In the last decade, methods to investigate the immune status of the tumor microenvironment (TME) and predict immune checkpoint blockade efficacy have been intensively developed as immunoscores or immune signatures. However, since the immunological gene signature is a complex and time-consuming approach, a simpler scoring system using numerical data is needed to evaluate a large number of tumors. We previously established a TME immune-type classification system based on PD-L1 and CD8B gene expression, and 5032 cancer patients were classified into 4 types. Based on the expression levels of immune response-associated genes in each type, these genes were assigned scores ranging 1 to 4, representing a spectrum from immunosuppressive to immunostimulating genes. We herein calculated tumor immune status scoring algorithm (TIMMUSCORA) scores based on the expression data of 300 immune response-associated genes in 5,013 pancancer patients, and investigated the relationship of these scores with the prognosis and other clinicopathological features of cancer patients. Rectal cancers with higher scores than the cut-off value of 0 showed a good prognosis, which was closely associated with the immune response-associated genes PDCD1, GZMB, TNFRSF10C, EBI3, and IRF1. A correlation analysis of the rectal cancer cohort suggested that high TIMMUSCORA scores correlated with high TMB value and the consensus molecular subtyping 1 status, while low scores correlated with WNT gene expression. Therefore, the TIMMUSCORA system has potential in evaluations of the immune status of the TME and the prognosis of solid cancers.
Ikeya et al. (Sat,) studied this question.