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The BCL2 inhibitor venetoclax has revolutionized the treatment of acute myeloid leukemia (AML) patients not benefitting from intensive chemotherapy. Nevertheless, treatment failure remains a challenge, and predictive markers are needed, particularly for relapsed or refractory (R/R) AML. Ex vivo drug sensitivity testing may correlate with outcomes, but its prospective predictive value remains unexplored. Here we report the results of the first stage of the prospective Phase 2 VenEx trial evaluating the utility and predictiveness of venetoclax sensitivity testing using different cell culture conditions and cell viability assays in patients receiving venetoclax-azacitidine (NCT04267081). Participants with de novo AML ineligible for intensive chemotherapy, R/R AML, or secondary AML were included. The primary endpoint was the treatment response in ex vivo sensitive participants and the key secondary endpoints were the correlation of sensitivity with responses and survival. Venetoclax sensitivity testing was successful in 38/39 participants. Experimental conditions significantly influenced predictive accuracy. Blast-specific venetoclax sensitivity measured in conditioned medium most accurately correlated with treatment outcomes; 88% of sensitive participants achieved treatment response. Median survival was significantly longer for ex vivo sensitive participants (14. 6 months for s ensitive, 3. 5 for insensitive, p < 0 . 001). T his analysis illustrates the feasibility of integrating drug-response profiling into clinical practice and demonstrates excellent predictivity.

Treatment of patients with high-grade serous ovarian carcinoma (HGSOC) and triple-negative breast cancer (TNBC) includes platinum-based drugs, gemcitabine, and PARP inhibitors. However, resistance to these therapies develops in most cases, highlighting the need for novel therapeutic approaches and biomarkers to guide the optimal treatment choice. Using a CRISPR loss-of-function screen for carboplatin sensitizers in the HGSOC cell line OVCAR8, we identifiedCSNK2A2, the gene encoding for the alpha’ (α’) catalytic subunit of casein kinase 2 (CK2). Expanding on this finding, we confirmed that the CK2 inhibitors silmitasertib and SGC-CK2-1 sensitized many, but not all, TNBC and HGSOC cell lines to the drugs that perturb DNA replication, including platinum drugs, gemcitabine, and PARP inhibitors. We identified RB1 tumor suppressor deficiency as a prerequisite context for the CK2 inhibition-mediated sensitization to these therapeutics. In RB1-deficient cells, CK2 inhibition resulted in accumulation of cells in S phase of the cell cycle, associated with micronuclei formation, and accelerated PARP inhibitor-induced aneuploidy and mitotic cell death. Patient HGSOC organoids that lacked RB1 expression displayed an enhanced long-term response to carboplatin and PARP inhibitor niraparib when combined with silmitasertib, suggesting RB1-stratified efficacy in patients. As RB1 deficiency affects up to 25% of HGSOC and 40% of TNBC cases, CK2 inhibition, proven safe from previous clinical exploration with silmitasertib, is a promising approach to overcome resistance to standard therapeutics in large strata of patients.

Radiation therapy (RT) increases tumor response to CTLA-4 inhibition (CTLA4i) in mice and in some patients, yet deep responses are rare. This raises the possibility that effector T cells are insufficiently activated by the combination. To address this question we use mouse models of triple negative breast cancer highly resistant to immunotherapy. We find that CTLA4i promotes the expansion of CD4+ T helper cells, whereas RT enhances T cell clonality and enriches for CD8+ T cells with an exhausted phenotype. Combination therapy decreases regulatory CD4+ T cells and increases CD8+ T cells with effector memory, early activation and precursor exhausted phenotype. A combined gene signature comprising these three CD8+ T cell clusters is associated with survival in triple negative breast cancer patients. Despite the expression of multiple immune checkpoints on intratumoral T cells, response to RT+CTLA4i is not increased by targeting additional checkpoints, including PD1. In contrast, agonistic CD40 therapy enhances responses in mice, indicating the need to target different immune compartments to increase responses to combinations of RT and CTLA4i.

Simple Summary New treatments are urgently needed for pancreatic ductal adenocarcinoma because it is one of the most aggressive and lethal cancers, detected too late and resistant to conventional chemotherapy. Tumors in most patients feature a similar set of core mutations but so far it has not been possible to design a one-fits-all treatment strategy. Instead, efforts are underway to personalize the therapies. To find the treatments that might work the best for each patient, entirely new experimental platforms based on living miniature tumors, organoids, have been developed. We review here the latest international findings in designing personalized treatments pancreatic cancer patients using organoids as testing beds. Our own work adds important clues about how such testing could, and perhaps should, be conducted. Pancreatic ductal adenocarcinoma (PDAC) is a silent killer, often diagnosed late. However, it is also dishearteningly resistant to nearly all forms of treatment. New therapies are urgently needed, and with the advent of organoid culture for pancreatic cancer, an increasing number of innovative approaches are being tested. Organoids can be derived within a short enough time window to allow testing of several anticancer agents, which opens up the possibility for functional precision medicine for pancreatic cancer. At the same time, organoid model systems are being refined to better mimic the cancer, for example, by incorporation of components of the tumor microenvironment. We review some of the latest developments in pancreatic cancer organoid research and in novel treatment design. We also summarize our own current experiences with pancreatic cancer organoid drug sensitivity and resistance testing (DSRT) in 14 organoids from 11 PDAC patients. Our data show that it may be necessary to include a cell death read-out in ex vivo DSRT assays, as metabolic viability quantitation does not capture actual organoid killing. We also successfully adapted the organoid platform for drug combination synergy discovery. Lastly, live organoid culture 3D confocal microscopy can help identify individual surviving tumor cells escaping cell death even during harsh combination treatments. Taken together, the organoid technology allows the development of novel precision medicine approaches for PDAC, which paves the way for clinical trials and much needed new treatment options for pancreatic cancer patients.

Therapeutic resistance to kinase inhibitors constitutes a major unresolved clinical challenge in cancer and especially in glioblastoma. Multi-kinase inhibitors may be used for simultaneous targeting of multiple target kinase and thereby potentially overcome kinase inhibitor resistance. However, in most cases identification of the target kinases mediating therapeutic effects of multi-kinase inhibitors has been challenging. To tackle this important problem, we developed an Actionable Targets of Multi-kinase Inhibitors (AToMI) strategy and used it for characterization of glioblastoma target kinases of staurosporine derivatives displaying synergy with protein phosphatase 2A (PP2A) reactivation. AToMI consists of interchangeable modules combining drug-kinase interaction assay, siRNA high-throughput screening, bioinformatics analysis and validation screening with more selective target kinase inhibitors. As a result, AToMI analysis revealed AKT and mitochondrial pyruvate dehydrogenase kinase PDK1 and PDK4 as kinase targets of staurosporine derivatives UCN-01, CEP-701, and K252a that synergized with PP2A activation across heterogeneous glioblastoma cells. Based on these proof-of-principle results we propose that application and further development of AToMI for clinically applicable multi-kinase inhibitors could provide significant benefits in overcoming the challenge of lack of knowledge of target specificity of multi-kinase inhibitors.

Large-scale multiparameter screening has become increasingly feasible and straightforward to perform thanks to developments in technologies such as high-content microscopy and high-throughput flow cytometry. The automated toolkits for analyzing similarities and differences between large numbers of tested conditions have not kept pace with these technological developments. Thus, effective analysis of multiparameter screening datasets becomes a bottleneck and a limiting factor in unbiased interpretation of results. Here we introduce compaRe, a toolkit for large-scale multiparameter data analysis, which integrates quality control, data bias correction, and data visualization methods with a mass-aware gridding algorithm-based similarity analysis providing a much faster and more robust analyses than existing methods. Using mass and flow cytometry data from acute myeloid leukemia and myelodysplastic syndrome patients, we show that compaRe can reveal interpatient heterogeneity and recognizable phenotypic profiles. By applying compaRe to high-throughput flow cytometry drug response data in AML models, we robustly identified multiple types of both deep and subtle phenotypic response patterns, highlighting how this analysis could be used for therapeutic discoveries. In conclusion, compaRe is a toolkit that uniquely allows for automated, rapid, and precise comparisons of large-scale multiparameter datasets, including high-throughput screens.Biology has seen huge advances in technology in recent years. This has led to state-of-the-art techniques which can test hundreds of conditions simultaneously, such as how cancer cells respond to different drugs. In addition to this, each of the tens of thousands of cells studied can be screened for multiple variables, such as certain proteins or genes. This generates massive datasets with large numbers of parameters, which researchers can use to find similarities and differences between the tested conditions. Analyzing these ‘high-throughput’ experiments, however, is no easy task, as the data is often contaminated with meaningless information, or ‘background noise’, as well as sources of bias, such as non-biological variations between experiments. As a result, most analysis methods can only probe one parameter at a time, or are unautomated and require manual interpretation of the data. Here, Chalabi Hajkarim et al. have developed a new toolkit that can analyze multiparameter datasets faster and more robustly than current methods. The kit, which was named ‘compaRe’, combines a range of computational tools that automatically ‘clean’ the data of background noise or bias: the different conditions are then compared and any similarities are visually displayed using a graphical interface that is easy to explore. Chalabi Hajkarim et al. used their new method to study data from patients with acute myeloid leukemia (AML) and myelodysplastic syndrome, two forms of cancer that disrupt the production of functional immune cells. The toolkit was able to identify subtle differences between the patients and categorize them into groups based on the proteins present on immune cells. Chalabi Hajkarim et al. also applied compaRe to high-throughput data on cells from patients and mouse models with AML that had been treated with large numbers of specific drugs. This revealed that different cell types in the samples responded to the treatments in distinct ways. These findings suggest that the toolkit created by Chalabi Hajkarim et al. can automatically, rapidly and precisely compare large multiparameter datasets collected using high-throughput screens. In the future, compaRe could be used to identify drugs that illicit a specific response, or to predict how newly developed treatments impact different cell types in the body.

We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. Significance: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB. See related commentary by Letai, p. 290. This article is highlighted in the In This Issue feature, p. 275

Purpose After some initial setbacks in the 1970s, ceramic implants seem to be a promising alternative to titanium implants. Since the surface of an implant system represents the interface to surrounding biologic structures, the study focuses on cleanliness and surface topography. Clinical documentation of the corresponding systems completes the picture and allows a better evaluation of zirconia implant systems. Materials and methods Five different ceramic implant systems were selected randomly and purchased via blind-shopping: Z5s (Z-Systems), ZiBone (COHO), W implant (TAVDental), ceramic. implant (vitaclinical), and BioWin!/Standard Zirkon Implantat (Champions-Implants/ZV3 system). Three samples of each implant system underwent scanning electron microscopy (SEM) imaging and elemental analysis (EDS). Where appropriate, subsequent Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) was performed to identify the chemical nature of impurities. Surface topography was evaluated, and a search for clinical trials in the PubMed database, on the websites and by written request to each dental implant manufacturer, was performed. Results Surfaces of Champions implants (ZV3) and Z-Systems implants were relatively clean, whereas the other investigated surfaces of vitaclinical, TAV Dental, and ZiBone implants all displayed organic contaminations on their surfaces. Four of the investigated ceramic implants showed a moderately rough implant surface. Only the vitaclinical ceramic.implant had minimal surface roughness. Three ceramic designs-vitaclinical, ZV3, and Z-Systems-had clinical trials documented with up to 3 years of follow-up and results varying between 82.5% and 100% survival. TAV Dental W and ZiBone implant systems lacked properly conducted clinical recording of results. Conclusion The results of this study showed that it is technically possible to produce zirconia implants that are largely residue-free. On the other hand, the variety of significant residues found in this analysis raises concerns, as contamination may lead to undesirable biologic effects. The lack of clinical studies in peer-reviewed journals does not seem to be relevant for the approval of marketing, nor does the lack of surface cleanliness. In the authors' opinion, a critical analysis of these aspects should be included in a more stringent future analysis prior to the marketing of oral implant systems.

The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts.

Accumulating preclinical and clinical evidence indicates that high degrees of heterogeneity among malignant cells constitute a considerable obstacle to the success of cancer therapy. This calls for the development of approaches that operate - or enable established treatments to operate - despite such intratumoral heterogeneity (ITH). In this context, oncolytic peptides stand out as promising therapeutic tools based on their ability to drive immunogenic cell death associated with robust anticancer immune responses independently of ITH. We review the main molecular and immunological pathways engaged by oncolytic peptides, and discuss potential approaches to combine these agents with modern immunotherapeutics in support of superior tumor-targeting immunity and efficacy in patients with cancer.

Cannabis (Cannabis sativa) is a widely used drug in the United States and the frequency of cannabis use is particularly high among people living with HIV (PLWH). One key component of cannabis, the non-psychotropic (−)-cannabidiol (CBD) exerts a wide variety of biological actions, including anticonvulsive, analgesic, and anti-inflammatory effects. However, the exact mechanism of action through which CBD affects the immune cell signaling remains poorly understood. Here we report that CBD modulates type I interferon responses in human macrophages. Transcriptomics analysis shows that CBD treatment significantly attenuates cGAS-STING-mediated activation of type I Interferon response genes (ISGs) in monocytic THP-1 cells. We further showed that CBD treatment effectively attenuates 2’3-cGAMP stimulation of ISGs in both THP-1 cells and primary human macrophages. Interestingly, CBD significantly upregulates expression of autophagy receptor p62/SQSTM1. p62 is critical for autophagy-mediated degradation of stimulated STING. We observed that CBD treated THP-1 cells have elevated autophagy activity. Upon 2’3’-cGAMP stimulation, CBD treated cells have rapid downregulation of phosphorylated-STING, leading to attenuated expression of ISGs. The CBD attenuation of ISGs is reduced in autophagy deficient THP-1 cells, suggesting that the effects of CBD on ISGs is partially mediated by autophagy induction. Lastly, CBD decreases ISGs expression upon HIV infection in THP-1 cells and human primary macrophages, leading to increased HIV RNA expression 24 hours after infection. However, long term culture with CBD in infected primary macrophages reduced HIV viral spread, suggesting potential dichotomous roles of CBD in HIV replication. Our study highlights the immune modulatory effects of CBD and the needs for additional studies on its effect on viral infection and inflammation.