Perspective: combined forces

Platinum Twin and Triplet Drugs Improve Chemoimmunotherapy

Several chemoimmunotherapy regimens have been approved by the U.S. FDA, verifying the great clinical value and potential of the strategy. However, the immunomodulatory function of chemotherapy was insufficient, which did not provide extra overall survival benefits, especially in a head-to-head comparison of chemoimmunotherapy versus immunotherapy. Here, we engineered twin and triplet drugs derived from an immunogenic chemotherapeutic drug (oxaliplatin) and small-molecule inhibitors of negative immunoregulation pathways (COX2 and IDO) in tumors as an improved chemotherapeutic component within chemoimmunotherapy. The twin and triplet drugs exhibited significantly improved synergy with anti-PD-1 in a CT26 colorectal mouse tumor model. Mechanistic analyses revealed that the drug induced immunogenic cell death and restored tumor immune microenvironment toward tumor clearance in vivo, resulting in a great decrease in tumor-infiltrating Tregs and an increase in the CD8+ T/Treg ratio when combined with anti-PD-1. Our work expands the application of platinum twin drugs in combination with an immune checkpoint blockade.

PROBABILISTIC LEARNING OF TREATMENT TREES IN CANCER

Accurate identification of synergistic treatment combinations and their underlying biological mechanisms is critical across many disease domains, especially cancer. In translational oncology research, preclinical systems such as patient-derived xenografts (PDX) have emerged as a unique study design evaluating multiple treatments administered to samples from the same human tumor implanted into genetically identical mice. In this paper, we propose a novel Bayesian probabilistic tree-based framework for PDX data to investigate the hierarchical relationships between treatments by inferring treatment cluster trees, referred to as treatment trees (Rx-tree). The framework motivates a new metric of mechanistic similarity between two or more treatments accounting for inherent uncertainty in tree estimation; treatments with a high estimated similarity have potentially high mechanistic synergy. Building upon Dirichlet Diffusion Trees, we derive a closed-form marginal likelihood encoding the tree structure, which facilitates computationally efficient posterior inference via a new two-stage algorithm. Simulation studies demonstrate superior performance of the proposed method in recovering the tree structure and treatment similarities. Our analyses of a recently collated PDX dataset produce treatment similarity estimates that show a high degree of concordance with known biological mechanisms across treatments in five different cancers. More importantly, we uncover new and potentially effective combination therapies that confer synergistic regulation of specific downstream biological pathways for future clinical investigations. Our accompanying code, data, and shiny application for visualization of results are available at: https://github.com/bayesrx/RxTree.

Fabrication of a Polymeric Inhibitor of Proximal Metabolic Enzymes in Hypoxia for Synergistic Inhibition of Cancer Cell Proliferation, Survival, and Migration

Since conventional molecular targeted drugs often result in side effects, the development of novel molecular targeted drugs with both high efficacy and selectivity is desired. Simultaneous inhibition of metabolically and spatiotemporally related proteins/enzymes is a promising strategy for improving therapeutic interventions in cancer treatment. Herein, we report a poly-α-l-glutamate-based polymer inhibitor that simultaneously targets proximal transmembrane enzymes under hypoxia, namely, carbonic anhydrase IX (CAIX) and zinc-dependent metalloproteinases. A polymer incorporating two types of inhibitors more effectively inhibited the proliferation and migration of human breast cancer cells than a combination of two polymers functionalized exclusively with either inhibitor. Synergistic inhibition of cancer cells would occur owing to the hetero-multivalent interactions of the polymer with proximate enzymes on the cancer cell membrane. Our results highlight the potential of polymer-based cancer therapeutics.

A cancer drug atlas enables synergistic targeting of independent drug vulnerabilities

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value.

Multiomic Profiling of Tyrosine Kinase Inhibitor-Resistant K562 Cells Suggests Metabolic Reprogramming To Promote Cell Survival

Resistance to chemotherapy can occur through a wide variety of mechanisms. Resistance to tyrosine kinase inhibitors (TKIs) often arises from kinase mutations-however, "off-target" resistance occurs but is poorly understood. Previously, we established cell line resistance models for three TKIs used in chronic myeloid leukemia treatment, and found that resistance was not attributed entirely to failure of kinase inhibition. Here, we performed global, integrated proteomic and transcriptomic profiling of these cell lines to describe mechanisms of resistance at the protein and gene expression level. We used whole transcriptome sequencing and SWATH-based data-independent acquisition mass spectrometry (DIA-MS), which does not require isotopic labels and provides quantitative measurements of proteins in a comprehensive, unbiased fashion. The proteomic and transcriptional data were correlated to generate an integrated understanding of the gene expression and protein alterations associated with TKI resistance. We defined mechanisms of resistance and two novel markers, CA1 and alpha-synuclein, that were common to all TKIs tested. Resistance to all of the TKIs was associated with oxidative stress responses, hypoxia signatures, and apparent metabolic reprogramming of the cells. Metabolite profiling and glucose-dependence experiments showed that resistant cells had routed their metabolism through glycolysis (particularly through the pentose phosphate pathway) and exhibited disruptions in mitochondrial metabolism. These experiments are the first to report a global, integrated proteomic, transcriptomic, and metabolic analysis of TKI resistance. These data suggest that although the mechanisms are complex, targeting metabolic pathways along with TKI treatment may overcome pan-TKI resistance.

Pragmatic medicine in solid cancer: a translational alternative to precision medicine

The precision medicine (PM) initiative is a response to the dismal outlook in solid cancer. Despite heterogeneity, common mechanistic denominators may exist across the spectrum of solid cancer. A shift from conventional research and development (R&D) toward PM will require conceptual and structural change. As individuals and as a society, we welcome innovation, but question change. We ask: In solid cancer, does PM identify and address the causes of prior failures, and, if so, are the proposed solutions feasible? And, when may we expect safer, more effective and affordable drugs in the clinic? Considerations that prompt a pragmatic rethink include a failure analysis of translational R&D in solid cancer suggesting that trials and regulations need to be aligned with the natural history of the disease. In successful therapeutic interventions in chronic, complex disease, surrogate markers and endpoints should be consistent with the Prentice's criteria. In solid cancer, drug induced tumor shrinkage, is a drug effect and not a disease response; tumor shrinkage does not reflect nor predict interruption of the disease. Overall, we support a pragmatic, multidisciplinary, and collaborative R&D, and suggest that direction be set by clinical need and utility, and by questions, not answers. PM will prove worthwhile if it could improve clinical outcomes. The lag in therapeutics relative to diagnostics is a cause for confusion. Overdiagnosis adds to fear and harm, especially in the absence of effective interventions. A revised initiative that prioritizes metastasis research could replicate the successful HIV/AIDS model in solid cancer. A pragmatic approach may further translational efforts toward meaningfully effective, generally available, and affordable solutions.

Mechanisms of acquired resistance to androgen receptor targeting drugs in castration-resistant prostate cancer

After initial response to androgen receptor (AR) targeting drugs abiraterone or enzalutamide, most patients develop progressive disease and therefore, castration resistant prostate cancer remains a terminal disease. Multiple mechanisms underlying acquired resistance have been postulated. Intratumoral androgen synthesis may resume after abiraterone treatment. A point mutation in the ligand-binding domain of AR may confer resistance to enzalutamide. Emergence of AR splice variants lacking the ligand-binding domain may mediate resistance to abiraterone and enzalutamide. Steroid receptors such as glucocorticoid receptor may substitute for AR. Drugs with novel mechanisms of action or combination therapy, along with biomarkers for patient selection, may be needed to improve the therapy of castration resistant prostate cancer.

Magnetic resonance guided high-intensity focused ultrasound for image-guided temperature-induced drug delivery

Magnetic resonance guided high-intensity focused ultrasound (MR-HIFU) is a versatile technology platform for noninvasive thermal therapies in oncology. Since MR-HIFU allows heating of deep-seated tissue to well-defined temperatures under MR image guidance, this novel technology has great potential for local heat-mediated drug delivery from temperature-sensitive liposomes (TSLs). In particular, MR provides the ability for image guidance of the drug delivery when an MRI contrast agent is co-encapsulated with the drug in the aqueous lumen of the liposomes. Monitoring of the tumor drug coverage offers possibilities for a personalized thermal treatment in oncology. This review focuses on MR-HIFU as a noninvasive technology platform, temperature-sensitive liposomal formulations for drug delivery and image-guided drug delivery, and the effect of HIFU-induced hyperthermia on the TSL and drug distribution. Finally, the opportunities and challenges of localized MR-HIFU-mediated drug delivery from temperature-sensitive liposomes in oncology are discussed.