A machine learning model reveals expansive downregulation of ligand-receptor interactions that enhance lymphocyte infiltration in melanoma with developed resistance to immune checkpoint blockade
Sahil Sahni(National Institutes of Health), Eytan Ruppin(Cedars-Sinai Medical Center), Sushant Patkar(National Institutes of Health), Matthew Nagy(National Institutes of Health), Saugato Rahman Dhruba(National Institutes of Health), Binbin Wang(National Cancer Institute), Di Wu(National Institutes of Health), Kun Wang(University of Illinois Urbana-Champaign), Chi-Ping Day(National Institutes of Health), Ingrid Ferreira(Cliniques Universitaires Saint-Luc)
Cited by 14
Related Papers
Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma
|Nature Medicine|2018|813
Synthetic Lethal and Resistance Interactions with BET Bromodomain Inhibitors in Triple-Negative Breast Cancer
|Molecular Cell|2020|207
Immunoproteasome expression is associated with better prognosis and response to checkpoint therapies in melanoma
|Nature Communications|2020|156