Cargando…

An assessment of prognostic immunity markers in breast cancer

Tumor-infiltrating lymphocytes (TIL) and immunity gene signatures have been reported to be significantly prognostic in breast cancer but have not yet been applied for calculation of risk of recurrence in clinical assays. A compact set of 17 immunity genes was derived herein from an Affymetrix-derive...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Benlong, Chou, Jeff, Tao, Yaozhong, Wu, Dengbin, Wu, Xinhong, Li, Xueqing, Li, Yan, Chu, Yiwei, Tang, Feng, Shi, Yanxia, Ma, Linlin, Zhou, Tong, Kaufmann, William, Carey, Lisa A, Wu, Jiong, Hu, Zhiyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206135/
https://www.ncbi.nlm.nih.gov/pubmed/30393759
http://dx.doi.org/10.1038/s41523-018-0088-0
_version_ 1783366309000511488
author Yang, Benlong
Chou, Jeff
Tao, Yaozhong
Wu, Dengbin
Wu, Xinhong
Li, Xueqing
Li, Yan
Chu, Yiwei
Tang, Feng
Shi, Yanxia
Ma, Linlin
Zhou, Tong
Kaufmann, William
Carey, Lisa A
Wu, Jiong
Hu, Zhiyuan
author_facet Yang, Benlong
Chou, Jeff
Tao, Yaozhong
Wu, Dengbin
Wu, Xinhong
Li, Xueqing
Li, Yan
Chu, Yiwei
Tang, Feng
Shi, Yanxia
Ma, Linlin
Zhou, Tong
Kaufmann, William
Carey, Lisa A
Wu, Jiong
Hu, Zhiyuan
author_sort Yang, Benlong
collection PubMed
description Tumor-infiltrating lymphocytes (TIL) and immunity gene signatures have been reported to be significantly prognostic in breast cancer but have not yet been applied for calculation of risk of recurrence in clinical assays. A compact set of 17 immunity genes was derived herein from an Affymetrix-derived gene expression dataset including 1951 patients (AFFY1951). The 17 immunity genes demonstrated significant prognostic stratification of estrogen receptor (ER)-negative breast cancer patients with high proliferation gene expression. Further analysis of blood and breast cancer single-cell RNA-seq datasets revealed that the 17 immunity genes were derived from TIL that were inactive in the blood and became active in tumor tissue. Expression of the 17 immunity genes was significantly (p < 2.2E-16, n = 91) correlated with TILs percentage on H&E in triple negative breast cancer. To demonstrate the impact of tumor immunity genes on prognosis, we built a Cox model to incorporate breast cancer subtypes, proliferation score and immunity score (72 gene panel) with significant prediction of outcomes (p < 0.0001, n = 1951). The 72 gene panel and its risk evaluation model were validated in two other published gene expression datasets including Illumina beads array data METABRIC (p < 0.0001, n = 1997) and whole transcriptomic mRNA-seq data TCGA (p = 0.00019, n = 996) and in our own targeted RNA-seq data TARGETSEQ (p < 0.0001, n = 303). Further examination of the 72 gene panel in single cell RNA-seq of tumors demonstrated tumor heterogeneity with more than two subtypes observed in each tumor. In conclusion, immunity gene expression was an important parameter for prognosis and should be incorporated into current multi-gene assays to improve assessment of risk of distant metastasis in breast cancer.
format Online
Article
Text
id pubmed-6206135
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-62061352018-11-02 An assessment of prognostic immunity markers in breast cancer Yang, Benlong Chou, Jeff Tao, Yaozhong Wu, Dengbin Wu, Xinhong Li, Xueqing Li, Yan Chu, Yiwei Tang, Feng Shi, Yanxia Ma, Linlin Zhou, Tong Kaufmann, William Carey, Lisa A Wu, Jiong Hu, Zhiyuan NPJ Breast Cancer Article Tumor-infiltrating lymphocytes (TIL) and immunity gene signatures have been reported to be significantly prognostic in breast cancer but have not yet been applied for calculation of risk of recurrence in clinical assays. A compact set of 17 immunity genes was derived herein from an Affymetrix-derived gene expression dataset including 1951 patients (AFFY1951). The 17 immunity genes demonstrated significant prognostic stratification of estrogen receptor (ER)-negative breast cancer patients with high proliferation gene expression. Further analysis of blood and breast cancer single-cell RNA-seq datasets revealed that the 17 immunity genes were derived from TIL that were inactive in the blood and became active in tumor tissue. Expression of the 17 immunity genes was significantly (p < 2.2E-16, n = 91) correlated with TILs percentage on H&E in triple negative breast cancer. To demonstrate the impact of tumor immunity genes on prognosis, we built a Cox model to incorporate breast cancer subtypes, proliferation score and immunity score (72 gene panel) with significant prediction of outcomes (p < 0.0001, n = 1951). The 72 gene panel and its risk evaluation model were validated in two other published gene expression datasets including Illumina beads array data METABRIC (p < 0.0001, n = 1997) and whole transcriptomic mRNA-seq data TCGA (p = 0.00019, n = 996) and in our own targeted RNA-seq data TARGETSEQ (p < 0.0001, n = 303). Further examination of the 72 gene panel in single cell RNA-seq of tumors demonstrated tumor heterogeneity with more than two subtypes observed in each tumor. In conclusion, immunity gene expression was an important parameter for prognosis and should be incorporated into current multi-gene assays to improve assessment of risk of distant metastasis in breast cancer. Nature Publishing Group UK 2018-10-29 /pmc/articles/PMC6206135/ /pubmed/30393759 http://dx.doi.org/10.1038/s41523-018-0088-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yang, Benlong
Chou, Jeff
Tao, Yaozhong
Wu, Dengbin
Wu, Xinhong
Li, Xueqing
Li, Yan
Chu, Yiwei
Tang, Feng
Shi, Yanxia
Ma, Linlin
Zhou, Tong
Kaufmann, William
Carey, Lisa A
Wu, Jiong
Hu, Zhiyuan
An assessment of prognostic immunity markers in breast cancer
title An assessment of prognostic immunity markers in breast cancer
title_full An assessment of prognostic immunity markers in breast cancer
title_fullStr An assessment of prognostic immunity markers in breast cancer
title_full_unstemmed An assessment of prognostic immunity markers in breast cancer
title_short An assessment of prognostic immunity markers in breast cancer
title_sort assessment of prognostic immunity markers in breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206135/
https://www.ncbi.nlm.nih.gov/pubmed/30393759
http://dx.doi.org/10.1038/s41523-018-0088-0
work_keys_str_mv AT yangbenlong anassessmentofprognosticimmunitymarkersinbreastcancer
AT choujeff anassessmentofprognosticimmunitymarkersinbreastcancer
AT taoyaozhong anassessmentofprognosticimmunitymarkersinbreastcancer
AT wudengbin anassessmentofprognosticimmunitymarkersinbreastcancer
AT wuxinhong anassessmentofprognosticimmunitymarkersinbreastcancer
AT lixueqing anassessmentofprognosticimmunitymarkersinbreastcancer
AT liyan anassessmentofprognosticimmunitymarkersinbreastcancer
AT chuyiwei anassessmentofprognosticimmunitymarkersinbreastcancer
AT tangfeng anassessmentofprognosticimmunitymarkersinbreastcancer
AT shiyanxia anassessmentofprognosticimmunitymarkersinbreastcancer
AT malinlin anassessmentofprognosticimmunitymarkersinbreastcancer
AT zhoutong anassessmentofprognosticimmunitymarkersinbreastcancer
AT kaufmannwilliam anassessmentofprognosticimmunitymarkersinbreastcancer
AT careylisaa anassessmentofprognosticimmunitymarkersinbreastcancer
AT wujiong anassessmentofprognosticimmunitymarkersinbreastcancer
AT huzhiyuan anassessmentofprognosticimmunitymarkersinbreastcancer
AT yangbenlong assessmentofprognosticimmunitymarkersinbreastcancer
AT choujeff assessmentofprognosticimmunitymarkersinbreastcancer
AT taoyaozhong assessmentofprognosticimmunitymarkersinbreastcancer
AT wudengbin assessmentofprognosticimmunitymarkersinbreastcancer
AT wuxinhong assessmentofprognosticimmunitymarkersinbreastcancer
AT lixueqing assessmentofprognosticimmunitymarkersinbreastcancer
AT liyan assessmentofprognosticimmunitymarkersinbreastcancer
AT chuyiwei assessmentofprognosticimmunitymarkersinbreastcancer
AT tangfeng assessmentofprognosticimmunitymarkersinbreastcancer
AT shiyanxia assessmentofprognosticimmunitymarkersinbreastcancer
AT malinlin assessmentofprognosticimmunitymarkersinbreastcancer
AT zhoutong assessmentofprognosticimmunitymarkersinbreastcancer
AT kaufmannwilliam assessmentofprognosticimmunitymarkersinbreastcancer
AT careylisaa assessmentofprognosticimmunitymarkersinbreastcancer
AT wujiong assessmentofprognosticimmunitymarkersinbreastcancer
AT huzhiyuan assessmentofprognosticimmunitymarkersinbreastcancer