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ERR1 and PGC1? 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-PGC1?-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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