Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model
Serous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > E...
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| Format: | Article |
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MDPI AG
2022-12-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/12/12/3128 |
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| author | Fengyuan Luo Na Li Qi Zhang Liyuan Ma Xinqiao Li Tao Hu Haijian Zhong Hongdong Li Guini Hong |
| author_facet | Fengyuan Luo Na Li Qi Zhang Liyuan Ma Xinqiao Li Tao Hu Haijian Zhong Hongdong Li Guini Hong |
| author_sort | Fengyuan Luo |
| collection | DOAJ |
| description | Serous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > Eb/Ea ≤ Eb) of gene pairs closely associated with serous ovarian prognosis, we tried constructing a potential individualized qualitative biomarker by the greedy algorithm and evaluated the performance in independent validation datasets. We constructed a prognostic biomarker consisting of 20 gene pairs (SOV-P20). The overall survival between high- and low-risk groups stratified by SOV-P20 was statistically significantly different in the training and independent validation datasets from other platforms (<i>p</i> < 0.05, Wilcoxon test). The average area under the curve (AUC) values of the training and three validation datasets were 0.756, 0.590, 0.630, and 0.680, respectively. The distribution of most immune cells between high- and low-risk groups was quite different (<i>p</i> < 0.001, Wilcoxon test). The low-risk patients tended to show significantly better tumor response to chemotherapy than the high-risk patients (<i>p</i> < 0.05, Fisher’s exact test). SOV-P20 achieved the highest mean index of concordance (C-index) (0.624) compared with the other seven existing prognostic signatures (ranging from 0.511 to 0.619). SOV-P20 is a promising prognostic biomarker for serous ovarian cancer, which will be applicable for clinical predictive risk assessment. |
| first_indexed | 2024-03-09T17:08:52Z |
| format | Article |
| id | doaj.art-f019bd9b933949128686dc3cccd5fc6b |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T17:08:52Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-f019bd9b933949128686dc3cccd5fc6b2023-11-24T14:19:10ZengMDPI AGDiagnostics2075-44182022-12-011212312810.3390/diagnostics12123128Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative ModelFengyuan Luo0Na Li1Qi Zhang2Liyuan Ma3Xinqiao Li4Tao Hu5Haijian Zhong6Hongdong Li7Guini Hong8School of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaAffiliated Hospital of Jiangxi, University of Chinese Medicine, Nanchang 330006, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSchool of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, ChinaSerous ovarian cancer is the most common type of ovarian epithelial cancer and usually has a poor prognosis. The objective of this study was to construct an individualized prognostic model for predicting overall survival in serous ovarian cancer. Based on the relative expression orderings (Ea > Eb/Ea ≤ Eb) of gene pairs closely associated with serous ovarian prognosis, we tried constructing a potential individualized qualitative biomarker by the greedy algorithm and evaluated the performance in independent validation datasets. We constructed a prognostic biomarker consisting of 20 gene pairs (SOV-P20). The overall survival between high- and low-risk groups stratified by SOV-P20 was statistically significantly different in the training and independent validation datasets from other platforms (<i>p</i> < 0.05, Wilcoxon test). The average area under the curve (AUC) values of the training and three validation datasets were 0.756, 0.590, 0.630, and 0.680, respectively. The distribution of most immune cells between high- and low-risk groups was quite different (<i>p</i> < 0.001, Wilcoxon test). The low-risk patients tended to show significantly better tumor response to chemotherapy than the high-risk patients (<i>p</i> < 0.05, Fisher’s exact test). SOV-P20 achieved the highest mean index of concordance (C-index) (0.624) compared with the other seven existing prognostic signatures (ranging from 0.511 to 0.619). SOV-P20 is a promising prognostic biomarker for serous ovarian cancer, which will be applicable for clinical predictive risk assessment.https://www.mdpi.com/2075-4418/12/12/3128serous ovarian cancerrelative expression orderingsprognostic biomarker |
| spellingShingle | Fengyuan Luo Na Li Qi Zhang Liyuan Ma Xinqiao Li Tao Hu Haijian Zhong Hongdong Li Guini Hong Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model Diagnostics serous ovarian cancer relative expression orderings prognostic biomarker |
| title | Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model |
| title_full | Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model |
| title_fullStr | Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model |
| title_full_unstemmed | Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model |
| title_short | Identification of an Individualized Prognostic Biomarker for Serous Ovarian Cancer: A Qualitative Model |
| title_sort | identification of an individualized prognostic biomarker for serous ovarian cancer a qualitative model |
| topic | serous ovarian cancer relative expression orderings prognostic biomarker |
| url | https://www.mdpi.com/2075-4418/12/12/3128 |
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