Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids
BackgroundOvarian cancer (OC) is a malignant tumor associated with poor prognosis owing to its susceptibility to chemoresistance. Cellular senescence, an irreversible biological state, is intricately linked to chemoresistance in cancer treatment. We developed a senescence-related gene signature for...
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| Format: | Article |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1291559/full |
| _version_ | 1827365324018679808 |
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| author | Xintong Cai Yanhong Li Jianfeng Zheng Li Liu Zicong Jiao Jie Lin Shan Jiang Xuefen Lin Yang Sun |
| author_facet | Xintong Cai Yanhong Li Jianfeng Zheng Li Liu Zicong Jiao Jie Lin Shan Jiang Xuefen Lin Yang Sun |
| author_sort | Xintong Cai |
| collection | DOAJ |
| description | BackgroundOvarian cancer (OC) is a malignant tumor associated with poor prognosis owing to its susceptibility to chemoresistance. Cellular senescence, an irreversible biological state, is intricately linked to chemoresistance in cancer treatment. We developed a senescence-related gene signature for prognostic prediction and evaluated personalized treatment in patients with OC.MethodsWe acquired the clinical and RNA-seq data of OC patients from The Cancer Genome Atlas and identified a senescence-related prognostic gene set through differential and cox regression analysis in distinct chemotherapy response groups. A prognostic senescence-related signature was developed and validated by OC patient-derived-organoids (PDOs). We leveraged gene set enrichment analysis (GSEA) and ESTIMATE to unravel the potential functions and immune landscape of the model. Moreover, we explored the correlation between risk scores and potential chemotherapeutic agents. After confirming the congruence between organoids and tumor tissues through immunohistochemistry, we measured the IC50 of cisplatin in PDOs using the ATP activity assay, categorized by resistance and sensitivity to the drug. We also investigated the expression patterns of model genes across different groups.ResultsWe got 2740 differentially expressed genes between two chemotherapy response groups including 43 senescence-related genes. Model prognostic genes were yielded through univariate cox analysis, and multifactorial cox analysis. Our work culminated in a senescence-related prognostic model based on the expression of SGK1 and VEGFA. Simultaneously, we successfully constructed and propagated three OC PDOs for drug screening. PCR and WB from PDOs affirmed consistent expression trends as those of our model genes derived from comprehensive data analysis. Specifically, SGK1 exhibited heightened expression in cisplatin-resistant OC organoids, while VEGFA manifested elevated expression in the sensitive group (P<0.05). Intriguingly, GSEA results unveiled the enrichment of model genes in the PPAR signaling pathway, pivotal regulator in chemoresistance and tumorigenesis. This revelation prompted the identification of potential beneficial drugs for patients with a high-risk score, including gemcitabine, dabrafenib, epirubicin, oxaliplatin, olaparib, teniposide, ribociclib, topotecan, venetoclax.ConclusionThrough the formulation of a senescence-related signature comprising SGK1 and VEGFA, we established a promising tool for prognosticating chemotherapy reactions, predicting outcomes, and steering therapeutic strategies. Patients with high VEGFA and low SGK1 expression levels exhibit heightened sensitivity to chemotherapy. |
| first_indexed | 2024-03-08T08:26:39Z |
| format | Article |
| id | doaj.art-9fb8b912dae7420ca48d212165398ec1 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-08T08:26:39Z |
| publishDate | 2024-02-01 |
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| series | Frontiers in Oncology |
| spelling | doaj.art-9fb8b912dae7420ca48d212165398ec12024-02-02T04:36:32ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2024-02-011310.3389/fonc.2023.12915591291559Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoidsXintong Cai0Yanhong Li1Jianfeng Zheng2Li Liu3Zicong Jiao4Jie Lin5Shan Jiang6Xuefen Lin7Yang Sun8Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Translational Medicine, Scientific Research System, Geneplus -Beijing Institute, Beijing, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaDepartment of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, ChinaBackgroundOvarian cancer (OC) is a malignant tumor associated with poor prognosis owing to its susceptibility to chemoresistance. Cellular senescence, an irreversible biological state, is intricately linked to chemoresistance in cancer treatment. We developed a senescence-related gene signature for prognostic prediction and evaluated personalized treatment in patients with OC.MethodsWe acquired the clinical and RNA-seq data of OC patients from The Cancer Genome Atlas and identified a senescence-related prognostic gene set through differential and cox regression analysis in distinct chemotherapy response groups. A prognostic senescence-related signature was developed and validated by OC patient-derived-organoids (PDOs). We leveraged gene set enrichment analysis (GSEA) and ESTIMATE to unravel the potential functions and immune landscape of the model. Moreover, we explored the correlation between risk scores and potential chemotherapeutic agents. After confirming the congruence between organoids and tumor tissues through immunohistochemistry, we measured the IC50 of cisplatin in PDOs using the ATP activity assay, categorized by resistance and sensitivity to the drug. We also investigated the expression patterns of model genes across different groups.ResultsWe got 2740 differentially expressed genes between two chemotherapy response groups including 43 senescence-related genes. Model prognostic genes were yielded through univariate cox analysis, and multifactorial cox analysis. Our work culminated in a senescence-related prognostic model based on the expression of SGK1 and VEGFA. Simultaneously, we successfully constructed and propagated three OC PDOs for drug screening. PCR and WB from PDOs affirmed consistent expression trends as those of our model genes derived from comprehensive data analysis. Specifically, SGK1 exhibited heightened expression in cisplatin-resistant OC organoids, while VEGFA manifested elevated expression in the sensitive group (P<0.05). Intriguingly, GSEA results unveiled the enrichment of model genes in the PPAR signaling pathway, pivotal regulator in chemoresistance and tumorigenesis. This revelation prompted the identification of potential beneficial drugs for patients with a high-risk score, including gemcitabine, dabrafenib, epirubicin, oxaliplatin, olaparib, teniposide, ribociclib, topotecan, venetoclax.ConclusionThrough the formulation of a senescence-related signature comprising SGK1 and VEGFA, we established a promising tool for prognosticating chemotherapy reactions, predicting outcomes, and steering therapeutic strategies. Patients with high VEGFA and low SGK1 expression levels exhibit heightened sensitivity to chemotherapy.https://www.frontiersin.org/articles/10.3389/fonc.2023.1291559/fullcell senescencechemoresistanceovarian cancerorganoidTCGA |
| spellingShingle | Xintong Cai Yanhong Li Jianfeng Zheng Li Liu Zicong Jiao Jie Lin Shan Jiang Xuefen Lin Yang Sun Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids Frontiers in Oncology cell senescence chemoresistance ovarian cancer organoid TCGA |
| title | Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids |
| title_full | Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids |
| title_fullStr | Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids |
| title_full_unstemmed | Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids |
| title_short | Modeling of senescence-related chemoresistance in ovarian cancer using data analysis and patient-derived organoids |
| title_sort | modeling of senescence related chemoresistance in ovarian cancer using data analysis and patient derived organoids |
| topic | cell senescence chemoresistance ovarian cancer organoid TCGA |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1291559/full |
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