Abstract

Background: Breast cancer (BC) is the most common malignant tumor and the leading cause of cancer-related death in women worldwide. Pyroptosis and long noncoding RNAs (lncRNAs) have been demonstrated to play vital roles in the tumorigenesis and development of BC. However, the clinical significance of pyroptosis-related lncRNAs in BC remains unclear. Methods: Using the mRNA and lncRNA profiles of BC obtained from TCGA dataset, a risk model based on the pyroptosis-related lncRNAs for prognosis was constructed using univariate and multivariate Cox regression model, and least absolute shrinkage and selection operator. Patients were divided into high- and low-risk groups based on the risk model, and the prognosis value and immune response in different risk groups were analyzed. Furthermore, functional enrichment annotation, therapeutic signature, and tumor mutation burden were performed to evaluate the risk model we established. Moreover, the expression level and clinical significance of the selected pyroptosis-related lncRNAs were further validated in BC samples. Results: 3,364 pyroptosis-related lncRNAs were identified using Pearson’s correlation analysis. The risk model we constructed comprised 10 pyroptosis-related lncRNAs, which was identified as an independent predictor of overall survival (OS) in BC. The nomogram we constructed based on the clinicopathologic features and risk model yielded favorable performance for prognosis prediction in BC. In terms of immune response and mutation status, patients in the low-risk group had a higher expression of immune checkpoint markers and exhibited higher fractions of activated immune cells, while the high-risk group had a highly percentage of TMB. Further analyses in our cohort BC samples found that RP11-459E5.1 was significantly upregulated, while RP11-1070N10.3 and RP11-817J15.3 were downregulated and significantly associated with worse OS. Conclusion: The risk model based on the pyroptosis-related lncRNAs we established may be a promising tool for predicting the prognosis and personalized therapeutic response in BC patients.

Highlights

  • Breast cancer (BC) is the most common malignant tumor and the leading cause of cancer-related death in women worldwide (Siegel et al, 2020)

  • Using the mRNA and long noncoding RNAs (lncRNAs) profiles of BC obtained from The Cancer Genome Atlas (TCGA) dataset, a risk model based on the pyroptosis-related lncRNAs for prognosis was constructed using univariate and multivariate Cox regression model, and least absolute shrinkage and selection operator

  • The risk model based on the pyroptosis-related lncRNAs we established may be a promising tool for predicting the prognosis and personalized therapeutic response in BC patients

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Summary

Introduction

Breast cancer (BC) is the most common malignant tumor and the leading cause of cancer-related death in women worldwide (Siegel et al, 2020). Owing to the development of local control and systematic treatment, including surgical resection, radiotherapy, systemic chemotherapy, in combination with targeted therapy, hormone replacement therapy, and other novel therapeutic methods, the survival outcome of BCs has significantly improved in the past decade (Harbeck and Gnant, 2017). Despite these efforts, the curative rate and prognosis of BC patients are still unsatisfactory, and up to 15% of cancerrelated deaths occurred after treatment according to GLOBOCAN 2018 (Bray et al, 2018). The clinical significance of pyroptosis-related lncRNAs in BC remains unclear

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