Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy
BackgroundHigh-grade serous ovarian cancer (HGSOC) is a common cause of death from gynecological cancer, with an overall survival rate that has not significantly improved in decades. Reliable bio-markers are needed to identify high-risk HGSOC to assist in the selection and development of treatment o...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2020.626555/full |
| _version_ | 1818417242956627968 |
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| author | Jiaxing Lin Xiao Xu Dan Sun Tianren Li |
| author_facet | Jiaxing Lin Xiao Xu Dan Sun Tianren Li |
| author_sort | Jiaxing Lin |
| collection | DOAJ |
| description | BackgroundHigh-grade serous ovarian cancer (HGSOC) is a common cause of death from gynecological cancer, with an overall survival rate that has not significantly improved in decades. Reliable bio-markers are needed to identify high-risk HGSOC to assist in the selection and development of treatment options.MethodThe study included ten HGSOC cohorts, which were merged into four separate cohorts including a total of 1,526 samples. We used the relative expression of immune genes to construct the gene-pair matrix, and the least absolute shrinkage and selection operator regression was performed to build the prognosis model using the training set. The prognosis of the model was verified in the training set (363 cases) and three validation sets (of 251, 354, and 558 cases). Finally, the differences in immune cell infiltration and gene enrichment pathways between high and low score groups were identified.ResultsA prognosis model of HGSOC overall survival rate was constructed in the training set, and included data for 35 immune gene-related gene pairs and the regression coefficients. The risk stratification of HGSOC patients was successfully performed using the training set, with a p-value of Kaplan-Meier of < 0.001. A score from this model is an independent prognostic factor of HGSOC, and prognosis was evaluated in different clinical subgroups. This model was also successful for the other three validation sets, and the results of Kaplan-Meier analysis were statistically significant (p < 0.05). The model can also predict patient progression-free survival with HGSOC to reflect tumor growth status. There was a lower infiltration level of M1 macrophages in the high-risk group compared to that in the low-risk group (p < 0.001). Finally, the immune-related pathways were enriched in the low-risk group.ConclusionThe prognostic model based on immune-related gene pairs developed is a potential prognostic marker for high-grade serous ovarian cancer treated with platinum. The model has robust prognostic ability and wide applicability. More prospective studies will be needed to assess the practical application of this model for precision therapy. |
| first_indexed | 2024-12-14T12:03:41Z |
| format | Article |
| id | doaj.art-e89ee183630441839a10a31ccdff194d |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-14T12:03:41Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-e89ee183630441839a10a31ccdff194d2022-12-21T23:01:55ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-02-011010.3389/fonc.2020.626555626555Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based ChemotherapyJiaxing Lin0Xiao Xu1Dan Sun2Tianren Li3Department of Urology, The First Hospital of China Medical University, Shenyang, ChinaDepartment of Pediatric Intensive Care Unit, The Shengjing Hospital of China Medical University, Shenyang, ChinaDepartment of Urology, The First Hospital of China Medical University, Shenyang, ChinaDepartment of Gynaecology, The First Hospital of China Medical University, Shenyang, ChinaBackgroundHigh-grade serous ovarian cancer (HGSOC) is a common cause of death from gynecological cancer, with an overall survival rate that has not significantly improved in decades. Reliable bio-markers are needed to identify high-risk HGSOC to assist in the selection and development of treatment options.MethodThe study included ten HGSOC cohorts, which were merged into four separate cohorts including a total of 1,526 samples. We used the relative expression of immune genes to construct the gene-pair matrix, and the least absolute shrinkage and selection operator regression was performed to build the prognosis model using the training set. The prognosis of the model was verified in the training set (363 cases) and three validation sets (of 251, 354, and 558 cases). Finally, the differences in immune cell infiltration and gene enrichment pathways between high and low score groups were identified.ResultsA prognosis model of HGSOC overall survival rate was constructed in the training set, and included data for 35 immune gene-related gene pairs and the regression coefficients. The risk stratification of HGSOC patients was successfully performed using the training set, with a p-value of Kaplan-Meier of < 0.001. A score from this model is an independent prognostic factor of HGSOC, and prognosis was evaluated in different clinical subgroups. This model was also successful for the other three validation sets, and the results of Kaplan-Meier analysis were statistically significant (p < 0.05). The model can also predict patient progression-free survival with HGSOC to reflect tumor growth status. There was a lower infiltration level of M1 macrophages in the high-risk group compared to that in the low-risk group (p < 0.001). Finally, the immune-related pathways were enriched in the low-risk group.ConclusionThe prognostic model based on immune-related gene pairs developed is a potential prognostic marker for high-grade serous ovarian cancer treated with platinum. The model has robust prognostic ability and wide applicability. More prospective studies will be needed to assess the practical application of this model for precision therapy.https://www.frontiersin.org/articles/10.3389/fonc.2020.626555/fullhigh-grade serous ovarian cancerCox modelprognostic markerimmune genegene pair |
| spellingShingle | Jiaxing Lin Xiao Xu Dan Sun Tianren Li Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy Frontiers in Oncology high-grade serous ovarian cancer Cox model prognostic marker immune gene gene pair |
| title | Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy |
| title_full | Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy |
| title_fullStr | Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy |
| title_full_unstemmed | Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy |
| title_short | Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy |
| title_sort | development and validation of an immune related gene pair model of high grade serous ovarian cancer after platinum based chemotherapy |
| topic | high-grade serous ovarian cancer Cox model prognostic marker immune gene gene pair |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2020.626555/full |
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