40425_2018_344_MOESM1_ESM.xlsx (1.35 MB)
Additional file 1: of Predicting response to checkpoint inhibitors in melanoma beyond PD-L1 and mutational burden
dataset
posted on 2018-05-09, 05:00 authored by Carl Morrison, Sarabjot Pabla, Jeffrey Conroy, Mary Nesline, Sean Glenn, Devin Dressman, Antonios Papanicolau-Sengos, Blake Burgher, Jonathan Andreas, Vincent Giamo, Moachun Qin, Yirong Wang, Felicia Lenzo, Angela Omilian, Wiam Bshara, Matthew Zibelman, Pooja Ghatalia, Konstantin Dragnev, Keisuke Shirai, Katherine Madden, Laura Tafe, Neel Shah, Deepa Kasuganti, Luis de la Cruz-Merino, Isabel Araujo, Yvonne Saenger, Margaret Bogardus, Miguel Villalona-Calero, Zuanel Diaz, Roger Day, Marcia Eisenberg, Steven Anderson, Igor Puzanov, Lorenzo Galluzzi, Mark Gardner, Marc ErnstoffTable S1 Clinical characteristics of the melanoma cohort. Table S2 Survival analyses for studied biomarkers. Table S3 Comprehensive gene expression and mutational profile of melanoma cohort. Table S4 Over representation test results of categorical variables for gene expression clusters. Table S5 Over representation test results of gene ranks for gene expression clusters. Table S6 ORR for all biomarker groups studied. Table S7 Objective response rates for studied biomarkers. Table S8 Objective response counts for melanoma cohort. Table S9 ORR for training set response score groups. (XLSX 1378 kb)
