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An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers
An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecul...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for Cancer Research
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540743/ https://www.ncbi.nlm.nih.gov/pubmed/37707389 http://dx.doi.org/10.1158/2767-9764.CRC-23-0196 |
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author | Guyot, Boris Clément, Flora Drouet, Youenn Schmidt, Xenia Lefort, Sylvain Delay, Emmanuel Treilleux, Isabelle Foy, Jean-Philippe Jeanpierre, Sandrine Thomas, Emilie Kielbassa, Janice Tonon, Laurie Zhu, Helen He Saintigny, Pierre Gao, Wei-Qiang de la Fouchardiere, Arnaud Tirode, Franck Viari, Alain Blay, Jean-Yves Maguer-Satta, Véronique |
author_facet | Guyot, Boris Clément, Flora Drouet, Youenn Schmidt, Xenia Lefort, Sylvain Delay, Emmanuel Treilleux, Isabelle Foy, Jean-Philippe Jeanpierre, Sandrine Thomas, Emilie Kielbassa, Janice Tonon, Laurie Zhu, Helen He Saintigny, Pierre Gao, Wei-Qiang de la Fouchardiere, Arnaud Tirode, Franck Viari, Alain Blay, Jean-Yves Maguer-Satta, Véronique |
author_sort | Guyot, Boris |
collection | PubMed |
description | An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecular identity of aggressive cancer cells. We used epithelial primary cells and developed a breast cancer stem cell–based progressive model. The superiority of the early-transformed isolated molecular index was evaluated by large-scale analysis in solid cancers. BMP2-driven cell transformation increases CD10 expression which preserves stemness properties. Our model identified a unique set of 159 genes enriched in G(2)–M cell-cycle phases and spindle assembly complex. Using samples predisposed to transformation, we confirmed the value of an early neoplasia index associated to CD10 (ENI10) to discriminate premalignant status of a human tissue. Using a stratified Cox model, a large-scale analysis (>10,000 samples, The Cancer Genome Atlas Pan-Cancer) validated a strong risk gradient (HRs reaching HR = 5.15; 95% confidence interval: 4.00–6.64) for high ENI10 levels. Through different databases, Cox regression model analyses highlighted an association between ENI10 and poor progression-free intervals for more than 50% of cancer subtypes tested, and the potential of ENI10 to predict drug efficacy. The ENI10 index constitutes a robust tool to detect pretransformed tissues and identify high-risk patients at diagnosis. Owing to its biological link with refractory cancer stem cells, the ENI10 index constitutes a unique way of identifying effective treatments to improve clinical care. SIGNIFICANCE: We identified a molecular signature called ENI10 which, owing to its biological link with stem cell properties, predicts patient outcome and drugs efficiency in breast and several other cancers. ENI10 should allow early and optimized clinical management of a broad number of cancers, regardless of the stage of tumor progression. |
format | Online Article Text |
id | pubmed-10540743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for Cancer Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-105407432023-09-30 An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers Guyot, Boris Clément, Flora Drouet, Youenn Schmidt, Xenia Lefort, Sylvain Delay, Emmanuel Treilleux, Isabelle Foy, Jean-Philippe Jeanpierre, Sandrine Thomas, Emilie Kielbassa, Janice Tonon, Laurie Zhu, Helen He Saintigny, Pierre Gao, Wei-Qiang de la Fouchardiere, Arnaud Tirode, Franck Viari, Alain Blay, Jean-Yves Maguer-Satta, Véronique Cancer Res Commun Research Article An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecular identity of aggressive cancer cells. We used epithelial primary cells and developed a breast cancer stem cell–based progressive model. The superiority of the early-transformed isolated molecular index was evaluated by large-scale analysis in solid cancers. BMP2-driven cell transformation increases CD10 expression which preserves stemness properties. Our model identified a unique set of 159 genes enriched in G(2)–M cell-cycle phases and spindle assembly complex. Using samples predisposed to transformation, we confirmed the value of an early neoplasia index associated to CD10 (ENI10) to discriminate premalignant status of a human tissue. Using a stratified Cox model, a large-scale analysis (>10,000 samples, The Cancer Genome Atlas Pan-Cancer) validated a strong risk gradient (HRs reaching HR = 5.15; 95% confidence interval: 4.00–6.64) for high ENI10 levels. Through different databases, Cox regression model analyses highlighted an association between ENI10 and poor progression-free intervals for more than 50% of cancer subtypes tested, and the potential of ENI10 to predict drug efficacy. The ENI10 index constitutes a robust tool to detect pretransformed tissues and identify high-risk patients at diagnosis. Owing to its biological link with refractory cancer stem cells, the ENI10 index constitutes a unique way of identifying effective treatments to improve clinical care. SIGNIFICANCE: We identified a molecular signature called ENI10 which, owing to its biological link with stem cell properties, predicts patient outcome and drugs efficiency in breast and several other cancers. ENI10 should allow early and optimized clinical management of a broad number of cancers, regardless of the stage of tumor progression. American Association for Cancer Research 2023-09-29 /pmc/articles/PMC10540743/ /pubmed/37707389 http://dx.doi.org/10.1158/2767-9764.CRC-23-0196 Text en © 2023 The Authors; Published by the American Association for Cancer Research https://creativecommons.org/licenses/by/4.0/This open access article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. |
spellingShingle | Research Article Guyot, Boris Clément, Flora Drouet, Youenn Schmidt, Xenia Lefort, Sylvain Delay, Emmanuel Treilleux, Isabelle Foy, Jean-Philippe Jeanpierre, Sandrine Thomas, Emilie Kielbassa, Janice Tonon, Laurie Zhu, Helen He Saintigny, Pierre Gao, Wei-Qiang de la Fouchardiere, Arnaud Tirode, Franck Viari, Alain Blay, Jean-Yves Maguer-Satta, Véronique An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers |
title | An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers |
title_full | An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers |
title_fullStr | An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers |
title_full_unstemmed | An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers |
title_short | An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers |
title_sort | early neoplasia index (eni10), based on molecular identity of cd10 cells and associated stemness biomarkers, is a predictor of patient outcome in many cancers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540743/ https://www.ncbi.nlm.nih.gov/pubmed/37707389 http://dx.doi.org/10.1158/2767-9764.CRC-23-0196 |
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