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Nat Commun. 2017 Feb 15;8:14423. doi: 10.1038/ncomms14423.

Haploinsufficiency networks identify targetable patterns of allelic deficiency in low mutation ovarian cancer.

Author information

1
Division of Gynecologic Oncology, Department of Reproductive Medicine, UCSD School of Medicine and UCSD Moores Cancer Center, 3855 Health Sciences Drive, La Jolla, California 39216, USA.
2
Centre de recherche en Cancérologie, INSERM 1052, CNRS 5286, Centre Léon Bérard, Université de Lyon, Lyon, France.
3
Division of Biomedical Informatics, Department of Medicine, UCSD School of Medicine and UCSD Moores Cancer Center, 3855 Health Sciences Drive, La Jolla, California 92093, USA.

Abstract

Identification of specific oncogenic gene changes has enabled the modern generation of targeted cancer therapeutics. In high-grade serous ovarian cancer (OV), the bulk of genetic changes is not somatic point mutations, but rather somatic copy-number alterations (SCNAs). The impact of SCNAs on tumour biology remains poorly understood. Here we build haploinsufficiency network analyses to identify which SCNA patterns are most disruptive in OV. Of all KEGG pathways (N=187), autophagy is the most significantly disrupted by coincident gene deletions. Compared with 20 other cancer types, OV is most severely disrupted in autophagy and in compensatory proteostasis pathways. Network analysis prioritizes MAP1LC3B (LC3) and BECN1 as most impactful. Knockdown of LC3 and BECN1 expression confers sensitivity to cells undergoing autophagic stress independent of platinum resistance status. The results support the use of pathway network tools to evaluate how the copy-number landscape of a tumour may guide therapy.

PMID:
28198375
PMCID:
PMC5316854
DOI:
10.1038/ncomms14423
[Indexed for MEDLINE]
Free PMC Article

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