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Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population

Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients wi...

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Autores principales: Hamilton, Alina M., Van Alsten, Sarah C., Gao, Xiaohua, Nsonwu-Farley, Joseph, Calhoun, Benjamin C., Love, Michael I., Troester, Melissa A., Hoadley, Katherine A.
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/PMC10035450/
https://www.ncbi.nlm.nih.gov/pubmed/36968228
http://dx.doi.org/10.1158/2767-9764.CRC-22-0267
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author Hamilton, Alina M.
Van Alsten, Sarah C.
Gao, Xiaohua
Nsonwu-Farley, Joseph
Calhoun, Benjamin C.
Love, Michael I.
Troester, Melissa A.
Hoadley, Katherine A.
author_facet Hamilton, Alina M.
Van Alsten, Sarah C.
Gao, Xiaohua
Nsonwu-Farley, Joseph
Calhoun, Benjamin C.
Love, Michael I.
Troester, Melissa A.
Hoadley, Katherine A.
author_sort Hamilton, Alina M.
collection PubMed
description Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency. SIGNIFICANCE: Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants.
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spelling pubmed-100354502023-03-24 Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population Hamilton, Alina M. Van Alsten, Sarah C. Gao, Xiaohua Nsonwu-Farley, Joseph Calhoun, Benjamin C. Love, Michael I. Troester, Melissa A. Hoadley, Katherine A. Cancer Res Commun Research Article Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency. SIGNIFICANCE: Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants. American Association for Cancer Research 2023-01-05 /pmc/articles/PMC10035450/ /pubmed/36968228 http://dx.doi.org/10.1158/2767-9764.CRC-22-0267 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
Hamilton, Alina M.
Van Alsten, Sarah C.
Gao, Xiaohua
Nsonwu-Farley, Joseph
Calhoun, Benjamin C.
Love, Michael I.
Troester, Melissa A.
Hoadley, Katherine A.
Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population
title Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population
title_full Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population
title_fullStr Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population
title_full_unstemmed Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population
title_short Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population
title_sort incorporating rna-based risk scores for genomic instability to predict breast cancer recurrence and immunogenicity in a diverse population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035450/
https://www.ncbi.nlm.nih.gov/pubmed/36968228
http://dx.doi.org/10.1158/2767-9764.CRC-22-0267
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