Identification of transcription factor co-regulators that drive prostate cancer progression
Abstract In prostate cancer (PCa), and many other hormone-dependent cancers, there is clear evidence for distorted transcriptional control as disease driver mechanisms. Defining which transcription factor (TF) and coregulators are altered and combine to become oncogenic drivers remains a challenge,...
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| Autores principales: | , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2020
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4631e065a23b463eb4e0b14a0f46990a |
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| Sumario: | Abstract In prostate cancer (PCa), and many other hormone-dependent cancers, there is clear evidence for distorted transcriptional control as disease driver mechanisms. Defining which transcription factor (TF) and coregulators are altered and combine to become oncogenic drivers remains a challenge, in part because of the multitude of TFs and coregulators and the diverse genomic space on which they function. The current study was undertaken to identify which TFs and coregulators are commonly altered in PCa. We generated unique lists of TFs (n = 2662), coactivators (COA; n = 766); corepressors (COR; n = 599); mixed function coregulators (MIXED; n = 511), and to address the challenge of defining how these genes are altered we tested how expression, copy number alterations and mutation status varied across seven prostate cancer (PCa) cohorts (three of localized and four advanced disease). Testing of significant changes was undertaken by bootstrapping approaches and the most significant changes were identified. For one commonly and significantly altered gene were stably knocked-down expression and undertook cell biology experiments and RNA-Seq to identify differentially altered gene networks and their association with PCa progression risks. COAS, CORS, MIXED and TFs all displayed significant down-regulated expression (q.value < 0.1) and correlated with protein expression (r 0.4–0.55). In localized PCa, stringent expression filtering identified commonly altered TFs and coregulator genes, including well-established (e.g. ERG) and underexplored (e.g. PPARGC1A, encodes PGC1α). Reduced PPARGC1A expression significantly associated with worse disease-free survival in two cohorts of localized PCa. Stable PGC1α knockdown in LNCaP cells increased growth rates and invasiveness and RNA-Seq revealed a profound basal impact on gene expression (~ 2300 genes; FDR < 0.05, logFC > 1.5), but only modestly impacted PPARγ responses. GSEA analyses of the PGC1α transcriptome revealed that it significantly altered the AR-dependent transcriptome, and was enriched for epigenetic modifiers. PGC1α-dependent genes were overlapped with PGC1α-ChIP-Seq genes and significantly associated in TCGA with higher grade tumors and worse disease-free survival. These methods and data demonstrate an approach to identify cancer-driver coregulators in cancer, and that PGC1α expression is clinically significant yet underexplored coregulator in aggressive early stage PCa. |
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