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Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes

BACKGROUND: A unique 12-chemokine gene expression score (CS) accurately predicted the presence of tumor-localized, ectopic lymph node-like structures (TL-ELNs) and improved overall survival (OS) in primary colorectal cancer and metastatic melanoma. We analyzed the correlation between CS, clinicopath...

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Autores principales: Prabhakaran, Sangeetha, Rizk, Victoria T., Ma, Zhenjun, Cheng, Chia-Ho, Berglund, Anders E., Coppola, Dominico, Khalil, Farah, Mulé, James J., Soliman, Hatem H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477261/
https://www.ncbi.nlm.nih.gov/pubmed/28629479
http://dx.doi.org/10.1186/s13058-017-0864-z
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author Prabhakaran, Sangeetha
Rizk, Victoria T.
Ma, Zhenjun
Cheng, Chia-Ho
Berglund, Anders E.
Coppola, Dominico
Khalil, Farah
Mulé, James J.
Soliman, Hatem H.
author_facet Prabhakaran, Sangeetha
Rizk, Victoria T.
Ma, Zhenjun
Cheng, Chia-Ho
Berglund, Anders E.
Coppola, Dominico
Khalil, Farah
Mulé, James J.
Soliman, Hatem H.
author_sort Prabhakaran, Sangeetha
collection PubMed
description BACKGROUND: A unique 12-chemokine gene expression score (CS) accurately predicted the presence of tumor-localized, ectopic lymph node-like structures (TL-ELNs) and improved overall survival (OS) in primary colorectal cancer and metastatic melanoma. We analyzed the correlation between CS, clinicopathological variables, molecular data, and 366 survival in Moffitt Cancer Center’s Total Cancer Care (TCC) patients with non-metastatic breast cancer. METHODS: Affymetrix gene expression profiles were used to interrogate the CS by the principal component method. Breast tumors were classified as high or low score based on median split, and correlations between clinicopathologic variables, PAM50 molecular subtype, and ELN formation were analyzed using the TCC dataset. Differences in overall survival (OS) and recurrence-free survival (RFS) in the larger KM Plot breast cancer public datasets were compared using Kaplan-Meier curves. RESULTS: We divided the Total Cancer Care (TCC) breast cancer patients into two groups of high or low CS. Mean CS was 0.24 (range, 2.2–2.1). Patients with higher CS were more likely to be white (172 vs. 159; p = 0.03), had poorly differentiated tumors (112 vs. 59; p <0.0001), ER/PR negative (41 vs. 26) and HER2 positive (36 vs. 19; p = 0.001), and contain TL-ELNs. Higher CS scores were also seen in the basal and HER2+ molecular subtypes. In the KM Plot breast cancer datasets higher CS patients demonstrated superior OS (HR = 0.73, p = 0.008) and RFS (HR 0.76, p = <0.0001), especially in basal and HER2+ patients. CONCLUSIONS: High CS breast tumors tend to be higher grade, basal or HER2+, and present more frequently in Caucasians. However, this group of patients also shows the presence of TL-ELNs within the tumor microenvironment and has better survival outcomes. The CS is a novel tool that can identify breast cancer patients with tumors of a unique intratumoral immune composition and better prognosis. Whether or not the CS is a predictive response marker in breast cancer patients undergoing immunotherapy remains to be determined. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-017-0864-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-54772612017-06-23 Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes Prabhakaran, Sangeetha Rizk, Victoria T. Ma, Zhenjun Cheng, Chia-Ho Berglund, Anders E. Coppola, Dominico Khalil, Farah Mulé, James J. Soliman, Hatem H. Breast Cancer Res Research Article BACKGROUND: A unique 12-chemokine gene expression score (CS) accurately predicted the presence of tumor-localized, ectopic lymph node-like structures (TL-ELNs) and improved overall survival (OS) in primary colorectal cancer and metastatic melanoma. We analyzed the correlation between CS, clinicopathological variables, molecular data, and 366 survival in Moffitt Cancer Center’s Total Cancer Care (TCC) patients with non-metastatic breast cancer. METHODS: Affymetrix gene expression profiles were used to interrogate the CS by the principal component method. Breast tumors were classified as high or low score based on median split, and correlations between clinicopathologic variables, PAM50 molecular subtype, and ELN formation were analyzed using the TCC dataset. Differences in overall survival (OS) and recurrence-free survival (RFS) in the larger KM Plot breast cancer public datasets were compared using Kaplan-Meier curves. RESULTS: We divided the Total Cancer Care (TCC) breast cancer patients into two groups of high or low CS. Mean CS was 0.24 (range, 2.2–2.1). Patients with higher CS were more likely to be white (172 vs. 159; p = 0.03), had poorly differentiated tumors (112 vs. 59; p <0.0001), ER/PR negative (41 vs. 26) and HER2 positive (36 vs. 19; p = 0.001), and contain TL-ELNs. Higher CS scores were also seen in the basal and HER2+ molecular subtypes. In the KM Plot breast cancer datasets higher CS patients demonstrated superior OS (HR = 0.73, p = 0.008) and RFS (HR 0.76, p = <0.0001), especially in basal and HER2+ patients. CONCLUSIONS: High CS breast tumors tend to be higher grade, basal or HER2+, and present more frequently in Caucasians. However, this group of patients also shows the presence of TL-ELNs within the tumor microenvironment and has better survival outcomes. The CS is a novel tool that can identify breast cancer patients with tumors of a unique intratumoral immune composition and better prognosis. Whether or not the CS is a predictive response marker in breast cancer patients undergoing immunotherapy remains to be determined. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-017-0864-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-19 2017 /pmc/articles/PMC5477261/ /pubmed/28629479 http://dx.doi.org/10.1186/s13058-017-0864-z Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Prabhakaran, Sangeetha
Rizk, Victoria T.
Ma, Zhenjun
Cheng, Chia-Ho
Berglund, Anders E.
Coppola, Dominico
Khalil, Farah
Mulé, James J.
Soliman, Hatem H.
Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
title Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
title_full Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
title_fullStr Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
title_full_unstemmed Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
title_short Evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
title_sort evaluation of invasive breast cancer samples using a 12-chemokine gene expression score: correlation with clinical outcomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477261/
https://www.ncbi.nlm.nih.gov/pubmed/28629479
http://dx.doi.org/10.1186/s13058-017-0864-z
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