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A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity
Tumor heterogeneity remains a major challenge for disease subtyping, risk stratification, and accurate clinical management. Exosome-based liquid biopsy can effectively overcome the limitations of tissue biopsy, achieving minimal invasion, multi-point dynamic monitoring, and good prognosis assessment...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232662/ https://www.ncbi.nlm.nih.gov/pubmed/37273850 http://dx.doi.org/10.1016/j.csbj.2023.05.013 |
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author | Long, Fei Ma, Haodong Hao, Youjin Tian, Luyao Li, Yinghong Li, Bo Chen, Juan Tang, Ying Li, Jing Deng, Lili Xie, Guoming Liu, Mingwei |
author_facet | Long, Fei Ma, Haodong Hao, Youjin Tian, Luyao Li, Yinghong Li, Bo Chen, Juan Tang, Ying Li, Jing Deng, Lili Xie, Guoming Liu, Mingwei |
author_sort | Long, Fei |
collection | PubMed |
description | Tumor heterogeneity remains a major challenge for disease subtyping, risk stratification, and accurate clinical management. Exosome-based liquid biopsy can effectively overcome the limitations of tissue biopsy, achieving minimal invasion, multi-point dynamic monitoring, and good prognosis assessment, and has broad clinical prospects. However, there is still lacking comprehensive analysis of tumor-derived exosome (TDE)-based stratification of risk patients and prognostic assessment for breast cancer with systematic dissection of biological heterogeneity. In this study, the robust corroborative analysis for biomarker discovery (RCABD) strategy was used for the identification of exosome molecules, differential expression verification, risk prediction modeling, heterogenous dissection with multi-ome (6101 molecules), our ExoBCD database (306 molecules), and 53 independent studies (481 molecules). Our results showed that a 10-molecule exosome-derived signature (exoSIG) could successfully fulfill breast cancer risk stratification, making it a novel and accurate exosome prognostic indicator (Cox P = 9.9E-04, HR = 3.3, 95% CI 1.6–6.8). Interestingly, HLA-DQB2 and COL17A1, closely related to tumor metastasis, achieved high performance in prognosis prediction (86.35% contribution) and accuracy (Log-rank P = 0.028, AUC = 85.42%). With the combined information of patient age and tumor stage, they formed a bimolecular risk signature (Clinmin-exoSIG) and a convenient nomogram as operable tools for clinical applications. In conclusion, as an extension of ExoBCD, this study conducted systematic analyses to identify prognostic multi-molecular panel and risk signature, stratify patients and dissect biological heterogeneity based on breast cancer exosomes from a multi-omics perspective. Our results provide an important reference for in-depth exploration of the "biological heterogeneity - risk stratification - prognosis prediction". |
format | Online Article Text |
id | pubmed-10232662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-102326622023-06-02 A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity Long, Fei Ma, Haodong Hao, Youjin Tian, Luyao Li, Yinghong Li, Bo Chen, Juan Tang, Ying Li, Jing Deng, Lili Xie, Guoming Liu, Mingwei Comput Struct Biotechnol J Research Article Tumor heterogeneity remains a major challenge for disease subtyping, risk stratification, and accurate clinical management. Exosome-based liquid biopsy can effectively overcome the limitations of tissue biopsy, achieving minimal invasion, multi-point dynamic monitoring, and good prognosis assessment, and has broad clinical prospects. However, there is still lacking comprehensive analysis of tumor-derived exosome (TDE)-based stratification of risk patients and prognostic assessment for breast cancer with systematic dissection of biological heterogeneity. In this study, the robust corroborative analysis for biomarker discovery (RCABD) strategy was used for the identification of exosome molecules, differential expression verification, risk prediction modeling, heterogenous dissection with multi-ome (6101 molecules), our ExoBCD database (306 molecules), and 53 independent studies (481 molecules). Our results showed that a 10-molecule exosome-derived signature (exoSIG) could successfully fulfill breast cancer risk stratification, making it a novel and accurate exosome prognostic indicator (Cox P = 9.9E-04, HR = 3.3, 95% CI 1.6–6.8). Interestingly, HLA-DQB2 and COL17A1, closely related to tumor metastasis, achieved high performance in prognosis prediction (86.35% contribution) and accuracy (Log-rank P = 0.028, AUC = 85.42%). With the combined information of patient age and tumor stage, they formed a bimolecular risk signature (Clinmin-exoSIG) and a convenient nomogram as operable tools for clinical applications. In conclusion, as an extension of ExoBCD, this study conducted systematic analyses to identify prognostic multi-molecular panel and risk signature, stratify patients and dissect biological heterogeneity based on breast cancer exosomes from a multi-omics perspective. Our results provide an important reference for in-depth exploration of the "biological heterogeneity - risk stratification - prognosis prediction". Research Network of Computational and Structural Biotechnology 2023-05-12 /pmc/articles/PMC10232662/ /pubmed/37273850 http://dx.doi.org/10.1016/j.csbj.2023.05.013 Text en © 2023 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Long, Fei Ma, Haodong Hao, Youjin Tian, Luyao Li, Yinghong Li, Bo Chen, Juan Tang, Ying Li, Jing Deng, Lili Xie, Guoming Liu, Mingwei A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
title | A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
title_full | A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
title_fullStr | A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
title_full_unstemmed | A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
title_short | A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
title_sort | novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10232662/ https://www.ncbi.nlm.nih.gov/pubmed/37273850 http://dx.doi.org/10.1016/j.csbj.2023.05.013 |
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