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Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis

Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients h...

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Autores principales: Radich, Jerald P., Wall, Matthew, Branford, Susan, Campbell, Catarina D., Chaturvedi, Shalini, DeAngelo, Daniel J., Deininger, Michael W., Guinney, Justin, Hochhaus, Andreas, Hughes, Timothy P., Kantarjian, Hagop M., Larson, Richard A., Li, Sai, Maegawa, Rodrigo, Mishra, Kaushal, Obourn, Vanessa, Pinilla-Ibarz, Javier, Purkayastha, Das, Sadek, Islam, Saglio, Giuseppe, Shrestha, Alok, White, Brian S., Druker, Brian J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Fondazione Ferrata Storti 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230428/
https://www.ncbi.nlm.nih.gov/pubmed/36727397
http://dx.doi.org/10.3324/haematol.2022.281878
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author Radich, Jerald P.
Wall, Matthew
Branford, Susan
Campbell, Catarina D.
Chaturvedi, Shalini
DeAngelo, Daniel J.
Deininger, Michael W.
Guinney, Justin
Hochhaus, Andreas
Hughes, Timothy P.
Kantarjian, Hagop M.
Larson, Richard A.
Li, Sai
Maegawa, Rodrigo
Mishra, Kaushal
Obourn, Vanessa
Pinilla-Ibarz, Javier
Purkayastha, Das
Sadek, Islam
Saglio, Giuseppe
Shrestha, Alok
White, Brian S.
Druker, Brian J.
author_facet Radich, Jerald P.
Wall, Matthew
Branford, Susan
Campbell, Catarina D.
Chaturvedi, Shalini
DeAngelo, Daniel J.
Deininger, Michael W.
Guinney, Justin
Hochhaus, Andreas
Hughes, Timothy P.
Kantarjian, Hagop M.
Larson, Richard A.
Li, Sai
Maegawa, Rodrigo
Mishra, Kaushal
Obourn, Vanessa
Pinilla-Ibarz, Javier
Purkayastha, Das
Sadek, Islam
Saglio, Giuseppe
Shrestha, Alok
White, Brian S.
Druker, Brian J.
author_sort Radich, Jerald P.
collection PubMed
description Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients have an excellent response to therapy, while others have a poor response? We studied gene expression in whole blood samples from 112 patients from a large phase III randomized trial (clinicaltrials gov. Identifier: NCT00471497), dichotomizing cases into good responders (BCR::ABL1 ≤10% on the International Scale by 3 and 6 months and ≤0.1% by 12 months) and poor responders (failure to meet these criteria). Predictive models based on gene expression demonstrated the best performance (area under the curve =0.76, standard deviation =0.07). All of the top 20 pathways overexpressed in good responders involved immune regulation, a finding validated in an independent data set. This study emphasizes the importance of pretreatment adaptive immune response in treatment efficacy and suggests biological pathways that can be targeted to improve response.
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spelling pubmed-102304282023-06-01 Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis Radich, Jerald P. Wall, Matthew Branford, Susan Campbell, Catarina D. Chaturvedi, Shalini DeAngelo, Daniel J. Deininger, Michael W. Guinney, Justin Hochhaus, Andreas Hughes, Timothy P. Kantarjian, Hagop M. Larson, Richard A. Li, Sai Maegawa, Rodrigo Mishra, Kaushal Obourn, Vanessa Pinilla-Ibarz, Javier Purkayastha, Das Sadek, Islam Saglio, Giuseppe Shrestha, Alok White, Brian S. Druker, Brian J. Haematologica Article - Chronic Myeloid Leukemia Tyrosine kinase inhibitor therapy revolutionized chronic myeloid leukemia treatment and showed how targeted therapy and molecular monitoring could be used to substantially improve survival outcomes. We used chronic myeloid leukemia as a model to understand a critical question: why do some patients have an excellent response to therapy, while others have a poor response? We studied gene expression in whole blood samples from 112 patients from a large phase III randomized trial (clinicaltrials gov. Identifier: NCT00471497), dichotomizing cases into good responders (BCR::ABL1 ≤10% on the International Scale by 3 and 6 months and ≤0.1% by 12 months) and poor responders (failure to meet these criteria). Predictive models based on gene expression demonstrated the best performance (area under the curve =0.76, standard deviation =0.07). All of the top 20 pathways overexpressed in good responders involved immune regulation, a finding validated in an independent data set. This study emphasizes the importance of pretreatment adaptive immune response in treatment efficacy and suggests biological pathways that can be targeted to improve response. Fondazione Ferrata Storti 2023-02-02 /pmc/articles/PMC10230428/ /pubmed/36727397 http://dx.doi.org/10.3324/haematol.2022.281878 Text en Copyright© 2023 Ferrata Storti Foundation https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (by-nc 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
spellingShingle Article - Chronic Myeloid Leukemia
Radich, Jerald P.
Wall, Matthew
Branford, Susan
Campbell, Catarina D.
Chaturvedi, Shalini
DeAngelo, Daniel J.
Deininger, Michael W.
Guinney, Justin
Hochhaus, Andreas
Hughes, Timothy P.
Kantarjian, Hagop M.
Larson, Richard A.
Li, Sai
Maegawa, Rodrigo
Mishra, Kaushal
Obourn, Vanessa
Pinilla-Ibarz, Javier
Purkayastha, Das
Sadek, Islam
Saglio, Giuseppe
Shrestha, Alok
White, Brian S.
Druker, Brian J.
Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
title Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
title_full Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
title_fullStr Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
title_full_unstemmed Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
title_short Molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
title_sort molecular response in newly diagnosed chronic-phase chronic myeloid leukemia: prediction modeling and pathway analysis
topic Article - Chronic Myeloid Leukemia
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10230428/
https://www.ncbi.nlm.nih.gov/pubmed/36727397
http://dx.doi.org/10.3324/haematol.2022.281878
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