Identification and validation of pyroptosis-related gene landscape in prognosis and immunotherapy of ovarian cancer

Abstract

Abstract Background Emerging evidence has highlighted the biological significance of pyroptosis in tumor tumorigenesis and progression. Nonetheless, the potential roles of pyroptosis in tumor immune microenvironment and target therapy of ovarian cancer (OC) remain unknown. Methods In this study, with a series of bioinformatic and machine learning approaches, we comprehensively evaluated genetic alterations and transcriptome profiles of pyroptosis-associated genes (PYAGs) with TCGA-OV datasets. Consensus molecular clustering was performed to determine pyroptosis-associated clusters (PACs) and gene clusters in OC. Subsequently, component analysis algorithm (PCA) was employed to construct Pyrsig score and a highly accurate nomogram was established to evaluate its efficacy. Meanwhile, we systematically performed association analysis for these groups with prognosis, clinical features, TME cell-infiltrating characteristics, drug response and immunotherapeutic efficacy. Immunohistochemistry was conducted to verify molecular expression with clinical samples. Results The somatic mutations and copy number variation (CNV) of 51 PYRGs in OC samples were clarified. Two distinct PACs (PAC1/2) and three gene clusters (A/B/C) were identified based on 1332 OC samples, PAC1 and gene cluster A were significantly associated with favorable overall survival (OS), clinicopathological features and TME cell-infiltrating characteristics. Subsequently, Pyrsig score was successfully established to demonstrate the prognostic value and immune characteristics of pyroptosis in OC, low Pyrsig score, characterized by activated immune cell infiltration, indicated prolonged OS, increased sensitivity of some chemotherapeutic drugs and enhanced efficacy of anti-PD-L1 immunotherapy, Consequently, a nomogram was successfully established to improve the clinical applicability and stability of Pyrsig score. With clinical OC samples, GSDMD and GZMB proteins were validated highly expressed in OC and associated with immune infiltration and Pyrsig score, GZMB and CD8 proteins were regarded as independent prognostic factors of OC. Conclusion This work revealed pyroptosis played a non-negligible role in prognosis value, clinicopathological characteristics and tumor immune infiltration microenvironment in OC, which provided novel insights into identifying and characterizing landscape of tumor immune microenvironment, thereby guiding more effective prognostic evaluation and tailored immunotherapy strategies of OC.

Keywords

• Ovarian cancer
• Pyroptosis
• Tumor microenvironment
• Immune and immunotherapy