Gene signature of antigen processing and presentation machinery predicts response to checkpoint blockade in non-small cell lung cancer (NSCLC) and melanoma.
Jeffrey C ThompsonChristiana DavisCharuhas DeshpandeWei-Ting HwangSeth JeffriesAlexander HuangTara C MitchellCorey J LangerSteven M AlbeldaPublished in: Journal for immunotherapy of cancer (2021)
Our data demonstrate that defects in antigen presentation may be an important feature in predicting outcomes to ICB in both lung cancer and melanoma.
Keyphrases
- small cell lung cancer
- skin cancer
- dna damage
- case report
- electronic health record
- machine learning
- copy number
- cell cycle
- genome wide
- deep learning
- basal cell carcinoma
- advanced non small cell lung cancer
- gene expression
- adipose tissue
- cell proliferation
- data analysis
- epidermal growth factor receptor
- oxidative stress
- transcription factor
- tyrosine kinase