Agent-based computational modeling of glioblastoma predicts that stromal density is central to oncolytic virus efficacy.

Oncolytic viruses (OVs) are emerging cancer immunotherapy. Despite notable successes in the treatment of some tumors, OV therapy for central nervous system cancers has failed to show efficacy. We used an tumor model developed from human glioblastoma tissue to evaluate the infiltration of herpes simplex OV rQNestin (oHSV-1) into glioblastoma tumors.

Systems biology informed neural networks (SBINN) predict response and novel combinations for PD-1 checkpoint blockade.

Anti-PD-1 immunotherapy has recently shown tremendous success for the treatment of several aggressive cancers. However, variability and unpredictability in treatment outcome have been observed, and are thought to be driven by patient-specific biology and interactions of the patient's immune system with the tumor. Here we develop an integrative systems biology and machine learning approach, built around clinical data, to predict patient response to anti-PD-1 immunotherapy and to improve the response rate.

Nanoengineered Disruption of Heat Shock Protein 90 Targets Drug-Induced Resistance and Relieves Natural Killer Cell Suppression in Breast Cancer.

Drug-induced resistance, or tolerance, is an emerging yet poorly understood failure of anticancer therapy. The interplay between drug-tolerant cancer cells and innate immunity within the tumor, the consequence on tumor growth, and therapeutic strategies to address these challenges remain undescribed. Here, we elucidate the role of taxane-induced resistance on natural killer (NK) cell tumor immunity in triple-negative breast cancer (TNBC) and the design of spatiotemporally controlled nanomedicines, which boost therapeutic efficacy and invigorate "disabled" NK cells.

Integrating Systems Biology and an Ex Vivo Human Tumor Model Elucidates PD-1 Blockade Response Dynamics.

Ex vivo human tumor models have emerged as promising, yet complex tools to study cancer immunotherapy response dynamics. Here, we present a strategy that integrates empirical data from an ex vivo human system with computational models to interpret the response dynamics of a clinically prescribed PD-1 inhibitor, nivolumab, in head and neck squamous cell carcinoma (HNSCC) biopsies (N = 50). Using biological assays, we show that drug-induced variance stratifies samples by T helper type 1 (Th1)-related pathways.

Cancer Immunotherapy and Personalized Medicine: Emerging Technologies and Biomarker-Based Approaches.

Purpose Of Review: The vision and strategy for the 21st century treatment of cancer calls for a personalized approach in which therapy selection is designed for each individual patient. While genomics has led the field of personalized cancer medicine over the past several decades by connecting patient-specific DNA mutations with kinase-targeted drugs, the recent discovery that tumors evade immune surveillance has created unique challenges to personalize cancer immunotherapy. In this mini-review we will discuss how personalized medicine has evolved recently to accommodate the emerging era of cancer immunotherapy.