Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping

SIMPLE SUMMARY: Triple-negative breast cancer (TNBC) is a heterogeneous disease. A proper classification system is needed to develop targetable biomarkers and guide personalized treatment in clinical practice. However, there has been no consensus on the molecular subtypes of TNBC, probably due to di...

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Autores principales: Yu, Xinjian, Liu, Yongjing, Chen, Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179838/
https://www.ncbi.nlm.nih.gov/pubmed/35681552
http://dx.doi.org/10.3390/cancers14112571
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author Yu, Xinjian
Liu, Yongjing
Chen, Ming
author_facet Yu, Xinjian
Liu, Yongjing
Chen, Ming
author_sort Yu, Xinjian
collection PubMed
description SIMPLE SUMMARY: Triple-negative breast cancer (TNBC) is a heterogeneous disease. A proper classification system is needed to develop targetable biomarkers and guide personalized treatment in clinical practice. However, there has been no consensus on the molecular subtypes of TNBC, probably due to discrepancies in technical and computational methods chosen by different research groups. In this paper, we reassessed each major step for TNBC subtyping and provided suggestions, which promote rational workflow design and ensure reliable and reproducible results for future studies. We presented a recommended pipeline to the existing data, validated established TNBC subtypes with a larger sample size, and revealed two intermediate subtypes with prognostic significance. This work provides perspectives on issues and limitations regarding TNBC subtyping, indicating promising directions for developing targeted therapy based on the molecular characteristics of each TNBC subtype. ABSTRACT: Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification.
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spelling pubmed-91798382022-06-10 Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping Yu, Xinjian Liu, Yongjing Chen, Ming Cancers (Basel) Article SIMPLE SUMMARY: Triple-negative breast cancer (TNBC) is a heterogeneous disease. A proper classification system is needed to develop targetable biomarkers and guide personalized treatment in clinical practice. However, there has been no consensus on the molecular subtypes of TNBC, probably due to discrepancies in technical and computational methods chosen by different research groups. In this paper, we reassessed each major step for TNBC subtyping and provided suggestions, which promote rational workflow design and ensure reliable and reproducible results for future studies. We presented a recommended pipeline to the existing data, validated established TNBC subtypes with a larger sample size, and revealed two intermediate subtypes with prognostic significance. This work provides perspectives on issues and limitations regarding TNBC subtyping, indicating promising directions for developing targeted therapy based on the molecular characteristics of each TNBC subtype. ABSTRACT: Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification. MDPI 2022-05-24 /pmc/articles/PMC9179838/ /pubmed/35681552 http://dx.doi.org/10.3390/cancers14112571 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Xinjian
Liu, Yongjing
Chen, Ming
Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping
title Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping
title_full Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping
title_fullStr Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping
title_full_unstemmed Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping
title_short Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping
title_sort reassessment of reliability and reproducibility for triple-negative breast cancer subtyping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9179838/
https://www.ncbi.nlm.nih.gov/pubmed/35681552
http://dx.doi.org/10.3390/cancers14112571
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AT liuyongjing reassessmentofreliabilityandreproducibilityfortriplenegativebreastcancersubtyping
AT chenming reassessmentofreliabilityandreproducibilityfortriplenegativebreastcancersubtyping