Article | Organochlorine exposure and colorectal cancer risk Despite this, few studies of OC exposure and colorectal cancer risk have been published. Some studies in occupationally exposed cohorts have shown mixed results (Acquavella et al. 1996; Bertazzi et al. 1987; Brown 1987; Cantor and Silberman 1999; Leet et al. 1996; Wilkinson et al. 1997), whereas studies with data on individual plasma levels are rare. One study of colorectal cancer in children from rural areas exposed to pesticides showed no differences in serum OC levels compared with controls (Caldwell et al. 1981). Higher (non- signiﬁcant) serum concentrations of DDT and β-HCH in cases than in controls were reported in a small study of farmers in Egypt (Soliman et al. 1997). To test the hypothesis that exposure to OCs plays an etiologic role in colorectal can- cer, we determined serum concentrations in a subset of samples from a hospital-based case–control study. In addition, we investi- gated the relationship between OC concen- trations and mutations of the K-ras and p53 genes. Materials and Methods Study population. We conducted a hospital- based case–control study to assess gene– environment interactions in relation to colo- rectal cancer risk. A detailed description of the population and study methods has already been published (Landi et al. 2003). Cases were patients with a new diagnosis of colorectal adenocarcinoma attending a university hospi- tal in Barcelona, Catalonia, Spain, between January 1996 and December 1998. Controls were selected from admissions to the same hospital during this period using age and sex as frequency-matching criteria. To avoid selec- tion bias of controls, the reason for admission had to be a disease not previously diagnosed for that patient. This criterion was used to avoid inclusion of patients with chronic dis- eases who might be repeatedly admitted to hospital and modify their habits because of their disease. This procedure paralleled the cri- terion for cases, who were also newly diagnosed incident cases. Main diagnosis groups of con- trols were acute digestive surgery (19%), urol- ogy (17%), gastroenterology (16%), and orthopedic surgery (15%). The study protocol was cleared by the ethics committee of the hos- pital, and all individuals gave written, informed consent to participate and for genetic analysis of their samples to be performed. Of 523 identified cases, there were 13 (2%) refusals and 74 (14%) exclusions, with reasons including mental or other impairment and death or discharge before recruitment. We identiﬁed a total of 488 con- trols, with 36 (7%) refusals and 22 (5%) exclusions (reasons as described above). From these 436 cases and 430 controls, we selected a random sample of 140 cases and 80 controls for OC analyses for budgetary reasons. The sample size and imbalance in number between cases and controls was chosen to retain statisti- cal power for our study of K-ras and p53 mutations among cases [80% power to detect odds ratios (ORs) of 2.25 for the exposures of interest]. Controls for this study were selected using strata based on age, sex, and energy intake, the latter being used as a frequency- matching criterion because diet is a main source of exposure to OCs. Twelve samples were lost or excluded because of bad quality during laboratory analyses, and statistical tests were conducted on 132 cases and 76 controls. Interviews. Cases and controls were inter- viewed by trained personnel using a structured questionnaire. A dietary history questionnaire, previously developed and validated in the framework of the EPIC study [European Prospective Investigation into Cancer and Nutrition (EPIC) Group of Spain 1997], focused on average food consumption 1 year before diagnosis. Food groups based on bro- matologic properties were calculated from reports of items consumed. Other risk factors measured were body mass index (BMI) at diagnosis and 10 years before, parity in women, and life-long history of nonsteroidal anti-inﬂammatory drugs (NSAIDs), tobacco, and alcohol use. Organochlorine analysis. Selection of OCs for analysis was based on a literature search of commonly studied contaminants and included representatives of industrial and agrochemical compounds. Among the large family of PCB congeners, those often referred to as the ICES 7 (from International Council for the Exploration of the Sea), were selected: mono-ortho PCB congeners 28 and 118 and di-ortho PCBs 52, 101, 138, 153, 180. These PCB congeners are frequently found at high concentrations in humans and wildlife. Nonfasting blood samples were obtained at diagnosis, and serum was isolated and analyzed “blind” for OCs. We calculated lipid-corrected concentrations of OCs by dividing serum OC concentrations by total plasma lipid concentra- tions estimated using the formula of Phillips et al. (1989), and data are expressed in nanograms of OC per gram of lipid. OCs were analyzed by gas chromatography after serum samples were subjected to liquid– liquid extraction and cleanup using concen- trated sulfuric acid and hexane (Porta et al. 1999). A mass spectrometer in negative chemi- cal ionization mode was used to quantify α-, β-, γ-, and δ-HCH isomers; pentachloro- benzene (Pe-CB), HCB, PCB congeners, p,p´-DDT, and p,p´-DDE (4,4´-dichloro- diphenyltrichloroethene) were quantiﬁed on a gas chromatograph with electron capture detection. On both instruments, quantiﬁcation was performed by external standards using PCB-142 as an injection standard to correct Environmental Health Perspectives • VOLUME 112 | NUMBER 15 | November 2004 for volume. This method performed satisfacto- rily in an international intercalibration exercise within the Arctic Monitoring and Assessment Programme (AMAP 2004). Point mutations in K-ras and p53 genes, and expression of p53 protein. Fresh tumor tis- sue and normal mucosa samples were obtained from surgically extracted specimens of cases. K-ras gene mutations in codons 12 and 13 were detected and characterized by polymerase chain reaction (PCR) followed by single-strand conformation polymorphism (SSCP) analysis (Tortola et al. 1999). Aspartic acid mutations at codons 12 and 13 were conﬁrmed by means of artiﬁcially introduced restriction fragment length polymorphism. Similarly, p53 exons 4–9 were analyzed by PCR and SSCP followed by direct sequencing whenever necessary. Expression of the p53 protein was determined by immunohistochemistry, using commercially available antibodies (ab-6 Pantropic; Oncogene Research Products, VWR International GmBH, Darmstadt, Germany). We studied microsatellite instability by analyzing five microsatellite sequences (Gonzalez-Garcia et al. 2000). Statistical analysis. OC concentrations were categorized using tertiles based on all subjects. Some compounds were not detected in a high proportion of individuals. For these, the reference category consisted of values below the detection limit (LOD). When the proportion of individuals with detectable val- ues was > 50%, the values were further divided into two groups using the median value of those with values > LOD. Logistic regression was used to test the association between OCs and colorectal can- cer. When cases were subdivided into groups according to genetic alterations, we used poly- tomous logistic regression, comparing each group of cases with the whole set of controls. All analyses were adjusted for age, sex, total energy intake, and BMI at diagnosis because these had been used as frequency-matching criteria or, in case of BMI, because of con- cerns about potential confounding of OC exposure by BMI, given that cases showing lower BMI might have undergone lipid- stored OC mobilization. The impact of these adjustments on risk estimates was minimal, however. We also excluded an association between OCs and tumor stage that would be indicative of bias, because more advanced tumors are associated with greater weight loss. Potential confounding by other variables asso- ciated with disease (alcohol, NSAIDs, and food groups) was explored and rejected. These were not included in the models to avoid losing efﬁciency in the estimates owing to excessive stratiﬁcation. ORs and 95% confidence intervals (CIs) were calculated for each group compared with the reference category. We tested for linear 1461