Immune Profiling Predicts Immunotherapy Response

Immunophenoscore (IPS) is a superior predictor of response to anti-CTLA-4 and anti-PD-1 regimens, which quantify the determinants of tumor immunogenicity and characterize the intratumoral immune landscapes and cancer antigenomes 42 (link). The scoring scheme developed from a panel of immune-related genes belonging to the four classes: MHC-related molecules (MHC), checkpoints or immunomodulators (CP), effector cells (EC) and suppressor cells (SC). The weighted averaged Z score was calculated by averaging the samplewise Z scores of the four classes within the respective category and the sum of the weighted averaged Z score was calculated as the IPS. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm proposed by Jiang et al. was utilized to model distinct tumor immune evasion mechanisms 45 (link), including dysfunction of tumor infiltration cytotoxic T lymphocytes (CTLs) and exclusion of CTLs by immunosuppressive factors. A higher TIDE score indicated tumor cells more likely to induce immune escape, thus indicating a lower response rate to ICI treatment. The Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE) algorithm 46 (link), which takes advantage of the unique properties of the transcriptional profiles to infer the tumor cellularity as well as the tumor purity. By using the ESTIMATE algorithm, we calculated the immune and stromal scores to predict the level of infiltrating immune and stromal cells and these form the basis to infer tumor purity. Tumor tissues with abundant immune cell infiltration represented a higher immune score and lower level of tumor purity.