Systematic identification of cancer cell vulnerabilities to natural killer cell-mediated immune surveillance.

Only a subset of cancer patients respond to T-cell checkpoint inhibitors, highlighting the need for alternative immunotherapeutics. We performed CRISPR-Cas9 screens in a leukemia cell line to identify perturbations that enhance natural killer effector functions. Our screens defined critical components of the tumor-immune synapse and highlighted the importance of cancer cell interferon-γ signaling in modulating NK activity. Surprisingly, disrupting the ubiquitin ligase substrate adaptor DCAF15 strongly sensitized cancer cells to NK-mediated clearance. DCAF15 disruption induced an inflamed state in leukemic cells, including increased expression of lymphocyte costimulatory molecules. Proteomic and biochemical analysis revealed that cohesin complex members were endogenous client substrates of DCAF15. Genetic disruption of DCAF15 was phenocopied by treatment with indisulam, an anticancer drug that functions through DCAF15 engagement. In AML patients, reduced DCAF15 expression was associated with improved survival. These findings suggest that DCAF15 inhibition may have useful immunomodulatory properties in the treatment of myeloid neoplasms.

Advancing systems immunology through data-driven statistical analysis.

Systems biology provides an effective approach to decipher, predict, and ultimately manipulate the complex and inter-connected networks that regulate the immune system. Advances in high-throughput, multiplexed experimental techniques have increased the availability of proteomic and transcriptomic immunological datasets, and as a result, have also accelerated the development of new data-driven computational algorithms to extract biological insight from these data. This review highlights how data-driven statistical models have been used to characterize immune cell subsets and their functions, to map the signaling and intercellular networks that regulate immune responses, and to connect immune cell states to disease outcomes to generate hypotheses for novel therapeutic strategies. We focus on recent advances in evaluating immune cell responses following viral infection and in the tumor microenvironment, which hold promise for improving vaccines, antiviral and cancer immunotherapy.

Systems analysis of latent HIV reversal reveals altered stress kinase signaling and increased cell death in infected T cells.

Viral latency remains the most significant obstacle to HIV eradication. Clinical strategies aim to purge the latent CD4+ T cell reservoir by activating viral expression to induce death, but are undercut by the inability to target latently infected cells. Here we explored the acute signaling response of latent HIV-infected CD4+ T cells to identify dynamic phosphorylation signatures that could be targeted for therapy. Stimulation with CD3/CD28, PMA/ionomycin, or latency reversing agents prostratin and SAHA, yielded increased phosphorylation of IκBα, ERK, p38, and JNK in HIV-infected cells across two in vitro latency models. Both latent infection and viral protein expression contributed to changes in perturbation-induced signaling. Data-driven statistical models calculated from the phosphorylation signatures successfully classified infected and uninfected cells and further identified signals that were functionally important for regulating cell death. Specifically, the stress kinase pathways p38 and JNK were modified in latently infected cells, and activation of p38 and JNK signaling by anisomycin resulted in increased cell death independent of HIV reactivation. Our findings suggest that altered phosphorylation signatures in infected T cells provide a novel strategy to more selectively target the latent reservoir to enhance eradication efforts.

Quantitative evaluation and optimization of co-drugging to improve anti-HIV latency therapy.

Human immunodeficiency virus 1 (HIV) latency remains a significant obstacle to curing infected patients. One promising therapeutic strategy is to purge the latent cellular reservoir by activating latent HIV with latency-reversing agents (LRAs). In some cases, co-drugging with multiple LRAs is necessary to activate latent infections, but few studies have established quantitative criteria for determining when co-drugging is required. Here we systematically quantified drug interactions between histone deacetylase inhibitors and transcriptional activators of HIV and found that the need for co-drugging is determined by the proximity of latent infections to the chromatin-regulated viral gene activation threshold at the viral promoter. Our results suggest two classes of latent viral integrations: those far from the activation threshold that benefit from co-drugging, and those close to the threshold that are efficiently activated by a single drug. Using a primary T cell model of latency, we further demonstrated that the requirement for co-drugging was donor dependent, suggesting that the host may set the level of repression of latent infections. Finally, we showed that single drug or co-drugging doses could be optimized, via repeat stimulations, to minimize unwanted side effects while maintaining robust viral activation. Our results motivate further study of patient-specific latency-reversing strategies.