Background: Alternative polyadenylation (APA) is emerging as a major post-transcriptional mechanism for gene regulation, and dysregulation of APA contributes to several human diseases. However, the functional consequences of APA in human cancer are not fully understood. Particularly, there is no large-scale analysis in cancer cell lines. Methods: We characterized the global APA profiles of 6398 patient samples across 17 cancer types from The Cancer Genome Atlas and 739 cancer cell lines from the Cancer Cell Line Encyclopedia. We built a linear regression model to explore the correlation between APA factors and APA events across different cancer types. We used Spearman correlation to assess the effects of APA events on drug sensitivity and the Wilcoxon rank-sum test or Cox proportional hazards model to identify clinically relevant APA events. Results: We revealed a striking global 3'UTR shortening in cancer cell lines compared with tumor samples. Our analysis further suggested PABPN1 as the master regulator in regulating APA profile across different cancer types. Furthermore, we showed that APA events could affect drug sensitivity, especially of drugs targeting chromatin modifiers. Finally, we identified 1971 clinically relevant APA events, as well as alterations of APA in clinically actionable genes, suggesting that analysis of the complexity of APA profiles could have clinical utility. Conclusions: Our study highlights important roles for APA in human cancer, including reshaping cellular pathways and regulating specific gene expression, exemplifying the complex interplay between APA and other biological processes and yielding new insights into the action mechanism of cancer drugs.
Background: Alternative polyadenylation (APA) is emerging as a major post-transcriptional mechanism for gene regulation, and dysregulation of APA contributes to several human diseases. However, the functional consequences of APA in humancancer are not fully understood. Particularly, there is no large-scale analysis in cancer cell lines. Methods: We characterized the global APA profiles of 6398 patient samples across 17 cancer types from The Cancer Genome Atlas and 739 cancer cell lines from the Cancer Cell Line Encyclopedia. We built a linear regression model to explore the correlation between APA factors and APA events across different cancer types. We used Spearman correlation to assess the effects of APA events on drug sensitivity and the Wilcoxon rank-sum test or Cox proportional hazards model to identify clinically relevant APA events. Results: We revealed a striking global 3'UTR shortening in cancer cell lines compared with tumor samples. Our analysis further suggested PABPN1 as the master regulator in regulating APA profile across different cancer types. Furthermore, we showed that APA events could affect drug sensitivity, especially of drugs targeting chromatin modifiers. Finally, we identified 1971 clinically relevant APA events, as well as alterations of APA in clinically actionable genes, suggesting that analysis of the complexity of APA profiles could have clinical utility. Conclusions: Our study highlights important roles for APA in humancancer, including reshaping cellular pathways and regulating specific gene expression, exemplifying the complex interplay between APA and other biological processes and yielding new insights into the action mechanism of cancer drugs.
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