Development of a risk model to predict prognosis in breast cancer based on cGAS-STING-related genes

Abstract

Background: Breast cancer (BRCA) is regarded as a lethal and aggressive cancer with increasing morbidity and mortality worldwide. cGAS-STING signaling regulates the crosstalk between tumor cells and immune cells in the tumor microenvironment (TME), emerging as an important DNA-damage mechanism. However, cGAS-STING-related genes (CSRGs) have rarely been investigated for their prognostic value in breast cancer patients.Methods: Our study aimed to construct a risk model to predict the survival and prognosis of breast cancer patients. We obtained 1087 breast cancer samples and 179 normal breast tissue samples from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEX) database, 35 immune-related differentially expression genes (DEGs) from cGAS-STING-related genes were systematically assessed. The Cox regression was applied for further selection, and 11 prognostic-related DEGs were used to develop a machine learning-based risk assessment and prognostic model.Results: We successfully developed a risk model to predict the prognostic value of breast cancer patients and its performance acquired effective validation. The results derived from Kaplan-Meier analysis revealed that the low-risk score patients had better overall survival (OS). The nomogram that integrated the risk score and clinical information was established and had good validity in predicting the overall survival of breast cancer patients. Significant correlations were observed between the risk score and tumor-infiltrating immune cells, immune checkpoints and the response to immunotherapy. The cGAS-STING-related genes risk score was also relevant to a series of clinic prognostic indicators such as tumor staging, molecular subtype, tumor recurrence, and drug therapeutic sensibility in breast cancer patients.Conclusion: cGAS-STING-related genes risk model provides a new credible risk stratification method to improve the clinical prognostic assessment for breast cancer.

Prognostic significance of STING expression in solid tumor: a systematic review and meta-analysis

“…Another way to evaluate STING activation would include assessment of downstream effector molecules. STING-related gene signatures were associated with prognosis in breast, prostate, and colorectal cancers ( 28 , 29 , 32 ). Therefore, developing alternative protein markers alongside STING could provide a more comprehensive understanding of STING activation and its functional implications even in cases when upstream signaling pathway is compromised by genetic alterations.…”

Deregulations of RNA Pol II Subunits in Cancer

“…In HER2 breast cancers, POLR2K gain of expression by mRNA upregulation or gene amplification was observed [144]; more recent studies showed that low expression of POLR2K significantly prolonged patients survival and reduced cancer rates in breast cancer, while the high expression of POLR2K was associated with poor patients' survival [145]. Recently, along with four other genes, higher POLR2K expression levels were found via machine learning approaches in a high-risk group of patients for breast cancer [146]. Using mRNA expression profiling, POLR2K was firstly identified in 2016 as a differentially expressed gene in prostate cancer tissues compared to normal tissues, and later, it was evident that POLR2K differential expression had a significant prognostic value for patients overall survival [147,148].…”