Abstract
Objective: Pyroptosis represents an emerging inflammatory form of programmed cell death. Herein, specific functions and clinical implications of pyroptosis-related genes were systematically characterized in breast cancer.Methods: Expression, somatic mutation and copy number variation of 33 pyroptosis-related genes were assessed in breast cancer from TCGA dataset. Their interactions, biological functions and prognostic values were then observed. By stepwise Cox regression analysis, a pyroptosis-related gene signature was generated. The predictive efficacy in survival was examined by survival analyses, ROCs, univariate and multivariate analyses and subgroup analyses. Associations between risk score (RS) and cancer immunity cycle, HLA, immune cell infiltrations, and immune checkpoints were analyzed.Results: Most of pyroptosis-related genes were abnormally expressed in breast cancer. CASP8, NLRC4, NLRP3, NLRP2, PLCG1, NLRP1, NLRP7, SCAF11, GSDMC, and NOD1 occurred somatic mutations as well as most of them had high frequency of CNV. There were closely interactions between them. These genes were distinctly enriched in immune-related processes. A three-gene signature was generated, containing IL-18, GSDMC, and TIRAP. High RS predicted poorer overall survival, progression, and recurrence. After verification, this RS was an independent and sensitive predictive index. This RS was negatively correlated to cancer immunity cycle. Also, low RS was characterized by high HLA, immune cell infiltrations and immune checkpoints. A nomogram including age and RS was generated for accurately predicting 5-, 8-, and 10-year survival probabilities.Conclusion: Pyroptosis-related genes exert key roles in cancer immunity and might be applied as a prognostic factor of breast cancer.
Highlights
Breast cancer represents a frequently diagnosed malignancy among women globally, with a high mortality [1]
Low risk score (RS) was characterized by high human lymphocyte antigen (HLA), immune cell infiltrations and immune checkpoints
We found that the risk score almost negatively participated in each step of cancer immunity cycle, including release of cancer cell antigens, cancer antigen presentation, priming and activation, T cell recruiting, Th1 cell recruiting, dendritic cell recruiting, Th22 cell recruiting, macrophage recruiting, monocyte recruiting, neutrophil recruiting, NK cell recruiting, eosinophil cell recruiting, basophil recruiting, Th17 cell recruiting, B cell recruiting, Th2 cell recruiting, Treg cell recruiting, infiltration of immune cells into tumors, recognition of cancer cells by T cells, and killing of cancer cells (Figure 6A)
Summary
Breast cancer represents a frequently diagnosed malignancy among women globally, with a high mortality [1]. This malignancy affects 1/20 globally and 1/8 in high-income countries [2]. Females with high risk of developing breast cancer are a heterogeneous population [3]. Further research requires to improve prognostic models to stratify high-risk patients. The biology in breast cancer progress is complex in which genetic and environmental elements are involved [4]. Conventional breast cancer classification primarily replies on clinicopathologic characteristics and routine markers, not capturing various clinical courses of individual patient [5]. Indepth understanding of the molecular mechanisms could lead to improvement in patients’ prognoses
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