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文章來源：Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade
IPS analysis
摘自參考文獻 Identification of an immune gene expression signature associated with favorable clinical features in Treg-enriched patient tumor samples
a patient’s IPS can be derived in an unbiased manner using machine learning by considering the four major categories of genes that determine immunogenicity (effector cells, immunosuppressive cells, MHC molecules, and immunomodulators) by the gene expression of the cell types these comprise (e.g., activated CD4+ T cells, activated CD8+ T cells, effector memory CD4+ T cells, Tregs, MDSCs). The IPS is calculated on a 0–10 scale based on representative cell type gene expression z-scores, where higher scores are associated with increased immunogenicity. This is because the IPS is positively weighted for stimulatory factors (e.g., CD8+ T cell gene expression) and negatively weighted for inhibitory factors (e.g., MDSC gene expression).
Finally, the IPS is calculated based on a 0–10 scale relative to the sum of the weighted averaged z-scores. A z-score of three or more translates to an IPS of 10, while a z-scores 0 or less translates to an IPS of 0, demonstrating a higher
IPS is representative of a more immunogenic tumor.
This method has been described in further detail with the immunogenic determinant categories, as well as corresponding cell types and gene sets, which can be found at tcia.at. We retrieved patient IPSs from The Cancer Immunome Atlas framework. 上文作者的IPS分數(shù)是直接摘錄自那個網(wǎng)站的。
Immunophenoscore 評分主要由四部分組成
active CD4 計算的基因
effector memory (TEM) CD4
