Gallinger, Steven

Abstract Background The associations between different types of diabetes, characterized by distinct pathophysiology and genetic architecture, and pancreatic ductal adenocarcinoma (PDAC) risk are not understood. Methods We investigated associations of genetic susceptibility to type 2 diabetes (T2D), 8 T2D mechanistic clusters, type 1 diabetes (T1D), and maturity-onset diabetes of the young (MODY) with PDAC risk. We used genome-wide association study (GWAS) summary-level statistics for T2D (242 283 cases, 1 569 734 controls), T1D (18 942 cases, 501 638 controls), and PDAC (10 244 cases and 360 535 controls) in individuals of European ancestry. Results Two-sample Mendelian randomization (MR) using the Robust Adjusted Profile Score (MR-RAPS) method indicated that genetically predicted T2D was associated with PDAC risk (OR = 1.10; 95% CI = 1.05 to 1.15), particularly the T2D obesity (OR = 1.28; 95% CI = 1.15 to 1.42) and lipodystrophy (OR = 1.25; 95% CI = 1.03 to 1.51) clusters. No association was observed for T1D with PDAC risk (OR = 1.01; 95% CI = 0.99 to 1.02). Pathway/gene-set analysis using the summary-based Adaptive Rank Truncated Product (sARTP) method revealed a significant association between the MODY gene-sets and PDAC risk (P = 1.5 × 10−8), which remained after excluding 20 known PDAC GWAS loci (P = 7.6 × 10−4). HNF1A, FOXA3, and HNF4A were the top contributing genes after excluding the previously identified GWAS loci regions. Conclusions Our results from this genetic association study support that T2D, particularly the obesity and lipodystrophy mechanistic clusters, and MODY genomic susceptibility regions play a role in the etiology of PDAC.

Abstract Background: Evidence suggests that, compared to later-onset colorectal cancer (CRC), early-onset CRC (diagnosed before 50 years of age) occur more frequently in rectal location and less frequently in proximal colon location. Studies also indicate heterogeneity of molecular characteristics within early-onset CRCs and between early-onset and later-onset CRCs. Understanding how tumor molecular features and biological aggressiveness of early-onset CRC differ by detailed tumor location is important in personalized patient management. Methods: Using 14,004 CRC cases including 3,089 early-onset cases from The Cancer Genome Atlas and the Genetics and Epidemiology of CRC Consortium (GECCO), we examined microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF mutations in cancers of the cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. We further conducted CRC-specific survival analyses of detailed tumor location stratified by molecular characteristics using multivariable Cox proportional hazards models. Results: The proportions of MSI-high, CIMP-high, and BRAF-mutated early-onset tumors gradually increased from the rectum (8.8%, 3.4%, and 3.5%, respectively) to the ascending colon (46% MSI-high; 15% CIMP-high) or transverse colon (8.6% BRAF-mutated), followed by declines in the cecum for MSI-high (36%) and BRAF-mutated (4.6%) tumors. Notably, later-onset MSI-high tumors showed a continuous decrease in KRAS mutation prevalence from the rectum (36%) to ascending colon (9%; Ptrend <0.001) followed by an increase in the cecum (14%), while early-onset MSI-high cancer showed no such trend. In survival analyses, there was a trend for better CRC-specific survival from the cecum to sigmoid colon (Ptrend<0.001) (but not to rectum), which did not significantly differ by age of diagnosis (Pinteraction=0.61). Multivariable-adjusted hazard ratios (HRs) for sigmoid vs. cecum were 0.86 (95% CI, 0.64-1.14) for early-onset cases and 0.81 (95% CI, 0.70-0.93) for later-onset cases. Notably, the prognostic association of tumor location differed by MSI status (Pinteraction=0.001). Non-MSI-high tumors exhibited the cecum-to-sigmoid trend for better CRC-specific survival [Ptrend <0.001; multivariable-adjusted HR for the sigmoid colon (vs. cecum), 0.80; 95% CI, 0.70-0.92], whereas MSI-high tumors demonstrated an opposite cecum-to-sigmoid trend for worse survival (Ptrend = 0.020; the corresponding HR, 2.13; 95% CI, 1.15-3.92). Conclusions: Our findings support biogeographical and pathogenic heterogeneity of CRC in different age groups and colorectal subsites. Both detailed colorectal location and tumor molecular features need to be accounted for prognostication of early-onset and later-onset CRCs to advance precision medicine. Citation Format: Tomotaka Ugai, Yin Cao, Koichiro Haruki, Tabitha A. Harrison, Daniel D. Buchanan, Peter T. Campbell, Andrew T. Chan, Steven Gallinger, Marc J. Gunter, Michael Hoffmeister, Mark A. Jenkins, Roger L. Milne, Polly A. Newcomb, Rish K. Pai, Andrew J. Pellatt, Robert E. Schoen, Bethany Van Guelpen, Michael O. Woods, Amanda I. Phipps, Ulrike Peters, Shuji Ogino. Molecular characteristics and prognosis of early-onset colorectal cancer according to detailed anatomical locations: Comparison to later-onset cases [abstract]. In: Proceedings of the AACR Special Conference on Colorectal Cancer; 2022 Oct 1-4; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_1):Abstract nr A010.

AbstractIt is of great scientific interest to identify interactions between genetic variants and environmental exposures that may modify the risk of complex diseases. However, larger sample sizes are usually required to detect gene‐by‐environment interaction (G × E) than required to detect genetic main association effects. To boost the statistical power and improve the understanding of the underlying molecular mechanisms, we incorporate functional genomics information, specifically, expression quantitative trait loci (eQTLs), into a data‐adaptive G × E test, called aGEw. This test adaptively chooses the best eQTL weights from multiple tissues and provides an extra layer of weighting at the genetic variant level. Extensive simulations show that the aGEw test can control the Type 1 error rate, and the power is resilient to the inclusion of neutral variants and noninformative external weights. We applied the proposed aGEw test to the Pancreatic Cancer Case–Control Consortium (discovery cohort of 3,585 cases and 3,482 controls) and the PanScan II genome‐wide association study data (replication cohort of 2,021 cases and 2,105 controls) with smoking as the exposure of interest. Two novel putative smoking‐related pancreatic cancer susceptibility genes, TRIP10 and KDM3A, were identified. The aGEw test is implemented in an R package aGE.

Abstract Registry-based epidemiologic studies suggest associations between chronic inflammatory intestinal diseases and pancreatic ductal adenocarcinoma (PDAC). As genetic susceptibility contributes to a large proportion of chronic inflammatory intestinal diseases, we hypothesize that the genomic regions surrounding established genome-wide associated variants for these chronic inflammatory diseases are associated with PDAC. We examined the association between PDAC and genomic regions (±500 kb) surrounding established common susceptibility variants for ulcerative colitis, Crohn's disease, inflammatory bowel disease, celiac disease, chronic pancreatitis, and primary sclerosing cholangitis. We analyzed summary statistics from genome-wide association studies data for 8,384 cases and 11,955 controls of European descent from two large consortium studies using the summary data-based adaptive rank truncated product method to examine the overall association of combined genomic regions for each inflammatory disease group. Combined genomic susceptibility regions for ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis were associated with PDAC at P values < 0.05 (0.0040, 0.0057, 0.011, and 3.4 × 10−6, respectively). After excluding the 20 PDAC susceptibility regions (±500 kb) previously identified by GWAS, the genomic regions for ulcerative colitis, Crohn disease, and inflammatory bowel disease remained associated with PDAC (P = 0.0029, 0.0057, and 0.0098, respectively). Genomic regions for celiac disease (P = 0.22) and primary sclerosing cholangitis (P = 0.078) were not associated with PDAC. Our results support the hypothesis that genomic regions surrounding variants associated with inflammatory intestinal diseases, particularly, ulcerative colitis, Crohn disease, inflammatory bowel disease, and chronic pancreatitis are associated with PDAC. Significance: The joint effects of common variants in genomic regions containing susceptibility loci for inflammatory bowel disease and chronic pancreatitis are associated with PDAC and may provide insights to understanding pancreatic cancer etiology.

Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, with few known risk factors and biomarkers. Several blood protein biomarkers have been linked to PDAC in previous studies, but these studies have assessed only a limited number of biomarkers, usually in small samples. In this study, we evaluated associations of circulating protein levels and PDAC risk using genetic instruments. Methods: To identify novel circulating protein biomarkers of PDAC, we studied 8,280 cases and 6,728 controls of European descent from the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium, using genetic instruments of protein quantitative trait loci. Results: We observed associations between predicted concentrations of 38 proteins and PDAC risk at an FDR of < 0.05, including 23 of those proteins that showed an association even after Bonferroni correction. These include the protein encoded by ABO, which has been implicated as a potential target gene of PDAC risk variant. Eight of the identified proteins (LMA2L, TM11D, IP-10, ADH1B, STOM, TENC1, DOCK9, and CRBB2) were associated with PDAC risk after adjusting for previously reported PDAC risk variants (OR ranged from 0.79 to 1.52). Pathway enrichment analysis showed that the encoding genes for implicated proteins were significantly enriched in cancer-related pathways, such as STAT3 and IL15 production. Conclusions: We identified 38 candidates of protein biomarkers for PDAC risk. Impact: This study identifies novel protein biomarker candidates for PDAC, which if validated by additional studies, may contribute to the etiologic understanding of PDAC development.

Abstract Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Abstract Background: Colorectal cancer (CRC) in densely affected families without Lynch Syndrome may be due to mutations in undiscovered genetic loci. Familial linkage analyses have yielded disparate results; the use of exome sequencing in coding regions may identify novel segregating variants. Methods: We completed exome sequencing on 40 affected cases from 16 multicase pedigrees to identify novel loci. Variants shared among all sequenced cases within each family were identified and filtered to exclude common variants and single-nucleotide variants (SNV) predicted to be benign. Results: We identified 32 nonsense or splice-site SNVs, 375 missense SNVs, 1,394 synonymous or noncoding SNVs, and 50 indels in the 16 families. Of particular interest are two validated and replicated missense variants in CENPE and KIF23, which are both located within previously reported CRC linkage regions, on chromosomes 1 and 15, respectively. Conclusions: Whole-exome sequencing identified DNA variants in multiple genes. Additional sequencing of these genes in additional samples will further elucidate the role of variants in these regions in CRC susceptibility. Impact: Exome sequencing of familial CRC cases can identify novel rare variants that may influence disease risk. Cancer Epidemiol Biomarkers Prev; 22(7); 1239–51. ©2013 AACR.