Targeting TBK1 to overcome resistance to cancer immunotherapy.

Despite the success of PD-1 blockade in melanoma and other cancers, effective treatment strategies to overcome resistance to cancer immunotherapy are lacking1,2. Here we identify the innate immune kinase TANK-binding kinase 1 (TBK1)3 as a candidate immune-evasion gene in a pooled genetic screen4. Using a suite of genetic and pharmacological tools across multiple experimental model systems, we confirm a role for TBK1 as an immune-evasion gene. Targeting TBK1 enhances responses to PD-1 blockade by decreasing the cytotoxicity threshold to effector cytokines (TNF and IFNγ). TBK1 inhibition in combination with PD-1 blockade also demonstrated efficacy using patient-derived tumour models, with concordant findings in matched patient-derived organotypic tumour spheroids and matched patient-derived organoids. Tumour cells lacking TBK1 are primed to undergo RIPK- and caspase-dependent cell death in response to TNF and IFNγ in a JAK-STAT-dependent manner. Taken together, our results demonstrate that targeting TBK1 is an effective strategy to overcome resistance to cancer immunotherapy.

Torin2 Exploits Replication and Checkpoint Vulnerabilities to Cause Death of PI3K-Activated Triple-Negative Breast Cancer Cells.

Frequent mutation of PI3K/AKT/mTOR signaling pathway genes in human cancers has stimulated large investments in targeted drugs but clinical successes are rare. As a result, many cancers with high PI3K pathway activity, such as triple-negative breast cancer (TNBC), are treated primarily with chemotherapy. By systematically analyzing responses of TNBC cells to a diverse collection of PI3K pathway inhibitors, we find that one drug, Torin2, is unusually effective because it inhibits both mTOR and other PI3K-like kinases (PIKKs). In contrast to mTOR-selective inhibitors, Torin2 exploits dependencies on several kinases for S-phase progression and cell-cycle checkpoints, thereby causing accumulation of single-stranded DNA and death by replication catastrophe or mitotic failure. Thus, Torin2 and its chemical analogs represent a mechanistically distinct class of PI3K pathway inhibitors that are uniquely cytotoxic to TNBC cells. This insight could be translated therapeutically by further developing Torin2 analogs or combinations of existing mTOR and PIKK inhibitors.

Inflammatory but not mitogenic contexts prime synovial fibroblasts for compensatory signaling responses to p38 inhibition.

Rheumatoid arthritis (RA) is a chronic inflammatory disorder that causes joint pain, swelling, and loss of function. Development of effective new drugs has proven challenging in part because of the complexities and interconnected nature of intracellular signaling networks that complicate the effects of pharmacological interventions. We characterized the kinase signaling pathways that are activated in RA and evaluated the multivariate effects of targeted inhibitors. Synovial fluids from RA patients activated the kinase signaling pathways JAK, JNK, p38, and MEK in synovial fibroblasts (SFs), a stromal cell type that promotes RA progression. Kinase inhibitors enhanced signaling of "off-target" pathways in a manner dependent on stimulatory context. Inhibitors of p38, which have been widely explored in clinical trials for RA, resulted in undesirable increases in nuclear factor κB (NF-κB), JNK, and MEK signaling in SFs in inflammatory, but not mitogenic, contexts. This was mediated by the transcription factor CREB, which functions in part within a negative feedback loop in MAPK signaling. CREB activation was induced predominately by p38 in response to inflammatory stimuli, but by MEK in response to mitogenic stimuli; hence, the effects of drugs targeting p38 or MEK were markedly different in SFs cultured under mitogenic or inflammatory conditions. Together, these findings illustrate how stimulatory context can alter dominance in pathway cross-talk even for a fixed network topology, thereby providing a rationale for why p38 inhibitors deliver limited benefits in RA and demonstrating the need for careful consideration of p38-targeted drugs in inflammation-related disorders.

Profiling drugs for rheumatoid arthritis that inhibit synovial fibroblast activation.

Activation of synovial fibroblasts (SFs) contributes to rheumatoid arthritis (RA) by damaging synovial membranes and generating inflammatory cytokines that recruit immune cells to the joint. In this paper we profile cytokine secretion by primary human SFs from healthy tissues and from donors with RA and show that SF activation by TNF, IL-1α, and polyinosinic-polycytidylic acid (Poly(I:C)) cause secretion of multiple cytokines found at high levels in RA synovial fluids. We used interaction multiple linear regression to quantify therapeutic and countertherapeutic drug effects across activators and donors and found that the ability of drugs to block SF activation was strongly dependent on the identity of the activating cytokine. (5z)-7-oxozeaenol (5ZO), a preclinical drug that targets transforming growth factor-ß-activated kinase 1 (TAK1), was more effective at blocking SF activation across all contexts than the approved drug tofacitinib, which supports the development of molecules similar to 5ZO for use as RA therapeutics.

A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks.

Functional interpretation of genomic variation is critical to understanding human disease, but it remains difficult to predict the effects of specific mutations on protein interaction networks and the phenotypes they regulate. We describe an analytical framework based on multiscale statistical mechanics that integrates genomic and biophysical data to model the human SH2-phosphoprotein network in normal and cancer cells. We apply our approach to data in The Cancer Genome Atlas (TCGA) and test model predictions experimentally. We find that mutations mapping to phosphoproteins often create new interactions but that mutations altering SH2 domains result almost exclusively in loss of interactions. Some of these mutations eliminate all interactions, but many cause more selective loss, thereby rewiring specific edges in highly connected subnetworks. Moreover, idiosyncratic mutations appear to be as functionally consequential as recurrent mutations. By synthesizing genomic, structural and biochemical data, our framework represents a new approach to the interpretation of genetic variation.