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Functional Taxonomy of CENPA-Bound Genes in Prostate Cancer

ABSTRACT: Functional Taxonomy of CENPA-Bound Genes in Prostate Cancer

PROVIDER: PRJNA525634 | ENA |

REPOSITORIES: ENA

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Functional Taxonomy of CENPA-Bound Genes in Prostate Cancer

Project description:Overexpression of centromeric proteins has been identified in a number of human malignancies, though their functional and mechanistic contributions to disease progression have not been characterized. CENPA, the centromeric histone H3 variant, is the epigenetic mark that determines centromere identity. Here, we demonstrate that CENPA is highly overexpressed in prostate cancer in both tissue and cell lines, and the level of CENPA expression correlates with the stage of disease. Gain-of- and loss-of-function experimentation confirms that CENPA promotes prostate cancer cell line growth. Integrated sequencing studies further reveal a previously unidentified function of CENPA as a transcriptional regulator that modulates expression of critical proliferation, cell-cycle, and centromere/kinetochore genes. Our findings, therefore, suggest a previously undescribed biological function for CENPA, a protein normally thought to be solely and importantly involved in centromere identity.

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Project description:Genomic sequencing of many thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for proliferation or survival in hundreds of cancer cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, it is likely that there exist many undiscovered tumor specific genetic dependencies, such as prostate cancer specific drivers, that represent drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated publicly available pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data revealed two known prostate cancer specific driver genes, AR and HOXB13, as the top two hits and also nominated a number of unexpected genes. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.

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