Research Paper Volume 11, Issue 21 pp 9328—9347

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

Fang Bai 1, *, , Yuchun Jin 1, *, , Peng Zhang 1, , Hongliang Chen 1, , Yipeng Fu 1, , Mingdi Zhang 1, , Ziyi Weng 2, , Kejin Wu 1, ,

  • 1 Breast Surgery, Obstetrics and Gynecology Hospital of Fudan University, Shanghai 200011, China
  • 2 Department of General Surgery, Shanghai International Medical Center, Shanghai 201318, China
* Equal contribution

received: May 13, 2019 ; accepted: October 12, 2019 ; published: November 12, 2019 ;

https://doi.org/10.18632/aging.102373
How to Cite

Copyright © 2019 Bai et al. 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.

Abstract

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.

Abbreviations

DEGs: differentially expressed genes; ESTIMATE: Estimation of STromal and Immune cells in MAlignant Tumours using Expression data; GO: gene ontology; LCK: lymphocyte-specific kinase; TCGA: The Cancer Genome Atlas; TNBC: triple-negative breast cancer; TPM: transcripts per kilobase million; WGCNA: weighted gene co-expression network analysis.