Metabolic regulation has been recognized as a powerful principle guiding immune responses. Inflammatory macrophages undergo extensive metabolic rewiring1 marked by the production of substantial amounts of itaconate, which has recently been described as an immunoregulatory metabolite2. Itaconate and its membrane-permeable derivative dimethyl itaconate (DI) selectively inhibit a subset of cytokines2, including IL-6 and IL-12 but not TNF. The major effects of itaconate on cellular metabolism during macrophage activation have been attributed to the inhibition of succinate dehydrogenase2,3, yet this inhibition alone is not sufficient to account for the pronounced immunoregulatory effects observed in the case of DI. Furthermore, the regulatory pathway responsible for such selective effects of itaconate and DI on the inflammatory program has not been defined. Here we show that itaconate and DI induce electrophilic stress, react with glutathione and subsequently induce both Nrf2 (also known as NFE2L2)-dependent and -independent responses. We find that electrophilic stress can selectively regulate secondary, but not primary, transcriptional responses to toll-like receptor stimulation via inhibition of IκBζ protein induction. The regulation of IκBζ is independent of Nrf2, and we identify ATF3 as its key mediator. The inhibitory effect is conserved across species and cell types, and the in vivo administration of DI can ameliorate IL-17–IκBζ-driven skin pathology in a mouse model of psoriasis, highlighting the therapeutic potential of this regulatory pathway. Our results demonstrate that targeting the DI–IκBζ regulatory axis could be an important new strategy for the treatment of IL-17–IκBζ-mediated autoimmune diseases.

Summary Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest—namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial—ENTHUSE M1—in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·39–4·62, p<0·0001; reference model: 2·56, 1·85–3·53, p<0·0001). The new model was validated further on the ENTHUSE M1 cohort with similarly high performance (iAUC 0·768). Meta-analysis across all methods confirmed previously identified...

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Altered metabolisms helps sustain cancer cell proliferation and survival. Most cancers, including prostate cancers, express the M2 splice isoform of pyruvate kinase (Pkm2), which can support anabolic metabolism to support cell proliferation. However, Pkm2 expression is dispensable for the formation and growth of many cancers in vivo. Expression of pyruvate kinase isoform M1 (Pkm1) is restricted to relatively few tissues and has been reported to promote growth of select tumors, but the role of Pkm1 in cancer has been less studied than Pkm2. To test how differential expression of pyruvate kinase isoforms affects cancer initiation and progression, we generated mice harboring a conditional allele of Pkm1, and crossed these mice or those with a Pkm2 conditional allele with a Pten loss-driven prostate cancer model. Pkm1 loss led to increased Pkm2 expression and accelerated prostate cancer development, while Pkm2 deletion of led to increased Pkm1 expression and suppressed tumor progression. Metabolic profiling revealed altered nucleotide levels in tumors with high Pkm1 expression, and failure of these tumors to progress was associated with DNA replication stress and senescence. Consistent with these data, a small molecule pyruvate kinase activator that mimics a high activity Pkm1-like state suppressed progression of established prostate tumors. Analysis of human specimens showed PKM2 expression is retained in most human prostate cancers. Overall, this study uncovers a role for pyruvate kinase isoforms in prostate cancer initiation and progression, and argues that pharmacological pyruvate kinase activation may be beneficial for treating prostate cancer.