Microenvironment Is a Key Determinant of Immune Checkpoint Inhibitor Response.
Shih-Feng ChoKenneth C AndersonYu-Tzu TaiPublished in: Clinical cancer research : an official journal of the American Association for Cancer Research (2022)
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/TGFβ gene signatures were associated with lower treatment response. See related article by Cristescu et al., p. 1680.
Keyphrases
- genome wide
- epithelial mesenchymal transition
- copy number
- single cell
- transforming growth factor
- bioinformatics analysis
- genome wide identification
- stem cells
- dna methylation
- endothelial cells
- clinical trial
- randomized controlled trial
- vascular endothelial growth factor
- open label
- advanced non small cell lung cancer
- mesenchymal stem cells
- combination therapy
- gene expression
- genome wide analysis
- bone marrow