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ERR1 and PGC1α associated mitochondrial alterations correlate with pan-cancer disparity in African Americans.


ABSTRACT:

Background

African American (AA) patients have higher cancer mortality rates and shorter survival times compared to European American (EA) patients. Despite a significant focus on socioeconomic factors, recent findings strongly argue the existence of biological factors driving this disparity. Most of these factors have been described in a cancer-type specific context rather than a pan-cancer setting.

Methods

A novel in silico approach based on Gene Set Enrichment Analysis (GSEA) coupled to Transcription Factor enrichment was carried out to identify common biological drivers of pan-cancer racial disparity using The Cancer Genome Atlas (TCGA) dataset. Mitochondrial content in patient tissues was examined using a multi-cancer tissue microarray approach (TMA).

Results

Mitochondrial oxidative phosphorylation was uniquely enriched in AA tumors compared to EA tumors across various cancer types. AA tumors also showed strong enrichment for the ERR1-PGC1α-mediated transcriptional program, which has been implicated in mitochondrial biogenesis. TMA analysis revealed that AA cancers harbor significantly more mitochondria compared to their EA counterparts.

Conclusions

These findings highlight changes in mitochondria as a common distinguishing feature between AA and EA tumors in a pan-cancer setting, and provide the rationale for the repurposing of mitochondrial inhibitors to treat AA cancers.

SUBMITTER: Piyarathna DWB 

PROVIDER: S-EPMC6546480 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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<h4>Background</h4>African American (AA) patients have higher cancer mortality rates and shorter survival times compared to European American (EA) patients. Despite a significant focus on socioeconomic factors, recent findings strongly argue the existence of biological factors driving this disparity. Most of these factors have been described in a cancer-type specific context rather than a pan-cancer setting.<h4>Methods</h4>A novel in silico approach based on Gene Set Enrichment Analysis (GSEA) c  ...[more]

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