Mechanism of prognostic marker SPOCK3 affecting malignant progression of prostate cancer and construction of prognostic model

BackgroundSPOCK3 is a secreted extracellular matrix proteoglycan. This study aimed to investigate the effect of SPOCK3 on the malignant progression of prostate cancer and to construct a prognostic model to predict DFS of patients with prostate cancer.MethodsClinical and transcriptome sequencing data for prostate cancer were download from the TCGA and GEO databases. The survival curve showed that SPOCK3 has prognostic significance. GO, KEGG, and GSEA enrichment analysis were used to investigate how SPOCK3 affects the malignant progression of prostate cancer. Based on ESTIMATE and ssGSEA, the relationship between SPOCK3 and immune cell infiltration in prostate cancer tissue was clarified. Univariate and multivariate COX regression analysis was used to identify the independent prognostic factors of prostate cancer OS and to construct a nomogram. The calibration curve and ROC curves were drawn to assess the nomogram's predictive power.ResultsThe survival curve revealed that patients in the low-expression group of SPOCK3 had a poor prognosis. According to enrichment analysis, SOPCK3-related genes were enriched in collagen-containing extracellular matrix, PI3K-Akt, and MAPK signaling pathway. ESTIMATE analysis revealed that SPOCK3 expression was positively correlated with the interstitial score, immune score, and ESTIMATE score. The results of ssGSEA analysis revealed that the infiltration levels of Mast cells, NK cells, and B cells were higher in the SPOCK3 high expression group. Cox regression analysis showed that SPOCK3 expression level, T and Gleason score were independent risk factors of patient prognosis, and a nomogram was constructed. The ROC curve showed the AUCs of DFS at 2, 3, and 5 years.ConclusionSPOCK3 is a protective factor for DFS in prostate cancer patients. SPOCK3 is significantly associated with immune cell infiltration. The prognostic model constructed based on SPOCK3 has excellent predictive performance.