2018
DOI: 10.1038/s41591-018-0157-9
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Abstract: Immune checkpoint blockade (ICB) therapy provides remarkable clinical gains and has been very successful in treatment of melanoma. However, only a subset of patients with advanced tumors currently benefit from ICB therapies, which at times incur considerable side effects and costs. Constructing predictors of patient response has remained a serious challenge because of the complexity of the immune response and the shortage of large cohorts of ICB-treated patients that include both 'omics' and response data. Her… Show more

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Cited by 481 publications
(399 citation statements)
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“…Database and annotation. The built-in database is manually curated from previous efforts [3][4][5][6][7][8][9][10] . The gene lists were combined and duplicates were removed to make a non-redundant ligandreceptor list.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Database and annotation. The built-in database is manually curated from previous efforts [3][4][5][6][7][8][9][10] . The gene lists were combined and duplicates were removed to make a non-redundant ligandreceptor list.…”
Section: Methodsmentioning
confidence: 99%
“…Ligand-receptor binding is one of the main forms of signal transduction between neighboring and distant cells. To characterize the ligand-receptor mediated intercellular cross-talk, we first manually curated a unique list of ligand-receptor gene pairs based on previous efforts [3][4][5][6][7][8][9][10] and made this as a built-in database for iTALK. This database collected a total of 2,648 nonredundant and known interacting ligand-receptor pairs, which were further classified into 4 categories based on the primary function of the ligand: cytokines/chemokines, immune checkpoint genes, growth factors, and others ( Fig.…”
mentioning
confidence: 99%
“…To evaluate the accuracy of SR based predictions, we collected a set of 11 immune checkpoint therapy datasets that included both pre-treatment transcriptomics data and therapy response information (either by RECIST or PFS). Our collection includes five melanoma datasets [35][36][37][38][39] and glioma 40 , and renal cell carcinoma 41 cohorts treated with anti-PD1 or anti-CTLA4. Figure 3A shows that higher SR-scores are indeed associated with better response to immune checkpoint blockade, with AUCs greater than 0.7 in 7 out of 10 datasets, where RECIST information is available (Figure 3B), and Figure S2 shows the corresponding precision-recall curves.…”
Section: Sr-based Prediction Of Response To Checkpoint Blockadementioning
confidence: 99%
“…High mutation and neoantigen burden in pretreated tumors, increased T cell infiltrates and induction of inflammatory pathways during treatment, and antigen presentation alterations have shown correlation with clinical benefit 3-18 . Although the expression of specific pathways has been associated with ICB response in particular patient cohorts 7,18,19 , uncovering broad predictive signatures based on gene expression profiles has been elusive due to difficulties in collecting high quality transcriptomic data from clinical sets.Recently, independent computational predictors were developed based on immune-related gene expression profiles, such as immune checkpoints, co-stimulatory molecules and T cell dysfunction and exclusion markers [20][21][22] . However, the utility of these approaches for patient stratification will require further validation.Mouse models have historically served as essential tools for plumbing mechanisms underlying tumor initiation, progression and drug response, and have enormous potential.…”
mentioning
confidence: 99%
“…Recently, independent computational predictors were developed based on immune-related gene expression profiles, such as immune checkpoints, co-stimulatory molecules and T cell dysfunction and exclusion markers [20][21][22] . However, the utility of these approaches for patient stratification will require further validation.…”
mentioning
confidence: 99%