Microenvironment Is a Key Determinant of Immune Checkpoint Inhibitor Response

Utilizing advanced RNA-sequencing techniques and rigorous bioinformatics analysis, this study identified gene signatures predicting responsiveness to pembrolizumab monotherapy. T-cell- inflamed gene expression profile was predictive for better treatment response, while angiogenesis, monocytic myeloid-derived suppressor cell, and stroma/epithelial-mesenchymal transition/TGF(3 gene signatures were associated with lower treatment response.

Automated summary

This study used advanced RNA-sequencing techniques and bioinformatics analysis to identify gene signatures that can predict the responsiveness to pembrolizumab monotherapy. The T-cell-inflamed gene expression profile was associated with a better treatment response, while angiogenesis, monocytic myeloid-derived suppressor cell, and stroma/epithelial-mesenchymal transition/TGF-beta gene signatures were associated with a lower treatment response.