Development and Validation of a <i>SPOP</i>-Associated Immune Prognostic Model for Prostate Cancer

Abstract

Background: SPOP mutation is the most common mutation in prostate cancer (Pca), and we systematically investigated effect of the SPOP mutation on immune status of Pca patients and its relationship with prognosis. Methods: SPOP mutation status combined with RNA-sequencing data were used to identify differentially-expressed immune-related genes (IRGs) between SPOPWT and SPOPMUT Pca patients. Then, an immune prognostic model was constructed to stratify patients, and immune microenvironment and clinical application value of the prognostic model were comprehensively analyzed. Findings: SPOP mutation enhanced expression levels of PD-L1 gene and AR gene. A prognostic model was constructed based on six most valuable predictive IRGs and showed good performance in stratifying patients into high-risk, mid-risk and low-risk groups, with high-risk patients tending to have a higher pathological T stage, higher gleason score and poorer prognosis. Moreover, high-risk patients had a lower relative percentage of CD8 T cells, macrophages and dendritic cells and higher relative proportions of B cells, CD4 T cells and neutrophil cells. High-risk patients had relatively higher immune scores and higher expression levels of PD-1, CTLA-4, TIM3, LAG3, IDO1 and TIGIT. Finally, a nomogram integrating the prognostic model and clinical factors was established and showed a more robust predictive performance for prognosis. Interpretation: Mutation of the SPOP gene is highly associated with immune status and clinicopathologic features of Pca patients. Our SPOP-associated prognostic model not only serves as an indicator of tumor immune status, but is also a useful tool for considering immunotherapy responsiveness and improving prediction of Pca patients’ prognosis. Funding: This study was funded by the National Natural Science Foundation of China (Nos. 81630019, 81870519, 81902584), Scientific Research Foundation of the Institute for Translational Medicine of Anhui Province (2017ZHYX02). Declaration of Interest: None.