Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers Journal Article

   

Authors:	Osmanbeyoglu, H. U.; Shimizu, F.; Rynne-Vidal, A.; Alonso-Curbelo, D.; Chen, H. A.; Wen, H. Y.; Yeung, T. L.; Jelinic, P.; Razavi, P.; Lowe, S. W.; Mok, S. C.; Chiosis, G.; Levine, D. A.; Leslie, C. S.
Article Title:	Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers
Abstract:	Chromatin accessibility data can elucidate the developmental origin of cancer cells and reveal the enhancer landscape of key oncogenic transcriptional regulators. We develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to combine chromatin accessibility data with large tumor expression data and model the effect of enhancers on transcriptional programs in multiple cancers. We generate a new ATAC-seq data profiling chromatin accessibility in gynecologic and basal breast cancer cell lines and apply PSIONIC to 723 patient and 96 cell line RNA-seq profiles from ovarian, uterine, and basal breast cancers. Our computational framework enables us to share information across tumors to learn patient-specific TF activities, revealing regulatory differences between and within tumor types. PSIONIC-predicted activity for MTF1 in cell line models correlates with sensitivity to MTF1 inhibition, showing the potential of our approach for personalized therapy. Many identified TFs are significantly associated with survival outcome. To validate PSIONIC-derived prognostic TFs, we perform immunohistochemical analyses in 31 uterine serous tumors for ETV6 and 45 basal breast tumors for MITF and confirm that the corresponding protein expression patterns are also significantly associated with prognosis. © 2019, The Author(s).
Journal Title:	Nature Communications
Volume:	10
ISSN:	2041-1723
Publisher:	Nature Publishing Group
Date Published:	2019-09-25
Start Page:	4369
Language:	English
DOI:	10.1038/s41467-019-12291-6
PUBMED:	31554806
PROVIDER:	scopus
PMCID:	PMC6761109
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072651929&doi=10.1038%2fs41467-019-12291-6&partnerID=40&md5=676b7676201e76be66020502503bfdb1
Notes:	Article -- Export Date: 1 November 2019 -- Source: Scopus

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