Dataset Information

Integrative analysis of DNA methylation and microRNA expression reveals mechanisms of disparity in hepatocellular carcinoma [RNA-Seq]

ABSTRACT: We evaluate the epigenetic mechanisms of racial disparity in HCC through an integrated analysis of DNA methylation, miRNA, and combined regulation of gene expression. Specifically, we acquired DNA methylation, mRNA-seq, and miRNA-seq data through the analysis of tumor and adjacent normal liver tissues from African Americans (AA) and European Americans (EA) with HCC. Results: Using mixed ANOVA, we identified cytosine-phosphate-guanine (CpG) sites, mRNAs, and miRNAs that are statistically significantly altered in HCC vs. adjacent normal in a race-specific manner. Through integrative analysis, we identified significantly differentially expressed genes in HCC with disparate epigenetic regulation, associated with changes in miRNA expression for AA and DNA methylation for EA.

ORGANISM(S): Homo sapiens

PROVIDER: GSE176271 | GEO | 2021/09/29

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Translational Relevance Historically, African Americans have been underrepresented in clinical cancer research. Diversity helps to ensure equal access to new cancer therapies and better treatment for everyone. Cancer research is increasingly focused on classifying patients according to molecular profiles for particular groups. We provide a detailed molecular analysis from paired NSCLC tissues that identified differential coding and noncoding RNA expression in NSCLC from African Americans (AA) and European Americans (EA). Similar to other tumor types, we determined that race-enriched gene and microRNA expression signatures suggest a more aggressive disease in African Americans. Based on predicted drug resistance to adjuvant chemotherapies, AA may not equally benefit from the same range of clinical drugs as EA. Our findings provide a rationale for integrating coding and noncoding transcriptome profiles, along with clinical, demographic, and genomic data, when determining treatment options. Abstract Purpose: To determine if racial differences in gene and microRNA expression translates to differences in lung tumor biology with clinical relevance in African Americans (AA) and European Americans (EA). Experimental Design: The NCI-Maryland Case Control Study includes seven Baltimore City hospitals and is overrepresented with AA patients (~40%). Patients that underwent curative NSCLC surgery between 1998 and 2014 were enrolled. Comparative molecular profiling used mRNA (n = 22 AAs and n = 19 EAs) and microRNA (n = 42 AAs and n = 55 EAs) expression arrays to track differences in paired fresh frozen normal tissues and lung tumor specimens from AA and EA. Pathway enrichment, predicted drug response, tumor microenvironment infiltration, cancer immunotherapy antigen profiling, and microRNA target enrichment were assessed. Results: AA-enriched differential gene expression was characterized by stem-cell and invasion pathways. Differential gene expression in lung tumors from EA were primarily characterized by cell proliferation pathways. Population-specific gene expression was partly driven by population-specific miRNA expression profiles. Drug susceptibility predictions revealed a strong inverse correlation between AA resistance and EA sensitivity to the same panel of drugs. Statistically significant differences in M1 and M2 macrophage infiltration was observed in AA (P <0.05), however, PD-L1, PD-L2 expression was similar between both. Conclusions: Comparative transcriptomic profiling revealed clear differences in lung tumor biology between AA and EA. Increased participation by AA in lung cancer clinical trials are needed to integrate, and leverage, transcriptomic differences with other clinical information to maximize therapeutic benefit in both AA and EA. GSEA, Connectivity Map, CIBERSORT, cancer immunotherapy antigen profiling, and hypergeometric testing for overlapping miRNA targets were performed.

Dataset Information

Integrative analysis of DNA methylation and microRNA expression reveals mechanisms of disparity in hepatocellular carcinoma [RNA-Seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets