Identification and Validation of a Novel Pyroptosis-Related Gene Signature for Prognosis Prediction in Soft Tissue Sarcoma

Lin Qi; Ruiling Xu; Lu Wan; Xiaolei Ren; WenChao Zhang; Keming Zhang; Chao Tu; Zhihong Li

doi:10.3389/fgene.2021.773373

Identification and Validation of a Novel Pyroptosis-Related Gene Signature for Prognosis Prediction in Soft Tissue Sarcoma

Front Genet. 2021 Dec 1:12:773373. doi: 10.3389/fgene.2021.773373. eCollection 2021.

Authors

Lin Qi^{1

2}, Ruiling Xu^{1

2}, Lu Wan^{1

2}, Xiaolei Ren^{1

2}, WenChao Zhang^{1

2}, Keming Zhang^{3

4}, Chao Tu^{1

2}, Zhihong Li^{1

2}

Affiliations

¹ Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, China.
² Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Changsha, China.
³ Department of Dermatology and Venereology, Changzheng Hospital, Second Military Medical University, Shanghai, China.
⁴ Shanghai Key Laboratory of Molecular Medical Mycology, Shanghai Institute of Medical Mycology, Changzheng Hospital, Second Military Medical University, Shanghai, China.

Abstract

Soft tissue sarcoma (STS) represents an uncommon and heterogenous group of malignancies, and poses substantial therapeutic challenges. Pyroptosis has been demonstrated to be related with tumor progression and prognosis. Nevertheless, no studies exist that delineated the role of pyroptosis-related genes (PRGs) in STS. In the present study, we comprehensively and systematically analyzed the gene expression profiles of PRGs in STS. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were utilized to identify differentially expressed PRGs. In total, 34 PRGs were aberrantly expressed between STS and normal tissues. Several PRGs were validated with RT-qPCR. Consensus clustering analysis based on PRGs was conducted to divide STS patients into two clusters, and significant survival difference was observed between two distinct clusters (p = 0.019). Differentially expressed genes (DEGs) were identified between pyroptosis-related clusters. Based on the least absolute shrinkage and selection operator (LASSO) COX regression analysis, the pyroptosis-related gene signature with five key DEGs was constructed. The high pyroptosis-related risk score group of TCGA cohort was characterized by poorer prognosis (p < 0.001), with immune infiltration and function significantly decreased. For external validation, STS patients from Gene Expression Omnibus (GEO) were grouped according to the same cut-off point. The survival difference between two risk groups of GEO cohort was also significant (p < 0.001). With the combination of clinical characteristics, pyroptosis-related risk score was identified to serve as an independent prognostic factor for STS patients. In conclusion, this study provided a comprehensive overview of PRGs in STS and the potential role in prognosis, which could be an important direction for future studies.

Keywords: gene signature; immune; prognosis; pyroptosis; soft tissue sarcoma.