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Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment

In the microenvironment of breast cancer, immune cell infiltration is associated with an improved prognosis. To identify immune-related prognostic markers and therapeutic targets, we determined the lymphocyte-specific kinase (LCK) metagene scores of samples from breast cancer patients in The Cancer...

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Autores principales: Bai, Fang, Jin, Yuchun, Zhang, Peng, Chen, Hongliang, Fu, Yipeng, Zhang, Mingdi, Weng, Ziyi, Wu, Kejin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874454/
https://www.ncbi.nlm.nih.gov/pubmed/31715586
http://dx.doi.org/10.18632/aging.102373
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author Bai, Fang
Jin, Yuchun
Zhang, Peng
Chen, Hongliang
Fu, Yipeng
Zhang, Mingdi
Weng, Ziyi
Wu, Kejin
author_facet Bai, Fang
Jin, Yuchun
Zhang, Peng
Chen, Hongliang
Fu, Yipeng
Zhang, Mingdi
Weng, Ziyi
Wu, Kejin
author_sort Bai, Fang
collection PubMed
description In the microenvironment of breast cancer, immune cell infiltration is associated with an improved prognosis. To identify immune-related prognostic markers and therapeutic targets, we determined the lymphocyte-specific kinase (LCK) metagene scores of samples from breast cancer patients in The Cancer Genome Atlas. The LCK metagene score correlated highly with other immune-related scores, as well as with the clinical stage, prognosis and tumor suppressor gene mutation status (BRCA2, TP53, PTEN) of patients in the four breast cancer subtypes. A weighted gene co-expression network analysis was performed to detect representative genes from LCK metagene-related gene modules. In two of these modules, the levels of the co-expressed genes correlated highly with LCK metagene levels, so we conducted an enrichment analysis to discover their functions. We also identified differentially expressed genes in samples with high and low LCK metagene scores. By examining the overlapping results from these analyses, we obtained 115 genes, and found that 22 of them were independent predictors of overall survival in breast cancer patients. These genes were validated for their prognostic and diagnostic value with external data sets and paired tumor and non-tumor tissues. The genes identified herein could serve as diagnostic/prognostic markers and immune-related therapeutic targets in breast cancer.
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spelling pubmed-68744542019-12-03 Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment Bai, Fang Jin, Yuchun Zhang, Peng Chen, Hongliang Fu, Yipeng Zhang, Mingdi Weng, Ziyi Wu, Kejin Aging (Albany NY) Research Paper In the microenvironment of breast cancer, immune cell infiltration is associated with an improved prognosis. To identify immune-related prognostic markers and therapeutic targets, we determined the lymphocyte-specific kinase (LCK) metagene scores of samples from breast cancer patients in The Cancer Genome Atlas. The LCK metagene score correlated highly with other immune-related scores, as well as with the clinical stage, prognosis and tumor suppressor gene mutation status (BRCA2, TP53, PTEN) of patients in the four breast cancer subtypes. A weighted gene co-expression network analysis was performed to detect representative genes from LCK metagene-related gene modules. In two of these modules, the levels of the co-expressed genes correlated highly with LCK metagene levels, so we conducted an enrichment analysis to discover their functions. We also identified differentially expressed genes in samples with high and low LCK metagene scores. By examining the overlapping results from these analyses, we obtained 115 genes, and found that 22 of them were independent predictors of overall survival in breast cancer patients. These genes were validated for their prognostic and diagnostic value with external data sets and paired tumor and non-tumor tissues. The genes identified herein could serve as diagnostic/prognostic markers and immune-related therapeutic targets in breast cancer. Impact Journals 2019-11-12 /pmc/articles/PMC6874454/ /pubmed/31715586 http://dx.doi.org/10.18632/aging.102373 Text en Copyright © 2019 Bai et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Bai, Fang
Jin, Yuchun
Zhang, Peng
Chen, Hongliang
Fu, Yipeng
Zhang, Mingdi
Weng, Ziyi
Wu, Kejin
Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
title Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
title_full Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
title_fullStr Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
title_full_unstemmed Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
title_short Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
title_sort bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874454/
https://www.ncbi.nlm.nih.gov/pubmed/31715586
http://dx.doi.org/10.18632/aging.102373
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