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Obesity shows statistically significant enrichment with distinct driver mutations in lung adenocarcinoma, endometrial carcinoma, and cancers of unknown primaries, independent of clinical and demographic covariates.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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[https://doi.org/10.1038/s41588-024-01969-3](https://doi.org/10.1038/s41588-024-01969-3)  \nObesity-dependent selection of driver mutations in cancer  \nReceived: 9 January 2024  \nAccepted: 1 October 2024  \n\n| Published online: 28 October 2024 |\n| --- |\n|  Check for updates |\n\nCerise Tang1, Venise Jan Castillon1, Michele Waters  1, Chris Fong1,  \nTricia Park  1, Sonia Boscenco1, Susie Kim1, Kelly Pekala  1,  \nJian Carrot-Zhang  1, A. Ari Hakimi  2, Nikolaus Schultz  1, Irina Ostrovnaya3, Alexander Gusev  4,5,6, Justin Jee  1,7  & Ed Reznik  1   \nObesity isa risk factor for cancer, but whether obesity is linked to specific genomic subtypes of cancer is unknown. We examined the relationship between obesity and tumor genotype in two clinicogenomic corpora. Obesity was associated with specific driver mutations in lung adenocarcinoma, endometrial carcinoma and cancers of unknown primaries, independent of clinical covariates, demographic factors and genetic ancestry. Obesity is therefore a driverofetiological heterogeneity in some cancers.  \nThe physiological and environmental forces leading to cancers with specific genotypes are largely unknown. Evenasoncogenic mutations emerge in healthy tissue, a confluence of physiological, immunological and epigenetic changes ultimately elicits tumorigenesis1. Obesity is a risk factor for the development of numerous cancers2,3 and growing evidence suggests that medical interventions to reduce obesity can reduce cancer risk4. Obesity itself is associated with changes in systemic immune surveillance, metabolism and inflammation5–7. In composite, these changes have the potential to shape the selective pressure for specific driver mutations in cancer, connecting the evolution of tumor-intrinsic genotypes to aspects of systemic health.  \nTesting the hypothesis that body mass index (BMI, a quantitative surrogate of obesity status) associates with specific tumor genotypesat population scale requires jointly collected clinical and genomic data, which is largely absent in large-scale cancer genomics datasets to date. We systematically extracted information on BMI and other demographic factors in 34,274 patients profiledas part of their routine clinical care by the MemorialSloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) clinical sequencing platform8 (Extended Data Fig. 1). We assessed the statistical association between BMI and tumor genotype by modeling the incidence of mutationsin 341 cancer-associated genes asa function of BMI, focusing on gene–cancer type pairs with sufficient numbers of mutant patients for adequate statistical power (Methods). Considering only oncogenic  \nmutations as annotated by a Food and Drug Administration-recognized database9, we identified six genes across three separate cancer types demonstrating statistically significant enrichment with BMI in specific cancer types (q \u003C 0.05) (Fig. 1a and Supplementary Table 1). In lung adenocarcinoma, three genes, KRAS (q = 2.6 × 10−5, estimate = 0.03), SETD2 (a tumor-suppressive histone methyltransferase, q = 1.31 × 10−2, estimate = 0.06) and PPP2R1A (a protein phosphatase known to regulate a variety of pathways, including phosphoinositide 3-kinase signaling, q = 1.31 × 10−2, estimate = 0.16), were mutated ata higher frequency inpatients with obesity and one (EGFR q = 3.0 × 10−10, estimate = −0.05) was mutated ata lower frequency in the same patient group, although the number of patients with SETD2 and PPP2R1A mutations was small (Table 1). In addition, we foundBAP1 in cancers of unknown primaries tobe positively associated with BMI (q = 3.5 × 10−2, estimate = 0.15) and POLE in uterine endometrioid carcinoma to be negatively associated with BMI (q = 1.6 × 10−2, estimate = −0.08). POLE was similarly associated withalow BMI ina cohort restricted to only patients with endometrioid carcinoma (P = 6 × 10−3, estimate = −0.09). In contrast, we found nostatistically signi","cbCaivHiwS3FLtHS","https://ap.wps.com/l/cbCaivHiwS3FLtHS","pdf",2484818,11,"English","# Overview\n# BMI and tumor genotype analysis\n# Significant gene–cancer type associations\n## Lung adenocarcinoma: KRAS, SETD2, PPP2R1A, EGFR\n## Uterine endometrioid carcinoma: POLE\n## Cancers of unknown primaries: BAP1\n# Lack of associations for silent mutations and copy number alterations","[{\"question\":\"What question does the study address about obesity and cancer?\",\"answer\":\"It tests whether obesity is associated with specific genomic subtypes of cancer rather than cancer risk alone.\"},{\"question\":\"How was obesity represented in the analysis?\",\"answer\":\"Obesity status was quantified using body mass index (BMI) as a surrogate variable.\"},{\"question\":\"Which cancer types and driver genes showed significant BMI associations?\",\"answer\":\"The study reports BMI-linked enrichment for specific driver mutations across lung adenocarcinoma, uterine endometrioid carcinoma, and cancers of unknown primaries, including genes such as KRAS, SETD2, PPP2R1A, EGFR, POLE, and BAP1.\"}]","Obesity-dependent selection of driver mutations in cancer | PDF",1789993657,28]