Background: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. Methods: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs.(Continued on next page)

Immune checkpoint blockade (ICB) therapies have globally improved the overall survival (OS) of patients with advanced cancers. However, the response rate to these treatments vary widely among patients, therefore exposing non-responders to immune-related adverse events, causing an urgent need of prior-treatment predictors of response to ICB. We investigated the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) samples from primary and metastatic sites to identify predictive molecular and cellular markers of response to ICB. We revealed a significant discrepancy in treatment response between TME subgroups inferred from metastatic sites. The C3 cluster was enriched in non-responders and harbored a lower fractions of T-CD8 and plasma B cells, as well as a decreased expression of immunoglobulin genes. In addition we developed a highly predictive score that reflects the Tumor-Immunity Differential (TID) in TME to predict immunotherapy response (AUC=0.88, log-rank tests for PFS P < 0.0001, OS P = 0.01). In addition, among TID-related genes (YWHAE, CXCR6 and BTF3), YWHAE was validated as a robust predictive marker of immunotherapy response in independent cohorts of melanoma and lung cancers based on pre or on-treatment biopsies. These findings provide insights into efficient ICB treatment selection in clinical practice for patients with advanced cancers.

Although the involvement of protein kinase CK2 in cancer is well-documented, there is a need for selective CK2 inhibitors suitable for investigating CK2 specific roles in cancer-related biological pathways and further explore its therapeutic potential. Here we have discovered AB668, a new bivalent inhibitor that binds both at the ATP site and an allosteric αD pocket unique to CK2. The molecule inhibits CK2 activity with an outstanding selectivity over other kinases. Using caspase activation assay, live-cell imaging and transcriptomic analysis, we have compared the effects of this bivalent inhibitor to the non-selective ATP-competitive inhibitor CX-4945 that reached clinic and to the selective ATP-competitive SGC-CK2-1 molecule. Our results show that in contrast to CX-4945 or SGC-CK2-1, AB668 has a distinct mechanism of action regarding its anti-cancer activity, inducing apoptotic cell death and stimulating distinct biological pathways in several cancer cell lines while sparing healthy cells. Our data suggest that targeting a cryptic CK2 αD pocket validates an allosteric approach to targeting CK2 and provides a starting point for creating drug-like CK2 inhibitors for aggressive cancers.

Clear cell Renal Cell Carcinoma (ccRCC) is one of the most prevalent kidney cancers, which is often asymptomatic and thus discovered at a metastatic state (mRCC). mRCC are highly heterogeneous tumors composed of subclonal populations that lead to poor treatment response rate. Several recent works explored the potential of ccRCC tumoroids culture derived from patients. However, these models were produced following a scaffold-based method using collagen I or Matrigel that exhibit lot variability and whose complexity could induce treatment response modifications and phenotypic alterations. Following the observation that ccRCC tumoroids can create their own niche by secreting extracellular matrix components, we developed the first scaffold-free tumoroid model of ccRCC tumors. Tumoroids from mice as well as from human tumors were generated with high success rate (≥90 %) using a magnetic suspension method and standard culture media. Immunofluorescence analysis revealed their self-organization capacities to maintain multiple tumor-resident cell types, including endothelial progenitor cells. Transcriptomic analysis showed the reproducibility of the method highlighting that the majority of gene expression patternswas conserved in tumoroids compared to their matching tumor tissue. Moreover, this model enables to evaluate drug effects and invasiveness of renal cancer cells in a 3D context, providing a robust preclinical tool for drug screening and biomarker assessment in line with alternative ex vivo methods like tumor tissue slice culture or in vivoxenograft models.