Mapping the functional interactions at the tumor-immune checkpoint interface

Abstract

The interactions between tumor intrinsic processes and immune checkpoints can mediate immune evasion by cancer cells and responses to immunotherapy. It is, however, challenging to identify functional interactions due to the prohibitively complex molecular landscape of the tumor-immune interfaces. We address this challenge with a statistical analysis framework, immuno-oncology gene interaction maps (ImogiMap). ImogiMap quantifies and statistically validates tumor-immune checkpoint interactions based on their co-associations with immune-associated phenotypes. The outcome is a catalog of tumor-immune checkpoint interaction maps for diverse immune-associated phenotypes. Applications of ImogiMap recapitulate the interaction of SERPINB9 and immune checkpoints with interferon gamma (IFNγ) expression. Our analyses suggest that CD86-CD70 and CD274-CD70 immunoregulatory interactions are significantly associated with IFNγ expression in uterine corpus endometrial carcinoma and basal-like breast cancer, respectively. The open-source ImogiMap software and user-friendly web application will enable future applications of ImogiMap. Such applications may guide the discovery of previously unknown tumor-immune interactions and immunotherapy targets.

A prognostic matrix gene expression signature defines functional glioblastoma phenotypes and niches

“…Distribution of immune checkpoint expression across M-H vs. M-L tumors. We analyzed the mRNA expression of immune checkpoint molecules for which targeting strategies are in clinical use or trials 40,88 . The statistical procedure is identical to that in Figure 3A.…”

“…For an integrated M-H vs. M-L comparison, the p-values for "M-H vs. M-La" and "M-H vs. M-Lb" were merged with the Stouffer method adjusted for multiple hypothesis testing using the Bonferroni method. For immune checkpoint analysis, we curated 31 therapeutically actionable immune checkpoints, which have been subject of immunotherapy clinical trials 40 . The RNA expression levels of immune checkpoints were analyzed for the same patient cohort as before: 153 samples (42 M-H, 58 M-La, 53 M-Lb).…”

KRAS Allelic Variants in Biliary Tract Cancers

“…The Cell-Type Identification By Estimating Relative Subsets of RNA Transcripts (CIBERSORT) 30 computational method was used to assess values of 22 immune cell types with the mRNA expression data and to conduct immune cell profiling analysis. The immuno-oncology gene interaction maps package (ImogiMap, a bioinformatics tool and resources for interactions between oncogenic events and immune checkpoints associated with immunotherapy responses 31 ) was used to calculate scores for epithelial to mesenchymal transition, 32 vascularization, 33 interferon (IFN)-γ expression score, and a T-cell inflammation gene expression signature. 34 …”

The biological function of Serpinb9 and Serpinb9-based therapy

“…Sb9 emerges as a signature gene of T cells dysfunction from the “statistical interaction test”, which is employed to identify specific genes in several cancer types that could be linked to patients’ abnormal tumor immune microenvironment. The identification of Sb9 as a hallmark of T cell dysfunction implies that the presence or high expression of this gene in a tumor immune microenvironment can serve as a biomarker of tumor immune evasion ( 50 , 72 ).…”

“…Sb9 is identified as the top immune-resistance gene in a study of somatic gene alterations correlating with immune cytolytic activity in a TCGA cohort of lung cancer ( 119 ). Notably, it stands out as the most upregulated gene in immune checkpoint non-responders compared to responders across various cancer types, indicating its potential utility as a predictive biomarker for immune checkpoint blockade (ICB) response and a prognostic marker ( 50 , 71 , 72 , 101 ). Sb9 expression is elevated not only in patients who are refractory to ICB therapy but also in those with post- versus pre-treatment cancers ( 101 ).…”