Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer
BackgroundCompelling evidence has demonstrated the pivotal role of autophagy in the prognosis of breast cancer. Breast cancer (BC) patients with early relapse consistently exhibited worse survival.MethodsThe autophagy-related genes were derived from the Human Autophagy Database (HADb) and high-seque...
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2022.824362/full |
| _version_ | 1819277567671140352 |
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| author | Yu Min Yang Feng Haojun Luo Daixing Hu Xiaoyuan Wei Danshuang He Guobing Yin Shenghao Fan |
| author_facet | Yu Min Yang Feng Haojun Luo Daixing Hu Xiaoyuan Wei Danshuang He Guobing Yin Shenghao Fan |
| author_sort | Yu Min |
| collection | DOAJ |
| description | BackgroundCompelling evidence has demonstrated the pivotal role of autophagy in the prognosis of breast cancer. Breast cancer (BC) patients with early relapse consistently exhibited worse survival.MethodsThe autophagy-related genes were derived from the Human Autophagy Database (HADb) and high-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Discrepantly expressed autophagy genes (DEAGs) between early relapse and long-term survival groups were performed using the Linear Models for Microarray data (LIMMA) method. Lasso Cox regression analysis was conducted for the selection of the 4-gene autophagy-related gene signature. GSE42568 and GSE21653 databases were enrolled in this study for the external validation of the signature. Then patients were divided into high and low-risk groups based on the specific score formula. GSEA was used to discover the related signaling pathway. The Kaplan-Meier curves and the receiver operating characteristic (ROC) curves were used to evaluate the discrimination and accuracy of the 4-gene signature.ResultsA signature composed of four autophagy-related mRNA including APOL1, HSPA8, SIRT1, and TP73, was identified as significantly associated with the early relapse in BC patients. Time-dependent receiver-operating characteristic at 1 year suggested remarkable accuracy of the signature [area under the curve (AUC = 0.748)]. The risk score model based on the autophagy-related signature showed favorable predicting value in 1-, 2-, and 3-year relapse-free survival (RFS) in training and two validating cohorts. The GSEA displayed gene sets were remarkably enriched in carcinogenic activation pathways and autophagy-related pathways. The nomogram involving three variables (progesterone receptor status, T stage, and 4-gene signature) exhibited relatively good discrimination with a C-index of 0.766.ConclusionsOur study establishes an autophagy-related 4-gene signature that can effectively stratify the high-risk and low-risk BC patients for early relapse. Combined with the clinicopathological variables, the signature could significantly help oncologists tailor more efficient treatment strategies for BC patients. |
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| institution | Directory Open Access Journal |
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| language | English |
| last_indexed | 2024-12-23T23:58:10Z |
| publishDate | 2022-02-01 |
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| series | Frontiers in Endocrinology |
| spelling | doaj.art-9e1439ba8bbf489b9402064825ab899f2022-12-21T17:25:12ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922022-02-011310.3389/fendo.2022.824362824362Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast CancerYu Min0Yang Feng1Haojun Luo2Daixing Hu3Xiaoyuan Wei4Danshuang He5Guobing Yin6Shenghao Fan7Department of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaDepartment of Cardiology, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, ChinaDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, ChinaBackgroundCompelling evidence has demonstrated the pivotal role of autophagy in the prognosis of breast cancer. Breast cancer (BC) patients with early relapse consistently exhibited worse survival.MethodsThe autophagy-related genes were derived from the Human Autophagy Database (HADb) and high-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Discrepantly expressed autophagy genes (DEAGs) between early relapse and long-term survival groups were performed using the Linear Models for Microarray data (LIMMA) method. Lasso Cox regression analysis was conducted for the selection of the 4-gene autophagy-related gene signature. GSE42568 and GSE21653 databases were enrolled in this study for the external validation of the signature. Then patients were divided into high and low-risk groups based on the specific score formula. GSEA was used to discover the related signaling pathway. The Kaplan-Meier curves and the receiver operating characteristic (ROC) curves were used to evaluate the discrimination and accuracy of the 4-gene signature.ResultsA signature composed of four autophagy-related mRNA including APOL1, HSPA8, SIRT1, and TP73, was identified as significantly associated with the early relapse in BC patients. Time-dependent receiver-operating characteristic at 1 year suggested remarkable accuracy of the signature [area under the curve (AUC = 0.748)]. The risk score model based on the autophagy-related signature showed favorable predicting value in 1-, 2-, and 3-year relapse-free survival (RFS) in training and two validating cohorts. The GSEA displayed gene sets were remarkably enriched in carcinogenic activation pathways and autophagy-related pathways. The nomogram involving three variables (progesterone receptor status, T stage, and 4-gene signature) exhibited relatively good discrimination with a C-index of 0.766.ConclusionsOur study establishes an autophagy-related 4-gene signature that can effectively stratify the high-risk and low-risk BC patients for early relapse. Combined with the clinicopathological variables, the signature could significantly help oncologists tailor more efficient treatment strategies for BC patients.https://www.frontiersin.org/articles/10.3389/fendo.2022.824362/fullbreast cancerearly relapseautophagysignaturenomogram |
| spellingShingle | Yu Min Yang Feng Haojun Luo Daixing Hu Xiaoyuan Wei Danshuang He Guobing Yin Shenghao Fan Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer Frontiers in Endocrinology breast cancer early relapse autophagy signature nomogram |
| title | Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer |
| title_full | Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer |
| title_fullStr | Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer |
| title_full_unstemmed | Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer |
| title_short | Identifying and Validating of an Autophagy-Related Gene Signature for the Prediction of Early Relapse in Breast Cancer |
| title_sort | identifying and validating of an autophagy related gene signature for the prediction of early relapse in breast cancer |
| topic | breast cancer early relapse autophagy signature nomogram |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2022.824362/full |
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