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The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design

BACKGROUND: The proportion of tumors of various histologies that may respond to drugs targeted to molecular alterations is unknown. NCI-MATCH, a collaboration between ECOG-ACRIN Cancer Research Group and the National Cancer Institute, was initiated to find efficacy signals by matching patients with...

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Autores principales: Flaherty, Keith T, Gray, Robert, Chen, Alice, Li, Shuli, Patton, David, Hamilton, Stanley R, Williams, Paul M, Mitchell, Edith P, Iafrate, A John, Sklar, Jeffrey, Harris, Lyndsay N, McShane, Lisa M, Rubinstein, Larry V, Sims, David J, Routbort, Mark, Coffey, Brent, Fu, Tony, Zwiebel, James A, Little, Richard F, Marinucci, Donna, Catalano, Robert, Magnan, Rick, Kibbe, Warren, Weil, Carol, Tricoli, James V, Alexander, Brian, Kumar, Shaji, Schwartz, Gary K, Meric-Bernstam, Funda, Lih, Chih-Jian, McCaskill-Stevens, Worta, Caimi, Paolo, Takebe, Naoko, Datta, Vivekananda, Arteaga, Carlos L, Abrams, Jeffrey S, Comis, Robert, O’Dwyer, Peter J, Conley, Barbara A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566320/
https://www.ncbi.nlm.nih.gov/pubmed/31922567
http://dx.doi.org/10.1093/jnci/djz245
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author Flaherty, Keith T
Gray, Robert
Chen, Alice
Li, Shuli
Patton, David
Hamilton, Stanley R
Williams, Paul M
Mitchell, Edith P
Iafrate, A John
Sklar, Jeffrey
Harris, Lyndsay N
McShane, Lisa M
Rubinstein, Larry V
Sims, David J
Routbort, Mark
Coffey, Brent
Fu, Tony
Zwiebel, James A
Little, Richard F
Marinucci, Donna
Catalano, Robert
Magnan, Rick
Kibbe, Warren
Weil, Carol
Tricoli, James V
Alexander, Brian
Kumar, Shaji
Schwartz, Gary K
Meric-Bernstam, Funda
Lih, Chih-Jian
McCaskill-Stevens, Worta
Caimi, Paolo
Takebe, Naoko
Datta, Vivekananda
Arteaga, Carlos L
Abrams, Jeffrey S
Comis, Robert
O’Dwyer, Peter J
Conley, Barbara A
author_facet Flaherty, Keith T
Gray, Robert
Chen, Alice
Li, Shuli
Patton, David
Hamilton, Stanley R
Williams, Paul M
Mitchell, Edith P
Iafrate, A John
Sklar, Jeffrey
Harris, Lyndsay N
McShane, Lisa M
Rubinstein, Larry V
Sims, David J
Routbort, Mark
Coffey, Brent
Fu, Tony
Zwiebel, James A
Little, Richard F
Marinucci, Donna
Catalano, Robert
Magnan, Rick
Kibbe, Warren
Weil, Carol
Tricoli, James V
Alexander, Brian
Kumar, Shaji
Schwartz, Gary K
Meric-Bernstam, Funda
Lih, Chih-Jian
McCaskill-Stevens, Worta
Caimi, Paolo
Takebe, Naoko
Datta, Vivekananda
Arteaga, Carlos L
Abrams, Jeffrey S
Comis, Robert
O’Dwyer, Peter J
Conley, Barbara A
author_sort Flaherty, Keith T
collection PubMed
description BACKGROUND: The proportion of tumors of various histologies that may respond to drugs targeted to molecular alterations is unknown. NCI-MATCH, a collaboration between ECOG-ACRIN Cancer Research Group and the National Cancer Institute, was initiated to find efficacy signals by matching patients with refractory malignancies to treatment targeted to potential tumor molecular drivers regardless of cancer histology. METHODS: Trial development required assumptions about molecular target prevalence, accrual rates, treatment eligibility, and enrollment rates as well as consideration of logistical requirements. Central tumor profiling was performed with an investigational next-generation DNA–targeted sequencing assay of alterations in 143 genes, and protein expression of protein expression of phosphatase and tensin homolog, mutL homolog 1, mutS homolog 2, and RB transcriptional corepressor 1. Treatments were allocated with a validated computational platform (MATCHBOX). A preplanned interim analysis evaluated assumptions and feasibility in this novel trial. RESULTS: At interim analysis, accrual was robust, tumor biopsies were safe (<1% severe events), and profiling success was 87.3%. Actionable molecular alteration frequency met expectations, but assignment and enrollment lagged due to histology exclusions and mismatch of resources to demand. To address this lag, we revised estimates of mutation frequencies, increased screening sample size, added treatments, and improved assay throughput and efficiency (93.9% completion and 14-day turnaround). CONCLUSIONS: The experiences in the design and implementation of the NCI-MATCH trial suggest that profiling from fresh tumor biopsies and assigning treatment can be performed efficiently in a large national network trial. The success of such trials necessitates a broad screening approach and many treatment options easily accessible to patients.
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spelling pubmed-75663202020-10-21 The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design Flaherty, Keith T Gray, Robert Chen, Alice Li, Shuli Patton, David Hamilton, Stanley R Williams, Paul M Mitchell, Edith P Iafrate, A John Sklar, Jeffrey Harris, Lyndsay N McShane, Lisa M Rubinstein, Larry V Sims, David J Routbort, Mark Coffey, Brent Fu, Tony Zwiebel, James A Little, Richard F Marinucci, Donna Catalano, Robert Magnan, Rick Kibbe, Warren Weil, Carol Tricoli, James V Alexander, Brian Kumar, Shaji Schwartz, Gary K Meric-Bernstam, Funda Lih, Chih-Jian McCaskill-Stevens, Worta Caimi, Paolo Takebe, Naoko Datta, Vivekananda Arteaga, Carlos L Abrams, Jeffrey S Comis, Robert O’Dwyer, Peter J Conley, Barbara A J Natl Cancer Inst Articles BACKGROUND: The proportion of tumors of various histologies that may respond to drugs targeted to molecular alterations is unknown. NCI-MATCH, a collaboration between ECOG-ACRIN Cancer Research Group and the National Cancer Institute, was initiated to find efficacy signals by matching patients with refractory malignancies to treatment targeted to potential tumor molecular drivers regardless of cancer histology. METHODS: Trial development required assumptions about molecular target prevalence, accrual rates, treatment eligibility, and enrollment rates as well as consideration of logistical requirements. Central tumor profiling was performed with an investigational next-generation DNA–targeted sequencing assay of alterations in 143 genes, and protein expression of protein expression of phosphatase and tensin homolog, mutL homolog 1, mutS homolog 2, and RB transcriptional corepressor 1. Treatments were allocated with a validated computational platform (MATCHBOX). A preplanned interim analysis evaluated assumptions and feasibility in this novel trial. RESULTS: At interim analysis, accrual was robust, tumor biopsies were safe (<1% severe events), and profiling success was 87.3%. Actionable molecular alteration frequency met expectations, but assignment and enrollment lagged due to histology exclusions and mismatch of resources to demand. To address this lag, we revised estimates of mutation frequencies, increased screening sample size, added treatments, and improved assay throughput and efficiency (93.9% completion and 14-day turnaround). CONCLUSIONS: The experiences in the design and implementation of the NCI-MATCH trial suggest that profiling from fresh tumor biopsies and assigning treatment can be performed efficiently in a large national network trial. The success of such trials necessitates a broad screening approach and many treatment options easily accessible to patients. Oxford University Press 2020-01-10 /pmc/articles/PMC7566320/ /pubmed/31922567 http://dx.doi.org/10.1093/jnci/djz245 Text en © The Author(s) 2019. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contactjournals.permissions@oup.com
spellingShingle Articles
Flaherty, Keith T
Gray, Robert
Chen, Alice
Li, Shuli
Patton, David
Hamilton, Stanley R
Williams, Paul M
Mitchell, Edith P
Iafrate, A John
Sklar, Jeffrey
Harris, Lyndsay N
McShane, Lisa M
Rubinstein, Larry V
Sims, David J
Routbort, Mark
Coffey, Brent
Fu, Tony
Zwiebel, James A
Little, Richard F
Marinucci, Donna
Catalano, Robert
Magnan, Rick
Kibbe, Warren
Weil, Carol
Tricoli, James V
Alexander, Brian
Kumar, Shaji
Schwartz, Gary K
Meric-Bernstam, Funda
Lih, Chih-Jian
McCaskill-Stevens, Worta
Caimi, Paolo
Takebe, Naoko
Datta, Vivekananda
Arteaga, Carlos L
Abrams, Jeffrey S
Comis, Robert
O’Dwyer, Peter J
Conley, Barbara A
The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design
title The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design
title_full The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design
title_fullStr The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design
title_full_unstemmed The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design
title_short The Molecular Analysis for Therapy Choice (NCI-MATCH) Trial: Lessons for Genomic Trial Design
title_sort molecular analysis for therapy choice (nci-match) trial: lessons for genomic trial design
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566320/
https://www.ncbi.nlm.nih.gov/pubmed/31922567
http://dx.doi.org/10.1093/jnci/djz245
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