M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome
BackgroundBreast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient’s outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as i...
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doaj-1030d58f6c214ea5b12e731f1782ccda2020-11-25T04:06:41ZengFrontiers Media S.A.Frontiers in Immunology1664-32242020-11-011110.3389/fimmu.2020.560074560074M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient OutcomeMahmood Yaseen Hachim0Ibrahim Yaseen Hachim1Ibrahim Yaseen Hachim2Iman M. Talaat3Iman M. Talaat4Iman M. Talaat5Nada M. Yakout6Rifat Hamoudi7Rifat Hamoudi8Rifat Hamoudi9College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab EmiratesSharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab EmiratesClinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab EmiratesSharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab EmiratesClinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab EmiratesPathology Department, Faculty of Medicine, Alexandria University, Alexandria, EgyptPathology Department, Faculty of Medicine, Alexandria University, Alexandria, EgyptSharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab EmiratesClinical Sciences Department, College of Medicine, University of Sharjah, Sharjah, United Arab EmiratesDivision of Surgery and Interventional Science, University College London, London, United KingdomBackgroundBreast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient’s outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells.ObjectivesTo mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches.Materials and MethodsTranscriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry.ResultsSeven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes.ConclusionAdding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach.https://www.frontiersin.org/articles/10.3389/fimmu.2020.560074/fullbasal likebreast cancermacrophagestumor infiltrated immune cellstranscriptomic |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mahmood Yaseen Hachim Ibrahim Yaseen Hachim Ibrahim Yaseen Hachim Iman M. Talaat Iman M. Talaat Iman M. Talaat Nada M. Yakout Rifat Hamoudi Rifat Hamoudi Rifat Hamoudi |
spellingShingle |
Mahmood Yaseen Hachim Ibrahim Yaseen Hachim Ibrahim Yaseen Hachim Iman M. Talaat Iman M. Talaat Iman M. Talaat Nada M. Yakout Rifat Hamoudi Rifat Hamoudi Rifat Hamoudi M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome Frontiers in Immunology basal like breast cancer macrophages tumor infiltrated immune cells transcriptomic |
author_facet |
Mahmood Yaseen Hachim Ibrahim Yaseen Hachim Ibrahim Yaseen Hachim Iman M. Talaat Iman M. Talaat Iman M. Talaat Nada M. Yakout Rifat Hamoudi Rifat Hamoudi Rifat Hamoudi |
author_sort |
Mahmood Yaseen Hachim |
title |
M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome |
title_short |
M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome |
title_full |
M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome |
title_fullStr |
M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome |
title_full_unstemmed |
M1 Polarization Markers Are Upregulated in Basal-Like Breast Cancer Molecular Subtype and Associated With Favorable Patient Outcome |
title_sort |
m1 polarization markers are upregulated in basal-like breast cancer molecular subtype and associated with favorable patient outcome |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Immunology |
issn |
1664-3224 |
publishDate |
2020-11-01 |
description |
BackgroundBreast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient’s outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells.ObjectivesTo mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches.Materials and MethodsTranscriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry.ResultsSeven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes.ConclusionAdding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach. |
topic |
basal like breast cancer macrophages tumor infiltrated immune cells transcriptomic |
url |
https://www.frontiersin.org/articles/10.3389/fimmu.2020.560074/full |
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