Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes
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 strategie...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-05-01
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| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-022-03440-5 |
| _version_ | 1811254271488819200 |
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| author | Halema Al-Farsi Iman Al-Azwani Joel A. Malek Lotfi Chouchane Arash Rafii Najeeb M. Halabi |
| author_facet | Halema Al-Farsi Iman Al-Azwani Joel A. Malek Lotfi Chouchane Arash Rafii Najeeb M. Halabi |
| author_sort | Halema Al-Farsi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T17:04:45Z |
| format | Article |
| id | doaj.art-cef8992aa6344a3d8dbeb94ea4a73873 |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-04-12T17:04:45Z |
| publishDate | 2022-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-cef8992aa6344a3d8dbeb94ea4a738732022-12-22T03:23:59ZengBMCJournal of Translational Medicine1479-58762022-05-0120111510.1186/s12967-022-03440-5Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genesHalema Al-Farsi0Iman Al-Azwani1Joel A. Malek2Lotfi Chouchane3Arash Rafii4Najeeb M. Halabi5College of Medicine, Qatar UniversityIntegrated Genomics Core, Sidra medicineGenomics Core, Weill Cornell Medicine in Qatar, Education City, Qatar FoundationGenetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar FoundationGenetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar FoundationGenetic Intelligence Laboratory, Weill Cornell Medicine in Qatar, Education City, Qatar FoundationAbstract 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.https://doi.org/10.1186/s12967-022-03440-5RNAiEpithelial ovarian cancerRNA-SeqNon-mutated genesUnmutated genesCancer somatic mutation |
| spellingShingle | Halema Al-Farsi Iman Al-Azwani Joel A. Malek Lotfi Chouchane Arash Rafii Najeeb M. Halabi Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes Journal of Translational Medicine RNAi Epithelial ovarian cancer RNA-Seq Non-mutated genes Unmutated genes Cancer somatic mutation |
| title | Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes |
| title_full | Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes |
| title_fullStr | Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes |
| title_full_unstemmed | Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes |
| title_short | Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes |
| title_sort | discovery of new therapeutic targets in ovarian cancer through identifying significantly non mutated genes |
| topic | RNAi Epithelial ovarian cancer RNA-Seq Non-mutated genes Unmutated genes Cancer somatic mutation |
| url | https://doi.org/10.1186/s12967-022-03440-5 |
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