Prognostic immune-related gene models for breast cancer: a pooled analysis

Abstract

Breast cancer, the most common cancer among women, is a clinically and biologically heterogeneous disease. Numerous prognostic tools have been proposed, including gene signatures. Unlike proliferation-related prognostic gene signatures, many immune-related gene signatures have emerged as principal biology-driven predictors of breast cancer. Diverse statistical methods and data sets were used for building these immune-related prognostic models, making it difficult to compare or use them in clinically meaningful ways. This study evaluated successfully published immune-related prognostic gene signatures through systematic validations of publicly available data sets. Eight prognostic models that were built upon immune-related gene signatures were evaluated. The performances of these models were compared and ranked in ten publicly available data sets, comprising a total of 2,449 breast cancer cases. Predictive accuracies were measured as concordance indices (C-indices). All tests of statistical significance were two-sided. Immune-related gene models performed better in estrogen receptor-negative (ER−) and lymph node-positive (LN+) breast cancer subtypes. The three top-ranked ER− breast cancer models achieved overall C-indices of 0.62–0.63. Two models predicted better than chance for ER+ breast cancer, with C-indices of 0.53 and 0.59, respectively. For LN+ breast cancer, four models showed predictive advantage, with C-indices between 0.56 and 0.61. Predicted prognostic values were positively correlated with ER status when evaluated using univariate analyses in most of the models under investigation. Multivariate analyses indicated that prognostic values of the three models were independent of known clinical prognostic factors. Collectively, these analyses provided a comprehensive evaluation of immune-related prognostic gene signatures. By synthesizing C-indices in multiple independent data sets, immune-related gene signatures were ranked for ER+, ER−, LN+, and LN− breast cancer subtypes. Taken together, these data showed that immune-related gene signatures have good prognostic values in breast cancer, especially for ER− and LN+ tumors.

Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer

“…Over the past decade, with the increased understanding of the immune microenvironment of breast cancer tissues, immune escape has been considered an important feature of breast cancer development ( Romaniuk and Lyndin, 2015 ; Takada et al, 2018 ). Targeting the tumor immune microenvironment in breast cancer is of high therapeutic interest ( Zhao et al, 2017 ). However, the therapeutic effects of immune checkpoint inhibition may be limited.…”

Development and verification of an immune‐related gene pairs prognostic signature in ovarian cancer

“…Their signature was associated with tumour staging and tumour type. Other immune‐related signatures have also been reported in cancers, including gastric cancer, 10 anaplastic gliomas, 11 breast cancer 12 and pancreatic cancer 13 . However, there have been no reports of immune‐related gene signatures in OV.…”

Development and Verification of an Immune-Related Gene Pairs Prognostic Signature in Ovarian Cancer

“…Their signature was associated with tumor staging and tumor type. Other immune-related signatures have also been reported in cancers, including gastric cancer (10), anaplastic gliomas (11), breast cancer (12), and pancreatic cancer (13). However, there have been no reports of immune-related gene signatures in OV.…”