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Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Predictive Biomarkers for Immune Checkpoint Inhibitor Therapy in Advanced Melanomas
Emma Wagner1, Banafshé Larijani2, Amanda Robinson Kirane1
1Division of General Surgery, Department of Surgery, Section of Surgical Oncology, Stanford University School of Medicine, 1201 Welch Road, Stanford, CA 94305, USA.
None:
Biomarkers capable of predicting adverse melanoma patient responses to immune checkpoint inhibitor (ICI) therapies are an unmet need. Clinical biomarkers are largely prognostic and current response guidelines do not reflect the complex tumor-immune cell interaction dynamics attributed to ICI therapies. Validation of enhanced predictive biomarkers is dependent upon adoption of novel spatial imaging platforms capable of quantifying immune checkpoint receptor-ligand interactions within the tumor microenvironment. Assessments of these interactions at multiple points during neoadjuvant ICI regimens would inform biomarker selection based on changes in receptor-ligand interactions that best correlate with patient survival.

