Predictive biomarkers for checkpoint inhibitor-based immunotherapy.

By G. Gibney, L. Weiner, M. Atkins. The Lancet Oncology, 2016

1,458 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Molecular profiling for precision cancer therapies (2020, methodology): “To date, two tests based on plasma ctDNA analysis have been FDA-approved for clinical use: the testing of EGFR mutations in patients with NSCLC and the methylation of the SEPT9 promoter as screening for colorectal cancer [56, 64, 67, 70].”
Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer (2022, background): “Detailed baseline data of CRC patients are displayed in Supplementary Data 5.”
Artificial intelligence as the next step towards precision pathology (2020, background): “However, its clinical success relies on numerous factors like the expression of immunomodulatory ligands (e.g. PD-L1 [30]), tumour mutational burden and TILs [31, 32].”