Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

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Tumor mutational load predicts survival after immunotherapy across multiple cancer types

R. Samstein, Chung-Han Lee, A. Shoushtari, et al.. (2019). Nature Genetics. Cited 3,193 times. https://doi.org/10.1038/s41588-018-0312-8

Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy

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Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

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Multi-stage Differentiation Defines Melanoma Subtypes with Differential Vulnerability to Drug-Induced Iron-Dependent Oxidative Stress.

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Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma

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Integrated molecular analysis of tumor biopsies on sequential CTLA-4 and PD-1 blockade reveals markers of response and resistance

Whijae Roh, Pei-Ling Chen, A. Reuben, et al.. (2017). Science Translational Medicine. Cited 747 times. https://doi.org/10.1126/scitranslmed.aah3560

A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade

Livnat Jerby-Arnon, Parin Shah, Michael S. Cuoco, et al.. (2018). Cell. Cited 575 times. https://doi.org/10.1016/j.cell.2018.09.006

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy

M. Łuksza, N. Riaz, V. Makarov, et al.. (2017). Nature. Cited 573 times. https://doi.org/10.1038/nature24473

The Cancer Genome Atlas Expression Subtypes Stratify Response to Checkpoint Inhibition in Advanced Urothelial Cancer and Identify a Subset of Patients with High Survival Probability.

Jaegil Kim, D. Kwiatkowski, D. McConkey, et al.. (2019). European urology. Cited 161 times. https://doi.org/10.1016/j.eururo.2019.02.017
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