Halema Al-Farsi1, Iman Al-Azwani2, Joel A Malek3, Lotfi Chouchane4, Arash Rafii5, Najeeb M Halabi6. 1. College of Medicine, Qatar University, Doha, Qatar. 2. Integrated Genomics Core, Sidra medicine, Doha, Qatar. 3. Genomics Core, Weill Cornell Medicine in Qatar, Education City, Qatar Foundation, Doha, Qatar. 4. Genetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar Foundation, Doha, Qatar. 5. Genetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar Foundation, Doha, Qatar. jat2021@qatar-med.cornell.edu. 6. Genetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar Foundation, Doha, Qatar. nah2024@qatar-med.cornell.edu.
Abstract
BACKGROUND: Mutated and non-mutated genes interact to drive cancer growth and metastasis. While research has focused on understanding the impact of mutated genes on cancer biology, understanding non-mutated genes that are essential to tumor development could lead to new therapeutic strategies. The recent advent of high-throughput whole genome sequencing being applied to many different samples has made it possible to calculate if genes are significantly non-mutated in a specific cancer patient cohort. METHODS: We carried out random mutagenesis simulations of the human genome approximating the regions sequenced in the publicly available Cancer Growth Atlas Project for ovarian cancer (TCGA-OV). Simulated mutations were compared to the observed mutations in the TCGA-OV cohort and genes with the largest deviations from simulation were identified. Pathway analysis was performed on the non-mutated genes to better understand their biological function. We then compared gene expression, methylation and copy number distributions of non-mutated and mutated genes in cell lines and patient data from the TCGA-OV project. To directly test if non-mutated genes can affect cell proliferation, we carried out proof-of-concept RNAi silencing experiments of a panel of nine selected non-mutated genes in three ovarian cancer cell lines and one primary ovarian epithelial cell line. RESULTS: We identified a set of genes that were mutated less than expected (non-mutated genes) and mutated more than expected (mutated genes). Pathway analysis revealed that non-mutated genes interact in cancer associated pathways. We found that non-mutated genes are expressed significantly more than mutated genes while also having lower methylation and higher copy number states indicating that they could be functionally important. RNAi silencing of the panel of non-mutated genes resulted in a greater significant reduction of cell viability in the cancer cell lines than in the non-cancer cell line. Finally, as a test case, silencing ANKLE2, a significantly non-mutated gene, affected the morphology, reduced migration, and increased the chemotherapeutic response of SKOV3 cells. CONCLUSION: We show that we can identify significantly non-mutated genes in a large ovarian cancer cohort that are well-expressed in patient and cell line data and whose RNAi-induced silencing reduces viability in three ovarian cancer cell lines. Targeting non-mutated genes that are important for tumor growth and metastasis is a promising approach to expand cancer therapeutic options.
BACKGROUND: Mutated and non-mutated genes interact to drive cancer growth and metastasis. While research has focused on understanding the impact of mutated genes on cancer biology, understanding non-mutated genes that are essential to tumor development could lead to new therapeutic strategies. The recent advent of high-throughput whole genome sequencing being applied to many different samples has made it possible to calculate if genes are significantly non-mutated in a specific cancer patient cohort. METHODS: We carried out random mutagenesis simulations of the human genome approximating the regions sequenced in the publicly available Cancer Growth Atlas Project for ovarian cancer (TCGA-OV). Simulated mutations were compared to the observed mutations in the TCGA-OV cohort and genes with the largest deviations from simulation were identified. Pathway analysis was performed on the non-mutated genes to better understand their biological function. We then compared gene expression, methylation and copy number distributions of non-mutated and mutated genes in cell lines and patient data from the TCGA-OV project. To directly test if non-mutated genes can affect cell proliferation, we carried out proof-of-concept RNAi silencing experiments of a panel of nine selected non-mutated genes in three ovarian cancer cell lines and one primary ovarian epithelial cell line. RESULTS: We identified a set of genes that were mutated less than expected (non-mutated genes) and mutated more than expected (mutated genes). Pathway analysis revealed that non-mutated genes interact in cancer associated pathways. We found that non-mutated genes are expressed significantly more than mutated genes while also having lower methylation and higher copy number states indicating that they could be functionally important. RNAi silencing of the panel of non-mutated genes resulted in a greater significant reduction of cell viability in the cancer cell lines than in the non-cancer cell line. Finally, as a test case, silencing ANKLE2, a significantly non-mutated gene, affected the morphology, reduced migration, and increased the chemotherapeutic response of SKOV3 cells. CONCLUSION: We show that we can identify significantly non-mutated genes in a large ovarian cancer cohort that are well-expressed in patient and cell line data and whose RNAi-induced silencing reduces viability in three ovarian cancer cell lines. Targeting non-mutated genes that are important for tumor growth and metastasis is a promising approach to expand cancer therapeutic options.
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Authors: Christopher Greenman; Philip Stephens; Raffaella Smith; Gillian L Dalgliesh; Christopher Hunter; Graham Bignell; Helen Davies; Jon Teague; Adam Butler; Claire Stevens; Sarah Edkins; Sarah O'Meara; Imre Vastrik; Esther E Schmidt; Tim Avis; Syd Barthorpe; Gurpreet Bhamra; Gemma Buck; Bhudipa Choudhury; Jody Clements; Jennifer Cole; Ed Dicks; Simon Forbes; Kris Gray; Kelly Halliday; Rachel Harrison; Katy Hills; Jon Hinton; Andy Jenkinson; David Jones; Andy Menzies; Tatiana Mironenko; Janet Perry; Keiran Raine; Dave Richardson; Rebecca Shepherd; Alexandra Small; Calli Tofts; Jennifer Varian; Tony Webb; Sofie West; Sara Widaa; Andy Yates; Daniel P Cahill; David N Louis; Peter Goldstraw; Andrew G Nicholson; Francis Brasseur; Leendert Looijenga; Barbara L Weber; Yoke-Eng Chiew; Anna DeFazio; Mel F Greaves; Anthony R Green; Peter Campbell; Ewan Birney; Douglas F Easton; Georgia Chenevix-Trench; Min-Han Tan; Sok Kean Khoo; Bin Tean Teh; Siu Tsan Yuen; Suet Yi Leung; Richard Wooster; P Andrew Futreal; Michael R Stratton Journal: Nature Date: 2007-03-08 Impact factor: 49.962
Authors: Tanja Kaufmann; Eva Kukolj; Andreas Brachner; Etienne Beltzung; Melania Bruno; Sebastian Kostrhon; Susanne Opravil; Otto Hudecz; Karl Mechtler; Graham Warren; Dea Slade Journal: J Cell Sci Date: 2016-11-14 Impact factor: 5.285