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Exogenous and Endogenous Risk Factors for Early-onset Colorectal Cancer

ABSTRACT: An increase in early-onset colorectal cancers (eoCRC), defined as a CRC before 50 years, is confirmed globally. CRC pathogenesis has been associated with several risk factors (family history, germline pathogenic variants, obesity, alcohol, physical activity, red meat, and a Western diet). Design: an international, multicenter, retrospective case-control study of prospectively enrolled patients; low-risk intervention study as it will perform a fecal occult blood test Endpoint: predictive power of a semi-quantitative food frequency questionnaire (SQFFQ) developed for eoCRC. Cases: Patients with a recent diagnosis of eoCRC (within 2 years from enrollment). Controls: matched by age (matching range ± 5 years) and sex. Healthy volunteers will be mainly enrolled among workers within the participating hospital center. The enrolled healthy volunteers will perform a fecal occult blood test. Variables of interest: age, sex, ethnicity, BMI at the time of eoCRC diagnosis and at 18 years old, country, tobacco smoking at the time of eoCRC diagnosis and at 18 years old, sitting time, TV-viewing time, moderate-to-vigorous physical activity (MVPA), waist circumference (cm), home blood pressure levels (mmHg), fasting blood glucose (mg/dl), regular consumption of aspirin/NSAID, calcium and folate supplements, oral contraceptive agents, post-menopausal hormones and years of consumptions, if the filled questionnaire reflects diet for the last 5-10 years before. Cases only: date of eoCRC diagnosis, symptoms at diagnosis, eoCRC localization, eoCRC stage, histological diagnosis, type of surgery, and date (if performed), chemotherapy and radiotherapy (if performed), vital status and duration of follow-up, family history of CRC and other cancers (uterus, ovary, stomach, small intestine, urinary tract/bladder/kidney, bile ducts, brain, pancreas, skin tumors), type of germline pathogenetic variant (if performed). Before the case-control study, three non-consecutive 24-hour Dietary Recalls (24hDRs) will validate the SQFFQ. The SQFFQ will be administered to the validation study group during three non-consecutive calls, including one non-weekday (30-minute 24-h-recall computer-aided personal interview). Primary Objective To measure the relative risk of specific dietary and lifestyle factors (smoking habit, alcohol intake, physical activity) for early-onset colorectal cancer in countries where eoCRC incidence is increasing versus stable/decreasing

DISEASE(S): Early Onset Colorectal Cancer,Diet Habit,Colon Cancer,Colorectal Cancer,Colorectal Neoplasms,Risk Reduction

PROVIDER: 8689 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:Background: The most important risk factors for head and neck squamous carcinoma (HNSCC) are tobacco smoking and alcohol consumption, while subgroups are caused by infection with human papillomaviruses (HPV) or Epstein-Barr virus (EBV). Here, we studied alterations of somatic copy-number in whole genome, p16 protein and TP53 mutations by alcohol drinking, smoking and viral infections. Methods: We conducted a prospective cohort study. DNA obtained from tumors and margin samples as well as peripheral blood was assayed by array comparative genomic hybridization using Agilent Whole Human Genome 180K. Mutations of p53 gene by direct sequencing, detection of HPV by polymerase-chain-reaction (PCR), quantification of EBV by reverse transcription-PCR and p16 immunohistochemical (IHC) staining were also performed. prospective cohort study: 225 tumor samples were analyzed by Agilent-022060 SurePrint G3 Human CGH miroarray 4x180K. Log2 Ratio (tumor sample DNA/normal DNA) were compared among none alcohol drinkers, moderate alcohol drinkers, heavy alcohol drinkers, none smokers, moderate smokers, heavy smokers and both. Sample characteristics weres scored as following; Human Papilloma Virus Infection (gene detected by PCR in tumor sample): positive=1; negative=0 p16 protein immunohistochemistry: positive=1; negative=0 tumor grade: matured=0; moderate=1; immature=2 Radiotherapy with or without chemotherapy after operation: performed =1; not performed =0 Recurrence/relapse: rec =1; not rec =0 suvival status:death=1; survive=0 smoking status (Pack year of smoking): none smoker=0; pack-year <20 = 1 (moderate smoker); pack-year <=20 = 2 (heavy smoker) alcohol drinking: Alcohol drinkers were divided into non-drinker or less than one drink per day =0: one and more but less than two drinks per day = moderate drinker 1: two and more drinks per day=heavy drinker 2: during the 20 years preceding their treatment for HNSCC. One drink was defined as containing approximately 10g of alcohol, which is considered equal to 30 ml of hard liquor, 100 ml of wine containing 12% alcohol, or 360 ml of beer.

Project description:Background: The incidence of colorectal cancer (CRC) has been steadily increasing in younger individuals over the past several decades for reasons that are incompletely defined. Identifying differences in gene expression profiles, or transcriptomes, in early-onset colorectal cancer (EOCRC, < 50 years old) patients versus later-onset colorectal cancer (LOCRC, > 50 years old) patients is one approach to understanding molecular and genetic features that distinguish EOCRC. Methods: We performed RNA-sequencing (RNA-seq) to characterize the transcriptomes of patient-matched tumors and adjacent, uninvolved (normal) colonic segments from EOCRC (n=21) and LOCRC (n=22) patients. The EOCRC and LOCRC cohorts were matched for demographic and clinical characteristics. We used The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) database for validation. We used a series of computational and bioinformatic tools to identify EOCRC-specific differentially expressed genes, molecular pathways, predicted cell populations, differential gene splicing events, and predicted neoantigens. Results: We identified an eight-gene signature in EOCRC comprised of ALDOB, FBXL16, IL1RN, MSLN, RAC3, SLC38A11, WBSCR27 and WNT11, from which we developed a score predictive of overall CRC patient survival. On the entire set of genes identified in normal tissues and tumors, cell type deconvolution analysis predicted a differential abundance of immune and non-immune populations in EOCRC versus LOCRC. Gene set enrichment analysis identified increased expression of splicing machinery in EOCRC. We further found differences in alternative splicing (AS) events, including one within the long non-coding RNA, HOTAIRM1. Additional analysis of AS found seven events specific to EOCRC that encode potential neoantigens. Conclusion: Our transcriptome analyses identified genetic and molecular features specific to EOCRC which may inform future screening, development of prognostic indicators, and novel drug targets.

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Exogenous and Endogenous Risk Factors for Early-onset Colorectal Cancer

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