Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer
Abstract Background Significant miss‐expressed gene indicators contributing to cisplatin resistance in ovarian cancer have not been completely understood. It seems that several regulatory genes and signaling pathways are associated with the emergence of the chemo‐resistant phenotype. Aims Here, a me...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-12-01
|
| Series: | Cancer Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/cnr2.1884 |
| _version_ | 1797344684886982656 |
|---|---|
| author | Somayeh Hashemi Sheikhshabani Zeinab Amini‐Farsani Nesa Kazemifard Parastoo Modarres Zahra Amini‐Farsani Mir Davood Omrani Soudeh Ghafouri‐Fard |
| author_facet | Somayeh Hashemi Sheikhshabani Zeinab Amini‐Farsani Nesa Kazemifard Parastoo Modarres Zahra Amini‐Farsani Mir Davood Omrani Soudeh Ghafouri‐Fard |
| author_sort | Somayeh Hashemi Sheikhshabani |
| collection | DOAJ |
| description | Abstract Background Significant miss‐expressed gene indicators contributing to cisplatin resistance in ovarian cancer have not been completely understood. It seems that several regulatory genes and signaling pathways are associated with the emergence of the chemo‐resistant phenotype. Aims Here, a meta‐analysis approach was adopted to assess deregulated genes involved in relapse after the first line of chemotherapy (cisplatin). Methods and Results To do so, six ovarian cancer libraries were gathered from GEO repository. Batch effect removal and quality assessment, and boxplots and PCA were performed using SVA and ggplot2 packages in R, respectively. Cisplatin‐resistant and ‐sensitive ovarian cancer groups were compared with find genes with significant expression changes using linear regression models in the LIMMA R package. The significance threshold for DEGs was taken as adj p‐value < .05 and − 1 > logFC > 1. A total of 261 genes were identified to have significant differential expression levels in the cisplatin‐resistant versus cisplatin‐sensitive group. Among the 10 top up‐regulated and down‐regulated genes, PITX2, SNCA, and EPHA7 (up), as well as TMEM98 (down) are indirect upstream regulators of PI3K/AKT signaling pathway, contributing greatly to the development of chemo‐resistance in cancer via promoting cell proliferation, survival, and cell cycle progression as well as inhibiting apoptosis. Moreover, a comprehensive assessment of DEGs revealed the dysregulation of not only membrane ion channels KCa1.1, Kv4, and CACNB4, affecting cell excitability, proliferation, and apoptosis but also cell adhesion proteins COL4A6, EPHA3, and CD9, affecting the attachment of normal cells to ECM and apoptosis, introducing good options to reverse cisplatin resistance. Conclusion Our results predict and suggest that upstream regulators of PI3K/AKT signaling pathway, ion channels, and cell adhesion proteins play important roles in cisplatin resistance development in ovarian cancer. |
| first_indexed | 2024-03-08T11:06:19Z |
| format | Article |
| id | doaj.art-6a85983b34164d75a28ebf4287ea6ec8 |
| institution | Directory Open Access Journal |
| issn | 2573-8348 |
| language | English |
| last_indexed | 2024-03-08T11:06:19Z |
| publishDate | 2023-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Cancer Reports |
| spelling | doaj.art-6a85983b34164d75a28ebf4287ea6ec82024-01-26T14:41:21ZengWileyCancer Reports2573-83482023-12-01612n/an/a10.1002/cnr2.1884Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancerSomayeh Hashemi Sheikhshabani0Zeinab Amini‐Farsani1Nesa Kazemifard2Parastoo Modarres3Zahra Amini‐Farsani4Mir Davood Omrani5Soudeh Ghafouri‐Fard6Student Research Committee, Department of Medical Genetics Shahid Beheshti University of Medical Sciences Tehran IranDepartment of Medical Genetics Shahid Beheshti University of Medical Sciences Tehran IranBasic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases Shahid Beheshti University of Medical Sciences Tehran IranDepartment of Cell and Molecular Biology and Microbiology University of Isfahan Isfahan IranBayesian Imaging and Spatial Statistics Group, Institute for Statistics Ludwig‐Maximilians‐Universität München Munich GermanyDepartment of Medical Genetics Shahid Beheshti University of Medical Sciences Tehran IranDepartment of Medical Genetics Shahid Beheshti University of Medical Sciences Tehran IranAbstract Background Significant miss‐expressed gene indicators contributing to cisplatin resistance in ovarian cancer have not been completely understood. It seems that several regulatory genes and signaling pathways are associated with the emergence of the chemo‐resistant phenotype. Aims Here, a meta‐analysis approach was adopted to assess deregulated genes involved in relapse after the first line of chemotherapy (cisplatin). Methods and Results To do so, six ovarian cancer libraries were gathered from GEO repository. Batch effect removal and quality assessment, and boxplots and PCA were performed using SVA and ggplot2 packages in R, respectively. Cisplatin‐resistant and ‐sensitive ovarian cancer groups were compared with find genes with significant expression changes using linear regression models in the LIMMA R package. The significance threshold for DEGs was taken as adj p‐value < .05 and − 1 > logFC > 1. A total of 261 genes were identified to have significant differential expression levels in the cisplatin‐resistant versus cisplatin‐sensitive group. Among the 10 top up‐regulated and down‐regulated genes, PITX2, SNCA, and EPHA7 (up), as well as TMEM98 (down) are indirect upstream regulators of PI3K/AKT signaling pathway, contributing greatly to the development of chemo‐resistance in cancer via promoting cell proliferation, survival, and cell cycle progression as well as inhibiting apoptosis. Moreover, a comprehensive assessment of DEGs revealed the dysregulation of not only membrane ion channels KCa1.1, Kv4, and CACNB4, affecting cell excitability, proliferation, and apoptosis but also cell adhesion proteins COL4A6, EPHA3, and CD9, affecting the attachment of normal cells to ECM and apoptosis, introducing good options to reverse cisplatin resistance. Conclusion Our results predict and suggest that upstream regulators of PI3K/AKT signaling pathway, ion channels, and cell adhesion proteins play important roles in cisplatin resistance development in ovarian cancer.https://doi.org/10.1002/cnr2.1884cisplatin resistancemeta‐analysisovarian cancer |
| spellingShingle | Somayeh Hashemi Sheikhshabani Zeinab Amini‐Farsani Nesa Kazemifard Parastoo Modarres Zahra Amini‐Farsani Mir Davood Omrani Soudeh Ghafouri‐Fard Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer Cancer Reports cisplatin resistance meta‐analysis ovarian cancer |
| title | Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer |
| title_full | Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer |
| title_fullStr | Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer |
| title_full_unstemmed | Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer |
| title_short | Meta‐analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer |
| title_sort | meta analysis of microarray data to determine gene indicators involved in the cisplatin resistance in ovarian cancer |
| topic | cisplatin resistance meta‐analysis ovarian cancer |
| url | https://doi.org/10.1002/cnr2.1884 |
| work_keys_str_mv | AT somayehhashemisheikhshabani metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer AT zeinabaminifarsani metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer AT nesakazemifard metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer AT parastoomodarres metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer AT zahraaminifarsani metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer AT mirdavoodomrani metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer AT soudehghafourifard metaanalysisofmicroarraydatatodeterminegeneindicatorsinvolvedinthecisplatinresistanceinovariancancer |