Tumor immune cell infiltration score based model predicts prognosis in multiple myeloma

Abstract The tumor microenvironment plays an important role in various processes, including tumorigenesis, cancer progression, and metastasis. Immune signatures have been identified and verified for use in diagnosis and prognosis prediction. We used single-sample Gene Set Enrichment Analysis to evaluate tumor immune cell infiltration score (TIICs) and verify their prognostic significance in both training and validation cohorts and using this information to build a prognostic model. A total of 1281 samples were obtained for further evaluation of the immune enrichment scores of 28 immune cells, showing that Th17 cell contributed most significantly to survival. Using the median TIICs as a cutoff to divide the samples into two groups, we found that the high-TIICs group was associated with favorable outcomes in both the training and validation sets. We then constructed a prognostic model to predict the 6, 8, and 10-year survival outcomes. Further analysis showed that immune score and tumor purity were higher in the high-TIICs group, while the matrix score was lower in this group. Forty-two differentially expressed genes were identified between the two groups. This new prognostic model based on immune cell infiltration indicates the potential for TIICs in predicting prognosis and as targets for treatment.