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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for Cancer Research 2023
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.
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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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