In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 2615-2615
Abstract:
Previous work indicates that identifying core transcription regulatory circuitries (CRCs) predicts tumor-specific genetic dependencies, in the form of transcription factors responsible for establishing this circuitry (Durbin, Zimmerman, Dharia, et al., 2018), which suggest targetable, onco-requisite factors. However, a systematic effort to identify CRCs across tumors has been challenging, since current approaches rely on data difficult to acquire in heterogeneous or low cell number samples. Here, we combine -omics approaches, including a newly developed algorithm to predict super-enhancer—driven CRCs in a range of tumor types. Our work leverages two characteristics CRC members: association with super-enhancers, defined using ChIP-Seq data, and highly cell type-specific expression, analyzed using the Cancer Cell-Type-Specificity (CaCTS) algorithm. CRC members uncovered with the CaCTS algorithm recover known drivers of specific tumor types and known misregulated pathways. We deeply characterized the CRC of high-grade serous ovarian cancer (HGSOC), a tumor type with poor overall prognosis for which few known driver mutations or targetable oncogenes are known. Our CRC models contain onco-requisite transcription factors that dominate the HGSOC gene expression program, including ESR1, MECOM (EVI1), and NOTCH2, each of which play important roles in other malignancies. Many of these CRC members represent HGSOC-selective dependencies in CRISPR/Cas9 screens. Profiling CRCs in HGSOC cells and presumed cells-of-origin (fallopian tube and ovarian tissue) highlights a set of CRC genes whose expression appears to have been evolved by HGSOC cells, including an isoform of the estrogen receptor. The dependence of HGSOC cells on transcription factors suggests a state of “transcriptional addiction,” which has been targeted with molecules against transcription apparatus. HGSOC lines are correspondingly susceptible to treatment with small molecules against transcriptional CDKs (CDK7 and CDK12). Also, some HGSOC-specific SEs are associated with genes druggable with existing small molecules. Thus, identifying the CRC governing HGSOC predicts dominant factors and suggests therapeutic avenues in this underserved disease. Similar predictions of CRCs in other poorly-studied tumors may also enhance understanding of those tumor cell identities and targetable nodes. Citation Format: Brian J. Abraham, Jessica Reddy, Marcos A. Fonseca, Isaac A. Klein, Lena K. Afeyan, Rosario I. Corona, Paloma Cejas, Felipe Segato, Beth Y. Karlan, Simon A. Gayther, Matthew L. Freedman, Houtan Noushmehr, Myles Brown, Ursula A. Matulonis, Kate Lawrenson, Richard A. Young. Systematic approaches to predict oncogenic transcriptional regulatory circuitries identify important nodes in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2615.
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2019-2615
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2019
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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