Jenkins, Mark A.

Background: Considering the pathophysiological importance of the intestine-passing microbiota, we hypothesized that the mutational and microbial profiles of colorectal cancer might gradually change along detailed anatomical locations and that these trends might differ by the age of diagnosis and the microsatellite instability (MSI) status. Methods: We assessed somatic mutations and selected bacterial species in colorectal carcinomas along the cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum, utilizing targeted sequencing data ( N = 5685) from the Genetics and Epidemiology of Colorectal Cancer Consortium and tissue microbial data ( N = 1389) from the Health Professionals Follow-up Study and Nurses’ Health Study. Results: There were decreasing trends from the cecum to rectum in the prevalence of gene mutations in the IGF/PI3K, receptor tyrosine kinase (RTK)/RAS, TGFB, and WNT signaling pathways (all P trend < 0.0001), as well as high levels of Bacteroides fragilis ( P trend < 0.0001) and high levels of Fusobacterium nucleatum ( P trend = 0.0029) (but not enterotoxigenic Bacteroides fragilis or pks+ Escherichia coli ). Conversely, TP53 pathway mutations showed an increasing cecum-to-rectum trend ( P trend < 0.0001). Similar to later-onset cases diagnosed at ages 50 years and older, in early-onset cases diagnosed under the age of 50 years, we found generally decreasing cecum-to-rectum trends of IGF/PI3K, RTK/RAS, TGFB, and WNT pathway mutations and an increasing cecum-to-rectum trend in TP53 pathway mutations. By contrast, the cecum-to-rectum prevalence-changing trends in IGF/PI3K, RTK/RAS, TGFB, and TP53 pathway mutations were present in non–MSI-high tumors but not in MSI-high tumors (all P interaction < 0.0052). Conclusion: Non–MSI-high colorectal cancers exhibited decreasing cecum-to-rectum trends of IGF/PI3K, RTK/RAS, and TGFB pathway mutations (and an increasing trend of TP53 pathway mutations), in contrast to MSI-high tumors that demonstrated no such trends. Our study highlights the importance of detailed colorectal subsite information combined with tumor molecular and microbial characteristics in colorectal cancer research.

Abstract Background Being able to estimate the risk of metachronous disease in a patient with colorectal cancer (CRC) could enable risk-appropriate surveillance. The aim of this study was to develop a risk-prediction model to estimate individual 10-year risk of metachronous disease following a CRC diagnosis. Methods A population-based cohort of patients with CRC was recruited soon after diagnosis between 1997 and 2012 from the United States, Canada, and Australia. Cox regression with the least absolute shrinkage and selection operator penalization was used to identify factors that predicted the risk of a new primary CRC diagnosed at least 1 year after the initial CRC diagnosis. Potential predictors included demography, anthropometry, lifestyle factors, comorbidities, personal and family cancer history, medication use, age at diagnosis, and pathological features of the first CRC. Internal validation through bootstrapping was used to evaluate the discrimination and calibration. Results We included 6085 CRC cases; 138 (2.3%) of these cases were diagnosed with metachronous disease over a median of 12 years (IQR = 5-17 years). Metachronous CRC risk was predicted by body mass index; smoking status; level of physical activity; family history of cancer and synchronous CRC; stage, grade, histological type, and DNA mismatch repair status; and age at diagnosis of the first CRC. The model was valid with a C statistic of 0.65 (95% CI = 0.63 to 0.68) and a calibration slope of 0.873 (SD = 0.087). Conclusions Metachronous CRC can be predicted with reasonable accuracy using a prediction model that consists of clinical variables collected as part of routine practice.

Abstract Menopausal users of hormone replacement therapy (HRT) are at increased breast cancer risk and decreased colorectal cancer (CRC) risk compared with individuals who have never used HRT, but these opposing associations may differ by familial risk of breast cancer and CRC. We harmonized data from 3 cohorts and generated separate breast cancer and CRC familial risk scores based on cancer family history. We defined moderate or strong family history as a risk score of 0.4 or higher, where 0.4 was equivalent to a 50-year-old woman with 1 parent diagnosed with either breast cancer or CRC at 55 years of age. Of 24 486 women assessed, 1243 and 405 were diagnosed with incident breast cancer and CRC, respectively. For breast cancer, menopausal HRT ever use versus never use hazard ratios were 1.27 (95% CI = 1.11 to 1.45) for a breast cancer familial risk score below 0.4 and 1.01 (95% CI = 0.82 to 1.25) for a breast cancer familial risk score of 0.4 or higher (Pdifference = .08). For CRC, menopausal HRT hazard ratios were 0.63 (95% CI = 0.50 to 0.78) for a CRC familial risk score below 0.4 and 1.21 (95% CI = 0.73 to 2.00) for a CRC familial risk score of 0.4 or higher (Pdifference = .03). Associations with menopausal HRT use that apply to the general population may not hold for women at moderate or strong familial risk of these cancers.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769 ), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047 ), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Abstract Deep learning may detect biologically important signals embedded in tumor morphologic features that confer distinct prognoses. Tumor morphologic features were quantified to enhance patient risk stratification within DNA mismatch repair (MMR) groups using deep learning. Using a quantitative segmentation algorithm (QuantCRC) that identifies 15 distinct morphologic features, we analyzed 402 resected stage III colon carcinomas [191 deficient (d)-MMR; 189 proficient (p)-MMR] from participants in a phase III trial of FOLFOX-based adjuvant chemotherapy. Results were validated in an independent cohort (176 d-MMR; 1,094 p-MMR). Association of morphologic features with clinicopathologic variables, MMR, KRAS, BRAFV600E, and time-to-recurrence (TTR) was determined. Multivariable Cox proportional hazards models were developed to predict TTR. Tumor morphologic features differed significantly by MMR status. Cancers with p-MMR had more immature desmoplastic stroma. Tumors with d-MMR had increased inflammatory stroma, epithelial tumor-infiltrating lymphocytes (TIL), high-grade histology, mucin, and signet ring cells. Stromal subtype did not differ by BRAFV600E or KRAS status. In p-MMR tumors, multivariable analysis identified tumor-stroma ratio (TSR) as the strongest feature associated with TTR [HRadj 2.02; 95% confidence interval (CI), 1.14–3.57; P = 0.018; 3-year recurrence: 40.2% vs. 20.4%; Q1 vs. Q2–4]. Among d-MMR tumors, extent of inflammatory stroma (continuous HRadj 0.98; 95% CI, 0.96–0.99; P = 0.028; 3-year recurrence: 13.3% vs. 33.4%, Q4 vs. Q1) and N stage were the most robust prognostically. Association of TSR with TTR was independently validated. In conclusion, QuantCRC can quantify morphologic differences within MMR groups in routine tumor sections to determine their relative contributions to patient prognosis, and may elucidate relevant pathophysiologic mechanisms driving prognosis. Significance: A deep learning algorithm can quantify tumor morphologic features that may reflect underlying mechanisms driving prognosis within MMR groups. TSR was the most robust morphologic feature associated with TTR in p-MMR colon cancers. Extent of inflammatory stroma and N stage were the strongest prognostic features in d-MMR tumors. TIL density was not independently prognostic in either MMR group.

AbstractSurvivors of colorectal cancer (CRC) are at risk of developing another primary colorectal cancer ‐ metachronous CRC. Understanding which pathological features of the first tumour are associated with risk of metachronous CRC might help tailor existing surveillance guidelines. Population‐based CRC cases were recruited from the United States, Canada and Australia between 1997 and 2012 and followed prospectively until 2022 by the Colon Cancer Family Registry. Metachronous CRC was defined as a new primary CRC diagnosed at least 1 year after the initial CRC. Those with the genetic cancer predisposition Lynch syndrome or MUTYH mutation carriers were excluded. Cox regression models were fitted to estimate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for the associations. Of 6085 CRC cases, 138 (2.3%) were diagnosed with a metachronous CRC over a median follow‐up time of 12 years (incidence: 2.0 per 1000 person‐years). CRC cases with a synchronous CRC were 3.4‐fold more likely to develop a metachronous CRC (adjusted HR: 3.36, 95% CI: 1.89–5.98) than those without a synchronous tumour. CRC cases with MMR‐deficient tumours had a 72% increased risk of metachronous CRC (adjusted HR: 1.72, 95% CI: 1.11–2.64) compared to those with MMR‐proficient tumours. Compared to cases who had an adenocarcinoma histologic type, those with an undifferentiated histologic type were 77% less likely to develop a metachronous CRC (adjusted HR: 0.23, 95% CI: 0.06–0.94). Existing surveillance guidelines for CRC survivors could be updated to include increased surveillance for those whose first CRC was diagnosed with a synchronous CRC or was MMR‐deficient.

Abstract Background: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors’ association with colorectal cancer risk and survival differs by SBS88. Methods: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer–specific survival using Cox proportional hazards regression (N = 3,465 cases). Results: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66–0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer–specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47–7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78–1.21, Pheterogeneity = 0.066). Conclusions: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer–specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. Impact: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.

Germline pathogenic variants in the DNA mismatch repair (MMR) genes (Lynch syndrome) predispose to colorectal (CRC) and endometrial (EC) cancer. Lynch syndrome specific tumor features were evaluated for their ability to support the ACMG/InSiGHT framework in classifying variants of uncertain clinical significance (VUS) in the MMR genes. Twenty-eight CRC or EC tumors from 25 VUS carriers (6xMLH1, 9xMSH2, 6xMSH6, 4xPMS2), underwent targeted tumor sequencing for the presence of microsatellite instability/MMR-deficiency (MSI-H/dMMR) status and identification of a somatic MMR mutation (second hit). Immunohistochemical testing for the presence of dMMR crypts/glands in normal tissue was also performed. The ACMG/InSiGHT framework reclassified 7/25 (28%) VUS to likely pathogenic (LP), three (12%) to benign/likely benign, and 15 (60%) VUS remained unchanged. For the seven re-classified LP variants comprising nine tumors, tumor sequencing confirmed MSI-H/dMMR (8/9, 88.9%) and a second hit (7/9, 77.8%). Of these LP reclassified variants where normal tissue was available, the presence of a dMMR crypt/gland was found in 2/4 (50%). Furthermore, a dMMR endometrial gland in a carrier of an MSH2 exon 1-6 duplication provides further support for an upgrade of this VUS to LP. Our study confirmed that identifying these Lynch syndrome features can improve MMR variant classification, enabling optimal clinical care.

Abstract Observational studies have suggested a protective role for eosinophils in colorectal cancer (CRC) development and implicated neutrophils, but the causal relationships remain unclear. Here, we aimed to estimate the causal effect of circulating white blood cell (WBC) counts (N = ~550 000) for basophils, eosinophils, monocytes, lymphocytes and neutrophils on CRC risk (N = 52 775 cases and 45 940 controls) using Mendelian randomisation (MR). For comparison, we also examined this relationship using individual‐level data from UK Biobank (4043 incident CRC cases and 332 773 controls) in a longitudinal cohort analysis. The inverse‐variance weighted (IVW) MR analysis suggested a protective effect of increased basophil count and eosinophil count on CRC risk [OR per 1‐SD increase: 0.88, 95% CI: 0.78‐0.99, P = .04; OR: 0.93, 95% CI: 0.88‐0.98, P = .01]. The protective effect of eosinophils remained [OR per 1‐SD increase: 0.88, 95% CI: 0.80‐0.97, P = .01] following adjustments for all other WBC subtypes, to account for genetic correlation between the traits, using multivariable MR. A protective effect of increased lymphocyte count on CRC risk was also found [OR: 0.84, 95% CI: 0.76‐0.93, P = 6.70e‐4] following adjustment. Consistent with MR results, a protective effect for eosinophils in the cohort analysis in the fully adjusted model [RR per 1‐SD increase: 0.96, 95% CI: 0.93‐0.99, P = .02] and following adjustment for the other WBC subtypes [RR: 0.96, 95% CI: 0.93‐0.99, P = .001] was observed. Our study implicates peripheral blood immune cells, in particular eosinophils and lymphocytes, in CRC development, highlighting a need for mechanistic studies to interrogate these relationships.

Abstract Background: DEPendency of association on the number of Top Hits (DEPTH) is an approach to identify candidate susceptibility regions by considering the risk signals from overlapping groups of sequential variants across the genome. Methods: We applied a DEPTH analysis using a sliding window of 200 SNPs to colorectal cancer data from the Colon Cancer Family Registry (CCFR; 5,735 cases and 3,688 controls), and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO; 8,865 cases and 10,285 controls) studies. A DEPTH score &gt; 1 was used to identify candidate susceptibility regions common to both analyses. We compared DEPTH results against those from conventional genome-wide association study (GWAS) analyses of these two studies as well as against 132 published susceptibility regions. Results: Initial DEPTH analysis revealed 2,622 (CCFR) and 3,686 (GECCO) candidate susceptibility regions, of which 569 were common to both studies. Bootstrapping revealed 40 and 49 candidate susceptibility regions in the CCFR and GECCO data sets, respectively. Notably, DEPTH identified at least 82 regions that would not be detected using conventional GWAS methods, nor had they been identified by previous colorectal cancer GWASs. We found four reproducible candidate susceptibility regions (2q22.2, 2q33.1, 6p21.32, 13q14.3). The highest DEPTH scores were in the human leukocyte antigen locus at 6p21 where the strongest associated SNPs were rs762216297, rs149490268, rs114741460, and rs199707618 for the CCFR data, and rs9270761 for the GECCO data. Conclusions: DEPTH can identify candidate susceptibility regions for colorectal cancer not identified using conventional analyses of larger datasets. Impact: DEPTH has potential as a powerful complementary tool to conventional GWAS analyses for discovering susceptibility regions within the genome.