocyte antigen (HLA) genes, 497 immune suppression, 496–​97 metabolism and biotransformation genes, 497 migrant studies of, 493 and non-​Hodgkin lymphoma (NHL), 780 precancerous/​precursor lesions, 489–​90 prevention, 498 risk factors, 498t survival, 490 temporal trends, 490–​91, 493 tumor classification, 489 NAT2 gene, 987, 988 NAT2 (N-​acetyltransferase 2) phenotype, 988 National Institute for Occupational Safety and Health (NIOSH), 1249 National Toxicology Program (NPT), 1241t, 1241–​42 natural experiments, 100b, 101 See also migrant studies natural killer lymphocytes (NK cells), 25, 253, 461, 735, 767, 770, 771f, 774 NBS1 gene, 465, 497 See also chromosomal instability neck cancer See head and neck cancer/​head and neck carcinoma; laryngeal cancer neighborhood environments See also residential segregation and socioeconomic status and socioeconomic status–​cancer association, 157, 159–​60 neoplasm(s) See also specific topics characteristics and definitions of, 19–​20 terminology, 19–​22, 21f nephroblastoma See Wilms’ tumor nerve sheath tumors, 1040, 1041t, 1043, 1054 See also malignant peripheral nerve sheath tumor nervous system tumors, 321, 1039 See also brain cancer; neuroblastoma in children, 1134–​36 classification, 1039, 1040t, 1135 clinical, 1040 histopathological, 1039, 1042–​43 molecular, 1039–​40 descriptive epidemiology, 1056, 1135 changes over time, 1042–​44, 1048f, 1049f geographic variation, 1042, 1045f, 1046t, 1047t, 1048f, 1049f, 1052f, 1053t incidence, 1040, 1041t, 1042, 1044t survival and mortality, 1042–​44, 1050t, 1051f, 1052f, 1053t, 1136  1295 Index future directions for the epidemiology of, 1056 prevention, 1056 risk factors and analytic epidemiology, 1044 animal studies, 1055–​56 cigarette smoking, 202 family history and familial aggregation, 1054 genetic factors, 1054–​55, 1135 non-​genetic factors, 1044–​49, 1051–​55, 1135–​36 nested case-​control studies, 437, 737 biomarkers and, 294 cohort studies analyzed as, 57 efficiency, 89 overview and nature of, 89, 282 reverse causality and, 476 neuroblastoma in children, 1136–​37 classification, 1136 descriptive epidemiology, 1136–​37 risk factors environmental exposures, 1137 genetic predisposition, 1137 survival and treatment, 1137 symptoms, clinical presentation, and diagnosis, 1136 neuroendocrine carcinomas, 32 neuroendocrine tumors, 672–​73 See also carcinoid tumors pancreatic, 626 small intestine, 672–​73 neurofibromatosis type (NF1), 1176–​77 neuroma, acoustic, 265, 266–​67t, 267, 268, 269f, 270 neutrophilic leukemia, chronic, 720 neutrophil:lymphocyte ratio, 831 neutrophils, 461, 466, 600, 675, 745 nevi and keratinocyte cancers, 1103 nevoid basal cell carcinoma syndrome (NBCCS)/​basal cell nevus syndrome (BCSS), 14, 1090, 1103, 1174 next-​generation sequencing (NGS), 33–​34, 989–​ 90, 1006–​7, 1126 NGS studies, 1055 whole exome sequencing and, 33, 34, 78, 989, 991, 1055 NFKB2, 466 nibrin See NBS1 gene nicotine, 190–​91 See also cigarette smoking; electronic nicotine delivery devices bioavailability, 191–​92 nicotine addiction, measures of, 196–​97 night shift work See shift work Nijmegen breakage syndrome (NBS), 465 nitrate biomarkers of genetic damage from, 318 and bladder cancer, 981 in drinking water, 313–​14, 318 future directions, 322 epidemiologic studies, 314, 315–​17t, 318 exposure, 313–​14 mechanisms of carcinogenesis, 314 and thyroid cancer, 851 nitrite, 314, 318 nitrosamides, 314, 318 nitrosamines, 314, 499, 616 and nasopharyngeal carcinoma, 494, 495, 497, 499 tobacco-​specific, 190, 192–​94, 197, 203, 616 N-​nitroso compounds (NOCs), 314, 494, 604, 691, 693, 983, 1049 N-​nitrosonornicotine (NNN), 197 NNK (4-​methylnitrosamino-​1-​3-​pyridyl-​1-​ butanone), 197 NNN (N-​nitrosonornicotine), 197 NOCs (N-​nitroso compounds), 314, 494, 604, 691, 693, 983, 1049 nodular lymphocyte predominant Hodgkin lymphoma (NLPHL), 745, 746 nodular melanoma (NM), 1061 nodular sclerosis Hodgkin lymphoma (NSHL), 745, 747, 748, 750, 751, 754, 757, 759 non-​alcoholic fatty liver disease (NAFLD) defined, 647 and liver cancer, 362–​63, 646, 647, 650 non-​alcoholic steatohepatitis (NASH) defined, 647 and liver cancer, 362–​63, 646, 647 non-​Hodgkin lymphoma (NHL) See also Burkitt lymphoma; lymphomas; MALT lymphoma descriptive epidemiology international comparisons, 772, 773f migrant data, 772 mortality, 772, 774f survival, 772, 774f time trends, 772–​73, 774f using World Health Organization (WHO) classification, 773–​74 future research, 787 post-​transplantation, 472–​73 See also post-​transplant lymphoproliferative disorder prevention, 787 risk factors alcohol, 220 allergic disease, 475 autoimmune disease, 474 birth order, 778 cigarette smoking, 202 family history and genetic factors, 785–​87 immune function and immunosuppression, 451, 472–​73, 778–​79 infectious agents, 447, 468, 470, 776–​77 lifestyle and personal factors, 783–​85 medical conditions and medications, 778–​81 occupational and environmental factors, 781–​83 small intestine, 673 tumor model and classification molecular pathogenesis, 767, 770 precursors, 772 WHO classification/​subtypes, 767, 768–​ 69t, 770, 773–​74, 775f nonintegrating viruses, 449 noninvasive follicular thyroid neoplasm with papillary-​like nuclear features (NIFTP), 33, 841 non-​ionizing radiation See also extremely low-​frequency electromagnetic fields; radiofrequency electromagnetic fields and leukemia, 729–​30, 1131 and nervous system tumors, 1045–​48, 1136 and thyroid cancer, 848–​49 non-​medullary thyroid cancer (NMTC), 854 non-​melanoma skin cancer (NMSC), 1089, 1090 See also basal cell carcinoma; keratinocyte cancers; squamous cell carcinoma (SCC) of the skin non-​muscle-​invasive bladder cancer (NMIBC), 985, 989, 990 nonsense mutations, 10f, 11, 12, 968 1295 non-​small cell lung cancer (NSCLC), 526, 527 See also lung cancer nonsteroidal anti-​inflammatory drugs (NSAIDS) and angiogenesis, 419, 650 and bladder cancer, 983 for cancer prevention, 1234–​35 and colorectal cancer, 694 and esophageal cancer, 585 and inflammation, 475–​76 and keratinocyte cancers, 1099 and leukemia, 733 and liver cancer, 650 and myeloma, 807 and non-​Hodgkin lymphoma (NHL), 780 and ovarian cancer, 893 and pancreatic cancer, 620 pharmacoepidemiology studies, 419–​20 and prostate cancer, 1008 and renal cell cancer, 967 and thyroid cancer, 852 non-​synonymous mutations, 636, 1001 non-​synonymous single-​nucleotide polymorphisms (SNPs), 10f, 58, 222 North America, cancer burden in, 126f NRAS and melanoma, 1062 nuclear accidents, 229–​30, 233–​34, 847 nuclear factor kappa B (NF-​kB/​NFKB), 625, 733, 755 nuclear power stations, cancer near, 234–​35 nuclear power/​weapons facilities, cancer near, 728, 855 bladder cancer, 986 thyroid cancer, 848 nuclear weapons See atomic bomb; nuclear power/​weapons facilities nuclear weapons tests, 229 military workers exposed to, 729 nuclear workers, 236–​38, 728 See also radiation workers nucleic acid hybridization, 44 nucleoside analogues (NAs), 448 nucleotide excision repair (NER), 252–​53 nucleotide mutations See non-​synonymous mutations; single-​nucleotide polymorphisms nutrients See also diet; specific nutrients and cervical cancer, 933–​34 macronutrients, 331–​32 micronutrients, 332–​36 and prostate cancer, 1009–​10 and renal cell cancer, 965–​66 nutrition See also diet health communication programs on, 1213 interaction with arsenic exposure, 309 and keratinocyte cancers, 1102–​3 and oral cavity cancer, 567 and oropharyngeal cancer, 567 nutritional epidemiology, 15 nutritional factors See also diet; nutrients and breast cancer, 331, 334, 335, 337f, 871–​72 Obamacare See Affordable Care Act of2010 obesity, 351, 1211 See also adiposity: excess; body mass index; weight gain epidemiology, 353, 353f estimated attributable fraction for incidence and survival, 363–​64 exposure parameters that influence risk of cancer from, 358 future research directions, 366 1296 1296 obesity (cont.) interaction between cigarette smoking and, 358 interaction between genes and, 623–​24 interpretation of temporal trends, 366 site-​specific mechanisms of carcinogenicity, 363–​64 and socioeconomic status–​cancer association, 154, 156 types of cancer caused by breast cancer, 872 colorectal cancer, 365 Hodgkin lymphoma, 757–​58 liver cancer, 646–​47 multiple primary cancers, 1180 myeloma, 805 non-​Hodgkin lymphoma (NHL), 784 oral cavity cancer, 565 oropharyngeal cancer, 566 pancreatic cancer, 617, 623 prostate cancer, 365, 1007 renal cancer, 365, 964–​65 thyroid cancer, 849–​50 obesity paradox, 365 obesity prevention, 366, 1211, 1212f, 1213 See also physical activity community-​based programs, 1213 health education and promotion, 1213 evidence-​based guidelines for a healthy lifestyle, 1213 health communication programs on physical activity and nutrition, 1213 policy approaches for population-​based prevention, 1211, 1212f food, nutrition, and agricultural policies, 1211–​12, 1213t policies concerning physical activity and sedentary behavior, 1212–​13, 1213t taxes and subsidies, 1211–​12 observational studies, 4, 5, 57, 98, 99, 101, 103, 178, 331f OCA2 (oculocutaneous albinism II gene), 1104 occupational cancer, 275–​76 attributable fraction, 284–​85 future directions, 285–​86 history, 276 quantitative risk assessment, 283–​84 and socioeconomic status–​cancer association, 142, 156–​57 types of bladder cancer, 979–​81 breast cancer, 874 cervical cancer, 934 Hodgkin lymphoma, 760 keratinocyte cancers, 1100 lung cancer, 530b melanoma, 1072 most common, 278, 280t myeloma, 806 nervous system tumors, 1048–​49 non-​Hodgkin lymphoma (NHL), 781 oral cavity cancer, 568 oropharyngeal cancer, 568 renal cell cancer, 966–​67 salivary gland cancer, 572 occupational cancer studies controversy regarding, 285 design of, 280 case-​control studies, 281–​82 cohort studies, 280–​82 cross-​sectional studies, 282 exposure assessment, 282–​83 Index genetic susceptibility, 283 proportional mortality studies, 281 evidence stimulating epidemiologic studies, 278–​80 occupational carcinogens accepted, 276, 277t, 278, 279t, 280t regulation, 1249 See also carcinogen regulation occupational epidemiology, 15 occupational exposures See also specific chemicals; specific occupations cigarette smoking and, 204 to extremely low-​frequency magnetic fields, 730 See also extremely low-​frequency electromagnetic fields Occupational Safety and Health Act of 1970, 1249 Occupational Safety and Health Administration (OSHA), 283, 1249 ocular melanoma/​uveal melanoma descriptive epidemiology demographic characteristics, 1077–​78 geographic variation, 1078 temporal trends, 1078 disease burden, 1076 etiologic factors environmental factors, 1079 familial aggregation, 1079–​80 gene mutations, 1080 genomic factors, 1079–​80 pigmentary phenotype, 1079 future research, 1082 pathways to, 1080 precancerous/​precursor lesions, 1077 survival, 1077 tumor classification, 1076 tumor progression models, 1076 oculocutaneous albinism II gene (OCA2), 1104 omega-​3 (Ω-​3) polyunsaturated fatty acids (PUFAs), 784 See also fish and keratinocyte cancers, 1101–​2 and prostate cancer, 1010 omega-​6 polyunsaturated fatty acids (PUFAs) and keratinocyte cancers, 1102 OMIC technologies, 1–​3, 283 See also biomarker technologies; specific technologies OncoArray initiative, 60, 62f oncogenes See also driver genes; HER2/​neu; proto-​oncogenes amplification, 24 See also gene amplification defined, 11 overview and nature of, 11 somatic mutations and, 11 See also somatic mutations oncogenic driver genes See driver genes 1000 Genomes Project, 45, 58, 59, 61, 62f oopherectomy, 880, 895 open research See transparency Opisthorchis species and biliary tract cancer, 475, 644, 665 and liver cancer, 644 O. felineus, 644 O. viverrini, 454, 644, 665 See also liver flukes oral cancers (oral cavity, oropharynx, lip, and salivary gland cancers), 543 See also lip cancer; oral cavity cancer; oropharyngeal cancer; salivary gland cancer; upper aerodigestive tract (UADT) cancer anatomic classification, 543 descriptive epidemiology geographic distribution, 545, 549f–​51f incidence and mortality rates in U.S., 545, 546t, 549f, 550f, 555f international incidence rates and trends, 545, 551f, 552f survival, 545, 548, 553t temporal trends by subsite and race/​ ethnicity in U.S., 545, 547f–​49f, 554t disease burden, 543, 545 etiologic factors, 548 indoor air pollution, 567 future research, 572 etiologic research, 573 methodologic issues, 573 translational epidemiologic research, 573 prevention, 548, 550, 572 subsequent primary cancers after, 548 tumor progression models, 545 oral cavity cancer (OCC) See also lip cancer; oral cancers; oropharyngeal cancer; salivary gland cancer; upper aerodigestive tract (UADT) cancer descriptive epidemiology age, sex, race, and ethnicity, 555 international incidence rates and trends, 555 migrant studies, 556 socioeconomic status, 555–​56 survival, 553t, 556 temporal trends and geographic variability in U.S., 547f, 548f, 554, 555, 556–​59f diet/​nutrition and, 567–​68 disease burden, 550 etiologic factors, 560–​61 alcohol, 563–​64 dental hygiene, 566–​67 HPV, 199, 564 mouthwash, 566–​67 obesity, 565 occupation, 568 physical activity, 566 tobacco use, 199, 561–​63, 565–​67 host factors familial aggregation, 568–​69 genetic variants, 569 inherited genetic susceptibility, 568–​69 predisposing medical conditions and immune function, 568 precancerous/​precursor lesions, 551–​52, 554 screening, 1197 terminology, 543 tumor classification, 544t, 550, 554t oral contraceptives (OCs), types of cancer caused by breast cancer, 870–​71 cervical cancer, 932–​33 choriocarcinoma, 955, 958 endometrial cancer, 915 hepatocellular carcinoma, 645 keratinocyte cancers, 1099 leukemia, 734 liver cancer, 645 non-​Hodgkin lymphoma (NHL), 780 ovarian cancer, 892 thyroid cancer, 853 oral erythroplakia, 551, 555 oral leukplakia, 551, 552, 555 oral potentially malignant disorders (OPMDs), 551, 552 oral submucous fibrosis, 551, 552, 555 orchiopexy, age at, 1023  1297 Index organochlorines, 667, 781–​82, 1024 See also DDT; pesticides organophosphate pesticides and non-​Hodgkin lymphoma (NHL), 782 organ transplantation, cancers associated with, 472t, 472–​73, 570 leukemia, 734–​35 melanoma, 1072 myeloma, 804 non-​Hodgkin lymphoma (NHL), 778 thyroid cancer, 845 orogenital intercourse, 445, 446 oropharyngeal cancer (OPC) See also oral cancers; oral cavity cancer; tongue cancer descriptive epidemiology, 445f age, sex, race, ethnicity, and socioeconomic status, 556f, 559 international incidence rates and trends, 559, 561f, 562f survival, 553t, 560 temporal trends and geographic variability in U.S., 559 disease burden, 558, 560 etiologic factors, 560–​61 alcohol, 564 asbestos, 568 dental hygiene, 567 diet/​nutrition, 567, 568 HPV, 199, 445f, 445–​46, 543, 564–​65 marijuana smoking, 565 mouthwash, 567 obesity, 566 occupation, 568 physical activity, 566 tobacco use, 199, 562–​63, 565 host factors familial aggregation, 569 genetic variants, 569 inherited genetic susceptibility, 569 predisposing medical conditions and immune function, 568 terminology, 543 tumor classification, 544t, 558–​61 ortho-​toluidine (o-​toluidine), occupational exposure to, 980 osteosarcoma/​osteogenic sarcoma, 24f See also bone cancers age-​specific incidence rate, 815, 817f association studies evaluating SNPs and, 821, 823–​24t birth weight and, 820t, 820–​21 genetic variants, 821, 823–​24t height and, 819–​20, 820t inherited cancer predisposition syndromes, 821, 822t survival, 817, 818t outdoor air pollution See also diesel exhaust combustion products in, 293–​94 concentrations of specific pollutants, 292t epidemiologic evidence, 297 ambient air pollution and lung cancer, 295–​96, 536 research approaches, 294–​95, 295t risk attribution, 296–​97 traffic-​related air pollution and childhood cancer, 297 exposures to inhaled carcinogens, 292–​93 fibers, 294 See also asbestos and lung cancer, 295–​97, 532–​33, 536, 537 methods of assessing exposure to, 294–​95, 295t point sources, 294 regulation, 1247–​48 ovarian cancer, 889 descriptive epidemiology demographic patterns, 890f, 890–​91, 891f geographic variation, 891, 891f migrant studies, 892 temporal trends, 891–​92 disease burden, 889 environmental factors, 892–​96 analgesic use and inflammation, 893 body size, 357, 894–​95 chemical agents, 895–​96 cigarette smoking, 201, 896 contraceptives, 892 dietary intake, 893–​94 hormone therapy, 892 physical activity, 388–​89, 895 radiation, 896 surgical interventions, 895 epidemiologic approaches to understanding tumor heterogeneity, 899, 900t, 900f epithelial, 59 future directions, 901 hereditary, 1174 histologic types, 32 host factors, 898 family history, 897 gene polymorphisms, 898 genetic predisposition/​gene mutations, 898 hormones, 898 reproductive factors, 896–​97 incidence, 889, 890f mortality, 889, 890, 891f preventive measures, 899–​901 screening and early detection, 899–​901, 1255 survival, 890 tumor pathogenesis, 889–​90 ovarian mucinous tumor, 198, 201, 888, 890, 893–​96 ovaries, surgical removal of (oopherectomy), 880, 895 overdiagnosis, 4, 22, 108–​9, 999, 1257–​58, 1263 definitions, 4, 108, 999, 1257 vs misdiagnosis, 1257 overweight See body mass index; obesity; weight gain ovulatory years and ovarian cancer, 896 oxyphilic cell thyroid cancer See Hürthle cell thyroid cancer p53 (tumor protein p53) See also TP53 (tumor protein p53) gene overexpression, 889, 956, 1075 signature mutations, 641, 873 p53 patches, 1090 P4502E1 See cytochrome P4502E1 paan/​pan, 194, 563 See also betel quid/​betel chewing Paget disease, 821 pan-​cancer analysis, 43, 44 pan-​cancer genomics, 47 pancreatic cancer (PC), 611 clinical and pathological features anatomy, presenting symptoms, and diagnosis, 611 molecular pathogenesis/​somatic mutations, 612 tumor subtypes, 611–​12, 626 current study limitations, 626 descriptive epidemiology, 612 1297 demographic characteristics, 612 geographic variation, 612–​14, 613f, 614f time trends in United States, 614–​15, 616f future directions, 627 genetic predisposition among sporadic PC patients, 621, 623 prevention, 626–​27 radiotherapy and subsequent, 1167 risk factors, 615, 1167 alcohol, 219–​20, 618, 626 allergies, 475, 625–​26 cigarette smoking, 200, 615–​17, 623, 626–​27 diabetes, 626 diet, 618, 624 drugs, 620–​21 epigenetic factors, 624 family history, 621, 622t genetic susceptibility, 621, 622t, 623–​24 infectious agents, 440, 625 inflammation, 625 insulin-​like growth factor (IGF-​1), 360–​61 insulin resistance, 361, 626 interactive effects between lifestyle and genetic variants, 623–​24 medical conditions, 618–​20 microbiome, 624–​25 molecular factors, 624 obesity, 356, 366 obesity and physical activity, 617, 623 occupation and physical environment, 620 physical activity, 387, 618 previous surgery, 626 pancreatic intraepithelial neoplasia (PanIN), 611 pancreatic neuroendocrine tumors (PNETs)/​islet cell tumors, 611, 626 functional vs non-​functional, 626 pancreatitis, chronic and pancreatic cancer, 619–​20, 625 papillary carcinoma in situ, 842 papillary thyroid cancer (PTC), 839, 840 See also thyroid cancer incidence, 840, 840f subtypes, 840–​41, 841t papilloma viruses See HPV parafollicular cells See C-​cells paranasal sinus cancer See also sinonasal cancer cigarette smoking and, 198 paraproteins, hyperphosphorylation of, 804 parasites, 454 paratarg-​7 (paraprotein target 7), hyperphosphorylated, 804 parity, 667 and biliary tract cancer, 667 and cervical cancer, 931–​32 and choriocarcinoma, 957 and gallbladder cancer, 667 and hepatocellular carcinoma, 648 and ovarian cancer, 896–​97 Parkinson’s disease and melanoma, 1072–​73 parotid gland, 270, 571–​72 particulate matter, fine (PM2.5), 293 passenger mutations, 11, 36, 254, 721 pathology in cancer diagnosis and research, 20 pathology techniques used to classify cancer, 29–​33 classical, 36 PDGFA gene, 11 PDGFR gene, 11 Pediatric Cancer Genome Project (PCGP), 44, 55 pedigree analyses, 56, 497, 604–​5, 735, 1055 1298 1298 pedigrees, inheritance of cancer in extended, 53, 54f pelvic inflammatory disease (PID) and ovarian cancer, 897 penetrance (genetics), 694, 1074–​75 See also low-​penetrance genes defined, 54 high-​penetrance variants in cancer predisposition genes, 55, 65 low-​penetrance genes in thyroid cancer, 854 penile cancer, 1029 descriptive epidemiology, 1029 age-​specific patterns, 1030 incidence and mortality in U.S., 1029 international variation in incidence, 1029, 1030f, 1031f marriage and partner status, 1031 racial/​ethnic patterns of incidence in U.S., 1030 socioeconomic patterns, 1030–​31 temporal trends in incidence, 1030 prevention, 1035–​36 risk factors, 1031 circumcision, 1033–​34 HPV, 443, 444 hygiene, 1033 immunosuppression, 1034 pathogenesis, 1034–​35 penile inflammatory conditions, 1033 phimosis and foreskin status, 1032–​33 sexual behavior, 1032 sexually transmitted diseases, 1031–​32 tobacco, 202, 1034 survival, 1035 sociodemographic factors and, 1035 tumor characteristics and, 1035 tumor classification, 1029 penile inflammatory conditions and penile cancer, 1033 people living with HIV/​AIDS (PLWHA), 1219 peptic ulcer disease, 421, 435 See also duodenal ulcer; gastric ulcer peptide hormones, 3, 673 See also anti-​ Müllerian hormone metabolic, 359–​62 See also adiponectin; insulin; insulin-​like growth factor 1 perchloroethylene (PCE) in drinking water, 319, 320 perfluorooctanoic acid (PFOA/​C8) and related compounds, community exposed to, 320 periampullary cancers, 675 See also ampullary cancer perinatal factors and testicular cancer, 1023 perinatal infection, 447, 640, 1217 peripheral nerve sheath tumor See malignant peripheral nerve sheath tumor; nerve sheath tumors peripheral T-​cell lymphoma (PTCL), 778, 779, 783, 785 peripheral T-​cell lymphoma, not otherwise specified (PTCL-​NOS), 774 pernicious anemia and stomach cancer, 606 person-​years of life lost (PYLL), 171, 173, 175 defined, 171 pesticides, 336 See also herbicides and biliary tract cancer, 667 and myeloma, 806 and non-​Hodgkin lymphoma (NHL), 781–​82 occupational exposure to, 286 and prostate cancer, 1009 regulation, 1248 and soft tissue sarcoma, 933 Index Peutz–​Jeghers syndrome, 675 pH, urine, 986 phagocytes, 461, 464 phagocytosis, 462 pharmaceutical drugs, 411 See also drug–​cancer associations; hormones; specific drugs; specific topics active and passive surveillance of adverse drug events, 412 for cancer prevention challenges in assessing efficacy and safety, 1230 side effects, 1230, 1232, 1232t under study, 1230 as chemical carcinogens, 411 defined, 411 future directions advances in pharmacoepidemiology and complementary methods, 424 new classifications of cancer and cancer subtypes, 423–​24 new databases and collaborative opportunities, 424 new drug agents and exposures, 423 translational research: discovery, validation, and clinical utility, 424 global trends in drug utilization, 411 increasing the selectivity of, 1229–​30 minimizing the dose of, 1230 most commonly dispensed prescriptions in U.S., 412f regulation, 1248 safety, 411–​12, 1248 targeted assessments of drug carcinogenicity, 412–​13, 413t, 414t pharmacoepidemiology See also drug–​cancer associations advances in, 424 pharyngeal cancer See oral cavity cancer; oropharyngeal cancer; upper aerodigestive tract (UADT) cancer phenacetin and bladder cancer, 983 and renal pelvis cancer, 970 and ureter cancer, 970 phenocopies, 54 phenotype See also CpG island methylator phenotype in genome-​wide association studies (GWAS), 59 pigmentary, 1073, 1079 phenotype definition, 59 phenotypic markers of UV exposure, 251 phenoxy herbicides, 833 phimosis, pathological vs foreskin nonretractability, 1032–​33 and penile cancer, 1033–​35 prevention, 1035 phosphatidylinositol-​3-​kinase (PI-​3K), 694 phosphatidyl inositol-​4,5-​bisphosphate 3-​kinase catalytic subunit-​α See PIK3CA gene phosphodiesterase type (PDE5) inhibitors, 423 photosensitizing medications, 1099 physical activity, 377 See also obesity prevention; sedentary behavior ascertaining the type, intensity, and amount needed to reduce cancer risk, 390 and cancer risk, 389, 391 future research on, 390–​91 meta-​and pooled analyses on, 380, 380t, 381f studies on, 380 summary of evidence regarding, 380, 382t definitions and core concepts, 377 guidelines for, 378 health communication programs on, 1213 measurement of, 377 application of novel technologies to improve, 391 job classifications/​occupational physical activity, 378 questionnaires, 377–​78 and mechanisms of carcinogenesis, 378–​79 policies concerning, 1212, 1213t changing the built environment, 1212–​13 and socioeconomic status–​cancer association, 156 and specific cancer types, 381t, 381–​89, 382t bladder cancer, 982 breast cancer, 873 colorectal cancer, 690, 691f endometrial cancer, 916 myeloma, 805 non-​Hodgkin lymphoma (NHL), 784–​85 oral cavity cancer, 566 oropharyngeal cancer, 566 ovarian cancer, 895 pancreatic cancer, 618 prostate cancer, 1010–​11 stomach cancer, 604 thyroid cancer, 852 surveys of, 378 pigmental cell instability, 1075 pigmentary phenotype and melanoma, 1073, 1079 pigmentation and keratinocyte cancers, 1103 pigment stones and biliary cancer, 665 PIK3CA gene, 11, 36, 545, 586, 602, 694, 862, 1002t PIK3CD gene, 466 pioglitazone, 421, 983–​84 pipe smoking, 203, 570 and bladder cancer, 979 and esophageal cancer, 582 historical perspective on, 185 and laryngeal cancer, 507–​8 and lip cancer, 570 and oral cavity cancer, 563 and oropharyngeal cancer, 563 pituitary tumor, 1041t, 1042, 1043f, 1047t plant polyphenol (in foods), 335–​36 plasma cell dyscrasia, 798t plasma cell genome, myeloma, 797 plasma cell myeloma, 25, 798 See also multiple myeloma asymptomatic, 798 plasma cell neoplasms, 25, 363, 472, 768t, 797, 770, 807 plasma cell proliferative disorders, asymptomatic premalignant, 797 See also monoclonal gammopathy of undetermined significance; smoldering multiple myeloma (SMM)/​asymptomatic myeloma plasma cells, 25, 363, 461, 462, 675, 799, 803, 804 See also bone marrow plasma cells Plasmodium falciparum, 452, 454, 776 plasticizers and breast cancer, 874 platelet-​derived growth factor receptor alpha (PDGFRA), 673 platelet disorders, 450, 465, 720, 735 platelets, 1235 aspirin and, 419, 650 platinum chemotherapy agents and leukemia, 732  129 Index plausibility and causation, 100b, 101 pleomorphic undifferentiated sarcoma (PUS) See malignant fibrous histiocytoma Plummer–​Vinson syndrome (PVS), 584, 585 point mutations, 9, 11, 45, 47, 48, 599, 675, 720, 835, 842 See also specific types of mutation radiation and, 856 single-​nucleotide polymorphisms (SNPs) and, 10f coding and, 10f, 636 tumor size and, 636 in tumor suppressor genes, 11 point sources of pollution, 294 polio model of Hodgkin lymphoma See late infection model of Hodgkin lymphoma polybrominated diphenyl ethers (PBDEs), 849 polychlorinated biphenyls (PCBs) and melanoma, 1072 and non-​Hodgkin lymphoma (NHL), 782–​83 and testicular cancer, 1024 polychlorinated dibenzo-​p-​dioxin (2,3,7,8-​TCDD), 833 polycyclic aromatic amines and breast cancer, 874 polycyclic aromatic hydrocarbons (PAHs), 292, 293 and keratinocyte cancers, 1100 and pancreatic cancer, 621 polycyclic organic matter (POM), 293 polycystic ovary syndrome (PCOS), 898, 913 polygenic (common variant small effect) model of cancer risk, 54–​55 polygenic risk score (PRS), 989, 1003 polymerase chain reactions (PCRs), 43, 44, 83 polymerase inhibitors, 450 polyposis See adenomatous polyposis coli (APC) gene; familial adenomatous polyposis polyps See also colorectal polyps hyperplastic, 682 See also colorectal polyps: serrated polyunsaturated fatty acids (PUFAs) omega-​3, 1010, 1101–​2 omega-​6, 1102 polyvinyl chloride (PVC) and liver cancer, 643 and melanoma, 1072 population, standard, 109 population aging, 108 population attributable fraction (PAF), 202–​3, 363–​64, 433 See also attributable fraction population-​based cancer registries (PBCRs), 107, 126, 265, 772, 840, 841 anal cancer and, 709 biliary tract cancer and, 662 cervical cancer and, 933 changing tumor classifications and, 3 childhood cancers and, 1119, 1120, 1128 choriocarcinoma and, 954 colorectal cancer and, 113 data linkage between other data sources and, 5 keratinocyte cancers and, 1097, 1105 lung cancer and, 520, 522, 527 melanoma and, 1078 multiple primary cancers and, 1155, 1156 myeloid neoplasms, leukemia, and, 716, 722, 727, 734, 736 nasopharyngeal carcinoma (NPC) and, 490, 496–​97 non-​Hodgkin lymphoma (NHL) and, 785–​86 overview and nature of, 107 small intestine cancer and, 671 stomach cancer and, 593 thyroid cancer and, 841 US SEER, 722 population-​based case-​control studies, 88 See also case-​control studies population risk vs individual risk, 1200 population studies, 102–​3, 129–​31, 133 porphyria and liver cancer, 646 post-​lactational involution, 861, 876 postmenopausal hormone therapy (PMT/​HT), 415, 805, 892, 917, 1196 See also hormone replacement therapy (HRT)/​ menopausal hormone therapy (MHT) post-​transplant lymphoproliferative disorder (PTLD), 472–​74, 477 hematopoietic cell transplantation (HCT) and, 1172 poverty See socioeconomic status precancerous lesions See precursor/​ precancerous lesions precautionary principle, in carcinogen regulation, 1243–​44 precision medicine, 179 preconception paternal irradiation (PPI) hypothesis, 1131 precursor B-​cell lymphoblastic leukemia, 724 See also B-​lymphoblastic leukemia precursor/​precancerous lesions, 22, 661, 831, 953, 1062, 1230 breast, 863–​64, 864f cervical, 22, 926 See also cervical intraepithelial neoplasia colorectal See colorectal adenoma keratinocyte, 1091 melanoma, 1062, 1077 nasopharyngeal, 489–​90 oral cavity, 551–​52, 554 squamous cell See squamous intraepithelial lesions stomach, 597–​98 precursors, cancer See also preneoplasia characteristics and definitions of, 19–​20 terminology, 22 precursor T-​cell lymphoblastic lymphoma, 774 pregnancy See also reproductive factors and choriocarcinoma, 957 and keratinocyte cancers, 1099 molar See hydatidiform moles and ovarian cancer, 896–​97 prehabilitation (prehab), exercise prescribed as, 389 preleukemia cells, 715 preleukemia subtypes, 721 preleukemic disorders, 737 preleukemic phase of t-​MDS/​AML, 201, 732 preleukemic states and entities, 715 pre-​malignant cells, 13 prenatal exposures, 402 and socioeconomic status–​cancer association, 153–​54 preneoplasia, 597–​98 See also precursor/​ precancerous lesions preneoplastic clones, 253 prevalence, 108 global, 108, 119f prevalence costs, 171–​73, 174f defined, 171 preventability of cancer, 1197–​98 depends on the assumed counterfactual, 1198 1299 prevention (and control) of cancer, 1193, 1205 See also attributable fraction; screening accomplishments in, 1194 early detection, 1196–​97 primary prevention, 1194–​96 approaches to, 1193–​94, 1194f contribution of epidemiologic data to, 1201 future directions in, 4–​6, 1201–​2 lack of cohesion in, 1199 new developments in, 1–​2 obstacles to, 1198–​99 constraints on screening and other interventions, 1200 voluntary vs involuntary exposures, 1199–​1200 preventive benefit, timing of, 1200–​1201 preventive interventions constraints on, 1200 evaluation of, 1200 Preventive Services Task Force, U.S., 879–​80 preventive therapy, 1229 for breast cancer, 1230–​33, 1231t, 1231f challenges in assessing efficacy and safety, 1230 drugs under study, 1230 side effects of agents considered for cancer prevention, 1230, 1232, 1232t strategies to improve and balance and benefits to risks, 1229 maximize benefits by selecting common diseases and high-​risk populations, 1229 minimize toxicity, 1229–​30 primary acquired melanosis (PAM), 1077, 1082 primary biliary cirrhosis (PBC), 647 primary central nervous system lymphoma (PCNSL) See central nervous system (CNS) lymphoma primary cutaneous anaplastic large cell lymphoma (PCALCL), 774 primary effusion lymphoma (PEL), 453, 777 primary fallopian tube cancer (PFTC) See tubal carcinoma primary immunodeficiencies/​primary immunodeficiency disorders (PIDs), 464t, 464–​68 combined immunodeficiencies, 465–​66 genetic polymorphisms, 466–​68 and non-​Hodgkin lymphoma (NHL), 719 primary mediastinal B-​cell lymphoma (PMBL), 1133 primary sclerosing cholangitis (PSC) and cholangiocarcinoma, 473, 474, 647 and liver cancer, 647 probability, 98–​99 probable carcinogens, 278 progenitor cell lines, 309 progenitor cells, 36, 252, 473, 493, 526, 527, 715, 720, 731, 733, 797, 863 progesterone, endogenous and endometrial cancer, 913 progesterone receptor (PR) status, 219, 354, 355, 359, 383, 384, 861–​63, 870, 871, 873 progestins estrogen therapy with, 397, 892, 910, 914 exogenous, and endometrial cancer, 913–​15 progestogens, 909, 910, 913, 915 prognosis, predictors of, 2, 20, 23, 25, 26, 29, 32–​37, 132 See also specific specific predictors prolactin and breast cancer, 399, 400, 875 proliferation, 20 proliferative inflammatory atrophy (PIA), 1001 130 1300 Propionibacterium acnes, 1008 proportional mortality studies (PMRs) of occupational cancer, 281 prostaglandin-​endoperoxide synthase-​2 (PTGS2), 683–​84, 694 prostaglandins, 419 prostate cancer, 997 advanced, 201, 357 aggressive, 1003, 1005–​6, 1013 molecular subtypes, 1013 descriptive epidemiology, 998, 999f, 1000f time trends, 135f disease burden, 997–​98, 998f education and mortality from, 152t etiologic factors adiponectin, 361 anthropometrics, 357, 360, 365 benzodiazepines, 422 chemical exposures, 1008–​9 demographics and family history, 1002, 1002f, 1003f diet, alcohol, coffee, tea, and vitamin/​ mineral supplements, 1009–​10 genome-​wide association studies (GWAS), 1002–​3, 1004–​5t, 1005–​7 infectious agents, 1008 insulin-​like growth factor (IGF-​1), 360–​61 interleukin-​6, 363 medical conditions, 1007–​8 medication use, 1008 physical activity, 387–​88, 1010–​11 tobacco use, 201, 1011 future research and topics of interest, 1012–​13 genetics of, 1003, 1005–​6, 1013 next-​generation sequencing studies, rare variants, and mutations, 1006–​7 hereditary, 1006 prevention of preventive agents, 1233t, 1233–​34 primary, 1011 secondary, 1012 screening for, 999–​1001 potential benefits from, 1265–​66 potential harms from, 1266–​67 socioeconomic status and, 144, 145, 147t, 148 somatic mutations in, 1001–​2, 1002t subsequent primary malignancies after, 1159t tumor classification, 1001–​2 molecular subtypes, 1001–​2, 1002t upgrading and downgrading of, 1001 prostate cancer-​specific mortality (PCSM), 1001 prostate-​specific antigen (PSA) test, 108, 121, 997–​1000, 1196 prostatic hyperplasia, benign, 1008 prostatic intraepithelial neoplasia (PIN), 1001 high-​grade, 1001 protein, dietary, 332 and laryngeal cancer, 511 and non-​Hodgkin lymphoma (NHL), 784 and renal cell cancer, 965 protein binding, chromatin immunoprecipitation (ChIP), 45, 49 protein patched homolog1 See PTCH1 proteome, 89 proteomics/​proteomic analysis, 34, 379 overview and nature of, 86 proton pump inhibitors (PPIs), 421–​22, 585 proto-​oncogenes, 55, 242, 529, 767, 776, 835, 854, 957 psoralen UVA therapy (PUVA), k252, 1033, 1098–​99 Index psoriasis, PUVA, and UVB treatment, 1098–​99 psychosocial factors and socioeconomic status–​cancer association, 157–​58 psychosocial mediators and socioeconomic status–​cancer association, 153 psychotropic drugs, 422–​23 PTCH1 (protein patched homolog 1), 14 See also basal cell carcinoma PTCH gene, 1090 pulmonary adenocarcinoma See lung cancer PUVA (psoralen UVA therapy), 252, 1033, 1098–​99 and keratinocyte cancers, 1098–​99 quid See chewing tobacco race/​ethnicity, 124–​26 and socioeconomic status–​cancer association, 143, 146t, 159 types of cancer associated with bladder cancer, 977, 979f bone cancer, 815, 818t bone cancers, 815, 818t breast cancer, 865f, 865–​66 choriocarcinoma, 955 colorectal cancer, 685, 686f esophageal cancer, 580–​81 Hodgkin lymphoma, 747, 749f keratinocyte cancers, 1092 liver cancer, 638–​39 lung cancer, 525–​26 melanoma, 1063, 1066t, 1078, 1080–​81 nervous system tumors, 1042, 1050t oral cancers, 545, 547f–​49f, 554t, 555, 556f, 559, 560f ovarian cancer, 890 pancreatic cancer, 612, 613t, 615, 616f penile cancer, 1030 renal cancer, 969 soft tissue sarcoma, 831, 832t testicular cancer, 1021, 1022f vulvar and vaginal cancer, 947, 948t radiation See ionizing radiation; non-​ionizing radiation; solar radiation; ultraviolet (UV) radiation radiation epidemiology, 15 radiation sensitivity syndromes, 1178 See also ataxia-​telangiectasia radiation signatures, 227, 242–​44 radiation therapy See radiotherapy/​radiation therapy radiation workers, 228, 231, 236–​40, 728–​29, 736, 819, 1100 radioactive iodine (RAI) See iodine-​131 radiofrequency electromagnetic fields (RF-​ EMFs) See also non-​ionizing radiation; radiofrequency radiation and childhood cancer, 1136 environmental exposure, 264 exposure sources, 264 See also mobile phone use occupational exposure, 264–​65 radiofrequency radiation See also non-​ionizing radiation; radiofrequency electromagnetic fields and nervous system tumors, 1045–​47 radiologic examinations, diagnostic, 726, 727, 736 See also diagnostic medical radiation radiologists, 238, 728, 736 See also radiation workers radionuclides, 293 See also specific radionuclides natural, 228–​29 radiotherapy/​radiation therapy, 230, 231, 236, 727 See also ionizing radiation; systemic cancer therapy for benign conditions, 727 bone cancer caused by, 819 leukemia caused by, 727, 736 non-​Hodgkin lymphoma (NHL) caused by, 780 second cancers after, 234t, 236, 239, 240, 243, 585, 736, 846, 1165–​68 future research directions, 1171 radiotherapy-​related exposures and, 1165 radiotherapy-​related risks, 1165–​68 radio waves See radiofrequency electromagnetic fields radium and non-​Hodgkin lymphoma (NHL), 783 radon indoor, 298–​99 and keratinocyte cancers, 1100 and leukemia, 729 and lung cancer, 532 RAF1 gene, 1126, 1128t raloxifene, 915 randomization, 98 randomized controlled trials (RCTs), 98, 330, 1259, 1268 rapamycin, 463 ras oncogene, 1090 RB (retinoblastoma) See retinoblastoma RB1 gene, 10, 55, 637, 821, 835, 890, 1074, 1137, 1138, 1173, 1176 REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals), 1243, 1251 recombination, genetic, 461, 624, 767 See also class-​switch recombination Fanconi anemia (FA) and, 1125, 1177 homologous, 724, 1125, 1177, 1178 radiation and, 240, 724, 1178 vaccines and, 939, 1218 recombination frequency and recombination fraction (θ), 56 recombination hotspots See hotspot mutations recombination process, 240, 462 recreational physical activity, 377 rectal cancer See also colorectal cancer physical activity and, 388, 388f red bone marrow (RBM) dose of radiation, and leukemia, 235, 235f red meat, 337, 343 See also diet; meat and colorectal cancer, 691f, 692–​93 defined, 691f and laryngeal cancer, 512 and liver cancer, 642–​43 nitrate in, 315–​17t, 318 5α-​reductase inhibitors, 1233–​34 Reed–​Sternberg cells, 25, 25f, 745, 751, 756 regional distribution of cancer burden, 109–​14, 110f See also geographic distribution of cancer burden regional patterns, 115–​16 Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), 1251 regulation See carcinogen regulation regulatory changes in cancer (gene expression), 12–​13 regulatory science, 1201 relative risk, 65, 88 relative survival (RS), 108 defined, 108  130 Index renal adenocarcinoma See also renal cancer; renal cell carcinoma cigarette smoking and, 200 renal cancer, 961 See also renal cell carcinoma in children, 1138 classification, 1138 histologic, 961, 962b demographic patterns incidence patterns, 962, 963t, 963f international variation, 961–​62, 962t mortality and survival, 962–​64, 963f, 964t descriptive epidemiology, 1138 future research, 971 genetic susceptibility for associated genetic variants, 969 family cancer history, 968 gene–​environment interactions, 969 genetic syndromes, 968–​69 genome-​wide studies of variants, 969 racial/​ethnic differences in, 969 prevention, 971 risk factors See also renal cell cancer alcohol, 220 environmental exposures, 1138 hypertension, 363–​64 obesity and body mass index (BMI), 356, 363–​65 physical activity, 384 predisposition, 1138 von Hippel-​Lindau disease, 968 survival and treatment, 1138 symptoms, clinical presentation, and diagnosis, 1138 renal cell cancer (RCC), risk factors for See also renal cancer; renal cell carcinoma diet, 965–​66 diuretics, 418 lifestyle factors, 964–​65 medical conditions, 966–​67 medications, 966–​67 obesity and body mass index (BMI), 365 occupation and environment, 967–​68 reproductive factors, 967 renal cell carcinoma (RCC) See also renal cancer; renal cell cancer in children, 1138 cigarette smoking and, 200 clinical and pathological characteristics of syndromic, 968–​69 kidney transplantation and, 473 renal conditions, chronic and renal cell cancer, 966–​67 renal failure See end-​stage renal disease renal parenchyma, cancer of, 963t renal pelvis cancer incidence, 962, 963t risk factors, 969–​71 cigarette smoking, 200 reproducibility, 103 reproductive factors, female See also hormone replacement therapy; pregnancy; sex steroid hormones interaction between anthropometric characteristics and, 916 interaction between physical activity and, 916 interaction between socioeconomic status (SES) and, 156 types of cancer associated with bladder cancer, 984 breast cancer, 870 choriocarcinoma, 957 endometrial cancer, 915–​16 leukemia, 734 melanoma, 1071 myeloma, 805 ovarian cancer, 896–​97 renal cell cancer, 967 thyroid cancer, 852–​54 reproductive history See also birth; parity; reproductive factors and multiple primary cancers, 1180 reproductive tract cancers See also specific cancers cigarette smoking and, 201 residential segregation and socioeconomic status (SES), 143 resistin, 403 Resource Conservation and Recovery Act of 1976 (RCRA), 1249 respiratory tract cancers See also specific cancers cigarette smoking and, 198–​99 RET gene and thyroid cancer, 841, 842, 854–​55 See also RET/​PTC (RET proto oncogene/​ papillary thyroid carcinoma) gene rearrangements reticuloendothelia neoplasms, subsequent primary malignancies after, 1157t retinoblastoma (RB) in children, 1137–​38 choriocarcinoma and, 956 classification, 1137 descriptive epidemiology, 1137 hereditary, 1176 risk factors, 1137 survival and treatment, 1137–​38 symptoms, clinical presentation, and diagnosis, 1137 retinoblastoma protein See RB1 gene RET/​PTC (RET proto oncogene/​papillary thyroid carcinoma) gene rearrangements, 242, 841, 848 retroviruses, 776 See also HIV; human T-​cell leukemia virus type 1 reverse causation/​reverse causality, 220, 618–​20, 758–​60, 780 obesity–​cancer association and, 363–​65 SES–​cancer association and, 151 reverse phase protein arrays (RPPA), 34 reverse transcriptase, 16, 44, 449, 453 See also TERT (telomerase reverse transcriptase) gene reverse transcriptase inhibitors, 471 rhabdoid tumors, 1044t, 1135 rhabdomyosarcoma (RMS), 24f, 1128t, 1140, 1141 See also soft tissue sarcoma rheumatoid arthritis (RA) and non-​Hodgkin lymphoma (NHL), 779 ribosomal RNA (rRNA), 44, 86, 455, 968 ribosome protein gene, mutation in, 821 ribosomopathies, 1126 risk See also attributable fraction; population attributable fraction absolute, 5, 65, 67–​68, 68f avoidable, 1198–​1200 vs burden, 107–​8 defined, 107 fortuitous reductions in, 1196 global trends in, 1–​2 new developments in the study of, 1–​3 population vs individual, 1200 principles for defining acceptable, 1243–​45 relative, 65, 88 risk assessment in carcinogen regulation, 1244–​45 elements of a, 1244 1301 risk factors, 108–​9 risk markers from published genome-​wide association studies (GWAS), 60, 61f, 62, 63t risk prediction, genome-​wide association studies (GWAS) and, 65–​66, 1003 risk prediction models, 1229 See also genetic risk prediction models bladder cancer, 991 breast cancer, 878, 879, 1229 cutaneous melanoma, 1075, 1082 genome-​wide association studies (GWAS) and, 5, 60, 65, 89, 1003 incorporation of biomarker information in, 89 lung cancer, 535–​36 ovarian cancer, 899, 900t overview and nature of, 5, 535 prostate cancer, 1003 single-​nucleotide polymorphisms (SNPs) and, 60, 63 risk stratification, 28, 102, 801, 808, 1039, 1138, 1139 RNA (ribonucleic acid), 33 See also introns; microRNAs Epstein–​Barr-​encoded, 776 messenger RNA (mRNA), 4, 597 non-​coding regions, 33, 43, 44, 50, 85, 624, 1022 See also exons reverse transcriptase and, 16, 44, 449, 453 ribosomal RNA (rRNA), 44, 86, 455, 968 RNA antisense purification (RAP), 50 RNA expression resource, 45–​46 RNA polymerase, 448, 640 RNA polymerase II, 50, 252 RNA regulation, long non-​coding, 50 RNAseq (RNA sequencing), 44–​46 Roadmap Epigenomics Project, 48, 82 Roundup See glyphosphate rRNA (ribosomal RNA), 44, 86, 455, 968 rubber manufacturing and leukemia, 731 safety See drug safety salivary gland cancer See also oral cancers cigarette smoking and, 199 incidence and death rates, 546t, 547f, 548f, 554t, 555f, 571, 571f ionizing radiation and subsequent, 1167 major, 571–​72 Salmonella enterica serovar Typhi and biliary tract cancer, 665 salt intake, dietary See also diet and stomach cancer, 603–​4 salt-​preserved foods and nasopharyngeal carcinoma, 494–​95 and stomach cancer, 603–​4 sarcoma, 24f, 24–​25 See also Ewing sarcoma; osteosarcoma/​osteogenic sarcoma; soft tissue sarcoma classification, 24–​25 SCCs See squamous cell carcinomas Schistosoma haematobium, 454 and bladder cancer, 986 and liver cancer, 643, 644 Schistosoma japonicum and liver cancer, 643–​44 schistosomiasis and liver cancer, 643–​44 schwannoma, vestibular, 145t, 1041t, 1042 See also acoustic neuroma sclerosing cholangitis See primary sclerosing cholangitis 1302 1302 screening, 29, 1267–​68 See also detection; specific cancer types and cancer risk and burden, 108 constraints on, 1200 historical context, 1255–​56 overview, 1255 and socioeconomic status–​cancer association, 158–​59 target population for, 1256 screening analytic framework, generic, 1258, 1259f screening modalities, 1260–​67 See also specific cancers; specific modalities screening program(s) determining the value of, 1258 importance of weighing net benefit, 1258–​60 evaluation of, 1256 potential benefits, 1258–​59 potential harms, 1259–​61 WHO criteria for a successful, 1256, 1256b “screening saves lives,” 1255, 1258 screening studies biases in, 1256t, 1256–​58 hierarchy of outcomes in, 1259, 1259f levels of evidence and strength of study design, 1259–​60 scurvy, 97 seafood See fish second-​hand smoke See environmental tobacco smoke (ETS)/​second-​hand smoke/​ passing smoking sedentary behavior, 389, 391 See also physical activity and breast cancer, 873 and cancer survivorship, 389–​90 and colorectal cancer, 690, 691f establishing its role in cancer incidence, 390 future research on, 389–​90 and occupational cancer, 286 policies concerning, 1212, 1213t changing the built environment, 1212–​13 and renal cell cancer, 965 SEER-​Medicare data, linked, 175–​77 SEER registry, 150, 535, 722, 1120 segregation, residential, 143 seizures, epilepsy, and glioma, 1052 selection bias, 415 selective estrogen receptor modulators (SERMs), 1229 See also tamoxifen and breast cancer, 877, 879, 880, 1232 and endometrial cancer, 914–​15 selective serotonin reuptake inhibitors (SSRIs), 422 selenium, 334–​35 and bladder cancer, 983 and esophageal cancer, 584 and hepatocellular carcinoma, 643 and prostate cancer, 1009–​11 and thyroid cancer, 851 seminoma See testicular cancer sentinel node biopsy, 24 sequencing See also genetic sequencing; whole exome sequencing high-​throughput, 2, 43, 44, 49 sequencing(-​based) technologies, 997, 1001, 1002 sequential estrogen plus progestin (SEP), 914 SES See socioeconomic status sessile serrated adenoma (SSA), 682 severe congenital neutropenia (SCN), 466 sex See gender sex differences See gender Index sex hormone-​binding globulin (SHBG), 360, 362, 399 sex steroid hormones, 362, 395–​96 See also androgen(s); estrogen(s); hormone replacement therapy; oral contraceptives; progestogens and breast cancer, 395–​400 future prospects regarding, 399–​400 hormonally-​linked risk factors, 396 unifying hypothesis regarding, 398–​99, 405 and keratinocyte cancers, 1099 physical activity and, 379 and prostate cancer, 400–​401 sexual behavior orogenital intercourse, 445, 446 and penile cancer, 1032 safe sexual practices, 1035 and socioeconomic status–​cancer association, 156 sexually transmitted infections (STIs) See also HPV and choriocarcinoma, 956 and ovarian cancer, 897 and penile cancer, 1032 and prostate cancer, 1008 and socioeconomic status–​cancer association, 156 Sézary syndrome (SS)/​Sézary disease, 774 SH2D1A gene, 465, 778 shade sails, 1213f, 1222 shade structures, 1222 SHH gene, 14 shift work and breast cancer, 874 and occupational cancer, 286 and socioeconomic status–​cancer association, 157 shingles See varicella zoster virus sibling recurrence risk ratios for various cancers, 54t sidestream smoke (SS), 190 See also environmental tobacco smoke (ETS)/​ second-​hand smoke/​passing smoking sigmoidoscopy, flexible, 1260, 1261 signature mutations, 15, 16, 47–​48, 537, 637 See also mesenchymal signature; radiation signature identification of, 47, 968 overview and nature of, 530 p53, 641, 873 ultraviolet (UV), 252–​54, 1061, 1062, 1071, 1076, 1080, 1082, 1090, 1091 simian virus40 See SV40 polyomavirus single-​cell analyses, 15, 17 single-​cell sequencing, 47, 87 single-​cell studies, 47, 404 single-​nucleotide polymorphisms (SNPs), 361 association studies of, 58–​69, 695 bone cancer and, 821–​24t, 825 breast cancer and, 876 coding, 58, 497 genome-​wide significant, 60, 62–​65, 695, 786, 822 Hodgkin lymphoma and, 755 linkage disequilibrium and, 58–​61, 64, 242, 1055 myeloma, MGUS, and, 803, 803t in non-​coding regions, 69, 695 non-​synonymous, 10f, 58, 222 risk prediction models and, 60, 63 SNP microarrays, 45 soft tissue sarcoma and, 835 tag, 58, 59 sinonasal cancer, cigarette smoking and, 198 Sjögren syndrome and non-​Hodgkin lymphoma (NHL), 474, 779 and thyroid cancer, 876 skin cancer See also basal cell carcinoma; keratinocyte cancers; melanoma; squamous cell carcinoma (SCC) of the skin indoor tanning and, 251, 1097–​98, 1105 screening, 1081 The Surgeon General’s Call to Action to Prevent Skin Cancer (2014), 255, 1223 UVA radiation and, 254, 1033, 1080, 1097–​99 UVB radiation and, 1072, 1079, 1080, 1090, 1091, 1097, 1099, 1223 skin conditions See atopic conditions/​atopic diseases; psoriasis SKT4 gene See MST1 (macrophage-​stimulating 1) gene SMAD4 gene, 586, 605, 612, 662 small cell carcinoma, 32 small cell lung cancer (SCLC), 526–​27, 529t, 535 small intestine, anatomy of, 672 small intestine adenocarcinoma See also small intestine cancer biologic implications of the infrequency of, 677 small intestine cancer See also colorectal cancer carcinoid, 672, 675 classification, 672–​73 epidemiology disease burden, 671, 672f, 673t, 675, 677 geographic variation, 671–​72 temporal trends, 672 etiologic risk factors alcohol and, 676 body mass index (BMI), 676 celiac disease, 675 diet, 676 genetics, 675 host factors, 675–​76 inflammatory bowel disease, 676 lifestyle risk factors, 676 tobacco, 202, 676 ulcerative colitis, 675 future research, 677 histopathology, 672–​73, 674t, 674f precursors, 673–​75 prevention, 677 small lymphocytic leukemia (SLL), 770, 773–​7 4, 776, 777, 779, 780, 785 small tumors, terminology used in classification of, 842 smokeless tobacco, types of cancer caused by bladder cancer, 979 nasopharyngeal carcinoma, 495 oral cavity cancer, 563 oropharyngeal cancer, 563 pancreatic cancer, 617 smokeless tobacco products, 203–​4 See also betel quid/​betel chewing; chewing tobacco novel, 204 smoking See also cigarette smoking; cigar smoking; marijuana smoking; pipe smoking bidi, 203, 563 chutta, 203  130 Index smoldering multiple myeloma (SMM)/​ asymptomatic myeloma, 797, 798t, 799 SNPs See single-​nucleotide polymorphisms snuff, 193, 204 snus, 204 social networks and the socioeconomic status–​cancer association, 157 social support and the socioeconomic status–​cancer association, 158 socioeconomic position (SEP), 142 socioeconomic status (SES), 141–​60 See also socioeconomic status (SES) measures area-​level, 144–​46 childhood, 756–​57 definitions, 142 individual-​level, 144, 145, 148, 150 and survival, 148–​51 socioeconomic status (SES)–​cancer association, 144, 145f, 146t, 147t, 148 See also socioeconomic status: and cancer mortality and cancer mortality, 143–​44, 148–​51, 149f, 151t explanations for the, 151–​53 factors and mechanisms underlying the, 153 adult exposures, 155–​59 alcohol, 156 childhood infection, 153, 154 cigarette smoking, 142, 152, 155 diet, 155–​56 early-​life exposures, 153–​55 education, 142, 152, 153 health care access, 158–​59 income, 142 lifestyle behaviors, 154 meta-​mechanisms, 141 neighborhood environments, 157, 159–​60 obesity, 154, 156 occupation, 142 occupational exposures, 142, 156–​57 psychosocial factors, 157–​58 reproductive factors, 156 reverse causation/​drift hypothesis, 151 sexual behavior, 156 social environment, 157 instrumental variable (IV) analysis of, 153 needed research on, 159–​60 race and, 143, 146t, 159 reasons for the weaker, 143–​44 SES gradient in cancer incidence and mortality, 143–​45, 148–​51, 155, 156, 159 in specific types of cancer, 145f choriocarcinoma, 955 colorectal cancer, 685–​86 Hodgkin lymphoma, 756–​57 hypopharyngeal cancer, 555–​56, 559 keratinocyte cancers, 1091–​92 melanoma, 1063, 1078, 1080–​81 oral cancers, 555–​56, 559 ovarian cancer, 891 penile cancer, 1030–​31 third variable bias and, 151–​53 socioeconomic status (SES) index, 148, 149f socioeconomic status (SES) measures, 142–​43 area-​level, and secular trends, 148–​50, 149f independent effects of individual-​and area-​level, 150 individual-​level, and secular trends, 150 “soda tax,” 1212 sodium intake, 335 and renal cell cancer, 965 soft tissue sarcoma (STS) See also Kaposi’s sarcoma cervical sarcoma, 926 in children, 1140–​41 cofactors, 834 descriptive epidemiology, 1140 age, sex, race/​ethnicity, 831, 832t incidence, 831, 831f, 832t, 833t survival, 831, 831f, 833 temporal trends, 831, 831f, 833t etiologic factors, 833 cigarette smoking, 202 environmental exposures, 1141 exposures, 833–​34 hormonal factors, 834, 835 immunosuppression, 834–​35 future research, 836 genetic susceptibility, 1140 chronic repair processes, 835–​36 familial aggregation, 835 genetic polymorphisms, 835 genetic syndromes, 835 molecular genetic characteristics of tumors, 829 precancerous/​precursor lesions, 831 prevention, 836 radiotherapy and subsequent, 1167 rhabdomyosarcoma (RMS), 24f, 1128t, 1140, 1141 survival and treatment, 1141 symptoms, clinical presentation, and diagnosis, 1140 systemic cancer therapy and subsequent, 1170 tumor classification, 829, 1140 histopathology, 829, 830t stage and grade, 829, 830t tumor progression models, 830–​31 solar radiation See also skin cancer; sun exposure; sun protection; vitamin D and lip cancer, 570 measuring personal exposure to, 250 biomarkers, 251 dosimetry, 250–​51 personal recollection, 251 phenotypic markers of UV exposure, 251 and melanoma, 1068, 1071, 1075, 1079, 1081 solvents and breast cancer, 874 and myeloma, 806 and non-​Hodgkin lymphoma (NHL), 782 somatic genomic alterations, See also somatic mutations somatic mutations, 10, 11, 34, 48, 67, 82, 242, 1125–​26, 1173 See also somatic genomic alterations in Down syndrome, 1133 infections and, 16 regulatory region functions and, 45 in specific cancers bladder cancer, 200–​201, 990, 991 breast cancer, 36, 862, 862t, 863 colorectal cancer, 695 esophageal cancer, 586–​87 head and neck cancer, 514 hepatocellular carcinoma, 636–​37 leukemia, 632 lung cancer, 529, 530, 534, 535, 537 lymphoma, 767 melanoma, 254, 1061, 1076, 1082 oral and oropharyngeal tumors, 545, 573 pancreatic cancer, 612 prostate cancer, 1001–​2, 1002t 1303 soft tissue sarcoma, 829, 835 stomach cancer, 605 thyroid cancer, 841 stem cells and, 13 stress and, 157–​58 treatment implications, 46 South America, cancer burden in, 124f, 125f soy, 338 and breast cancer, 871–​72 and prostate cancer, 1010 specificity, causation and, 100b, 100–​101 spillovers, 141 spine, tumors of See nervous system tumors spleen, 26, 461–​62 tumors arising in, 25 splenic marginal-​zone lymphoma (SMZL), 773 spliceosome proteins, 43 spurious relationship/​spurious correlation See third, unobserved variable squamous cell carcinoma (SCC) of the skin See also keratinocyte cancers cigarette smoking and, 202 molecular characteristics, 1090, 1090t trends in incidence rates of, 1093, 1094–​95t, 1096 squamous cell carcinomas (SCCs), 22, 23f See also anal cancer; cervical cancer; esophageal squamous cell carcinoma; vaginal cancer; vulvar cancer hematopoietic cell transplantation (HCT) and subsequent, 1172–​73 of lung, 527, 529t penile, 1029, 1031 See also penile cancer squamous intraepithelial lesions (SIL), 708 See also cervical intraepithelial neoplasia; high-​grade squamous intraepithelial lesions; intraepithelial neoplasia; low-​grade squamous intraepithelial lesions Src-​family kinases (SFKs), 1090 STAG2 gene, 989 stage, cancer, 477 defined, 23 staging, 23–​24, 26 See also TNM (tumor, node, and metastasis) staging system statins, 417–​19, 620, 807 and breast cancer, 871 and liver cancer, 649 and non-​Hodgkin lymphoma (NHL), 780 and prostate cancer, 1008 and thyroid cancer, 852 steatohepatitis See non-​alcoholic steatohepatitis stem cell model of gastric carcinogenesis, 598 stem cells cancer, 13 gastric carcinogenesis and, 598f lineage, 1022 model, 13 stem cell transplantation See also hematopoietic stem cell transplantation (HSCT)/​ hematopoietic cell transplantation (HCT) autologous, 801 stochastic heterogeneity, 37 stomach cancer, 22, 22f classification of, 31, 593–​95 anatomic subtypes, 595, 595f, 596f histologic subtypes, 595–​96, 596f Laurén classification, 595–​96, 596t molecular classifications, 595f, 597 WHO histologic classification, 596t, 596–​97 1304 1304 stomach cancer (cont.) consecutive steps for development of, 438f descriptive epidemiology, 599 demographic characteristics, 599 geographic variation, 599–​600 level of Human Development Index (HDI) and incidence, 112 migrant studies, 600 temporal trends, 112, 113f, 600 disease burden, 593, 594f etiologic factors, 600 See also Helicobacter pylori alcohol, 604 body mass index (BMI), 356, 604 cigarette smoking, 199, 603 Epstein–​Barr virus (EBV), 451, 595f, 602–​3 food and nutrition, 603–​4 histamine antagonists, 421–​22 ionizing radiation, 604, 606 physical activity, 604 proton pump inhibitors (PPIs), 421–​22 future research, 606 host factors, 606 familial risk, 604–​5 genetic factors, 604–​6, 605t precancerous/​precursor lesions, 597–​98 socioeconomic status and, 154 survival, 599 tumor grade and stage, 597 TNM staging, 597 tumor progression models, 598–​99 stool tests, 697, 1261 stress and socioeconomic status–​cancer association, 157–​58 stromal cells, 15 See also ovarian cancer stromal differentiation, cancers demonstrating, 24–​25 stromal interactions, 22, 23 stromal tumor See gastrointestinal stromal tumor structural variations, genomic See also copy number variations; germline mutations; hotspot mutations; point mutations frameshift mutations, 11, 12, 599, 835, 968 indel (insertions or deletions), 10f, 44 nonsense mutations, 10f, 11, 12, 968 somatic See driver mutations; passenger mutations; somatic genomic alterations; somatic mutations styrene and leukemia, 731 subclones, 26, 34, 36, 46, 47f, 863 subcutaneous adipose tissue (SAT), 693 subcutaneous panniculitis-​like T-​cell lymphoma (SPTCL), 774 subglottic cancer See laryngeal cancer subsequent neoplasms (SN)/​second cancers, 1155 See also multiple primary cancers; therapy-​related AML; therapy-​related MDS/​AML after adolescent or young adult cancer, 1158t, 1158–​59 after breast cancer, 1160, 1161f after cervical cancer, 934 after childhood cancer, 1156, 1157t, 1158 after Hodgkin lymphoma, 1160–​61, 1162t, 1163f after keratinocyte carcinoma, 1161–​62 after later adulthood cancer, 1159t, 1159–​60 after oral cavity and oropharyngeal cancer, 548 Index genetic variants associated with treatment-​ related, 1178–​79 genetic variation as a modifier of treatment-​ related, 1178–​79 radiation sensitivity syndromes, 1178 sugar-​sweetened beverages (SSBs), 1211–​13 sulfonylurea, 421 sulforaphane (SFN), 1102 sulfur dioxide (SO2), 293 sun exposure See also melatonin; solar radiation balancing the risks and benefits of, 1225 and non-​Hodgkin lymphoma (NHL), 785 and ovarian cancer, 896 sunglasses, 1222 sun protection, 1221 hierarchy of, 1221 clothing to protect skin, 1222 hats and umbrellas to protect skin and eyes, 1224 minimizing time outdoors when UV levels are high, 1221–​22 seeking shade, 1222 sunglasses and UV-​absorbing contact lenses, 1222 sunscreen, 1222–​24, 1223f need for, 1221 potential risks, 1225 sun protection factor (SPF), 1223, 1223f, 1224 effectiveness of different SPFs at preventing sunburn, 1223, 1223f sun-​protection programs efficacy in reducing skin cancer incidence, 1225 successful, 1224–​25 sunscreen, 1222–​24, 1223f SunSmart, 255, 1224–​25 superficial spreading melanoma (SSM), 1061 supraglottic cancer See laryngeal cancer Surgeon General of the United States The Surgeon General’s Call to Action to Prevent Skin Cancer (2014), 255, 1223, 1225 on tobacco, 199–​204, 615, 962 The Health Consequences of Involuntary Exposure to Tobacco Smoke (2006), 291, 299 The Health Consequences of Involuntary Smoking (1986), 100, 102, 299, 1203 The Health Consequences of Smoking (2004), 199, 204 The Health Consequences of Smoking— 50 Years of Progress (2014), 197, 198, 200–​201, 529, 615, 627, 642, 689, 871, 1192, 1197 Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service (1964), 97, 100–​102, 142, 188, 524, 1192, 1203 surgical interventions and ovarian cancer, 895 surveillance, 4–​6, 29, 107, 130, 136, 1012, 1202 Surveillance, Epidemiology, and End Results cancer registry–​Medicare insurance claims data (SEER-​Medicare), 175–​77 survival, 108 See also specific cancers absolute, 1257 relative, 108, 1257 socioeconomic status and, 148–​51 survival patterns, 107, 114–​15 future directions, 129–​33, 136 future scale and profile of cancer 2030, 136 survival “rate,” 108 survivorship, cancer, 4–​5 SV40 polyomavirus (simian virus 40) and brain tumors, 1054 and non-​Hodgkin lymphoma (NHL), 777 swimming pools, shade sails over, 1222, 1223f synergistic effects, 473, 562 additive, 65–​68, 88, 232, 338, 399, 448, 532, 846, 854, 931, 932, 981, 988–​89, 1168, 1170 alcohol and, 204, 217, 218, 448, 449, 511, 562, 563, 641 environmental toxins and, 157, 298, 309, 319, 532 genetics and, 65–​68, 68f, 88, 854, 969, 981, 988–​89, 1178 hormones and, 360, 399 infections and, 218, 319, 441, 446, 448, 449, 471, 603, 606, 641, 649, 932, 939 multiple primary cancers and, 1168, 1170, 1171, 1178 multiplicative, 68, 88, 204, 232, 240, 298, 319, 532, 562, 563, 641, 649, 846, 969, 1167, 1168, 1179 on stomach cancer risk, 603, 606, 1168, 1170 tobacco smoking and, 157, 204, 217, 232, 240, 281, 296, 298, 309, 446, 471, 511, 532, 562, 563, 603, 931, 969, 989, 990f, 1179 synonymous mutations, 636 systemic cancer therapy, subsequent primary malignancies after, 1169–​71 future research directions, 1171 systemic therapy–​related exposures and, 1169 systemic therapy–​related risks for solid cancers, 1170 systemic therapy–​risks for t-​MDS/​AML, 1169 systemic lupus erythematosus (SLE) and cervical cancer, 934 and non-​Hodgkin lymphoma (NHL), 779 tacrolimus, 1099 See also calcineurin inhibitors tag single-​nucleotide polymorphisms (SNPs), 58, 59 tamoxifen, 1231–​32 See also selective estrogen receptor modulators long-​term impact on breast cancer incidence, 1231, 1231f tanning, indoor reducing exposure, 1225 and skin cancer, 251, 1097–​98, 1105 tar content of cigarettes, 189, 192, 193, 194f targeted sequencing (TS), 33–​34 targeted therapies, 530 See also tyrosine kinase inhibitors taxonomy See classification T-​cell acute lymphoblastic leukemia (T-​ALL), 774 T-​cell differentiation and T-​cell neoplasms, 767, 771f T-​cell non-​Hodgkin lymphoma (NHL), 454, 774, 776, 778, 779, 783, 785, 786 T-​cell prolymphocytic leukemia (T-​PLL), 774 T cells/​T lymphocytes, 16, 462 cytotoxic (CD8+), 445, 461, 497, 755, 776 helper (CD4+), 461, 463, 756, 771f See also cytotoxic T-​lymphocyte–​associated antigen 4 naïve and memory, 16, 253, 461–​62, 771f TCGA (The Cancer Genome Atlas), 28, 35, 36, 545, 597, 990  1305 Index tea, 338 and esophageal cancer, 584 and keratinocyte cancers, 1102 and liver cancer, 642 and nasopharyngeal carcinoma, 496 and oral cavity cancer, 567–​68 and oropharyngeal cancer, 568 and ovarian cancer, 893–​94 and prostate cancer, 1010 team science, 4 Techa River nuclear installation, 235 telangiectasia See ataxia-​telangiectasia telomerase reverse transcriptase See TERT gene telomere attrition, 624 telomere length, 16, 624 telomeres and socioeconomic status–​cancer association, 159 temporality, causation and, 100b, 101 teratoid tumors, 1044t, 1135 Terc, 16 TERC gene, 735 terminal duct lobular units (TDLUs), 861, 878 TDLU involution, 878, 878f Tert, 16 TERT (telomerase reverse transcriptase) gene, 45, 63, 498, 534, 636, 637, 662, 841, 898, 1055, 1061, 1062, 1074, 1076, 1077 testicular cancer See also testicular germ cell tumors demographic patterns age, 1021, 1021f birth cohort effect on incidence, 1021 incidence, mortality, and survival around the world, 1019–​20, 1020f migration effect on incidence, 1021 endogenous factors age at puberty, 1023 body size, 1023 perinatal factors, 1023 exogenous factors cigarette smoking, 202 diet, 1025 endocrine disrupting chemicals, 1023–​24 marijuana, 1024 occupation, 1024–​25 physical activity, 1025 socioeconomic status, 1025 future directions, 1025 host genetics, 1022 medical conditions and, 1022–​23 preventive measures, 1025 subsequent primary malignancies after, 1158f tumor classification and histopathology, 1019 tumor genomics, 1022 testicular dysgenesis syndrome (TDS), 1022 testicular germ cell tumors (TGCTs), 1019–​25 See also testicular cancer testicular microlithiasis, 1023 testosterone, 362, 379, 395, 403, 404, 463, 1023, 1024 and breast cancer, 399–​400, 875 and hepatocellular carcinoma (HCC), 648 and ovarian cancer, 898 and prostate cancer, 400, 401 smoking and, 1011, 1023, 1024 2,3,7,8-​tetrachlorodibenzodioxin See polychlorinated dibenzo-​p-​dioxin tetrachloroethylene and bladder cancer, 981 textile industry and nasopharyngeal cancer, 496 TGF-​β1 (transforming growth factor beta 1), 241, 463, 733 therapy-​related AML (t-​AML), 732, 737, 1163–​64 See also subsequent neoplasms (SN)/​second cancers therapy-​related MDS/​AML (t-​MDS/​AML), 716, 720, 727, 728, 731, 732, 1164, 1165, 1178 See also subsequent neoplasms (SN)/​second cancers thiazolidinediones, 421, 983–​84 third, unobserved variable, 151–​53 third variable bias, 152 Thorotrast and liver cancer, 643 thymine dimers and thymine dimerization, 47, 251 thymus, 1076 immunity and, 16, 461, 462, 465, 534, 767 T-​cell neoplasms and, 767, 771f thymus cancer, 780 thymus involution, 462 thyroid cancer, 839, 855 cancer treatment and subsequent hematopoietic cell transplantation (HCT), 1173 radiotherapy, 1167 systemic cancer therapy, 1170 Chernobyl accident and, 227, 233–​34, 841, 847, 848, 854, 1142 descriptive epidemiology, 842 international patterns of incidence and mortality, 842, 843t trends over time, 843–​44, 844f, 1258, 1258f U.S. patterns of incidence and mortality, 842 multiple primary cancers and, 1179 physical activity and, 388 precursor conditions, 842 prevention, 855 risk factors anthropometric factors, 849–​50 chemical exposures, 849 cigarette smoking, 202 environmental exposures, 849 future research, 855–​56 genetic susceptibility, 854–​55 lifestyle factors, 849–​52 obesity and body mass index (BMI), 357 predisposing medical conditions, 844–​46 radiation, 846–​49, 1167 See also under Chernobyl accident reproductive and hormonal factors, 852–​54 in utero exposures, 854 screening, 855 subsequent primary malignancies after, 1158f tumor classification, 839 evolving classification, 841 histological and molecular subtypes, 840–​41, 841t histological types, 839–​40, 840f, 840t staging, 841 terminology used in classification of small tumors, 842 thyroid carcinoma See also thyroid cancer in children, 1142 thyroid disease, benign, 844–​45 thyroid hormones, 403–​4 thyroid-​stimulating hormone (TSH), 404, 839, 855 thyroid nodules, 839 tissue life cycle, 32f, 32–​33 tissue microarrays (TMAs), 30 limitations of the utility of, 30 1305 tissue morphology See also morphological classification of cancer as putative intermediate endpoints, 32 T-​lymphoblastic leukemia/​lymphoma (T-​ALL/​ LBL), 774 T lymphocytes See T cells/​T lymphocytes TMC6/​8 (EVER1/​2) genes, 466 t-​MDS/​AML See therapy-​related MDS/​AML TNFBR2 gene, 468 TNM (tumor, node, and metastasis) staging system, 26, 490, 597, 841 tobacco future research directions, 205–​6 harmful and potentially harmful constituents (HPHCs), 196 See also nicotine; tobacco carcinogens historical perspective on, 185, 186f, 187f tobacco carcinogen exposure factors that influence, 191–​93 product design and composition, 191–​92 measurement of, 195–​97 biomarkers of exposure, 197 biomarkers of genotoxicity, 197 questionnaire measures, 195–​96 nature of, 190–​95 tobacco carcinogens, 190, 191t, 192, 196, 203, 689 tobacco cessation, 205, 562, 563, 979 See also cigarette smoking: cessation of; tobacco control measures treatment to promote cessation, 1209 Tobacco Control Act of 2009, 1208, 1209 tobacco control measures, 536, 537, 1207–​10 See also tobacco cessation; tobacco use: prevention accomplishments, 1194–​95 education, 1207 harm reduction and e-​cigarettes, 1209 marketing bans, 1208 package labeling/​health warnings, 1208–​9, 1209f product and marketing regulation, 1208 scientific basis for, 1207 smoke-​free legislation, 1207–​9 taxation, 1208 tobacco products, 190, 573 See also cigarettes black vs blond tobacco, 979 combustible, 193, 203 commonly used, 185, 186t design and composition, 192 non-​cigarette cancer risks from, 203 non-​combusted products, 193–​94 See also chewing tobacco; smokeless tobacco products; snuff novel products, 194–​95 per capita sales, 185, 186, 186f, 188, 188f tobacco smoke composition, 190, 191t, 689 See also nicotine; tobacco carcinogens involuntary exposure to See environmental tobacco smoke (ETS)/​second-​hand smoke/​passing smoking mainstream vs sidestream, 190 tobacco-​specific nitrosamines (TSNAs), 190, 192–​94, 197, 203, 616 tobacco use, 185–​86 See also cigarette smoking; cigar smoking; pipe smoking; Surgeon General of the United States: on tobacco global patterns of geographic distribution, 186, 187f temporal variation, 186, 186f–​90f, 188–​90 1306 1306 tobacco use (cont.) interaction with other exposures, 204 in middle and high school students, 190, 191f prevention, 205, 1036 increasing the age at initiation, 205 types of cancer caused by biliary tract cancer, 202, 667 bladder cancer, 201–​2, 978–​79, 980f colorectal cancer, 689–​90 hypopharyngeal cancer, 197, 203, 508, 509, 561–​65 keratinocyte cancers, 202, 1100 multiple primary cancers, 1179 nervous system tumors, 1051 non-​Hodgkin lymphoma (NHL), 783 penile cancer, 1034 pharyngeal cancer, 563 prostate cancer, 1011 small intestine cancer, 676 soft tissue sarcoma, 834 tocopherols See alpha-​tocopherol; vitamin E toluidine, occupational exposure to, 980 Toms River, New Jersey, 320–​21 tongue cancer, 543, 544t See also oral cancers; oropharyngeal cancer epidemiology, 545, 546t, 550, 554t, 555, 558, 559 familial aggregation, 569 HPV and, 199, 564, 565, 585 subsequent primary malignancies after, 548 survival, 556 terminology, 551 tonsil cancer, 558–​60, 560f, 565 See also oral cancers; oropharyngeal cancer tonsils, 445 HPV in, 445, 565 topoisomerase II inhibitors, subsequent leukemia after treatment with, 732, 1169 Toxic Substances Control Act of1976 (TSCA), 1248 TP53 (tumor protein p53) gene See also p53 and keratinocyte cancers, 1090 and soft tissue sarcoma, 835 TP53 Pro allele, 1178 TP63, 506, 529t, 545, 623, 987, 988t TP73, 529t, 1178 tracheal cancer See also head and neck cancer/​head and neck carcinoma cigarette smoking and, 198–​99 traditional Chinese medicine (TCM), 496 traditional serrated adenoma (TSA), 682 traffic-​related air pollution See also diesel exhaust and childhood cancer, 297 transcription-​coupled NER (TC-​NER), 252, 253 transcription factors (TFs), 82, 83f, 469t, 470t, 721, 735, 755, 786, 821, 822, 854, 969, 1002, 1008, 1074, 1090, 1138, 1140 See also p53; RNA polymerase binding sites and, 49 GLI family of, 14 myeloid differentiation and, 735 nuclear, 220, 332 oncogenes and, 11 regulatory region functions and, 45 transcriptome, 206 See also RNAseq Human Genome Project and, 33 regulation of See also gene overexpression; histone modification gene silencing, 49, 50, 83, 340, 529, 602, 987, 991 Index RNA and, 34, 50 white blood cell, 85–​86 transcriptomics, 661–​62 DNA methylation, chromatin state, and, 82–​85 overview, 85–​86 transdisciplinary research, 4 transformation zone (TZ) of the cervix, 445 transforming growth factor beta (TGF-​β1), 241, 463, 733 transfusions See blood transfusions transient abnormal myelopoiesis (TAM), 1133 transitional cell carcinoma (TCC) See renal pelvis cancer; ureter cancer/​ureteral cancer translational bioinformatics, 424 translational research, 424, 573 See also application research transparency (research), 103 transplants See organ transplantation transvaginal ultrasound (TVUS), 1255 traumatic brain injury (TBI) and brain tumors, 1052 trichloroethylene (TCE) drinking water, 319, 320 and metabolomics, 79, 80f and myeloma, 806 and non-​Hodgkin lymphoma (NHL), 782 and renal cell cancer, 967 Trichomonas vaginalis and prostate cancer, 1008 tricyclic antidepressants (TCAs), 422, 780 trihalomethanes (THMs), 312, 313 and bladder cancer, 981 triple-​negative breast cancer, 862, 865, 865f, 866, 869t, 870–​72 trisomy21 See Down syndrome tubal carcinoma, 32 tubal intraepithelial carcinoma (TIC), 889 tubal ligation and ovarian cancer, 895 tubulopapillary neoplasm, 661 tumor, odyssey of a, 9 tumor classification See classification tumor composition See also clones; subclones intertumoral heterogeneity See classification intratumoral heterogeneity, 37 tumor development, cancer development and differentiation tumor diagnosis See also cancer diagnosis; detection ongoing challenges in, 3–​4 tumor differentiation and evolution, 14, 14f tumorigenesis See carcinogenesis tumor infiltrating lymphocyte (TIL), 1062 tumor initiation See malignant transformation tumor location, anatomic, 31 See also cancer sites tumor markers, 3, 989–​91 See also specific markers tumor microenvironment (TME), 15 tumor necrosis factor (TNF), 778 tumor necrosis factor (TNF) inhibitors, 423 tumor necrosis factor α (TNFα), 319, 359, 379, 448, 601, 605, 646, 893, 1034 tumor node metastasis (TNM) stage See TNM (tumor, node, and metastasis) staging system tumor progression See also angiogenesis; metastasis invasion, 13 tumor protein p53 (TP53) See p53; TP53 (tumor protein p53) gene tumor protein p63 See TP63 tumor protein p73 See TP73 tumor size See also small tumors point mutations and, 636 tumor suppressor genes, 497–​98 inactivation of, 9–​12, 47, 82, 445, 535, 545, 605, 612, 616, 662, 675, 682, 767, 835, 909, 933, 989, 1137 See also inactivating mutations point mutations in, 11 See also point mutations role of, 10–​11 tumor terminology, 19, 21f See also cancer: terminology Turcot syndrome and CNS tumors, 1135 twin studies, 53, 54, 66 in Hodgkin lymphoma, 753–​54 in leukemia, 735 in non-​Hodgkin lymphoma (NHL), 779, 874 in testicular cancer, 1022 type2 diabetes mellitus (T2DM) See diabetes mellitus: type 2 typhoid carrier state and biliary tract cancer, 665 tyrosine kinase inhibitors, 11, 48, 530 tyrosine kinases, 11, 48 tyrosinemia and hepatocellular carcinoma, 646 UGT1A6 gene, 514, 987, 988 ulcerative colitis (UC) See also colitis-​ associated colorectal carcinoma; inflammatory bowel disease and colorectal cancer, 683, 695 and small intestine cancer, 675 ultrasound, transvaginal, 1255 ultraviolet A (UVA) radiation, 249, 1225 artificial sources of, 252, 1072, 1098–​99 and DNA damage, 252, 1097 and erythema, 1223 and immune suppression, 253, 1098, 1223 and skin cancer, 254, 1033, 1080, 1097–​99 solar, 249, 250, 1072 sun protection and, 1222–​24 ultraviolet B (UVB) radiation, 249, 1225 artificial sources of, 252, 1098, 1099 and DNA damage, 252, 254, 1090, 1091, 1097, 1099, 1225 and erythema, 1223 and immune suppression, 253 and skin cancer, 1072, 1079, 1080, 1090, 1091, 1097, 1099, 1223 solar, 249–​50, 1221, 1225 sun protection and, 1222–​24 and vitamin D synthesis, 253, 332, 1222, 1225 ultraviolet C (UVC) radiation, 249–​50 ultraviolet (UV) index (UVI), 250 ultraviolet protection factor (UVF), 1222 ultraviolet (UV) radiation (UVR), 571–​72 See also solar radiation; UVB treatment; vitamin D artificial sources, 251–​52 See also tanning cancers associated with, 254 Hodgkin lymphoma, 759–​60 keratinocyte cancers, 253–​54, 1097, 1105 melanoma, 254, 1068, 1071, 1075, 1079 non-​Hodgkin lymphoma (NHL), 785 ovarian cancer, 896 thyroid cancer, 848–​49 determinants of solar irradiance and solar dose, 249–​50 future research, 255  1307 Index methods of measurement, 249 phenotypic markers of exposure, 251 prevention reducing sun exposure, 254–​55 restricting indoor tanning, 255 protection from See sun protection solar radiation and the electromagnetic spectrum, 249 ultraviolet (UV) radiation (UVR) carcinogenesis, biologic mechanisms of DNA damage, 252 DNA repair, 252–​53 gene expression, 253 immunosuppression, 253 mutagenesis, 253 vitamin D synthesis, 253 ultraviolet (UV) signature mutations, 252–​54, 1061, 1062, 1071, 1076, 1080, 1082, 1090, 1091 umbrellas to protect skin and eyes from sun, 1224 under-​diagnosis, 109 United States Preventive Services Task Force (USPSTF), 879–​80 upper aerodigestive tract (UADT) cancer, 217–​18, 220, 566 See also esophageal cancer; laryngeal cancer; oral cancers; oral cavity cancer uranium, military workers exposed to depleted, 729 ureter cancer/​ureteral cancer incidence, 962, 963t risk factors, 969–​71 cigarette smoking, 200 urinary mutagens and bladder cancer, 987 urinary stasis and bladder cancer, 985–​86 urinary tract cancers See also specific cancers cigarette smoking and, 200 urinary tract infections (UTIs) and bladder cancer, 984–​85 urine pH and bladder cancer, 986 urothelial carcinoma (UCC) See renal pelvis cancer; ureter cancer/​ureteral cancer uterine cancer See endometrial cancer uterine cervix, cancer of See cervical cancer UVB treatment, 1099 See also ultraviolet B (UVB) radiation uveal melanoma See ocular melanoma/​uveal melanoma vaccine-​preventable oncogenic infections, 1217–​19 See also specific infections future directions, 1219 vaccines See also HPV vaccination hepatitis B, 649, 1217–​18 and non-​Hodgkin lymphoma (NHL), 781 vaginal cancer demographic trends, 947, 948f, 948t disease burden, 947 future research, 950 genetics, 950 personal and family history of anogenital cancers and, 950 prevention, 950 risk factors, 949–​50 cigarette smoking, 201 temporal trends, 947, 948f tumor classification, 948–​49 histology, 947–​48, 949t HPV-​ vs non-​HPV-​related cancers, 948 vaginal intraepithelial neoplasia (VAIN), 947, 948t, 948f, 949, 950 variant allele fraction (VAF), 46 variants of unknown significance (VUS), 48, 65 varicella zoster virus (VZV), and glioma, 1054 vascular endothelial growth factor (VEGF), 332, 463 vasculature, 15 See also angiogenesis vegetables See fruit and vegetable consumption vegetarianism, 339, 505 VEGF (vascular endothelial growth factor), 332, 463 VEGF pathway, 463 VERB (CDC program to increase physical activity in children), 1214 vestibular schwannoma, 145t, 1041t, 1042 See also acoustic neuroma VHL gene, 10, 961, 968, 1177 See also von Hippel–​Lindau (VHL) disease vinyl chloride (VC) and angiosarcoma, 643 and soft tissue sarcoma, 933–​34 viral capsid antigen (VCA), 493, 751, 752 viral infections, 16, 103 See also infections; specific viruses and socioeconomic status–​cancer association, 153, 154 types of cancer caused by See also cervical cancer: HPV in childhood cancers, 1127 keratinocyte cancers, 1101 myeloma, 804 nervous system tumors, 1054 salivary gland cancer, 572 soft tissue sarcoma, 834 visceral adipose tissue (VAT), 351, 352, 693 visual inspection with acetic acid (VIA), 938, 1196 visual inspection with Lugol’s iodine (VILI), 927, 938 vitamin A, 334 See also beta-​carotene and bladder cancer, 982 vitamin B complex See also folate and bladder cancer, 983 vitamin C, 334 and laryngeal cancer, 512 vitamin D, 253, 332–​33 See also solar radiation; ultraviolet (UV) radiation and bladder cancer, 983 and colorectal cancer, 692 and Hodgkin lymphoma, 759–​60 and HPV and cervical cancer, 934 and keratinocyte cancers, 1102 and non-​Hodgkin lymphoma (NHL), 784 and ovarian cancer, 896 and renal cell cancer, 965 sun exposure, sun protection, and, 1221, 1224, 1225 ultraviolet (UV) radiation and synthesis of, 253 vitamin E, 334 See also alpha-​tocopherol and esophageal cancer, 584 and prostate cancer, 1009–​11 vitamin K antagonists (VKA), 423 vitamins See also nutrients; specific vitamins and ovarian cancer, 894, 896 vitamin and mineral combinations, 335 1307 von Hippel–​Lindau (VHL) disease, 9, 968, 1177 See also VHL gene and renal cell cancer, 968 vulvar cancer demographic trends, 947, 948f, 948t disease burden, 947 future research, 950 genetics and, 950 personal and family history of anogenital cancers and, 950 prevention, 950 risk factors, 949–​50 cigarette smoking, 201 HPV, 443, 444 temporal trends, 947, 948f tumor classification, 948–​49 histology, 947–​48 HPV-​ vs non-​HPV-​related cancers, 948 vulvar intraepithelial neoplasia (VIN), 947, 948, 948f, 948t, 949 VUS (variants of unknown significance), 48, 65 waist circumference (WC), 352, 693, 805, 872–​73 waist-​to-​hip ratio (WHR), 352, 693, 805, 872–​73 Waldenström macroglobulinemia See lymphoplasmacytic lymphoma/​ Waldenström macroglobulinemia warfarin, 423 watchful waiting See active surveillance (AS) cohorts water, drinking, 305 See also specific contaminants climate change and, 321 communities exposed to industrial chemicals in, 319–​21 disinfection byproducts in, 312–​13, 322 exposure misclassification in epidemiologic studies, 305 future directions, 305–​6 regulation of, 1239, 1249–​50, 1250t EPA standards for contaminants, 1249–​50, 1250t waterborne exposures, 321 See also under water, drinking waterpipes, 203 weight, birth See birth weight weight change, timing of, 352–​53 weight gain, 352, 354–​55, 355t See also obesity and breast cancer, 872 physical activity and prevention of, 379 and renal cell cancer, 964–​65 and thyroid cancer, 849–​50 weight loss changes in biomarkers with, 359 effect of, 358–​59 intentional, 358–​59 WHIM (warts, hypogammaglobulinemia, immunodeficiency, and myelokathexis) syndrome, 950 white blood cell (WBC) transcriptomes, 85–​86 WHO (World Health Organization) See International Classification of Diseases for Oncology whole exome sequencing (WES), 2, 11, 623, 1178 See also exome-​wide sequencing vs exome sequencing, 1055 genome-​wide association studies (GWAS) and, 89 vs linkage analysis, 56 1308 1308 whole exome sequencing (WES) (cont.) next-​generation sequencing (NGS) and, 33, 34, 78, 989, 991, 1055 strengths and weaknesses, 34t, 44 technology advancement in, 222 vs whole genome sequencing (WGS), 45, 1055 whole exome sequencing (WES) studies, 12, 44, 45, 66, 89, 804, 1006, 1055, 1056, 1178 See also TCGA; whole exome sequencing whole genome amplification (WGA), 46, 46f, 47 whole genome sequencing (WGS), 11, 12, 33, 34, 44, 45, 59, 61, 69, 83, 446, 804 WGS reference panels, 58 vs whole exome sequencing, 45, 1055 Index whole genome shotgun bisulfite sequencing (WGBS-​seq), 49–​50 Wilms’ tumor, 1138 wine, 215, 216, 564, 1102 See also alcohol consumption Wiskott-​Aldrich syndrome (WAS), 465, 778 women See also females; gender; reproductive factors; specific topics cancer mortality rates by age and socioeconomic status, 149f leading causes of cancer death among, 118f most common cancer sites in, 109–​10, 111f wood industry/​woodworking and nasopharyngeal cancer, 496 World Cancer Research Fund (WCRF), 329 World Health Organization (WHO) See International Classification of Diseases for Oncology xeroderma pigmentosa (XP), 1103, 1104 X-​linked hyper-​IgM syndrome See class-​switch recombination (CSR) deficiencies X-​linked lymphoproliferative disease (XLP), 465, 778 X-​linked recessive disorders, 465, 778, 1126, 1177 X-​rays See ionizing radiation zalcitabine, 417 zidovudine, 417 ... case-​control and 10 cohort studies), 1985– 20 01 Utah, Genealogy database, 1966– 20 10 Minnesota, Case series, 20 00– 20 04 3 62 174 363 484 20 0 24 7 888 326 654 323 1183 1408 136 123 4 20 99 22 00 420 888 6 52 697... 888 6 52 697 323 120 5 5 .25 5.0 2. 8 3 .2 2.09 2. 49 3.3 1 .23 2. 79 3.67 1.76 2. 1–​13 .2 1 .2 24 .5 1.3–​6.3 1.8–​5.6 1.01–​4.33 1.3–​4.7 1.8–​6.1 0.53– 2. 85 1.44–​4.08 1. 02 ​13.14 1.19– 2. 61 (Falk et al.,... features and EBV genome polymorphisms Gastric Cancer, 18 (2) , 24 6– 25 5 PMID: 24 7710 02 Chun N, and Ford JM 20 12 Genetic testing by cancer site: stomach Cancer J, 18(4), 355–​363 PMID: 22 846738 Coggon