Abstract A010: Deciphering molecular and cellular differences between black and white colorectal cancers through in-depth transcriptomic analyses

Abstract

Abstract Background Compared to all other racial groups, black Americans are most likely to be diagnosed with colorectal cancer (CRC) and are most likely to die from the disease. These racial disparities have been largely attributed to social and economic conditions that impact the prevalence of co-morbidities and access to quality health care. However, the molecular and cellular differences in CRC tumors between black and white subjects remain largely uncharacterized. Methods We analyzed paired tumor and adjacent normal RNA sequencing reads collected from 15 black and 18 white subjects at Downstate Medical Center and Stony Brook University Hospital (DSSBU). 273 additional RNA sequencing and clinicopathologic data from The Cancer Genome Atlas (TCGA) were used as a validation cohort. In the TCGA dataset, 54 black subjects were propensity score matched to 108 white subjects by age, sex, tumor location and tumor stage. Differential expression analysis was performed with EdgeR and Wilcoxon rank-sum test, which was recently recommended for human population samples. Gene Ontology (GO) enrichment analysis of DEGs (absolute log 2-fold change > 1, adjust p value < 0.05) was performed using enrichR. Gene set enrichment analysis (GSEA) of hallmark gene sets was applied to the gene list ranked by fold changes. The TPM (transcript per million) data was used to estimate relative cell abundance via xCell. Antitumor immune response likelihood scores were generated via the Estimate Systems Immune Response (EaSIeR) R package. Results EdgeR analysis identified 15 and 80 DEGs in the DSSBU and TCGA datasets, respectively. Two DEGs, CXCL10 and RPPH1 have decreased expression while EEF1A1P13 has higher expression in black samples from both datasets. CXCL10 remained a DEG under the Wilcoxon test in the TCGA dataset and in propensity score matched samples. GO enrichment analysis identified “Chemokine-mediated signaling pathway” as a significantly different biological process between tumor groups with a FDR of 0.043 and 0.0004 in TCGA and DSSBU respectively. GSEA computed a negative enrichment score for IL6 JAK STAT3 signaling, Interferon alpha response, Interferon gamma response, Allograft rejection and Myc targets V1 in the black group from both datasets. xCell analysis of the DSSBU data revealed significant enrichment for endothelial cells, adipocytes and hematopoietic stem cells in black tumor samples, while white samples were significantly enriched for basophils, T helper 2 cells and common lymphoid progenitor cells. No significant differences in cell type enrichment were identified in the TCGA dataset. Predicted immunotherapy response scores were not significantly different between races in both cohorts. Conclusion Our results show differences in genes and pathways associated with inflammation and immune cell recruitment which may impact anti-tumor activity. Our future work will include experimental validation of interesting genes accounting for the differences. Citation Format: Dimitri F. Joseph, Ellen Li, Bin Chen, Joseph F. LaComb, Alexandra Guillaume. Deciphering molecular and cellular differences between black and white colorectal cancers through in-depth transcriptomic analyses [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A010.