{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["McDonald HG"],"funding":["NIA NIH HHS","NCI NIH HHS"],"pagination":["612-624"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12606903"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["240(4)"],"pubmed_abstract":["<h4>Background</h4>Colon cancer is a leading cause of mortality in Appalachian Kentucky. Studies suggest that the microbiome may influence cancer outcomes. We investigate differential gene expression, the tumor microbiome, and their association as potential drivers of disparities in colon cancer outcomes.<h4>Study design</h4>This study analyzed patients diagnosed with colon adenocarcinoma between 2010 and 2023. Demographic data were extracted from Kentucky Cancer Registry. Somatic mutations and significantly mutated genes were identified using Fisher's exact t -test. RNASeq data were processed for gene expression analysis and Holm-Bonferroni method was used to adjust p values for multiple comparisons. The STAR aligner (exotic), v2.1 pipeline, and KrakenUniq database were used to classify m"],"journal":["Journal of the American College of Surgeons"],"pubmed_title":["Survival Disparity and the Unique Genomic and Microbiome Profiles of Colon Cancer in Appalachian Kentucky."],"pmcid":["PMC12606903"],"funding_grant_id":["P30 CA177558","K01 AG070310"],"pubmed_authors":["McDonald HG","Evers BM","Bhakta AS","Hoyd R","Wang C","Goettl R","Faisal ASM","Spakowicz D","Kim J","Reagan AM"],"additional_accession":[]},"is_claimable":false,"name":"Survival Disparity and the Unique Genomic and Microbiome Profiles of Colon Cancer in Appalachian Kentucky.","description":"<h4>Background</h4>Colon cancer is a leading cause of mortality in Appalachian Kentucky. Studies suggest that the microbiome may influence cancer outcomes. We investigate differential gene expression, the tumor microbiome, and their association as potential drivers of disparities in colon cancer outcomes.<h4>Study design</h4>This study analyzed patients diagnosed with colon adenocarcinoma between 2010 and 2023. Demographic data were extracted from Kentucky Cancer Registry. Somatic mutations and significantly mutated genes were identified using Fisher's exact t -test. RNASeq data were processed for gene expression analysis and Holm-Bonferroni method was used to adjust p values for multiple comparisons. The STAR aligner (exotic), v2.1 pipeline, and KrakenUniq database were used to classify m","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Apr","modification":"2026-06-05T14:58:06.412Z","creation":"2026-05-18T03:12:42.737Z"},"accession":"S-EPMC12606903","cross_references":{"pubmed":["39868697"],"doi":["10.1097/XCS.0000000000001299","10.1097/xcs.0000000000001299"]}}