AUTHOR=Liu Mengmeng , Li Quan , Liang Yao 

TITLE=Pyroptosis-related genes prognostic model for predicting targeted therapy and immunotherapy response in soft tissue sarcoma

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2023.1188473

DOI=10.3389/fphar.2023.1188473

ISSN=1663-9812

ABSTRACT=Several research have indicated that pyroptosis were expected to become a biological target for cancer treatment. Herein, for pyroptosis-related genes (PRGs), their particular roles and clinical implications in soft tissue sarcoma (STS) were considerably described. Based on differently expressed PRGs in STS compared normal tissue, the interactions, biological function and prognostic values of those PRGs were systematically evaluated in STS. Through LASSO COX regression analysis, a five-gene survival related-risk score (PLCG1, PYCARD, CASP8, NOD1, and NOD2) was created, which examined both in TCGA cohort and training cohort (GSE21050, GSE30929, and GSE63157). In addition, with a decent accuracy of prediction evidenced by calibration curves, a nomogram incorporating the clinic factor and the risk scores of the PRGs was developed. Additionally, in the context of analyzing the Tumor Immune Dysfunction and Exclusion Algorithm (TIDE) and IMvigor 210 cohorts to investigate the immunotherapy response, immunotherapy’s benefit for patients with minimal risk of PRGs was found greater than those exhibiting greater risk. Finally, GDSC and CAMP databases were used to screen out a batch of existing or unmarketed effective chemotherapy or targeted drugs that are sensitive to the high-risk populations, including doxorubicin, imatinib and sorafenib. In conclusion, this study comprehensively analyzed the PRGs landscape in STS, and constructed a novel risk model to predict prognosis and different therapeutic responses of STS patients, which is helpful to achieve precision medicine.