Summary Macrophages are a crucial component of the innate immune system in sensing pathogens and promoting local and systemic inflammation. RIPK1 and RIPK3 are homologous kinases, previously linked to activation of necroptotic death. In this study we have described roles for these kinases as master regulators of pro-inflammatory gene expression induced by lipopolysaccharide, independent of their well-documented cell death functions. In primary macrophages, this regulation was elicited in the absence of caspase-8 activity, required the adaptor molecule TRIF, and proceeded in a cell autonomous manner. RIPK1 and RIPK3 kinases promoted sustained activation of Erk, cFos and NFκB, which were required for inflammatory changes. Utilizing genetic and pharmacologic tools, we showed that RIPK1 and RIPK3 account for acute inflammatory responses induced by lipopolysaccharide in vivo; notably, this regulation did not require exogenous manipulation of caspases. These findings identified a new pharmacologically accessible pathway that may be relevant to inflammatory pathologies.

Summary RIPK1 and RIPK3, two closely related RIPK family members, have emerged as important regulators of pathologic cell death and inflammation. In the current work, we report that the Bcr-Abl inhibitor and anti-leukemia agent ponatinib is also a first-in-class dual inhibitor of RIPK1 and RIPK3. Ponatinib potently inhibited multiple paradigms of RIPK1- and RIPK3-dependent cell death and inflammatory TNFα gene transcription. We further describe design strategies that utilize the ponatinib scaffold to develop two classes of inhibitors (CS and PN series), each with greatly improved selectivity for RIPK1. In particular, we detail the development of PN10, a highly potent and selective ‘hybrid’ RIPK1 inhibitor, capturing the best properties of two different allosteric RIPK1 inhibitors, ponatinib and necrostatin-1. Finally, we show that RIPK1 inhibitors from both classes are powerful blockers of TNF-induced injury in vivo. Altogether, these findings outline promising candidate molecules and design approaches for targeting RIPK1/3-driven inflammatory pathologies.

The innate immune response is a central element of the initial defense against bacterial and viral pathogens. Macrophages are key innate immune cells that upon encountering pathogen associated molecular patterns respond by producing cytokines, including Interferon-β (IFNβ). In this study, we identify a novel role for RIPK1 and RIPK3, a pair of homologous serine/threonine kinases previously implicated in the regulation of necroptosis and pathologic tissue injury, in directing IFNβ production in macrophages. Using genetic and pharmacologic tools we show that catalytic activity of RIPK1 directs IFNβ synthesis induced by lipopolysaccharide (LPS) in mice. Additionally, we report that RIPK1 kinase-dependent IFNβ production may be elicited in an analogous fashion using LPS in bone-marrow derived macrophages (BMDMs) upon inhibition of caspases. Notably, this regulation requires kinase activities of both RIPK1 and RIPK3, but not the necroptosis effector protein, MLKL. Mechanistically, we provide evidence that a necrosome-like RIPK1 and RIPK3 aggregates facilitate canonical TRIF-dependent IFNβ production downstream of the LPS receptor TLR4. Intriguingly, we also show that RIPK1 and RIPK3 kinase-dependent synthesis of IFNβ is markedly induced by avirulent strains of gram-negative bacteria, Yersinia and Klebsiella, and less-so by their wild-type counterparts. Overall, these observations identify unexpected roles for RIPK1 and RIPK3 kinases in the production of IFNβ during the host inflammatory responses to bacterial infection and suggest that the axis in which these kinases operate may represent a target for bacterial virulence factors.

Sirtuins can promote deacetylation of a wide range of substrates in diverse cellular compartments and regulate many cellular processes1,2. Recently Narayan et al., reported that SIRT2 was required for necroptosis based on their findings that SIRT2 inhibition, knock-down or knock-out prevented necroptosis. We sought to confirm and explore the role of SIRT2 in necroptosis and tested four different sources of the SIRT2 inhibitor AGK2, three independent siRNAs against SIRT2, and cells from two independently generated Sirt2−/− mouse strains, however we were unable to show that inhibiting or depleting SIRT2 protected cells from necroptosis. Furthermore, Sirt2−/− mice succumbed to TNF induced Systemic Inflammatory Response Syndrome (SIRS) more rapidly than wild type mice while Ripk3−/− mice were resistant. Our results therefore question the importance of SIRT2 in the necroptosis cell death pathway.

Intratumour heterogeneity is increasingly recognized as a frequent problem for cancer treatment as it allows for the evolution of resistance against treatment. While cancer genotyping becomes more and more established and allows to determine the genetic heterogeneity, less is known about the phenotypic heterogeneity among cancer cells. We investigate how phenotypic differences can impact the efficiency of therapy options that select on this diversity, compared to therapy options that are independent of the phenotype. We employ the ecological concept of trait distributions and characterize the cancer cell population as a collection of subpopulations that differ in their growth rate. We show in a deterministic model that growth rate-dependent treatment types alter the trait distribution of the cell population, resulting in a delayed relapse compared to a growth rate-independent treatment. Whether the cancer cell population goes extinct or relapse occurs is determined by stochastic dynamics, which we investigate using a stochastic model. Again, we find that relapse is delayed for the growth rate-dependent treatment type, albeit an increased relapse probability, suggesting that slowly growing subpopulations are shielded from extinction. Sequential application of growth rate-dependent and growth rate-independent treatment types can largely increase treatment efficiency and delay relapse. Interestingly, even longer intervals between decisions to change the treatment type may achieve close-to-optimal efficiencies and relapse times. Monitoring patients at regular check-ups may thus provide the temporally resolved guidance to tailor treatments to the changing cancer cell trait distribution and allow clinicians to cope with this dynamic heterogeneity.