Sperm Autoantigenic Protein 17 Predicts the Prognosis and the Immunotherapy Response of Cancers: A Pan-Cancer Analysis - Tu, Zewei; Peng, Jie; Long, Xiaoyan; Li, Jingying; Wu, Lei; Huang, Kai; Zhu, Xingen (Frontiers in Immunology, 2022)
Background Sperm autoantigen protein 17 (SPA17) is a highly conserved mammalian protein that participates in the acrosome reaction during fertilization and is a recently reported member of the cancer-testicular antigen (CTA) family. It has been reported that the SPA17 expression is limited in adult somatic tissues and re-expressed in tumor tissues. Recently, studies have found that SPA17 regulates the progression of various cancers, but its role in cancer immunotherapy is not clear. Methods The pan-cancer and normal tissue transcriptional data were acquired from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. We explored the SPA17 pan-cancer genomic alteration analysis in the cBioPortal webtool. The Human Protein Atlas (HPA) and ComPPI websites were used to mine the SPA17 protein information. We performed a western blotting assay to validate the upregulated SPA17 expression in clinical glioblastoma (GBM) samples. The univariate Cox regression and Kaplan–Meier method were used to assess the prognostic role of SPA17 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was used to search the associated cancer hallmarks with SPA17 expression in each cancer type. TIMER2.0 was the main platform to investigate the immune cell infiltrations related to SPA17 in pan-cancer. The associations between SPA17 and immunotherapy biomarkers were performed by Spearman correlation analysis. The drug sensitivity information from the Connectivity Map (CMap) dataset was downloaded to perform SAP17-specific inhibitor sensitivity analysis. Findings SPA17 was aberrantly expressed in most cancer types and exhibited prognosis predictive ability in various cancers. In addition, our results also show that SPA17 was significantly correlated with immune-activated hallmarks (including pathways and biological processes), immune cell infiltrations, and immunoregulator expressions. The most exciting finding was that SPA17 could significantly predict anti-PDL1 and anti-PD1 therapy responses in cancer patients. Finally, specific inhibitors, like irinotecan and puromycin, which correlate with SPA17 expression in different cancer types, were also screened using Connectivity Map (CMap). Conclusions Our results reveal that SPA17 was abnormally expressed in cancer tissues, and this expression pattern could be associated with immune cell infiltrations in tumor microenvironments. Clinically, SPA17 not only acted as a potent prognostic factor to predict the clinical outcomes of cancer patients but was also a promising immunotherapy predictive biomarker for cancer patients treated with immune-checkpoint inhibitors (ICIs).