Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer
Background Triple-negative breast cancer (TNBC) is an aggressive subtype with a poor prognosis. Although circular RNAs (circRNAs) have been implicated in cancer progression, their roles in TNBC remain poorly understood. In this study, we aimed to develop a prognostic model for TNBC by constructing a...
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PeerJ Inc.
2025-02-01
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| author | Yimin Zhu Jiayu Wang Binghe Xu |
| author_facet | Yimin Zhu Jiayu Wang Binghe Xu |
| author_sort | Yimin Zhu |
| collection | DOAJ |
| description | Background Triple-negative breast cancer (TNBC) is an aggressive subtype with a poor prognosis. Although circular RNAs (circRNAs) have been implicated in cancer progression, their roles in TNBC remain poorly understood. In this study, we aimed to develop a prognostic model for TNBC by constructing a competing endogenous RNA (ceRNA) network. This network integrates circRNAs, long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) to identify potential biomarkers and therapeutic targets for improving clinical outcomes. Methods Differentially expressed circRNAs, lncRNAs, and mRNAs were identified from GEO datasets (144 samples: 94 TNBC and 50 normal tissues). A ceRNA network was constructed, and key genes were validated using The Cancer Genome Atlas (TCGA) dataset (115 TNBC and 113 para-cancer tissues). Multivariate Cox regression analysis was performed to develop a prognostic model, and Gene Set Enrichment Analysis (GSEA) was performed to identify associated pathways. Results Nine genes (SH3BGRL2, CA12, LRP8, NAV3, GFRA1, DCDC2, CDC7, ABAT, NPTX1) were identified as key factors in the prognostic model, which demonstrated an area under the curve (AUC) of 0.90. Patients classified as high-risk patients exhibited significantly shorter overall survival (median OS: 8.12 years vs. 9.51 years, P < 0.01). The mitogen-activated protein kinase (MAPK) signaling pathway was identified as a key regulatory pathway, with circRNAs (hsa_circ_0005455, hsa_circ_000632, hsa_circ_0001666, and hsa_circ_0000069) regulating CA12, GFRA1, and NPTX1 expression. Conclusion This study developed a novel prognostic model based on a ceRNA network analysis, highlighting the critical role of circRNAs and the MAPK signaling pathway in TNBC progression. These findings offer valuable insights into potential biomarkers for TNBC prognosis and reveal promising therapeutic targets for improving patient outcomes. |
| format | Article |
| id | doaj-art-67a67f34a6c2429584a2192e6b0e5677 |
| institution | DOAJ |
| issn | 2167-8359 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | PeerJ Inc. |
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| spelling | doaj-art-67a67f34a6c2429584a2192e6b0e56772025-08-20T03:05:09ZengPeerJ Inc.PeerJ2167-83592025-02-0113e1906310.7717/peerj.19063Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancerYimin Zhu0Jiayu Wang1Binghe Xu2Medical Oncology Department, Chinese People’s Liberation Army General Hospital, Beijing, ChinaNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medicao College, Beijing, ChinaNational Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medicao College, Beijing, ChinaBackground Triple-negative breast cancer (TNBC) is an aggressive subtype with a poor prognosis. Although circular RNAs (circRNAs) have been implicated in cancer progression, their roles in TNBC remain poorly understood. In this study, we aimed to develop a prognostic model for TNBC by constructing a competing endogenous RNA (ceRNA) network. This network integrates circRNAs, long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) to identify potential biomarkers and therapeutic targets for improving clinical outcomes. Methods Differentially expressed circRNAs, lncRNAs, and mRNAs were identified from GEO datasets (144 samples: 94 TNBC and 50 normal tissues). A ceRNA network was constructed, and key genes were validated using The Cancer Genome Atlas (TCGA) dataset (115 TNBC and 113 para-cancer tissues). Multivariate Cox regression analysis was performed to develop a prognostic model, and Gene Set Enrichment Analysis (GSEA) was performed to identify associated pathways. Results Nine genes (SH3BGRL2, CA12, LRP8, NAV3, GFRA1, DCDC2, CDC7, ABAT, NPTX1) were identified as key factors in the prognostic model, which demonstrated an area under the curve (AUC) of 0.90. Patients classified as high-risk patients exhibited significantly shorter overall survival (median OS: 8.12 years vs. 9.51 years, P < 0.01). The mitogen-activated protein kinase (MAPK) signaling pathway was identified as a key regulatory pathway, with circRNAs (hsa_circ_0005455, hsa_circ_000632, hsa_circ_0001666, and hsa_circ_0000069) regulating CA12, GFRA1, and NPTX1 expression. Conclusion This study developed a novel prognostic model based on a ceRNA network analysis, highlighting the critical role of circRNAs and the MAPK signaling pathway in TNBC progression. These findings offer valuable insights into potential biomarkers for TNBC prognosis and reveal promising therapeutic targets for improving patient outcomes.https://peerj.com/articles/19063.pdfTriple-Negative Breast cancerPrognostic indexceRNA networkNon-coding RNAcircRNAsTCGA |
| spellingShingle | Yimin Zhu Jiayu Wang Binghe Xu Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer PeerJ Triple-Negative Breast cancer Prognostic index ceRNA network Non-coding RNA circRNAs TCGA |
| title | Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer |
| title_full | Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer |
| title_fullStr | Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer |
| title_full_unstemmed | Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer |
| title_short | Development of a prognostic model based on the ceRNA network in Triple-Negative Breast cancer |
| title_sort | development of a prognostic model based on the cerna network in triple negative breast cancer |
| topic | Triple-Negative Breast cancer Prognostic index ceRNA network Non-coding RNA circRNAs TCGA |
| url | https://peerj.com/articles/19063.pdf |
| work_keys_str_mv | AT yiminzhu developmentofaprognosticmodelbasedonthecernanetworkintriplenegativebreastcancer AT jiayuwang developmentofaprognosticmodelbasedonthecernanetworkintriplenegativebreastcancer AT binghexu developmentofaprognosticmodelbasedonthecernanetworkintriplenegativebreastcancer |