https://openworks.mdanderson.org/sumexp23/1113/thumbnail.jp

Bohlender, Ryan, PhD

Huff, Chad, PhD

Kaul, Medha

Yu, Yao, PhD

English

OpenWorks @ MD Anderson

Background• Colorectal cancer (CRC) is the third most common cancer diagnosed in both men and women in the US1.• Several genes are known to affect CRC risk, but they only explain a small proportion of the disease heritability2.MethodsReferences1) Colorectal cancer statistics: How common is colorectal cancer? American Cancer Society. Accessed August 9, 2023. https://www.cancer.org/cancer/types/colon-rectal-cancer/about/key-statistics.html. 2) Schubert SA, Morreau H, de Miranda NFCC, van Wezel T. The missing heritability of familial colorectal cancer. Mutagenesis. 2020;35(3):221-231. doi:10.1093/mutage/gez027 3) Sudlow C, Gallacher J, Allen N, et al. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age. PLoS Med. 2015;12(3). doi:10.1371/journal.pmed.1001779 4) The “All of Us” Research Program. New England Journal of Medicine. 2019;381(7):668-676. doi:10.1056/nejmsr1809937 5) Yandell M, Huff C, Hu H, et al. A probabilistic disease-gene finder for personal genomes. Genome Res. 2011;21(9):1529-1542. doi:10.1101/gr.123158.1116) Li B, Leal SM. Methods for Detecting Associations with Rare Variants for Common Diseases: Application to Analysis of Sequence Data. Am J Hum Genet. 2008;83(3):311-321. doi:10.1016/j.ajhg.2008.06.024 7) Pearlman R, Frankel WL, Swanson B, et al. Prevalence and spectrum of germline cancer susceptibility gene mutations among patients with early-onset colorectal cancer. JAMA Oncol. 2017;3(4):464-471. doi:10.1001/jamaoncol.2016.5194 8) Xu T, Zhang Y, Zhang J, et al. Germline Profiling and Molecular Characterization of Early Onset Metastatic Colorectal Cancer. Front Oncol. 2020;10. doi:10.3389/fonc.2020.568911 9) Jang E, Chung DC. Hereditary colon cancer: Lynch syndrome. Gut Liver. 2010;4(2):151-160. doi:10.5009/gnl.2010.4.2.151 ResultsResponsible Conduct of Research• Limited representation of diverse groups in MDA and UKB may exacerbate disparities in understanding genetic basis of CRC.• These disparities will be explored through African, Asian, and Hispanic representation in AOS.Acknowledgements: This work was supported by NIH/NCI R25CA056452 (Medha Kaul, Shine Chang, Ph.D., Principal Investigator). ​ Thank you to my PI, Dr. Chad Huff, and my lab team members Yao and Ryan for all the guidance and support on this project.Hypothesis The missing heritability of CRC is explained in part by undiscovered rare, intermediate-risk genetic variants.Objectives• Identify novel CRC susceptibility genes • Produce risk estimates for variants in established CRC genes and novel candidate genesMDA UKB AOSGene VAAST pval CMC pval VAAST pval CMC pval VAAST pval CMC pvalMSH6 0.13 0.012 ≤5.0 x 10-7 ≤5.0 x 10-7 ≤5.0 x 10-5 2.3 x 10-3MSH2 3.5 x 10-5 1.0 x 10-5 2.0 x 10-4 ≤5.0 x 10-7 0.023 6.4 x 10-3MLH1 7.4 x 10-4 1.8 x 10-4 5.5 x 10-6 ≤5.0 x 10-7 5.9 x 10-3 0.69APC 3.7 x 10-3 3.9 x 10-3 0.024 5.6 x 10-3 ≤5.0 x 10-5 8.1 x 10-3BRCA1 0.83 0.72 2.5 x 10-6 ≤5.0 x 10-7 0.034 0.13CHEK2 0.053 0.34 5.2 x 10-5 6.5 x 10-6 0.54 0.39BRCA2 0.85 0.74 ≤5.0 x 10-7 ≤5.0 x 10-7 0.38 0.14ATM 0.025 0.066 0.087 0.024 0.030 0.21PMS2 0.18 0.11 0.013 0.019 0.22 0.31SDHA 8.7 x 10-3 0.40 0.82 0.60 0.037 0.24CDKN2A 0.99 0.99 5.6 x 10-3 0.023 0.43 0.058RAD51C 0.59 0.99 6.3 x 10-4 5.4 x 10-3 0.17 0.86Table 1. Results of gene-based association analyses: VAAST and CMC p values from MDA, UKB, and AOS. Based on the meta-analysis results, the most significant established CRC genes and nominally significant a priori candidates with previous germline evidence for CRC were included in the table. Significant p values are bolded (genome-wide or nominal). P values with a ≤ sign are the smallest obtainable values given the number of permutations used in their respective analyses.Table 2.  ACAT-combined p values from MDA, UKB, and AOS and meta-analysis p values. Based on the meta-analysis results, the most significant established CRC genes and nominally significant a priori candidates with previous germline evidence for CRC were included in the table. Significant p values are bolded (genome-wide or nominal). Genes with an asterisk reached genome-wide significance. P values with a ≤ sign are the smallest obtainable values given the number of permutations used in the VAAST and CMC analyses.Whole-exome and whole-genome sequencing of CRC cases and controlsMD Anderson (MDA)2161 cases 4097 controlsAll of Us (AOS) European43046 cases 86140 controlsUK Biobank (UKB)33690 cases 75850 controlsGene-based association testsCMC6One df test of protein-truncating variantsVAAST5Weights rare coding variants by estimated degree of dysfunctionFor all three studies:Combine VAAST and CMC p values• Combine p values from VAAST and CMC analyses using ACAT method• Replace all p values with mid p valuesMeta-analyze p values from MDA, UKB, and AOSMeta-analyze ACAT-combined p values from MDA, UKB, and AOS • Fisher’s method (unweighted)• Stouffer’s z score method (weighted by square root of effective sample size)Generate variant-based odds ratios• Generate ORs for each study using logistic regression• Meta-analyze ORs from MDA, UKB, and AOS using METAL (weighted by inverse variance)For established and candidate genes meeting significance threshold: Calculate percent of familial relative risk explained Use OR estimates and carrier counts to calculate the percent of log familial relative risk explained by the identified variants in each geneTable 3.  Meta-analyzed variant-based odds ratios and percent of log familial relative risk explained. Based on the meta-analysis results, the most significant established CRC genes and nominally significant a priori candidates with previous germline evidence were included in the table. Significant ORs are bolded.1FRR= Familial Relative RiskTable 3 ContinuedBRCA1Truncating and pathogenic missense 0.297 1.38 (0.893, 2.14) 0.0163CHEK2Truncating and pathogenic missense 0.810 1.23 (0.951, 1.58) 0.0157BRCA2Truncating and pathogenic missense 0.437 1.45 (1.06, 1.99) 0.0333

Identifying and Characterizing Genetic Variants Associated with Colorectal Cancer

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Identifying and Characterizing Genetic Variants Associated with Colorectal Cancer

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