ArticleFrontiers in genetics2021
Identification and Validation of a Novel Pyroptosis-Related Gene Signature for Prognosis Prediction in Soft Tissue Sarcoma.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Article
- Development and validation of a prognostic risk signature for lung adenocarcinoma constructed by six ferroptosis, necroptosis, and pyroptosis-related lncRNAs.Journal of thoracic disease · 2022Article
- Pyroptosis related genes signature predicts prognosis and immune infiltration of tumor microenvironment in hepatocellular carcinoma.BMC cancer · 2022Article
- A Novel Pyroptosis-Related Gene Signature for Predicting Prognosis in Kidney Renal Papillary Cell Carcinoma.Frontiers in genetics · 2022Article
- Cross-Talk of Multiple Types of RNA Modification Regulators Uncovers the Tumor Microenvironment and Immune Infiltrates in Soft Tissue Sarcoma.Frontiers in immunology · 2022Article
- Molecular characterization of immunogenic cell death indicates prognosis and tumor microenvironment infiltration in osteosarcoma.Frontiers in immunology · 2022Article
- A Necroptosis-Related lncRNA Signature Predicts Prognosis and Indicates the Immune Microenvironment in Soft Tissue Sarcomas.Frontiers in genetics · 2022Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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 (
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