A model based on tumor-infiltrating immune cells for predicting the relapse rates of patients with testicular germ cell tumors.

OBJECTIVE: The activities of tumor-infiltrating immune cells (TIICs) play an important role in the outcomes of many types of cancers. Here, we sought to describe the landscape of TIICs in testicular germ cell tumors (TGCT) and to develop a prognostic model based on this information. METHODS: The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to determine the proportions of 22 types of TIICs in a TGCT dataset (n = 74). Univariate and multivariate Cox regression analysis were used to develop an immune risk score (IRS) based on the association between TIICs and disease-free survival (DFS). The predictive accuracy of the IRS was evaluated using receiver operating characteristic curves, and the predictive accuracy of a prognostic nomogram was assessed using C-index and calibration curves. The biological functions of IRS-associated genes were evaluated by gene set enrichment analysis. RESULTS: The relative abundances of three TIICs (plasma cells, M2 macrophages, and resting mast cells) were significantly associated with DFS in TGCT patients. In receiver operating characteristic curve analysis, the resulting IRS had areas under the curve of 0.70, 0.793, and 0.827, for predicting 1-, 2-, and 3-year DFS, respectively. Kaplan-Meier analysis confirmed that DFS was shorter for patients with high IRS compared with low IRS. IRS was an independent predictor of disease recurrence (hazard ratio 1.306, 95% confidence interval 1.022-1.668; P = 0.033). The C-index for the nomogram was 0.733. Genes involved in cancer-associated and immunity-associated pathways were enriched in TGCT samples from patients in the high- and low-risk groups, respectively, and expression of four immune checkpoint regulators was significantly lower in the high IRS group compared with the low IRS group. CONCLUSIONS: A TIIC-based IRS may have utility as a complementary tool to predict relapse in patients with TGCT.