Bioanalytical strategies for the quantification of xenobiotics in biological fluids and tissues 4

Chapter Chapter Screening of PCB congeners from ovarian tumor cyst fluids using GC-MS with compound composer database software for simultaneous analysis 75 Chapter 4.1 Preface to chapter This investigation was performed to profile the level of polychlorinated biphenyls congeners in ovarian tumor cyst fluid samples to reveal the association of these persistent organic pollutants in the disease progression. A simple method using porous membrane protected µ-SPE coupled with GC-MS was used for the simultaneous quantization of 209 PCB congeners in a single GC-MS run. Each congener was individually detected and the concentration was calculated using the response factor for a group congener with the same number of chlorine atoms. This is the first research work of its kind to be carried out and the method showed good linearity of the standard calibration solutions over a concentration range of 0.50 to 100 µg L-1, and good linearity with correlation coefficients of 0.9878–0.9999 were obtained. LODs for the analytes at a signal-to-noise ratio of under GC-MS selective ion monitoring, ranged between and 29 ng L−1. The relative recoveries ranged from 81.8 to 102% with RSD values between 7.8 and 16.5%. These results further demonstrated that the µ-SPE–GC–MS system is highly effective for analyzing trace PCBs in tumor cyst fluid samples. From the 30 benign and malignant samples, 87 PCB congeners were detected, of which, 13 congeners present in more than 60% of the samples. Most of the total PCBs mean levels are significantly elevated in malignant samples. Each congener is individually detected and the concentration is calculated and the values show the higher levels of most persistent and abundant congeners, namely, CB-153 and CB-110. This investigation is significant in the research on the influence of persistent organic pollutants on the tumor malignancies. 76 Chapter 4.2 Introduction PCBs are a class of persistent organic pollutants POPs and lipophilic human- made compounds widely used in industrial and consumer products for decades before their production was banned in the United States and other developed countries in the late 1970s. PCBs remain ubiquitous environmental contaminants because of their extensive use and persistence. Furthermore, they are distributed globally via the atmosphere, oceans, and other pathways, PCBs released in one part of the world have contaminated even remote regions far from their source of origin [1, 2]. The half-life of PCBs in the blood ranges from < to > 10 years, depending on the congener [3, 4]. PCBs can be measured in most of the general population because of their environmental ubiquity and persistence. For instance, in a report of a large and statistically representative sampling of 1,800 individuals 12 years of age and older from the U.S. population, 31 of 35 PCB congeners measured were detected in over 60% of serum samples, and 21 congeners were detected in over 95% of samples [5]. The general population is exposed primarily through ingestion of contaminated foods (e.g., fish, meat, and dairy products), although occupational, ambient, and indoor sources of exposure may exist as well [6-11]. Exposure to PCBs can result in an internal dose to the female reproductive tract, as PCBs have been measured in human follicular fluid [12-14], ovarian tissue [15], placenta, uterine muscle, and amniotic fluid [16], providing evidence of exposure to critical tissues and fluid of reproductive system. PCBs have been associated with a range of adverse health effects. A large number of studies have reported that some PCB mixtures possess diverse deleterious 77 Chapter effects including carcinogenicity. Many have been shown to disrupt development and functioning of certain endocrine pathways, to alter growth, development, cognitive function, and to exhibit immunotoxicity in experimental animals, biota, and humans [17, 18]. In 1999 the Agency for Toxic Substances and Disease Registry (ATSDR) stated in their updated Toxicological Profile for Polychlorinated Biphenyls that, “Overall, the human studies provide some evidence that PCBs are carcinogenic” [19]. Many higher-chlorinated biphenyls, persistent and predominant in foods, are active as promoters in carcinogenesis. Lower-chlorinated biphenyls, predominating in indoor and outdoor air, are more readily metabolized and inhalation of such biphenyls may expose humans to reactive, possibly carcinogenic intermediates [20]. Measurements of the PCBs or their metabolites in body tissues and fluids (often called biological monitoring) have been carried out as useful approach for assessing the exposure risk in the epidemiological studies. It tries to assess how much of a contaminant can be absorbed by an exposed target individual and how much of the absorbed quantity is actually available to create a biological effect. Exposure data concerning the human reproductive system are essential for risk assessment, to identify relationships between chemical exposure and diseases or development abnormalities and to distinguish between exposed and control groups. The data obtained from contaminant profiling of body fluids, especially tumor cyst fluids, may provide supporting evidence pertaining to the tumor etiology to some extent. Unfortunately, the analysis of PCBs and their metabolites in biological fluid and tissue samples involves complex, and time-and solvent-consuming extraction, separation and clean-up steps. 78 Chapter Sample preparation and sample amount are critical steps in the analytical procedure of POPs in human biological fluids. They play an important role and can influence the results provided by the instrumental techniques in quantitative determination, which is the final step of the analysis. Classical methods use relatively large volumes of solvents i.e. 10 to 200 mL, and limit the application of these methods to adults only [21]. In addition, most of them require fractionation into subsamples during sample preparation and/or multiple chromatographic injections. Recently modern microextraction techniques such as SPME [22], dispersive liquid– liquid microextraction [23], LPME [24] have been developed for PCB analysis from biological samples. However, extremely small sample size and meager quantities of analytes present in the samples drive the need for an more efficient extraction technique suitable for complex ovarian cyst fluid samples. Porous membrane-protected µ-SPE is an effective technique for the extraction of various target analytes from complex samples without additional sample clean up [25-28]. Previously, µ-SPE has been successfully employed for the ovarian tumor cyst fluid samples and for the extraction of estrogens by our group [29]. The preparation of µ-SPE device has been explained in chapter 2. GC-MS is the most frequently used analytical technique because of its high sensitivity, selectivity, and flexibility, even for monitoring trace amounts of chemicals. However, before actual samples can be tested, standards of target substances must be analyzed for the determination of retention times and the preparation of calibration curves, which are often affected by subtle differences in GC-MS conditions [30, 31]. The necessity for standards restricts the number of 79 Chapter chemicals that can be simultaneously analyzed by GC-MS; at the present time, that number seems to be on the order of hundreds. To overcome this problem, we employed an analytical approach that can simultaneously determine 209 PCB congeners by means of GC-MS. For quantification, exact retention times are essential for correct identification of targets; standard substances must be analyzed for exact retention times; and preparing all standards before sample analysis is costly and time consuming. On this basis, new compound composer database software for simultaneous analysis (Shimadzu) by GCMS has been employed to overcome some of the limitations of traditional GC-MS analysis. The database consists of three databases - mass spectra, retention times, and calibration curves, all of which are essential for both identification and quantification of target substances. As long as the GC-MS conditions remain constant, the database system can be used to predict exact retention times and to obtain reliable quantification results without prior analysis of standards. In addition, new substances can be easily added to the database. Therefore, any chemical to which the specified GC conditions are applicable can be analyzed by means of the system. Moreover, if similar databases were constructed using different GC conditions, it would theoretically be possible to analyze, without standards, most of the chemicals to which GC is applicable. In this current study, for the first time, µ-SPE coupled with GC-MS with compound composer database software for simultaneous analysis was used for the simultaneous quantization of 209 PCB congeners from the malignant and benign ovarian tumor cyst fluid samples in a single GC-MS run. Each congener is 80 Chapter individually detected and the concentration is calculated using the response factor for a group congener with the same number of chlorine atoms. 4.3 Experimental 4.3.1 Chemicals HPLC grade solvent n-Hexane was purchased from Tedia Company. Sodium chloride & sodium sulfate were ordered from Goodrich Chemical Enterprise (Singapore). Ultrapure water was prepared from a Nanopure water purification system (Barnstead, Dubuque, USA). Surrogate standard solution (1 µg mL-1) containing 13CLabelled Mono-Deca PCBs, Internal standard solution Perylene-d12 with a concentration of 200 µg mL-1 and PCB standard solution (1 µg mL-1; mono- and diCB; µg mL-1) were purchased from Cambridge Isotope Laboratories, Inc (Andover, MA, USA). Accurel polypropylene flat sheet membrane (200 µm wall thickness, 0.2 µm pore size) was purchased from Membrana. The ethylsilane (C2) modified silica, octylsilane (C8) modified silica and octadecylsilane (C18) modified silica, activated activated carbon, Carbograph were purchased from Alltech (Carnforth, Lancashire, UK). The Ultrasonicator was bought from Midmark (Versailles, OH, USA). 4.3.2 Preparation of Standards Standard solutions of the following concentrations: Surrogate standard solution (20 ng mL-1), Perylene-d12 internal standard solution (2 µg mL-1 and 20 µg mL-1), PCB standard solution (10 ng mL-1) were prepared by stock dilution in hexane. GC-MS check standard (1µg mL-1) was made by diluting 100 µL of the custom retention index and 10 µL of method 525.2 GC-MS performance check mix in a 10 mL volumetric flask with hexane. Perylene-d12 was used as an internal standard. All working solutions and stock standard solutions were stored at 4˚C. 81 Chapter 4.3.3 Human cyst fluid samples Cyst fluid obtained from benign and malignant ovarian tumor samples were collected following approval from the Domain Specific Review Board, National Health Group, Singapore. Thirty cyst fluid samples were collected from patients who were diagnosed to have benign and malignant cysts. Small volumes of cyst fluid were collected from patients and diluted with ultrapure water to a 1:1 ratio to avoid matrix interferences and to improve the extraction precision and extraction efficiency. Moreover for complex body fluids, it is probable that the dilution reduced the extent of interferences by the protein (clogging on the membrane) and the low viscosity of the matrix that allowed more efficient extraction. Standard safety precautions were put in place during the handling of body fluids. All body fluids and solvents used in this work were discarded according to standard biohazard disposal protocols. 4.3.4 GC-MS Analysis A Restek-PCB capillary column (60 mm × 0.25 mm i.d., df = 0.25 mm, Restek Coporation, USA) was used. Helium was used as a carrier gas with linear flow rate of 32.6 cm s-1. The injection port and interface temperatures were both set at 280˚C. The GC-MS system temperature was set at 110˚C (hold for min); 15˚C min-1 to 210˚C; 2˚C min-1 to 310˚C min-1 and 5˚C min-1 to 320˚C (hold for 10 min). µL of the sample was injected into the GC-MS in splitless mode and the total GC-MS analysis time was 55.00 min. SIM mode employed for the set of target PCB compounds. The method file “PCB_RtxPCB.qgm” was obtained from the United Nations University, Tokyo; and used in this analysis. The retention indices of 209 PCBs are registered in the method file. Correction of retention time was carried out using n-alkane data. 82 Chapter 4.3.5 Preparation of µ-SPE device The preparation of the µ-SPE device has been described previously of Chapter 2. Briefly, the device consisted of sorbent held within an envelope made from polypropylene membrane sheet of dimension cm × 1.5 cm. The edges were heat sealed. Before use, each µ-SPE device was conditioned (ultrasonication for 10 with mL of methanol) and stored in the same solvent. 4.3.6 µ-SPE procedure For extraction, the µ-SPE device after drying in air for few minutes was placed in 10mL of sample solution. The sample solution was agitated at 105 rad s−1 for 60 to facilitate extraction. After extraction, the device was taken out of the sample solution, dried thoroughly with lint free tissue and placed in a 500 µL auto sampler vial for desorption. 100 µL of acetone and BSTFA mixture (5:1 ratio) was added and ultrasonicated for min. After desorption, the µ-SPE was removed from the desorption vial and the extract was kept in a water bath at 60◦C for 20 min. Finally, µL of derivatized extract was injected into the GC-MS for analysis. 4.4 Results and discussion The µ-SPE is the equilibrium based extraction procedure involving the dynamic portioning of analytes between the sorbent material and the sample solution [10]. To evaluate µ-SPE, consideration was given to factors that influence extraction efficiency such as sample size, extraction time and desorption time, desorption solvents, pH, and ionic strength. 83 Chapter 4.4.1 Extraction time Since µ-SPE involves dynamic partitioning of the PCBs between the sorbent material and the sample solution, the extraction efficiency depends on the mass transfer of analyte from the aqueous sample to the solid sorbent phase packed within the µ-SPE device. The effect of extraction time was examined in this study as mass transfer is a time-dependent process. The sample was continuously stirred at room temperature (25˚C) with a magnetic stirrer to aid the mass transfer process and to decrease the time required for equilibrium to be established. The stirring speed was fixed at 105 rad s-1. The adsorption profile of the PCBs in tumor cyst fluid sample on the µ-SPE was determined by extracting the analytes for 10 to 40 min. The highest extraction was achieved at 30 min, and after more than 30 min, no considerable improvement in peak area response was observed. In fact, for some analytes, extraction decreases beyond 30 min. This result is often observed in similar extraction work. Therefore, 30 was chosen as optimum extraction time. 4.4.2 Type of sorbent materials and ratio of composition The selection of a suitable sorbent is an important parameter. Various sorbents including ethylsilane (C2) modified silica, octylsilane (C8) modified silica and octadecylsilane (C18) modified silica, (divinylbenzeneethyleneglycoldimethacrylate), activated and carbon, Carbograph, HayeSep B (divinylbenzenepolyethyleneimine) were evaluated for µ-SPE. C18 has the highest hydrophobicity followed by C8 and C2. HayeSep A is of intermediate polarity and HayeSep B is of high polarity. Different combinations of polar and non-polar (1:1, 10 mg of each) sorbent materials were tested in extracting target analytes (An unpublished previous experiment showed efficient extraction with combination of 84 Chapter polar and non-polar sorbents for PCBs). A total of six different combinations were investigated by weighing an equal ratio of two types of sorbent materials within each µ-SPE device. The combinations tested were: (i) HayeSep A with C18; (ii) HayeSep A with C8; (iii) HayeSep A with C2; (iv) HayeSep B with C18; (v) HayeSep B with C8; (vi) HayeSep B with C2 (Figure 4.1). Based on peak area analysis, HayeSep A-C18 was found to be the effective combination for adsorption than others. The moderate to high hydrophobicity of the mixture was probably most compatible to the analytes considered. 4.4.3 Sorbent mass After selecting HayeSep A-C18 as a suitable sorbent, the suitable amount of sorbent material (ranging from to 20 mg) was investigated. Obviously, it was found that with increasing sorbent amount, the extraction efficiency increased, as denoted by higher peak areas during GC-MS analysis. The auto sampler vial cannot accommodate more than 20 mg of sorbent material. Thus, 20 mg of sorbent was the maximum amount used in all experiments. 85 Chapter Figure 4.1 Suitability of various sorbents for µ-SPE from spiked samples. Samples were spiked at levels of 10 µg L−1 of each analyte. µ-SPE conditions: samples were extracted for 30 with 10 desorption by ultrasonication; 20mg of sorbent was used. 4.4.4 Extraction volume The influence of extraction sample volume (from 10 to 25 mL) on extraction efficiency was investigated. Larger extraction efficiencies were observed as sample volumes were increased. This phenomenon is due to increasing analyte enrichment with increasing volume of the sample. A limit to this enrichment is reached when the analyte fully saturated with the adsorption sites of the sorbent. The extraction efficiency was reached at a maximum at 20 mL of sample. Hence, 20 mL was selected as the optimal sample volume. 4.4.5 Desorption solvent Selection of a suitable desorption solvent was assessed based on solubilization capability. Various organic solvents such as methanol, acetone, toluene, dichloromethane and hexane were tested. Polar solvents such as methanol and acetone were not effective in desorbing the target analytes as peak areas from analysis of respective extracts were relatively small. Since PCBs are generally non polar compounds, they should be more favorably desorbed by non-polar solvents. This proved to be the case as hexane and toluene gave comparatively better results than the other solvents, with the latter showing the most favorable performance. 4.4.6 Desorption time and carryover effects The effect of desorption time over the range of to 20 was investigated. All the PCBs were desorbed completely within 15 of ultra-sonication. Desorption efficiency was declined when shorter periods of time were used. Above 15 min, no significant increase in peak area response was observed (Figure 4.2). 86 Chapter Figure 4.2 Desorption time profiles of PCBs. Samples were spiked at levels of 10 ng L-1 of each analyte and other optimized µ-SPE conditions were used. After the first desorption, the µ-SPE device was further desorbed in toluene for a second time, to investigate carryover effects. No analytes were detected after the second desorption. Hence, the µ-SPE device could be reused; this could be done by simply rinsing the used µ-SPE device in ultrapure water, followed by ultra-sonication (2 min) in methanol. 4.4.7 Quantification of PCB congeners in cyst fluid samples To access the practical applicability µ-SPE method for PCBs, the optimized conditions were adopted in the evaluation of the method’s linearity, LODs and precision (Table 4.1). External calibration lines were plotted using cyst fluid samples spiked with known concentrations of PCBs ranging from 0.5 to 100 µg L-1, and good linearity with correlation coefficients of 0.9878–0.9999 were obtained. The relative standard deviations RSDs for samples spiked with 10 µg L-1 (three replicates) were less than 20 % showing that this method was acceptable. LODs for the analytes at a signal-to-noise ratio of under GC-MS selective ion monitoring, ranged between and 29 ng L−1 (Table 4. 1). 87 Chapter µ-SPE is a non-exhaustive procedure; therefore, relative (rather than absolute) recoveries and RSDs were calculated on the basis of three extractions of raw sample (with pre-determined (using the present technique) PCB concentrations) spiked at 10 µg L-1 of each of the analytes. The relative recoveries ranged from 81.8 to 102% (Table 4.1) with RSD values between 7.8 and 16.5%. These results further demonstrated that the µ-SPE–GC–MS system is highly effective for analyzing trace PCBs in tumor cyst fluid samples. 4.4.8 Sample analysis For the current study, cyst fluids from malignant and benign ovarian cancer tumor, under serous, mucinous, clear cells and endometroid subtypes were subjected to µ-SPE-GC–MS to determine the concentration of PCBs. A total of 15 samples collected from patients with malignant stage and 15 samples from patients with benign stage were analyzed. Before extraction, these samples were diluted with deionized water at 1:1 ratio to address matrix interferences. Extractions were performed under previously determined extraction conditions. The mean PCB concentrations in benign and malignant cyst fluid samples were shown in the Table 4.2. These results are graphically represented in Figure 4.3, which clearly shows the significant difference between benign and malignant samples studied. All group congeners were present significantly higher in malignant samples than benign samples in terms of mean concentration. Especially di-, hepta-, nano- and deca-CB group congeners are present highly elevated levels in malignant samples than benign. To measure the magnitude of the difference, the relative mean concentration of PCBs in malignant and benign samples were calculated. The CM/CB values are, 3, 2.8, 2.8 and 88 Chapter 2.9 for di-, hepta-, nano- and deca-CB respectively. The values are graphically depicted in Figure 4.4. Figure 4.3 Mean concentration profile of PCB congeners in malignant and benign ovarian tumor cyst fluid samples. Figure 4.4 Relative means of PCB congeners concentration in malignant and benign ovarian tumor cyst fluid samples. One of the strengths of the current study is the ability to measure the levels of many individual congeners. Overall, sum of the 87 congeners were detected in all 30 samples. 13 congeners were detected in greater than 60% of the sample, among them, congeners were persistent and were non-persistent congeners. CBs assigned as 89 Chapter persistent were those known or expected to have long physiological half-lives in humans due to high lipid solubility and/or low rates of metabolism [30]. Conversely, non-persistent congeners were those known to be more readily metabolized and excreted; these are indicators of recent and/or ongoing PCB exposure. The mean level of PCBs in different structural groupings and of individual congeners can be compared in both types of samples. This enables the differentiation of persistent and non-persistent congeners as well as other relevant congener groupings (Table 4.3). The maximum level of total PCBs was 0.879 µg L-1 (mean 0.568 µg L-1). Only 13 individual congeners (8 persistent and non-persistent) were detected in 60% or more of the samples and total PCBs ranging from 0.082 to 0.32 µg L-1. Malignant groups had significantly higher levels of Total PCBs, ∑13PCB60%, and ∑8PerPCBs. Conversely, non-persistent congeners were found to have marginally yet significantly higher levels in benign samples than malignant samples (Figure 4.5). No specific reasons can be drawn, since the number of samples and congeners is restricted. 90 Chapter Table 4. µ -SPE of PCB congeners: Linearity range, limit of detection and Precision (% RSD). Congeners Linearity range (µg L-1) Coefficient of correlation (r) CB-1 CB-8 CB-18 CB-44 CB-74 CB-118 CB-153 CB-189 CB-194 CB-206 CB-209 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.50 - 100 0.9899 0.9891 0.9878 0.9994 0.9977 0.9949 0.9997 0.9999 0.9998 0.9996 0.9924 Limits of detection (ng L-1) 18 22 13 21 12 42 11 29 19 20 Limits of RSD quantization (ng L-1) (%, n=3) 59 68 41 60 20 35 125 33 90 60 59 12.6 16.5 10.4 8.9 14.6 7.8 11 9.2 13.9 8.3 14.6 Avgerage recovery (%) 81.8 98.6 98.7 90.7 101.6 93.6 93.5 88.9 93.2 102.5 102 91 Chapter Table 4. Concentration of PCBs congeners and ∑PCB found benign and malignant ovarian tumor cyst fluids (mean ± s.d., n=3). PCB Congeners Mono-CB Di-CB Tri-CB Tetra-CB Penta-CB Hexa-CB Hepta-CB Octa-CB Nona-CB Deca-CB ∑PCB Mean concentration (µg L-1) Malignant samples (n = 15) Benign samples (n = 15) 0.012 ± 0.007 0.04 ± 0.003 0.013± 0.002 0.091 ± 0.07 0.083± 0.03 0.023 ± 0.02 0.1 ± 0.01 0.091 ± 0.03 0.023 ± 0.011 0.076 ± 0.027 0.552± 0.21 0.1± 0.042 0.013± 0.008 0.007± 0.002 0.07± 0.053 0.052± 0.034 0.013± 0.011 0.04± 0.024 0.062± 0.051 0.008± 0.003 0.026± 0.005 0.391± 0.233 92 Chapter 93 Chapter Table 4.3 Total PCB congeners level in ovarian tumor cyst fluid samples (Concentration in µg L-1). a,b Malignant (n =15) Mean Min Max 0.568 0.277 0.879 0.231 0.109 0.39 0.188 0.096 0.284 0.043 0.013 0.106 Benign (n=15) Mean Min Max 0.391 0.158 0.524 0.201 0.082 0.294 0.132 0.062 0.195 0.069 0.02 0.017 ∑PCBs ∑13 PCB60%a,c ∑8 PerPCBsa,d a,e ∑5 Non-perPCBs a Values below the detection limit have been replaced by the value midway between the detection limit and zero. b ∑Total PCBs: Sum of all PCB congeners tested. c ∑13PCB60%: Sum of CBs - 28,52,74,87,95,99,101,105,110,118,138,153,180. d ∑8 PerPCBs: Sum of CBs - 28,74,99,105,118,138,153,180. e ∑5 Non-perPCBs: Sum of CBs - 52,87,95,101,110. Of the individual congeners found in 60% or more of the sample, only CB-138 (0.09 µg L-1) and CB-74 (0.1 µg L-1) were significantly higher in the malignant group. Similarly CB-52 (0.11 µg L-1) and CB-118 (0.083 µg L-1) were present in higher level in benign group of samples. As expected, the most abundant and persistent congener CB153 was present in 89% of both samples. Of the 87 congeners detected congeners (CBs 18, 31, 44, 66, 149, 174, 180, 194 and 203) were present in more than 20% of the samples. The results indicated that there is a significant disparity between malignant and benign ovarian tumor cyst fluids in terms of overall total PCBs mean levels. Malignant cyst fluids shows elevated levels total PCBs in all group congeners compared to benign samples. Organic compounds including persistent organic pollutants levels in ovarian tumor cyst fluids had been discussed in chapter three in detail. Compared to those groups 94 Chapter of chemicals (heterocyclic amines, aromatic amines, organic acids, OCPs, PBDEs, nitrosamines), PCBs shows more significant variation between two groups of samples. Especially, persistent PCB congeners were present in more than 60% of the samples and were present in highly elevated levels. This is owing to its persistent nature and its abundance in the environment. Non-persistent congeners were not significantly differed among the samples; however the mean levels of total non-persistent PCBs (∑5NonperPCBs) slightly higher in benign samples than malignant. This result indicates that the recent or ongoing exposure of PCBs might not significantly associate with the malignant transformation of ovarian tumor. Figure 4.5 Total PCBs profiles: ∑Total PCBs - Sum of all PCB congeners tested, ∑13PCB60% - Sum of 13 PCB congeners present in more than 60%, ∑8 PerPCBs – Sum of persistent PCBs detected more than 60% of the samples, ∑5 Non-perPCBs - Sum of non-persistent PCBs detected more than 60% of the samples. 95 Chapter 4.5 Conclusion In this present study, porous membrane protected µ-SPE conjunction with GC-MS was successfully applied to profile the 209 PCB congeners simultaneously in a single run from ovarian tumor cyst fluid samples. The extraction conditions and choice of sorbent were optimized for efficient extraction of analytes. The method was applied to quantitate the PCBs in 30 cyst fluid samples, of which 15 were malignant and 15 were benign cyst fluids. Surprisingly, 87 PCB congeners were detected, of them 13 congeners which are abundant in environment, present in more than 60% of the samples. Most of the total PCBs mean levels are significantly elevated in malignant samples. 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[31] [32] 98 [...]... depicted in Figure 4. 4 Figure 4. 3 Mean concentration profile of PCB congeners in malignant and benign ovarian tumor cyst fluid samples Figure 4. 4 Relative means of PCB congeners concentration in malignant and benign ovarian tumor cyst fluid samples One of the strengths of the current study is the ability to measure the levels of many individual congeners Overall, sum of the 87 congeners were detected in. .. min) in methanol 4. 4.7 Quantification of PCB congeners in cyst fluid samples To access the practical applicability µ-SPE method for PCBs, the optimized conditions were adopted in the evaluation of the method’s linearity, LODs and precision (Table 4. 1) External calibration lines were plotted using cyst fluid samples spiked with known concentrations of PCBs ranging from 0.5 to 100 µg L-1, and good linearity... performance 4. 4.6 Desorption time and carryover effects The effect of desorption time over the range of 5 to 20 min was investigated All the PCBs were desorbed completely within 15 min of ultra-sonication Desorption efficiency was declined when shorter periods of time were used Above 15 min, no significant increase in peak area response was observed (Figure 4. 2) 86 Chapter 4 Figure 4. 2 Desorption time profiles... these are indicators of recent and/ or ongoing PCB exposure The mean level of PCBs in different structural groupings and of individual congeners can be compared in both types of samples This enables the differentiation of persistent and non-persistent congeners as well as other relevant congener groupings (Table 4. 3) The maximum level of total PCBs was 0.879 µg L-1 (mean 0.568 µg L-1) Only 13 individual... and CB- 74 (0.1 µg L-1) were significantly higher in the malignant group Similarly CB-52 (0.11 µg L-1) and CB-118 (0.083 µg L-1) were present in higher level in benign group of samples As expected, the most abundant and persistent congener CB153 was present in 89% of both samples Of the 87 congeners detected 9 congeners (CBs 18, 31, 44 , 66, 149 , 1 74, 180, 1 94 and 203) were present in more than 20% of. .. fluid samples The extraction conditions and choice of sorbent were optimized for efficient extraction of analytes The method was applied to quantitate the PCBs in 30 cyst fluid samples, of which 15 were malignant and 15 were benign cyst fluids Surprisingly, 87 PCB congeners were detected, of them 13 congeners which are abundant in environment, present in more than 60% of the samples Most of the total PCBs... recoveries and RSDs were calculated on the basis of three extractions of raw sample (with pre-determined (using the present technique) PCB concentrations) spiked at 10 µg L-1 of each of the analytes The relative recoveries ranged from 81.8 to 102% (Table 4. 1) with RSD values between 7.8 and 16.5% These results further demonstrated that the µ-SPE–GC–MS system is highly effective for analyzing trace PCBs in. .. significantly elevated in malignant samples Each congener is individually detected and the concentration is calculated and the values show the higher levels of most persistent and abundant congeners, namely, CB-153 and CB-110 This investigation is highly important in the research on the cumulative effect of persistent organic pollutants on the progression of ovarian tumor 96 Chapter 4 4.6 References [1]... found to be the effective combination for adsorption than others The moderate to high hydrophobicity of the mixture was probably most compatible to the analytes considered 4. 4.3 Sorbent mass After selecting HayeSep A-C18 as a suitable sorbent, the suitable amount of sorbent material (ranging from 5 to 20 mg) was investigated Obviously, it was found that with increasing sorbent amount, the extraction... samples in terms of mean concentration Especially di-, hepta-, nano- and deca-CB group congeners are present highly elevated levels in malignant samples than benign To measure the magnitude of the difference, the relative mean concentration of PCBs in malignant and benign samples were calculated The CM/CB values are, 3, 2.8, 2.8 and 88 Chapter 4 2.9 for di-, hepta-, nano- and deca-CB respectively The values . 2˚C min -1 to 310˚C min -1 and 5˚C min -1 to 320˚C (hold for 10 min). 4 µL of the sample was injected into the GC-MS in splitless mode and the total GC-MS analysis time was 55.00 min. SIM. protein (clogging on the membrane) and the low viscosity of the matrix that allowed more efficient extraction. Standard safety precautions were put in place during the handling of body fluids. . supporting evidence pertaining to the tumor etiology to some extent. Unfortunately, the analysis of PCBs and their metabolites in biological fluid and tissue samples involves complex, and time-and