Nghiên cứu tính đa hình thái đơn nucleotid (SNP) và đột biến một số gen trong ung thư buồng trứng TT TIENG ANH

MINISTRY OF EDUCATION AND MINISTRY OF TRAINING HEATH HANOI MEDICAL UNIVERSITY ====== LE NGUYEN TRONG NHAN SINGLE NUCLEOTIDE POLYMORPHISMS (SNP) AND MUTATIONS OF SOME GENES IN OVARIAN CANCER Specialism : Obstetrics-Gynecology Code : 9720105 ABSTRACT OF THESIS HA NOI - 2022 The thesis has been completed at HANOI MEDICAL UNIVERSITY Supervisors: Supervisor: Prof Nguyen Viet Tien M.D Ph.D Reviewer 1: Prof Cao Ngoc Thanh M.D Ph.D Reviewer 2: Prof Luong Thi Lan Anh M.D Ph.D Reviewer 3: Trinh Hung Dung M.D Ph.D The thesis will be presented in front of the board of university examiners and reviewers at… on ….2022 This thesis can be found at: National Library Library of Hanoi Medical University INTRODUCTION Nowadays, the incidence and mortality from cancer diseases worldwide tend to increase rapidly Ovarian cancer (OC) is one of the most common cancers in women The disease often progresses silently with non-specific or no symptoms in the early stages, so it is often missed and diagnosed late However, if the condition is detected and treated promptly at an early stage, the prognosis is much better than that of the advanced stage Most ovarian cancers develop spontaneously About 10% of ovarian cancer cases are related to genetic factors Most are related to Hereditary Breast and Ovarian Cancer (HBOC) syndrome due to mutations in two tumor suppressor genes BRCA1 and BRCA2, leading to decreased DNA repair function A woman's lifetime ovarian cancer risk is 1.22%, but this rate rises to 27-63% in patients with a BRCA1/2 gene mutation Women from high-risk families should receive genetic counseling and testing to promptly personalize screening, diagnosis, prevention, and treatment methods In addition, single nucleotide polymorphisms (SNPs) of DNA double-strand break repair genes such as RAD51 and XRCC3 are not pathogenic, but through altered expression of the encoded protein can affect function to repair DNA double-strand breaks, which is related to the risk of cancerous tumors, including ovarian cancer The most studied SNPs related to ovarian cancer are rs861539, rs1799794, rs1799796 of the XRCC3 gene and rs1801320, rs1801321 of the RAD51 gene, but the results of studies on patients of different ethnicities are still inconsistent To better understand the association between BRCA1, BRCA2 genes mutations, single nucleotide polymorphism (SNP) on the XRCC3, RAD51 gene, and ovarian cancer risk, we conducted this study with two objectives: Identifying BRCA1, BRCA2 gene mutations in ovarian cancer patients and their association with histopathology Identifying some single nucleotide polymorphisms (SNPs) on the XRCC3, RAD51 genes associated with the ovarian cancer risk SUMMARY OF THE NEW CONTRIBUTIONS OF THE THESIS This is the first scientific study in Vietnam on single nucleotide polymorphisms and gene mutations in ovarian cancer Identifying BRCA1 and BRCA2 gene mutations is beneficial for ovarian cancer patients to guide the use of targeted therapy with highly effective PARP inhibitors, as well as beneficial for patient’s relatives, who may be consulted for genetic testing to detect the possibility of carrying BRCA1, BRCA2 gene mutations, and for appropriate screening and prevention guidelines for breast and ovarian cancer Study results have identified eight mutations, including six on the BRCA1 gene and two on the BRCA2 gene, in 20 ovarian cancer patients associated with Hereditary breast-ovarian cancer syndrome (HBOC) All eight mutations tested on genetic databases, and bioinformatics tools for pathogenicity predicting, are pathogenic mutations that increase breast and ovarian cancer risk There is a novel mutation BRCA2:c.4022delC, has not been published yet Apply applications on large databases to personalize cancer screening and prevention advice for BRCA1, BRCA2 gene mutation carriers The identified single-nucleotide polymorphisms of two DNA double-strand break repair genes RAD51 and XRCC3, contribute to the Vietnamese genetic database Identified four single nucleotide polymorphisms of RAD51 and XRCC3 genes associated with ovarian cancer risk: rs1801320 and rs1801321 of the RAD51 gene, rs1799794 and rs1799796 of the XRCC3 gene Single nucleotide polymorphism rs861539 XRCC3 gene is not associated with ovarian cancer risk All SNPs are not related to the histology and stage of Ovarian Cancer THESIS STRUCTURE The thesis has 135 pages, including four chapters, 33 tables, charts, diagrams, 46 pictures Introduction-2 pages, Overview- 36 pages, Subjects and research methods- 15 pages, Results- 37 pages, Discussion- 42 pages, Conclusion- 02 pages, Recommendation- 01 page, References- 157 documents Article published of the thesis: 05 Chapter – OVERVIEW 1.1 Ovarian cancer Ovarian cancer is a disease in which normal ovarian cells grow abnormally and uncontrollably and produce malignant tumors on one or both ovaries The cause of ovarian cancer is still unknown Factors that affect the ovarian cancer risk include modifiable factors such as hormone replacement therapy, nutrition, lifestyle (smoking, alcohol, physical exercise), living environment, and unchangeable factors such as family history, uninterrupted menstrual cycle, endometriosis, ethnicity, especially genetic factors such as BRCA1/2 gene mutations , Ovarian cancer often progresses silently with un-specific symptoms, so it is often diagnosed late Diagnosis of ovarian cancer is gathered from clinical and subclinical examination results such as ultrasound (IOTA index malignancy assessment system, …), laboratory tests (CA125, HE4, ROMA index, RMI ), histopathological biopsies In addition to conventional treatment methods such as surgery, chemotherapy, radiation therapy, endocrine therapy, immunotherapy, patients carrying the BRCA1/2 gene mutation can use targeted therapy with Poly ADP ribose polymerase (PARP) inhibitor 1.2 BRCA1/2 gene mutations linked to ovarian cancer The BRCA1 gene is a tumor suppressor gene associated with breast and ovarian cancer that was first identified and cloned in 1994, located on the long arm of chromosome 17 (17q21) BRCA1 contains 24 exons, of which 22 coding exons are about 100 kb The normal allele produces 7.8kb mRNA and encodes the BRCA1 protein with 1863 amino acids The BRCA2 gene is located on the long arm of chromosome 13 (13q12.3) and contains 27 exons, was identified in 1994 The normal allele produces 10.4kb mRNA– encoding a protein with 3418 amino-acids In normal cells, BRCA1 and BRCA2 proteins play essential roles in maintaining genetic stability through DNA damage repair and apoptosis Loss of function of the BRCA1 and BRCA2 proteins leads to abnormal cell proliferation, leading to cancer cell formation In addition, the BRCA1 protein has endogenous ubiquitin ligase activity that has many functions, including tumor suppressor activity in breast and ovarian cancer Hereditary Breast & Ovarian Cancer syndrome (HBOC) is a syndrome that increases the risk of developing familial breast or ovarian cancer due to BRCA1 or BRCA2 Mutations in the germ cells in one allele and subsequently loss of heterozygosity in the somatic tissue Signs of this syndrome include multiple family members with breast and/or ovarian cancer, early breast/ovarian cancer, personal history of both breast and breast cancer, family history with male breast cancer According to the BRCA Exchange Database, more than 33 684 variants on the BRCA1 gene and 32 973 variants on BRCA2 The rate of variants associated with Hereditary breast and ovarian cancer (HBOC) syndromes is 66% in the BRCA1 gene and 34% in the BRCA2 gene The frequency of pathogenic BRCA1/2 Mutations in the general population is about 1/400-1/800 Remarkably, the carrying rate of BRCA1/2 mutations in ovarian cancer patients ranges from 5% to 30% but varies greatly depending on the community Mutations in the BRCA1/2 gene increase the ovarian cancer risk and other cancers Table 1.1 Cancer risk in BRCA1/2 gene mutation carriers Cancer risk Cancer site BRCA1 mutation BRCA2 mutation Population carrier carrier Breast cancer 12% 46%-87% 38%-84% Contralateral 2% in years 21.1% in 10 years 10.8% in 10 years breast cancer Ovarian cancer 1%-2% 37%-63% 16.5%-27% Male breast cancer 0.1% 1.2% to 8.9% Prostate cancer 6% to 69 y.o 8,6% to 65 y.o 15% to 65 y.o Pancreas cancer 0.5% 1%-3% 2%-7% Melanoma 1.6% increased The Jewish population is at high risk for HBOC due to the high frequency of carrying the BRCA1/2 mutations, but common are three well-studied mutations: mutations on BRCA1 (187delAG and 5385insC) and one on BRCA2 (6174delT) In different populations, BRCA1/2 mutations are exceptionally high in frequency and restricted to populations as a result of a "founder" effect (in population-genetic) called "founder" mutations 1.3 Single-nucleotide polymorphisms of RAD51, XRCC3 genes associated with ovarian cancer Single nucleotide polymorphism (SNP) is the most common type of genetic variation, where a single nucleotide substitution at a specific location in the genome between individuals of a species results in the polymorphism of genes For example, at the same position in the DNA fragment could be Adenine (A), Guanine (G) or Thymine (T) The RAD51 and XRCC3 genes are essential in repairing DNA double-strand breaks by homologous recombination The SNPs of these two genes can alter gene expression and affect overall cancer susceptibility Recent studies report that several SNPs of the RAD51 gene and the XRCC3 gene affect ovarian cancer risk 1.3.1 Single-nucleotide polymorphisms of RAD51 gene associated with ovarian cancer The RAD51 gene has position 15q15.1 (long arm of chromosome 15, region 1, band 5, sub-band 1), starting at base pair 40,694,774 and ending at base pair 40,732,340 The gene consists of 37,567 base pairs and has 14 exons The mRNA of the RAD51 gene is 2255 bp in size RAD51 protein has 339 amino acids, molecular weight 36,966Da Two common SNPs of RAD51, rs1801320 and rs1801321, have been studied as risk factors for various cancers such as breast, larynx, colorectal and ovarian cancer, etc Both SNPs are located in the 5'terminal untranslated restriction (5'UTR) region, which has been reported to be associated with alterations in gene transcription and mRNA expression SNP RAD51-rs1801320 (135G>C) is located on the 5'UTR region of exon 1; there is a conversion of Guanine (G) to Cytosine (C) at position 40,695,330 SNP RAD51-rs1801321 (172G>T) is also located on the 5'UTR region of exon 1, with a Guanine (G) to Thymine (T) transformation at position 40,695,367 1.3.2 Single-nucleotide polymorphisms of XRCC3 gene associated with ovarian cancer The XRCC3 gene is located at position 14q32.33 (long arm of chromosome 14, region 3, band 2, sub-band 33), starting from base pair 103,697,611 and ending at base pair 103,715,486 with size 17,896 bp The ten exons regulate the synthesis of the 2574 bp mRNA molecule mRNA after translation, creates a protein molecule XRCC3 with 346 amino acids, weight 37850Da Proteins involved in homologous recombination maintain genome stability XRCC3 gene SNPs such as rs861539, rs1799794 and 1799796 have been reported by many studies to be associated with the risk of cancers such as colorectal cancer, ovarian cancer, head and neck cancer, and breast cancer These SNPs directly affect XRCC3 protein structure or indirectly regulate XRCC3 gene expression, leading to changes in homologous recombination that repair DNA damage SNP XRCC3-rs861539 is located on exon 8, at position 103,699,416, where Cytosine (C) is converted to Thymine (T) which converts Threonine to Methionine on the XRCC3 protein SNP XRCC3rs1799794 located on the 5'UTR exon region at position 103,712,930 has Adenine (A) converted to Guanine (G) SNPXRCC3-rs1799796 is located on intron at position 103,699,590, with Adenine (A) converted to Guanine (G) CHAPTER - SUBJECTS AND METHODS 2.1 Subjects Objective - Identify BRCA1, BRCA2 mutations in ovarian cancer Ovarian cancer patients are diagnosed with ovarian cancer and have one or both of the following hereditary breast cancer-ovarian syndrome criteria: (1) with breast cancer, (2) have at least one close relative with ovarian cancer and/or breast cancer Objective - Identify some single nucleotide polymorphisms (SNPs) on the XRCC3, RAD51 genes that are associated with the ovarian cancer risk a Patients group: Ovarian cancer patients at the National Hospital of Obstetrics and Gynecology were diagnosed with histopathological results, did not have other cancers and agreed to participate in the study b Control group: Women with no history of ovarian cancer or other cancers came to the National Hospital of Obstetrics and Gynecology for medical examination or treatment for benign diseases The age is similar to the disease group 2.2 Research Methods 2.2.1 Research design Objective 1- Cross-sectional descriptive research method Select 20 patients who meet the conditions for taking samples for testing Then, for patients with a gene Mutation, invite family members to participate in the study to determine the same gene Mutation as the patient Make a pedigree chart Objective - Case-control study Based on the study results of Quaye (2009) and the formula for calculating sample size for casecontrol studies with estimated risk ratio (OR): With 1st type error α = 0.05 and 2nd type error β = 0.02, the constant C = 7.85 and OR = 0.65, p = 0.351, we get N = 743 Therefore, each research group should select a minimum of 372 people We selected 380 patients for patients group, 380 women without cancer for control group 2.2.2 Research process: Identifying BRCA1, BRCA2 gene mutations in ovarian cancer patients - Collect blood samples from ovarian cancer patients - Extract DNA from whole blood - New generation gene sequencing (NGS ) - Analysis and identification of gene mutations using CLC Main Workbench software - Designing primers, retesting by sequencing according to Sanger - Based on the genetic data system BRCA exchange, ClinVar, ENIGMA to determine the mutation’s pathogenicity - Take blood samples from relatives of patients carrying the mutation for gene sequencing according to Sanger - Create the genetic pedigree of the mutation Identification of single nucleotide polymorphisms of RAD51, XRCC3 genes - Collect blood samples from patients and control groups - Extract DNA from whole blood - Amplification of gene segments containing single nucleotide polymorphisms by PCR - Determination of single nucleotide polymorphisms of RAD51 and XRCC3 genes by PCR-RFLP method (restriction fragment length polymorphism) - Using statistical methods to determine the rate of single nucleotide polymorphisms and their association with ovarian cancer risk and 2.3 Time and location of research: - Research location: National Hospital of Obstetrics and Gynecology, Gene - Protein Research Center, Hanoi Medical University - Research period: From January 2017 to October 2020 2.4 Data analysis: SPSS 20.0 analysis software was used for statistical analysis Quantitative variables were tested for normal distribution by the Kolmogorov - Smirnov test The mean values of the variables were compared according to the normal distribution using the Student T-test After the genotypes of each sample were determined, the genotype and allele frequencies in the disease and control groups were compared using either the Chi-squared test or the Phi and Cramer's test and calculated the odds ratio (OR), with a 95% confidence interval (CI) With a p-value < 0.05, it was considered to be statistically significant 2.5 Ethics in the research The study was approved by the Ethics Council of Hanoi Medical University under certificate No 107/HĐĐĐHYHN dated May 30, 2017 The subjects participated voluntarily and had the right to withdraw from the study Patient information is kept confidential The technique of manipulation on the patient ensures the right expertise The research topic is done for scientific purposes and not for other purposes 2.6 Expense: The study is supported with funding from the ministerial-level study "Research and development of a process to identify single nucleotide polymorphisms and mutation on some genes related to breast and ovarian cancer", chaired by Prof Dr Nguyen Viet Tien CHAPTER – RESULTS 3.1 Identifying BRCA1, BRCA2 gene mutations in ovarian cancer patients After being extracted from the blood sample, the entire DNA sample of the patient was sequenced with new generation sequencing, resulting in out of 20 patients carrying BRCA1 and BRCA2 mutations Samples carrying the mutation were tested by Sanger sequencing with specifically designed primer pairs (40%) patients had mutations, including six patients carrying BRCA1 mutations and two patients carrying BRCA2 mutations 12 (60%) patients did not carry the mutation 3.1.1 Age characteristics of the patients Bảng 3.1 Age characteristics of the patients Mean age at diagnosis Mutation carrier BRCA1 BRCA2 mutation mutation N=06 N=02 47.67 63.50 ± 5.99 ±19.09 Total N=8 51.63 ±11.46 NonTotal carrier N=12 50.58 ±9.37 p N=20 51.00 0.147 ±9.97 The average age of diagnosis of patients carrying BRCA1 mutation is 47.67, BRCA2 mutation is 63.5 The mean age at diagnosis of mutation carriers was 51.63 and was not different from that of patients without the mutation (50.58) 3.1.2.Results of identifying BRCA1, BRCA2 gene mutations The sequenced results were compared with the standard sequence on GeneBank using CLC Main Workbench software, analyzing the BRCA1 and BRCA2 mutations' positional characteristics, and analyzing pathogenicity by the databases about BRCA1/2 mutations 11 The older sister has breast cancer KBT2.2, and the younger sister KBT2.3 does not have cancer, carrying the mutation The daughter of KBT2 (KBT2.5), her other older sister of KBT2.1, and sister’s daughter not have the mutation Figure 3.2 Pedigree mutation BRCA1:c.1621C>T of patient KBT2 Square: Male Circle: female Arrow: proband Brown: ovarian cancer Grey: Breast cancer AD BC: age of breast cancer diagnosis AD OC: age of ovarian cancer diagnosis BRCA+: Mutation carrier BRCA-: non-carrier KBT: patients and relatives ID BRCA1:c.1621C>T is present in both breast cancer patients, ovarian cancer patients, and those who have not had these cancer The mutation in KBT2 is heterozygous, not passed on to her daughter 3.2 Identifying RAD51, XRCC3 SNPs and their association with OC 380 patients and 380 matched controls should be recorded and analyzed 3.2.1 General characteristics of patient group and control group Table 3.4 General characteristics of patient and the control groups General characteristics ≤ 39 40-59 ≤ 60 The mean age The mean age of menarche Menstrual Menstruating status Menopause Age group Patient group n=380 100% 93 24.5 173 45.5 114 30.0 49.80± 15.50 15.22±1.77 166 43.7 214 56.3 Control group n=380 100% 102 26.8 170 44.7 108 28.4 49.26± 13.88 15.01±1.85 177 46.6 203 53.4 P 0.739 0.610 0.096 0.423 12 The age group distribution of both the patient and control groups was similar, with the greatest in the 40-59 age group and the lowest under 40 The mean age of the patient group (49.8) and control group (49.26) was not significantly different The mean age of menarche and menstrual status between the two groups were not also quite different 3.2.2 SNP RAD51-rs1801320 and association with OC risk Table 3.5 Genotypic/allele rateSNP rs1801320 and association with OC risk RAD51rs1801320 G Allele Genotype Recessive model Patient group Control group n % n 586 77.1 638 C 174 22.9 122 GG 242 63.7 264 GC 102 26.8 110 CC 36 9.5 GG + GC 344 90.5 374 CC 36 9.5 242 63.7 264 138 36.3 116 GG Dominant model GC + CC % Total N % p OR (CI95%) 83.9 1224 80.5 1.0 1.553 16.1 296 19.5 (1.201-2.008) 69.5 506 66.6 1.0 1.012 28.9 212 27.9 0.000 (0.734-1.394) 6.545 1.6 42 5.5 (2.710-15.807) 98.4 1.0 0.000 6.523 1.6 (2.715-15.673) 69.5 1.0 0.091 1.298 30.5 (0.959-1.756) 0.001 In the total of groups, the rate of the C allele (19%) was lower than the G allele The GG genotype had the highest frequency and the lowest CC The C allele has a 55% higher ovarian cancer risk than the G allele (ORC/G=1.55, CI95% 1.201-2.008) The frequency of CC genotypes in the Patient group was higher than in the control group, and this difference was statistically significant (p1, although the CI95% contained 3.2.6 SNP XRCC3-rs1799796 and its association with OC risk Table 3.9 Genotypic/allele rateSNP rs1799796 and association with OC risk XRCC3- rs1799796 A Allele Genotype Recessive model Patient group Control group Total n % n % N % 451 59.3 418 55.0 869 57.2 G 309 40.7 342 45.0 651 GG 60 15.8 89 23.4 149 AG 189 49.7 164 43.2 353 AA 131 34.5 127 33.4 258 AG + GG 249 65.5 253 66.6 AA 131 34.5 127 33.4 60 15.8 89 23.4 320 84.2 291 76.6 GG Dominant model AA + AG p OR (CI95%) 1.0 0.837 42.8 (0.683-1.026) 19.6 1.0 1.709 46.4 0.024 (1.159-2.521) 1.530 33.9 (1.017-2.302) 1.0 0.759 1.048 (0.776-1.415) 1.0 0.008 1.631 (1.134-2.347) 0.087 In the total of groups, the rate of the G allele (42.8%) is lower than the rate of the A allele and the GG genotype has the lowest frequency, the AG genotype has the highest frequency The rate of the G allele in the patient group (40.7%) was lower than that of the control group (45.0%) The G allele carries a lower ovarian cancer risk than the A allele with ORG/A = 0.837, but it is not statistically significant because the CI95% contains (p = 0.656) The proportion of AA and AG genotypes in the disease group was higher than in the control group; while GG was lower, the difference was statistically significant (p=0.024) Genotypes AG and AA had a 70% and 53% higher ovarian cancer risk than GG, respectively, with ORAG/GG = 1,709, ORAA/GG = 1,530, and 95% CIs not containing In dominant model genotype 16 group containing allele A (AA+AG) carries a 63% higher ovarian cancer risk than GG with ORGG/(AA+AG)=1,631 and CI95% without CHAPTER - DISCUSSION 4.1 Identifying BRCA1, BRCA2 mutations in ovarian cancer patients The gene sequencing process to identify BRCA1 and BRCA2 mutations have been designed by experts from the Gen-Protein Center, Hanoi Medical University, and accepted in the ministry-level project " Research and development of a process to identify single nucleotide polymorphisms and mutation on some genes related to breast and ovarian cancer” by Prof Dr Nguyen Viet Tien The study was conducted on 20 samples of ovarian cancer patients with one or both factors (1) co-existing with breast cancer and (2) having a relative with breast and/or ovarian cancer In 20 ovarian cancer patients with BRCA1 and BRCA2 genes sequenced by next-generation sequencing, eight mutations were identified and verified by Sanger sequencing, including (30%) patients carry BRCA1 mutations, (10%) patients have BRCA2 mutations The ratio of BRCA1:BRCA2 mutations = 3:1 is similar to the ratio of BRCA1/BRCA2 mutations associated with HBOC syndrome is 66%:34% in the overview of these two genes on the National Center Biotechnology Information (NCBI) Ginburg (2010), in a study of 292 Vietnamese breast cancer patients without a family history with only three patients with HBOC syndrome, determined the carrier rate of BRCA1/2 mutations was only 0.68%, only BRCA1 mutation and BRCA2 mutation; however, both patients were not related to HBOC syndrome Hoang Anh Vu (2020) on 101 patients with unselected ovarian cancer, eight patients with BRCA1 mutations (7.9%) and no BRCA2 mutation were identified In the database of the Myriad Genetic Testing Center, USA, observed on 162 914 patients with two criteria like this study, rate of mutation carriers from 12.1% to 64,5% The mean age at the time of diagnosis of the group of patients carrying the mutation (51.63) and the non-carrier (50.58) was similar (p=0.826) (Table 3.1) The age at diagnosis of patients with BRCA1 mutations (47.67) 17 was lower in patients with BRCA2 mutations 51.63, consistent with previous studies that ovarian cancer in BRCA2 mutation carriers occurs an average of 8-10 years later than BRCA1 mutations carriers The BRCA1/2 gene amplification products were sequenced and compared with the standard sequences on GeneBank (BRCA1: NM_007294.3 or NG_005905, BRCA2: NM_000059.3 or NG_012772) using CLC Main Workbench software The analysis results are shown in Table 3.2 and summarized in Diagram 3.1 and Diagram 3.2 According to the Human Genome Variation Society's notation principle, the names of mutations follow the nucleotide change and the proteinlevel variation In mutations of the BRCA1 gene, there are mutations on exon 11 (c.1016del A, c.1621C>T and c.2760-2763delACAG), on intron 16 (c.4986+4A>T), on exon 17 (c.4997dupA) and on exon 22 (c.5335delC) The two mutations in the BRCA2 gene are located on exon 11, where c.4022delC is a novel mutation that has not been reported, and c5453C>A has been reported previously Of the eight mutations on BRCA1 and BRCA2, there are four nonsense mutations (N) causing the premature stop-codon right at the mutation position, three frameshift mutations (F) causing the premature stop-codon after the mutated position some codons and one splice-site mutation (Ss) on the intron of 16 BRCA1 genes All eight mutations are assessed by the databases as pathogenic mutations, increasing the likelihood of HBOC-associated cancers Of the eight mutations, there are nonsense mutations (N) causing the premature termination triplet code right at the mutation position, frameshift mutations (F) causing the premature stop-codon, after the mutated position some codon and one splice-site mutation (Ss) on the intron of 16 BRCA1 genes All eight mutations are assessed by the databases bioinformatic tools to predict the pathogenicity, as pathogenic, increasing the risk of HBOC syndrome-associated cancers There are four mutations located on the ovarian cancer cluster region (OCCR) (c.1621C>T, c.2760-2763delACAG on BRCA1- 18 OCCR3 and c.4022delC, c.5453C>A on BRCA2-OCCR1) is thought to have a higher ovarian cancer risk and a lower breast cancer risk compared with extra-regional mutations In contrast, three mutations on BRCA1 c.4986+4A>T, c.4997dupA and c.5335delC located in the breast cancer cluster region (BCCR2) carry a higher breast cancer risk and a lower ovarian cancer risk compared with mutations outside this region And at the same time, three mutations in BCCR are also located in the functional region- BRCT binding with the BACH1 protein, which is thought to have a 26% higher breast cancer risk than non-carrier, and lower ovarian cancer risk, although there is no statistical significance, about 14% 4.1.3.The association between BRCA1/2 mutations and histopathology Histopathological results are mainly serous carcinoma (16 people account for 80%), of which six patients carry BRCA1/2 gene mutations, accounting for 75% of mutation carriers (Table 3.3) Although there was no statistically significant difference in histopathology between the group mutation carriers and non-carrier (p=0.358), the results were similar to previous studies reporting the rate serous carcinoma accounted for 75100% of ovarian cancer patients with BRCA1/2 mutation 4.1.4 Identifying BRCA1/2 mutations in patient's relatives Among 17 relatives of patients with BRCA1/2 mutations, who were collected for sequencing, (35.3%) carried the same mutations as in the patients The BRCA1:c.1621C>T mutation was identified in an ovarian cancer patient KBT2 whose mother and older sister both had breast cancer under the age of 50, a characteristic feature of HBOC syndrome The results of gene sequencing of family members of the patient (Figure 3.1) show that one older sister (with breast cancer) and one younger sister (who has not been diagnosed with breast cancer) carry the mutation The BRCA1:c1621C>T mutation genetic pedigree of the KBT2 patient's family was created based on the mutation test results and collected information (Figure 3.2) This mutation is present in breast cancer patient under 50 years old, ovarian cancer patient and people who have not had these cancers Mutation in patient KBT2 is heterozygous, was not inherited to her daughter 19 Patients and relatives are consulted about test results For patients with mutations, clinicians can advise selecting targeted therapy with PARP inhibitors and risk assessment for other cancers And at the same time, inform the patient's relatives to assess the risk of carrying a BRCA1/2 mutation and the ovarian and breast cancer risk Apply largedatabase-based applications to personalize the risk of carrying BRCA1/2 mutations for people with features of HBOC syndrome, and estimate the cancer risk for mutation carriers who have not yet developed cancer, as well as the impact of screening and prevention measures For example, applying the CanRisk Tool of BOADICEA research group, University of Cambridge, UK with personal and family data of KBT2.3 subject (younger sister of patient KBT2) carrying mutations without cancer to provide the diagram visually illustrates the cancer risks by age and up to 80 years of age (Diagram 4.1 and Picture 4.1) Diagram 4.1 Risk of breast (A) and ovarian (B) cancer by age Picture 4.1 The risk of breast (A) and ovarian (B) cancer to age 80 20 The Decision Tool of the National Cancer Institute, Stanford University, USA (brcatool.stanford.edu/brca.html) supports specific counseling for BRCA1/2 mutation carriers who have not had breast or ovarian cancer on the benefits of screening and prevention measures for breast and ovarian cancer, comparison of measures at different time Table 4.1 Outcomes possiblity prediction KBT2.2 Measures Screening for screening, Bilateral mastectomy prevention Bilateral (age) Salpingoophorectomy Died of other causes Died from ovarian cancer Died from breast cancer Possibility Survivors after ovarian to age 70 cancer (a) (per 100 Survivors after breast people) cancer (b) Survivors without breast and ovarian cancer (c) Survivors to age 70 (per 100 people) =(a)+(b)+(c) - MG+ - MRI - 45 - - - - MG - MG+ MRI Non- 45 mutation carrier - 50 45 45 - 11 11 17 18 18 15 12 12 11 15 14 18 18 5 10 19 13 14 11 11 12 13 5 25 27 31 12 33 24 16 18 18 17 38 24 40 53 79 54 56 60 63 62 67 74 85 (-) does not execute MG-Mammogram every year MRI-Magnetic Resonance Mammogram every year The number of survivors to age 70 (per 100) increases with the sequential and combined application of screening measures and prophylactic surgery; effectiveness of screening with combined mammography and MRI is higher than with mammography alone; Prophylactic surgery of bilateral ovary and salpingectomy alone is more effective than prophylactic surgery of bilateral mastectomy alone; The time to perform preventive surgery early will be better 4.2 Identifying RAD51, XRCC3 SNPs and association OC The incredible advances of modern genetics, especially the results of stem cell research and human genome mapping, have helped scientists predict the body's response by analyzing the patient's genome Based on each person's genetic map, personalized medicine uses detailed and delicate diagnoses to provide an accurate treatment plan that matches each person's genetic characteristics at the molecular level 21 Science has shown that many diseases are genetic in origin, so this is an essential step towards more effective treatment with fewer side effects 4.2.1 General characteristics of the patient and the control group General characteristics such as mean age, distribution of age groups, mean age of menarche and menopause status were similar between patient and control group There was no statistically significant difference (p>0.05) ) In the patients group, the age group from 40 to 60 years old accounted for the most 45.5%, and the age group