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.
Highlights
Identification of specific oncogenic gene changes has enabled the modern generation of targeted cancer therapeutics
48% of studied tumours have no mutations in these oncogenes or tumour suppressors, other than TP53 (Fig. 1b)
Since mutant p53 alone is insufficient for tumour formation[9,10], these tumours likely contain somatic copy-number alterations (SCNAs) drivers[5] which aid in tumorigenesis
Summary
OV tumours have been characterized[8] as being uniquely low in mutations and high in SCNAs (Fig. 1a). It is possible that despite relatively low mutation rates, each OV tumour contains multiple tumour suppressor or oncogene mutations that drive cancer formation. To investigate this possibility, we analysed The Cancer Genome Atlas (TCGA) OV data for mutations in well-known tumour-driver genes[8]. While Gene Set Enrichment Analysis (GSEA) looks at multiple genes within a pathway to determine statistical significance at the cohort level[13], we designed our tool to incorporate two additional pieces of information to better characterize genetic disturbance of pathway biology:
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
