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Mounting evidence indicates that immunogenic therapies engaging the unfolded protein response (UPR) following endoplasmic reticulum (ER) stress favor proficient cancer cell-immune interactions, by stimulating the release of immunomodulatory/proinflammatory factors by stressed or dying cancer cells. UPR-driven transcription of proinflammatory cytokines/chemokines exert beneficial or detrimental effects on tumor growth and antitumor immunity, but the cell-autonomous machinery governing the cancer cell inflammatory output in response to immunogenic therapies remains poorly defined. Here, we profiled the transcriptome of cancer cells responding to immunogenic or weakly immunogenic treatments. Bioinformatics-driven pathway analysis indicated that immunogenic treatments instigated a NF-κB/AP-1-inflammatory stress response, which dissociated from both cell death and UPR. This stress-induced inflammation was specifically abolished by the IRE1α-kinase inhibitor KIRA6. Supernatants from immunogenic chemotherapy and KIRA6 co-treated cancer cells were deprived of proinflammatory/chemoattractant factors and failed to mobilize neutrophils and induce dendritic cell maturation. Furthermore, KIRA6 significantly reduced the in vivo vaccination potential of dying cancer cells responding to immunogenic chemotherapy. Mechanistically, we found that the anti-inflammatory effect of KIRA6 was still effective in IRE1α-deficient cells, indicating a hitherto unknown off-target effector of this IRE1α-kinase inhibitor. Generation of a KIRA6-clickable photoaffinity probe, mass spectrometry, and co-immunoprecipitation analysis identified cytosolic HSP60 as a KIRA6 off-target in the IKK-driven NF-κB pathway. In sum, our study unravels that HSP60 is a KIRA6-inhibitable upstream regulator of the NF-κB/AP-1-inflammatory stress responses evoked by immunogenic treatments. It also urges caution when interpreting the anti-inflammatory action of IRE1α chemical inhibitors., (© 2021. The Author(s).)

Melanoma cells are highly resistant to conventional genotoxic agents, and BRAFV600/MEK-targeted therapies as well as immunotherapies frequently remain inefficient. Alternative means to treat melanoma, in particular through the induction of programmed cell death modalities such as apoptosis or necroptosis, therefore still need to be explored. Here, we report that melanoma cell lines expressing notable amounts of RIPK1, RIPK3 and MLKL, the key players of necroptosis signal transduction, fail to execute necroptotic cell death. Interestingly, the activity of transforming growth factor β-activated kinase 1 (TAK1) appears to prevent RIPK1 from contributing to cell death induction, since TAK1 inhibition by (5Z)-7-Oxozeaenol, deletion of MAP3K7 or the expression of inactive TAK1 were sufficient to sensitize melanoma cells to RIPK1-dependent cell death in response to TNFα or TRAIL based combination treatments. However, cell death was executed exclusively by apoptosis, even when RIPK3 expression was high. In addition, TAK1 inhibitor (5Z)-7-Oxozeaenol suppressed intrinsic or treatment-induced pro-survival signaling as well as the secretion of cytokines and soluble factors associated with melanoma disease progression. Correspondingly, elevated expression of TAK1 correlates with reduced disease free survival in patients diagnosed with primary melanoma. Overall, our results therefore demonstrate that TAK1 suppresses the susceptibility to RIPK1-dependent cell death and that high expression of TAK1 indicates an increased risk for disease progression in melanoma.

Malignant melanoma is a highly aggressive form of skin cancer responsible for the majority of skin cancer-related deaths. Recent insight into the heterogeneous nature of melanoma suggests more personalised treatments may be necessary to overcome drug resistance and improve patient care. To this end, reliable molecular signatures that can accurately predict treatment responsiveness need to be identified. In this study, we applied multiplex phosphoproteomic profiling across a panel of 24 melanoma cell lines with different disease-relevant mutations, to predict responsiveness to MEK inhibitor trametinib. Supported by multivariate statistical analysis and multidimensional pattern recognition algorithms, the responsiveness of individual cell lines to trametinib could be predicted with high accuracy (83% correct predictions), independent of mutation status. We also successfully employed this approach to case specifically predict whether individual melanoma cell lines could be sensitised to trametinib. Our predictions identified that combining MEK inhibition with selective targeting of c-JUN and/or FAK, using siRNA-based depletion or pharmacological inhibitors, sensitised resistant cell lines and significantly enhanced treatment efficacy. Our study indicates that multiplex proteomic analyses coupled with pattern recognition approaches could assist in personalising trametinib-based treatment decisions in the future.