{"title":"Immune Gene Signature Expression Differs between African American and Caucasian Patients with Renal Cell Carcinoma","authors":"P. Ghatalia, Aangi J Shah, M. Slifker","doi":"10.3233/kca-220003","DOIUrl":null,"url":null,"abstract":"BACKGROUND: Predictive immune signatures such as the T-effector, the 26-gene “Renal 101 Immuno signature” and the 18-gene T-cell inflamed gene expression profile were developed in clinical trials enrolling predominantly Caucasians and there is a dearth of literature comparing tumor biology between African American (AA) and Caucasian patients. OBJECTIVE: To compare the immune gene signature expression in AA (n = 55) and Caucasian (n = 457) patients. METHODS: Raw gene expression count data were downloaded from the TCGA KIRC dataset and tumor samples from “white” and “black or AA” patients were selected. The gene expression values of the immune signatures were VST-transformed normalized counts and compared between the groups. RESULTS: There were 457 Caucasian and 55 AA patients in the TCGA. The immune gene expression in all three signatures was significantly lower in AA patients compared to Caucasians (p < 0.05). We validated our findings in an independent dataset using Nanostring Immune Profile Panel. Since the majority of AA tumors in TCGA were stage I (71%), we compared gene expression between stage I AA tumors (n = 39) with stage I Caucasian tumors (n = 220). Once again, the immune gene expression was significantly lower in AA patients compared to Caucasians (p < 0.05), indicating differences in tumor biology between the races. CONCLUSIONS: Low expression of predictive immune gene signatures in AA compared to Caucasian patients indicates a possible difference in the biology of their tumors. Future studies are needed to validate our findings in other datasets and to study the predictive role of these signatures in AA patients.","PeriodicalId":17823,"journal":{"name":"Kidney Cancer","volume":" ","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kidney Cancer","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/kca-220003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
BACKGROUND: Predictive immune signatures such as the T-effector, the 26-gene “Renal 101 Immuno signature” and the 18-gene T-cell inflamed gene expression profile were developed in clinical trials enrolling predominantly Caucasians and there is a dearth of literature comparing tumor biology between African American (AA) and Caucasian patients. OBJECTIVE: To compare the immune gene signature expression in AA (n = 55) and Caucasian (n = 457) patients. METHODS: Raw gene expression count data were downloaded from the TCGA KIRC dataset and tumor samples from “white” and “black or AA” patients were selected. The gene expression values of the immune signatures were VST-transformed normalized counts and compared between the groups. RESULTS: There were 457 Caucasian and 55 AA patients in the TCGA. The immune gene expression in all three signatures was significantly lower in AA patients compared to Caucasians (p < 0.05). We validated our findings in an independent dataset using Nanostring Immune Profile Panel. Since the majority of AA tumors in TCGA were stage I (71%), we compared gene expression between stage I AA tumors (n = 39) with stage I Caucasian tumors (n = 220). Once again, the immune gene expression was significantly lower in AA patients compared to Caucasians (p < 0.05), indicating differences in tumor biology between the races. CONCLUSIONS: Low expression of predictive immune gene signatures in AA compared to Caucasian patients indicates a possible difference in the biology of their tumors. Future studies are needed to validate our findings in other datasets and to study the predictive role of these signatures in AA patients.