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Original Research

Identification of Novel Pyroptosis-Related lncRNAs Associated with the Prognosis of Breast Cancer Through Interactive Analysis

& ORCID Icon
Pages 7175-7186 | Published online: 15 Sep 2021
 

Abstract

Background

The role of pyroptosis and lncRNAs in breast cancer remains controversial. This study aimed to explore the pyroptosis-related lncRNAs in breast cancer.

Methods

All the data used for bioinformatics analysis were downloaded from The Cancer Genome Atlas database. Limma package was used to perform difference analysis, and distinguish mRNA and lncRNA. Survival package was used to conduct prognosis analysis. LASSO algorithm, univariate cox analysis and multivariate cox analysis were used to construct the prognosis model. P value <0.05 was regarded as statistically significant.

Results

Based on the seven pyroptosis-related lncRNAs tightly associated with patients’ prognosis, a prognostic prediction model was finally developed, which showed powerful effectiveness (Training cohort, one-year AUC = 0.82, 95% Cl = 0.69–0.95, three-year AUC = 0.77, 95% Cl = 0.68–0.85, five-year AUC = 0.74, 95% Cl = 0.66–0.82; Validation cohort, one-year AUC = 0.68, 95% Cl = 0.53–0.84, three-year AUC = 0.72, 95% Cl = 0.64–0.81, five-year AUC = 0.67, 95% Cl = 0.57–0.77). GSEA analysis demonstrated that the protein secretion, angiogenesis, TGF-β signaling and MTORC1 signaling might be involved in the high-risk patients. Moreover, immune infiltration analysis showed that the risk score was positively correlated with Tgd and Th2 cells, yet negatively correlated with CD8+ T cells, cytotoxic cells and T helper cells, which might partly explain the poor prognosis of high-risk patients. Finally, the expression level of seven model lncRNAs in the real world was validated by qRT-PCR using four cancer cell lines (MCF-7, T47D, MDA-MB-231, MDA-MB-469).

Conclusion

In conclusion, our study identified lncRNAs that are remarkably correlated with patients’ survival and might participate in the pyroptosis process, which might be underlying tumor biomarker and therapeutic targets. This study may provide direction for future research.

Abbreviations

lncRNAs, long-noncoding RNAs; PPI, Protein-protein interaction; GO, Gene oncology; KEGG, Kyoto Encyclopedia of Genes and Genomes; GSEA, Gene set enrichment analysis; qRT-PCR, Quantitative Real-time PCR.

Data Sharing Statement

The transcriptional profiles and clinical data of breast cancer were downloaded from the TCGA database and are available from the website (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga). The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests.