High-throughput combinatorial screening identifies drugs that cooperate with ibrutinib to kill activated B-cell-like diffuse large B-cell lymphoma cells

Venetoclax confers synthetic lethality to chidamide in preclinical models with transformed follicular lymphoma

Transformed follicular lymphoma (t-FL) is an aggressive and heterogeneous hematological malignancy with limited treatment success; the development of novel therapeutic approaches is urgently needed for patients with t-FL. Here, we conducted high-throughput screening (HTS) and in vitro experiments using t-FL cell lines and primary samples to assess the synergistic effects of the histone deacetylase inhibitor chidamide and the BCL-2 inhibitor venetoclax. In vivo efficacy was further tested in xenograft models. The combination of venetoclax and chidamide significantly inhibited cell proliferation, induced apoptosis, and arrested the cell cycle in the G0/G1 phase across multiple t-FL cell lines. Furthermore, the combined therapy effectively reduced tumor burden, extended overall survival in xenograft models, and synergistically targeted patient samples, while sparing normal PBMCs. Mechanistically, this combination disrupted mitochondrial membrane potential and modulated the Wnt signaling pathway, as evidenced by decreased protein expression levels of Wnt3a, Wnt5a/b, β-catenin, and phosphorylated GSK3β. Concurrently, the combined regimen enhanced their respective anticancer effects by inhibiting the key genes HDAC10 and BCL-xL. Taken together, venetoclax combined with chidamide presents a potent anticancer strategy in preclinical models of t-FL and merits further exploration in clinical trials to validate its effectiveness and safety for treating t-FL.

Bruton's tyrosine kinase inhibitor zanubrutinib-based regimens in relapsed/refractory primary diffuse large B-cell lymphoma of the central nervous system

Patients with relapsed/refractory primary central nervous system lymphoma (R/R PCNSL) usually have a poor prognosis and limited treatment options. We respectively reviewed 38 patients with R/R PCNSL treated with zanubrutinib-based regimens in our center. The overall response rate, complete response rate and disease control rate were 76.3%, 47.4% and 92.1%, respectively. The median progression-free survival (PFS) was 31.0 months, the median overall survival (OS) was not reached. Unitivariate analysis by Cox's proportional hazards model revealed that overall response (vs. no response, HR = 0.18, 95%CI:0.07,0.48, p = 0.001), long duration of zanubrutinib (≥6months vs 2-5 months, HR = 0.20, 95%CI:0.06,0.63, p = 0.006) were independent factors for prolonged PFS. The log-rank analysis indicated a prolongation of PFS among patients exhibiting a higher Tumor mutational burden (TMB, ≥14.75muts/Mb) following zanubrutinib-based treatment (p = 0.016). Our data showed promising efficacy with tolerable safety of zanubrutinib-based therapies in patients with R/R PCNSL. Long duration of zanubrutinib may be associated with prolonged PFS.

Bioprinted platform for parallelized screening of engineered microtissues in vivo

Human engineered tissues hold great promise for therapeutic tissue regeneration and repair. Yet, development of these technologies often stalls at the stage of in vivo studies due to the complexity of engineered tissue formulations, which are often composed of diverse cell populations and material elements, along with the tedious nature of in vivo experiments. We introduce a "plug and play" platform called parallelized host apposition for screening tissues in vivo (PHAST). PHAST enables parallelized in vivo testing of 43 three-dimensional microtissues in a single 3D-printed device. Using PHAST, we screen microtissue formations with varying cellular and material components and identify formulations that support vascular graft-host inosculation and engineered liver tissue function in vivo. Our studies reveal that the cellular population(s) that should be included in engineered tissues for optimal in vivo performance is material dependent. PHAST could thus accelerate development of human tissue therapies for clinical regeneration and repair.

AI-driven discovery of synergistic drug combinations against pancreatic cancer

Pancreatic cancer treatment often relies on multi-drug regimens, but optimal combinations remain elusive. This study evaluates predictive approaches to identify synergistic drug combinations using a dataset from the National Center for Advancing Translational Sciences (NCATS). Screening 496 combinations of 32 anticancer compounds against the PANC-1 cells experimentally determined the degree of synergism and antagonism. Three research groups (NCATS, University of North Carolina, and Massachusetts Institute of Technology) leverage these data to apply machine learning (ML) approaches, predicting synergy across 1.6 million combinations. Of the 88 tested, 51 show synergy, with graph convolutional networks achieving the best hit rate and random forest the highest precision. Beyond highlighting the potential of ML, this work delivers 307 experimentally validated synergistic combinations, demonstrating its practical impact in treating pancreatic cancer.

Large-scale human myeloma cell line small molecule compound screen dataset

Multiple myeloma, a hematopoietic malignancy of terminally differentiated B cells, is the second most common hematological malignancy after leukemia. While patients have benefited from numerous advances in treatment in recent years resulting in significant increases to average survival time following diagnosis, myeloma remains incurable and relapse is common. To help identify novel therapeutic agents with efficacy against the disease and to search for biomarkers associated with differential response to treatment, a large-scale pharmacological screen was performed with 1,912 small molecule compounds tested at 11 doses for 47 human myeloma cell lines (HMCL). Raw and processed versions of the drug screen dataset are provided, as well as supportive information including drug and cell line metadata and high-level characterization of the most salient features of each. The dataset is publicly available at Zenodo and the workflow code used for data processing and generation of supporting figures and tables are available on GitHub.

Exploiting the therapeutic vulnerability of IDH-mutant gliomas with zotiraciclib

Isocitrate dehydrogenase (IDH)-mutant gliomas have distinctive metabolic and biological traits that potentially render them susceptible to targeted treatments. Here, by conducting a high-throughput drug screen, we pinpointed a specific vulnerability of IDH-mutant gliomas to zotiraciclib (ZTR). ZTR exhibited selective growth inhibition across multiple IDH-mutant glioma in vitro and in vivo models. Mechanistically, ZTR at low doses suppressed CDK9 and RNA Pol II phosphorylation in IDH-mutant cells, disrupting mitochondrial function and NAD+ production, resulting in oxidative stress. Integrated biochemical profiling of ZTR kinase targets and transcriptomics unveiled that ZTR-induced bioenergetic failure was linked to the suppression of PIM kinase activity. We posit that the combination of mitochondrial dysfunction and an inability to adapt to oxidative stress resulted in significant cell death upon ZTR treatment, ultimately increasing the therapeutic vulnerability of IDH-mutant gliomas. These findings prompted a clinical trial evaluating ZTR in IDH-mutant gliomas (NCT05588141).

Triple Combination of MEK, BET, and CDK Inhibitors Significantly Reduces Human Malignant Peripheral Nerve Sheath Tumors in Mouse Models

PURPOSE

Malignant peripheral nerve sheath tumor (MPNST) is an aggressive soft-tissue sarcoma that develops sporadically or in patients with neurofibromatosis type 1 (NF1). Its development is marked by the inactivation of specific tumor suppressor genes (TSG): NF1, CDKN2A, and SUZ12/EED (polycomb repressor complex 2). Each TSG loss can be targeted by particular drug inhibitors, and we aimed to systematically combine these inhibitors, guided by TSG inactivation status, to test their precision medicine potential for MPNSTs.

EXPERIMENTAL DESIGN

We performed a high-throughput screening in 3 MPNST cell lines testing 14 MEK inhibitors (MEKi), 11 cyclin-dependent kinase 4/6 inhibitors (CDKi), and 3 bromodomain inhibitors (BETi) as single agents and 147 pairwise co-treatments. Best combinations were validated in nine MPNST cell lines, and three were tested in one sporadic and one NF1-associated patient-derived orthotopic xenograft (PDOX) MPNST mouse model. A final combination of the three inhibitor classes was tested in the same PDOX models.

RESULTS

A high degree of redundancy was observed in the effect of compounds of the same inhibitory class, individually or in combination, and responses matched with TSG inactivation status. The MEKi-BETi (ARRY-162 + I-BET151) co-treatment triggered a reduction in half of the NF1-related MPNST PDOXs and all the sporadic tumors, reaching 65% reduction in tumor volume in the latter. Remarkably, this reduction was further increased in both models combining the three inhibitor classes, reaching 85% shrinkage on average in the sporadic MPNST.

CONCLUSIONS

Our results strongly support precision therapies for MPNSTs guided by TSG inactivation status. MEKi-BETi CDKi triple treatment elicits a significant reduction of human MPNST PDOXs.

Prediction of cancer cell line-specific synergistic drug combinations based on multi-omics data

Compared to single-drug therapy, combination therapy involves the use of two or more drugs to reduce drug dosage, decrease drug toxicity, and improve treatment efficacy. We developed an extreme gradient boosting (XGBoost)-based drug-drug cell line prediction model (XDDC) to predict synergistic drug combinations. XDDC was based on XGBoost and used one of the largest drug combination datasets, NCI-ALMANAC. In XDDC, drug chemical structures, adverse drug reactions, and target information were selected as drug features; gene expression, methylation, mutations, copy number variations, and RNA interference data were used as cell line features; and pathway information was incorporated to link drug features and cell line features. XDDC improved the interpretability of drug combination features and outperformed other machine learning methods. It achieved an area under the curve (AUC) of 0.966 ± 0.002 and an AUPR of 0.957 ± 0.002 when cross-validated on NCI-ALMANAC data. Different types of omics data were evaluated and compared in the model. Literature and experimental verification confirmed some of our predictions. XDDC could help medical professionals to rapidly screen synergistic drug combinations against specific cancer cell lines.

High-throughput screening identifies Aurora kinase B as a critical therapeutic target for Merkel cell carcinoma

Merkel cell carcinoma (MCC) is a rare, aggressive skin cancer. Most MCCs contain Merkel cell polyomavirus (virus-positive MCC; VP-MCC), and the remaining are virus-negative (VN-MCC). Immune checkpoint inhibitors are the first-line treatment for metastatic MCC, but durable responses are achieved in less than 50% of patients. To identify new treatments, we screen ~4,000 compounds for their ability to reduce MCC viability and demonstrate that VP-MCC and VN-MCC exhibit distinct response profiles. Aurora kinase inhibitors selectively reduce VP-MCC viability, with RNAi screening independently identifying AURKB as an essential gene for MCC survival, especially in VP-MCC. AZD2811, a selective AURKB inhibitor, induces mitotic dysregulation and apoptosis in MCC cells, with greater efficacy in VP-MCC. In mice, AZD2811 nanoparticles inhibit tumor growth and increase survival in both VP-MCC and VN-MCC xenograft models. Overall, our unbiased screens identify AURKB as a promising therapeutic target and AZD2811NP as a potential treatment for MCC.

Targeting NAD+ Metabolism Vulnerability in FH-Deficient Hereditary Leiomyomatosis and Renal Cell Carcinoma with the Novel NAMPT Inhibitor OT-82

Hereditary leiomyomatosis and renal cell cancer (HLRCC) is an inherited cancer syndrome caused by germline pathogenic variants in the fumarate hydratase (FH) gene. Affected individuals are at risk for developing cutaneous and uterine leiomyomas and aggressive FH-deficient renal cell carcinoma (RCC) with a papillary histology. Due to a disrupted tricarboxylic acid cycle, FH-deficient kidney cancers rely on aerobic glycolysis for energy production, potentially creating compensatory metabolic vulnerabilities. This study conducted a high-throughput drug screen in HLRCC cell lines, which identified a critical dependency on nicotinamide adenine dinucleotide (NAD), a redox cofactor produced by the biosynthetic enzyme nicotinamide phosphoribosyltransferase (NAMPT). Human HLRCC tumors and HLRCC-derived cell lines exhibited elevated NAMPT expression compared with controls. FH-deficient HLRCC cells, but not FH-restored HLRCC or normal kidney cells, were sensitive to NAMPT inhibition. HLRCC cell line viability was significantly decreased in both 2D and 3D in vitro cultures in response to the clinically relevant NAMPT inhibitor OT-82. NAMPT inhibition in vitro significantly decreased the total amount of NAD+, NADH, NADP, NADPH, and poly-ADP-ribose levels, and the effects of NAMPT inhibition could be rescued by the downstream NAD precursor nicotinamide mononucleotide (NMN), confirming the on-target activity of OT-82. Moreover, NAMPT inhibition by OT-82 in two HLRCC xenograft models resulted in severely reduced tumor growth. OT-82 treatment of HLRCC xenograft tumors in vivo inhibited glycolytic flux as demonstrated by reduced lactate/pyruvate ratio in hyperpolarized 13C-pyruvate magnetic resonance spectroscopic imaging experiments. Overall, our data define NAMPT inhibition as a potential therapeutic approach for FH-deficient HLRCC-associated RCC.

T Cells Spatially Regulate B Cell Receptor Signaling in Lymphomas through H3K9me3 Modifications

Activated B cell-like diffuse large B-cell lymphoma (ABC-DLBCL) is a subtype associated with poor survival outcomes. Despite identifying therapeutic targets through molecular characterization, targeted therapies have limited success. New strategies using immune-competent tissue models are needed to understand how DLBCL cells evade treatment. Here, synthetic hydrogel-based lymphoma organoids are used to demonstrate how signals in the lymphoid tumor microenvironment (Ly-TME) can alter B cell receptor (BCR) signaling and specific histone modifications, tri-methylation of histone 3 at lysine 9 (H3K9me3), dampening the effects of BCR pathway inhibition. Using imaging modalities, T cells increase DNA methyltransferase 3A expression and cytoskeleton formation in proximal ABC-DLBCL cells, regulated by H3K9me3. Expansion microscopy on lymphoma organoids reveals T cells increase the size and quantity of segregated H3K9me3 clusters in ABC-DLBCL cells. Findings suggest the re-organization of higher-order chromatin structures that may contribute to evasion or resistance to therapy via the emergence of novel transcriptional states. Treating ABC-DLBCL cells with a G9α histone methyltransferase inhibitor reverses T cell-mediated modulation of H3K9me3 and overcomes T cell-mediated attenuation of treatment response to BCR pathway inhibition. This study emphasizes the Ly-TME's role in altering DLBCL fate and suggests targeting aberrant signaling and microenvironmental cross-talk that can benefit high-risk patients.

Multi-Component, Time-Course screening to develop combination cancer therapies based on synergistic toxicity

Clinical trials in cancer are ideally built on a foundation of sound mechanistic rationale and well-validated drug activity in relevant disease models. The screening of approved and investigational drugs in cell-based phenotypic assays can provide evidence of drug activity, but alternative screening paradigms are needed to develop and optimize multidrug combination regimens. Here, we utilize in vitro screening outcomes across a panel of lymphoma cell lines to dissect the activity of four small-molecule drugs (Venetoclax, Ibrutinib, Prednisolone, and Lenalidomide) currently under investigation within ongoing clinical trials in lymphoma. Data from multiple concentration ranges and time points show that synergistic drug combinations promote apoptosis and cytotoxicity responses at concentrations and time points that are consistent with in vivo drug exposures. To fully map the interaction landscape of these agents in relevant cell models, we developed an in vitro assay format that facilitated time-course evaluations involving concurrent multidrug exposure which further highlighted rapid, synergistic apoptosis induction as a central engine for the activity of this multicomponent targeted therapy. In addition to several instances of exceptional drug+drug synergy, the genetically similar diffuse large B cell lymphoma models also displayed substantial heterogeneity in the degree of synergism between drug pairs. A parallel survey of chemotherapies exhibited limited combination benefit, supporting recent findings that multicomponent chemotherapy outcomes are driven by individual drug activity. Collectively, these data demonstrate how in vitro drug screening data can identify multidrug combinations that exploit drug synergy to overcome the functional diversity of human malignancies.

Drug-Drug Interactions and Synergy: From Pharmacological Models to Clinical Application

This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts, such as concentration-response curves, additive effects, and predictive models, are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. Although various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors, such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care. SIGNIFICANCE STATEMENT: Combining drugs with different mechanisms of action for synergistic interactions optimizes treatment efficacy and safety. Accurate interpretation of synergy requires the identification of the expected additive effect. Despite innovative models to predict the additive effect, consensus in drug-drug interactions research is lacking, hindering the bench-to-bedside development of combination therapies. Collaboration among science, industry, and regulation is crucial for advancing combination therapy development, ensuring rigorous application of predictive models in clinical settings.

High-throughput screening for small-molecule stabilizers of misfolded glucocerebrosidase in Gaucher disease and Parkinson's disease

Glucocerebrosidase (GCase) is implicated in both a rare, monogenic disorder (Gaucher disease, GD) and a common, multifactorial condition (Parkinson's disease, PD); hence, it is an urgent therapeutic target. To identify correctors of severe protein misfolding and trafficking obstruction manifested by the pathogenic L444P-variant of GCase, we developed a suite of quantitative, high-throughput, cell-based assays. First, we labeled GCase with a small proluminescent HiBiT peptide reporter tag, enabling quantitation of protein stabilization in cells while faithfully maintaining target biology. TALEN-based gene editing allowed for stable integration of a single HiBiT-GBA1 transgene into an intragenic safe-harbor locus in GBA1-knockout H4 (neuroglioma) cells. This GD cell model was amenable to lead discovery via titration-based quantitative high-throughput screening and lead optimization via structure-activity relationships. A primary screen of 10,779 compounds from the NCATS bioactive collections identified 140 stabilizers of HiBiT-GCase-L444P, including both pharmacological chaperones (ambroxol and noninhibitory chaperone NCGC326) and proteostasis regulators (panobinostat, trans-ISRIB, and pladienolide B). Two complementary high-content imaging-based assays were deployed to triage hits: The fluorescence-quenched substrate LysoFix-GBA captured functional lysosomal GCase activity, while an immunofluorescence assay featuring antibody hGCase-1/23 directly visualized GCase lysosomal translocation. NCGC326 was active in both secondary assays and completely reversed pathological glucosylsphingosine accumulation. Finally, we tested the concept of combination therapy by demonstrating synergistic actions of NCGC326 with proteostasis regulators in enhancing GCase-L444P levels. Looking forward, these physiologically relevant assays can facilitate the identification, pharmacological validation, and medicinal chemistry optimization of small molecules targeting GCase, ultimately leading to a viable therapeutic for GD and PD.

Towards unbiased interpretations of interactive effects in ecotoxicological studies

Ecotoxicological research has increasingly focused on the interactive effects of chemical mixtures on biological models, emphasising additive, synergistic, or antagonistic interactions. However, these combination studies often test chemicals at unique concentrations (e.g. x:y), limiting our understanding of the effects across the full spectrum of possible combinations. Evidence from human toxicology suggests that interactive effects among chemicals can vary significantly with total concentration (e.g. x:y vs. 2x:2y), their ratio (e.g. x:2y vs. 2x:y), and the magnitude of the tested effect (e.g. LC10vs. LC50). Our non-exhaustive review of studies on binary mixtures in bee ecotoxicology reveals that such parameters are frequently neglected. Of the 60 studies we examined, only two utilised multiple total concentrations and ratios, thus exploring a broad range of possible combinations. In contrast, 26 studies tested only a single concentration of each chemical, resulting in incomplete interpretations of the potential interactive effects. Other studies utilised various concentrations and/or ratios but failed to capture a broad spectrum of possible combinations. We also discuss potential discrepancies in interactive effects based on different metrics and exposure designs. We advocate for future ecotoxicological studies to investigate a wider spectrum of chemical combinations, including various concentrations and ratios, and to address different levels of effects.

Conditional lethality profiling reveals anticancer mechanisms of action and drug-nutrient interactions

Chemical screens across hundreds of cell lines have shown that the drug sensitivities of human cancers can vary by genotype or lineage. However, most drug discovery studies have relied on culture media that poorly reflect metabolite levels in human blood. Here, we perform drug screens in traditional and Human Plasma-Like Medium (HPLM). Sets of compounds that show conditional anticancer activity span different phases of global development and include non-oncology drugs. Comparisons of the synthetic and serum-derived components that comprise typical media trace sets of conditional phenotypes to nucleotide synthesis substrates. We also characterize a unique dual mechanism for brivudine, a compound approved for antiviral use. Brivudine selectively impairs cell growth in low folate conditions by targeting two enzymes involved in one-carbon metabolism. Cataloged gene essentiality data further suggest that conditional phenotypes for other compounds are linked to off-target effects. Our findings establish general strategies for identifying drug-nutrient interactions and mechanisms of action by exploiting conditional lethality in cancer cells.

Challenges and Outlooks in Precision Medicine: Expectations Versus Reality

Recent developments in technology have led to rapid advances in precision medicine, especially due to the rise of next-generation sequencing and molecular profiling. These technological advances have led to rapid advances in research, including increased tumor subtype resolution, new therapeutic agents, and mechanistic insights. Certain therapies have even been approved for molecular biomarkers across histopathological diagnoses; however, translation of research findings to the clinic still faces a number of challenges. In this review, the authors discuss several key challenges to the clinical integration of precision medicine, including the blood-brain barrier, both a lack and excess of molecular targets, and tumor heterogeneity/escape from therapy. They also highlight a few key efforts to address these challenges, including new frontiers in drug delivery, a rapidly expanding treatment repertoire, and improvements in active response monitoring. With continued improvements and developments, the authors anticipate that precision medicine will increasingly become the gold standard for clinical care.

Deep PIM kinase substrate profiling reveals new rational cotherapeutic strategies for acute myeloid leukemia

ABSTRACT

Provirus integration site for Moloney murine leukemia virus (PIM) family serine/threonine kinases perform protumorigenic functions in hematologic malignancies and solid tumors by phosphorylating substrates involved in tumor metabolism, cell survival, metastasis, inflammation, and immune cell invasion. However, a comprehensive understanding of PIM kinase functions is currently lacking. Multiple small-molecule PIM kinase inhibitors are currently being evaluated as cotherapeutics in patients with cancer. To further illuminate PIM kinase functions in cancer, we deeply profiled PIM1 substrates using the reverse in-gel kinase assay to identify downstream cellular processes targetable with small molecules. Pathway analyses of putative PIM substrates nominated RNA splicing and ribosomal RNA (rRNA) processing as PIM-regulated cellular processes. PIM inhibition elicited reproducible splicing changes in PIM-inhibitor-responsive acute myeloid leukemia (AML) cell lines. PIM inhibitors synergized with splicing modulators targeting splicing factor 3b subunit 1 (SF3B1) and serine-arginine protein kinase 1 (SRPK1) to kill AML cells. PIM inhibition also altered rRNA processing, and PIM inhibitors synergized with an RNA polymerase I inhibitor to kill AML cells and block AML tumor growth. These data demonstrate that deep kinase substrate knowledge can illuminate unappreciated kinase functions, nominating synergistic cotherapeutic strategies. This approach may expand the cotherapeutic armamentarium to overcome kinase inhibitor-resistant disease that limits durable responses in malignant disease.

IRF4 requires ARID1A to establish plasma cell identity in multiple myeloma

Multiple myeloma (MM) is an incurable plasma cell malignancy that exploits transcriptional networks driven by IRF4. We employ a multi-omics approach to discover IRF4 vulnerabilities, integrating functional genomics screening, spatial proteomics, and global chromatin mapping. ARID1A, a member of the SWI/SNF chromatin remodeling complex, is required for IRF4 expression and functionally associates with IRF4 protein on chromatin. Deleting Arid1a in activated murine B cells disrupts IRF4-dependent transcriptional networks and blocks plasma cell differentiation. Targeting SWI/SNF activity leads to rapid loss of IRF4-target gene expression and quenches global amplification of oncogenic gene expression by MYC, resulting in profound toxicity to MM cells. Notably, MM patients with aggressive disease bear the signature of SWI/SNF activity, and SMARCA2/4 inhibitors remain effective in immunomodulatory drug (IMiD)-resistant MM cells. Moreover, combinations of SWI/SNF and MEK inhibitors demonstrate synergistic toxicity to MM cells, providing a promising strategy for relapsed/refractory disease.

Combination Targeted Therapy in Relapsed Diffuse Large B-Cell Lymphoma

BACKGROUND

The identification of oncogenic mutations in diffuse large B-cell lymphoma (DLBCL) has led to the development of drugs that target essential survival pathways, but whether targeting multiple survival pathways may be curative in DLBCL is unknown.

METHODS

We performed a single-center, phase 1b-2 study of a regimen of venetoclax, ibrutinib, prednisone, obinutuzumab, and lenalidomide (ViPOR) in relapsed or refractory DLBCL. In phase 1b, which included patients with DLBCL and indolent lymphomas, four dose levels of venetoclax were evaluated to identify the recommended phase 2 dose, with fixed doses of the other four drugs. A phase 2 expansion in patients with germinal-center B-cell (GCB) and non-GCB DLBCL was performed. ViPOR was administered every 21 days for six cycles.

RESULTS

In phase 1b of the study, involving 20 patients (10 with DLBCL), a single dose-limiting toxic effect of grade 3 intracranial hemorrhage occurred, a result that established venetoclax at a dose of 800 mg as the recommended phase 2 dose. Phase 2 included 40 patients with DLBCL. Toxic effects that were observed among all the patients included grade 3 or 4 neutropenia (in 24% of the cycles), thrombocytopenia (in 23%), anemia (in 7%), and febrile neutropenia (in 1%). Objective responses occurred in 54% of 48 evaluable patients with DLBCL, and complete responses occurred in 38%; complete responses were exclusively in patients with non-GCB DLBCL and high-grade B-cell lymphoma with rearrangements of MYC and BCL2 or BCL6 (or both). Circulating tumor DNA was undetectable in 33% of the patients at the end of ViPOR therapy. With a median follow-up of 40 months, 2-year progression-free survival and overall survival were 34% (95% confidence interval [CI], 21 to 47) and 36% (95% CI, 23 to 49), respectively.

CONCLUSIONS

Treatment with ViPOR was associated with durable remissions in patients with specific molecular DLBCL subtypes and was associated with mainly reversible adverse events. (Funded by the Intramural Research Program of the National Cancer Institute and the National Center for Advancing Translational Sciences of the National Institutes of Health and others; ClinicalTrials.gov number, NCT03223610.).

Molecular targets of glucocorticoids that elucidate their therapeutic efficacy in aggressive lymphomas

Glucocorticoids have been used for decades to treat lymphomas without an established mechanism of action. Using functional genomic, proteomic, and chemical screens, we discover that glucocorticoids inhibit oncogenic signaling by the B cell receptor (BCR), a recurrent feature of aggressive B cell malignancies, including diffuse large B cell lymphoma and Burkitt lymphoma. Glucocorticoids induce the glucocorticoid receptor (GR) to directly transactivate genes encoding negative regulators of BCR stability (LAPTM5; KLHL14) and the PI3 kinase pathway (INPP5D; DDIT4). GR directly represses transcription of CSK, a kinase that limits the activity of BCR-proximal Src-family kinases. CSK inhibition attenuates the constitutive BCR signaling of lymphomas by hyperactivating Src-family kinases, triggering their ubiquitination and degradation. With the knowledge that glucocorticoids disable oncogenic BCR signaling, they can now be deployed rationally to treat BCR-dependent aggressive lymphomas and used to construct mechanistically sound combination regimens with inhibitors of BTK, PI3 kinase, BCL2, and CSK.

Development of quantitative high-throughput screening assays to identify, validate, and optimize small-molecule stabilizers of misfolded β-glucocerebrosidase with therapeutic potential for Gaucher disease and Parkinson's disease

Glucocerebrosidase (GCase) is implicated in both a rare, monogenic disorder (Gaucher disease, GD) and a common, multifactorial condition (Parkinson's disease); hence, it is an urgent therapeutic target. To identify correctors of severe protein misfolding and trafficking obstruction manifested by the pathogenic L444P-variant of GCase, we developed a suite of quantitative, high-throughput, cell-based assays. First, we labeled GCase with a small pro-luminescent HiBiT peptide reporter tag, enabling quantitation of protein stabilization in cells while faithfully maintaining target biology. TALEN-based gene editing allowed for stable integration of a single HiBiT-GBA1 transgene into an intragenic safe-harbor locus in GBA1-knockout H4 (neuroglioma) cells. This GD cell model was amenable to lead discovery via titration-based quantitative high-throughput screening and lead optimization via structure-activity relationships. A primary screen of 10,779 compounds from the NCATS bioactive collections identified 140 stabilizers of HiBiT-GCase-L444P, including both pharmacological chaperones (ambroxol and non-inhibitory chaperone NCGC326) and proteostasis regulators (panobinostat, trans-ISRIB, and pladienolide B). Two complementary high-content imaging-based assays were deployed to triage hits: the fluorescence-quenched substrate LysoFix-GBA captured functional lysosomal GCase activity, while an immunofluorescence assay featuring antibody hGCase-1/23 provided direct visualization of GCase lysosomal translocation. NCGC326 was active in both secondary assays and completely reversed pathological glucosylsphingosine accumulation. Finally, we tested the concept of combination therapy, by demonstrating synergistic actions of NCGC326 with proteostasis regulators in enhancing GCase-L444P levels. Looking forward, these physiologically-relevant assays can facilitate the identification, pharmacological validation, and medicinal chemistry optimization of new chemical matter targeting GCase, ultimately leading to a viable therapeutic for two protein-misfolding diseases.

Activity of the Ubiquitin-activating Enzyme Inhibitor TAK-243 in Adrenocortical Carcinoma Cell Lines, Patient-derived Organoids, and Murine Xenografts

Current treatment options for metastatic adrenocortical carcinoma (ACC) have limited efficacy, despite the common use of mitotane and cytotoxic agents. This study aimed to identify novel therapeutic options for ACC. An extensive drug screen was conducted to identify compounds with potential activity against ACC cell lines. We further investigated the mechanism of action of the identified compound, TAK-243, its synergistic effects with current ACC therapeutics, and its efficacy in ACC models including patient-derived organoids and mouse xenografts. TAK-243, a clinical ubiquitin-activating enzyme (UAE) inhibitor, showed potent activity in ACC cell lines. TAK-243 inhibited protein ubiquitination in ACC cells, leading to the accumulation of free ubiquitin, activation of the unfolded protein response, and induction of apoptosis. TAK-243 was found to be effluxed out of cells by MDR1, a drug efflux pump, and did not require Schlafen 11 (SLFN11) expression for its activity. Combination of TAK-243 with current ACC therapies (e.g., mitotane, etoposide, cisplatin) produced synergistic or additive effects. In addition, TAK-243 was highly synergistic with BCL2 inhibitors (Navitoclax and Venetoclax) in preclinical ACC models including patient-derived organoids. The tumor suppressive effects of TAK-243 and its synergistic effects with Venetoclax were further confirmed in a mouse xenograft model. These findings provide preclinical evidence to support the initiation of a clinical trial of TAK-243 in patients with advanced-stage ACC. TAK-243 is a promising potential treatment option for ACC, either as monotherapy or in combination with existing therapies or BCL2 inhibitors.

SIGNIFICANCE

ACC is a rare endocrine cancer with poor prognosis and limited therapeutic options. We report that TAK-243 is active alone and in combination with currently used therapies and with BCL2 and mTOR inhibitors in ACC preclinical models. Our results suggest implementation of TAK-243 in clinical trials for patients with advanced and metastatic ACC.

Response to Bruton's tyrosine kinase inhibitors in aggressive lymphomas linked to chronic selective autophagy

Diffuse large B cell lymphoma (DLBCL) is an aggressive, profoundly heterogeneous cancer, presenting a challenge for precision medicine. Bruton's tyrosine kinase (BTK) inhibitors block B cell receptor (BCR) signaling and are particularly effective in certain molecular subtypes of DLBCL that rely on chronic active BCR signaling to promote oncogenic NF-κB. The MCD genetic subtype, which often acquires mutations in the BCR subunit, CD79B, and in the innate immune adapter, MYD88L265P, typically resists chemotherapy but responds exceptionally to BTK inhibitors. However, the underlying mechanisms of response to BTK inhibitors are poorly understood. Herein, we find a non-canonical form of chronic selective autophagy in MCD DLBCL that targets ubiquitinated MYD88L265P for degradation in a TBK1-dependent manner. MCD tumors acquire genetic and epigenetic alterations that attenuate this autophagic tumor suppressive pathway. In contrast, BTK inhibitors promote autophagic degradation of MYD88L265P, thus explaining their exceptional clinical benefit in MCD DLBCL.

Exploiting the therapeutic vulnerability of IDH-mutant gliomas with zotiraciclib

Isocitrate dehydrogenase (IDH)-mutant gliomas have distinctive metabolic and biological traits that may render them susceptible to targeted treatments. Here, by conducting a high-throughput drug screen, we pinpointed a specific susceptibility of IDH-mutant gliomas to zotiraciclib (ZTR). ZTR exhibited selective growth inhibition across multiple IDH-mutant glioma in vitro and in vivo models. Mechanistically, ZTR at low doses suppressed CDK9 and RNA Pol II phosphorylation in IDH-mutant cells, disrupting mitochondrial function and NAD+ production, causing oxidative stress. Integrated biochemical profiling of ZTR kinase targets and transcriptomics unveiled that ZTR-induced bioenergetic failure was linked to the suppression of PIM kinase activity. We posit that the combination of mitochondrial dysfunction and an inability to adapt to oxidative stress resulted in significant cell death upon ZTR treatment, ultimately increasing the therapeutic vulnerability of IDH-mutant gliomas. These findings prompted a clinical trial evaluating ZTR in IDH-mutant gliomas towards precision medicine ( NCT05588141 ).

Highlights

Zotiraciclib (ZTR), a CDK9 inhibitor, hinders IDH-mutant glioma growth in vitro and in vivo . ZTR halts cell cycle, disrupts respiration, and induces oxidative stress in IDH-mutant cells.ZTR unexpectedly inhibits PIM kinases, impacting mitochondria and causing bioenergetic failure.These findings led to the clinical trial NCT05588141, evaluating ZTR for IDH-mutant gliomas.

Drug Responses in Plexiform Neurofibroma Type I (PNF1) Cell Lines Using High-Throughput Data and Combined Effectiveness and Potency

Background: Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by heterozygous germline NF1 gene mutations that predispose patients to developing plexiform neurofibromas, which are benign but often disfiguring tumors of the peripheral nerve sheath induced by loss of heterozygosity at the NF1 locus. These can progress to malignant peripheral nerve sheath tumors (MPNSTs). There are no approved drug treatments for adults with NF1-related inoperable plexiform neurofibromas, and only one drug (selumetinib), which is an FDA-approved targeted therapy for the treatment of symptomatic pediatric plexiform neurofibromas, highlighting the need for additional drug screening and development. In high-throughput screening, the effectiveness of drugs against cell lines is often assessed by measuring in vitro potency (AC50) or the area under the curve (AUC). However, the variability of dose-response curves across drugs and cell lines and the frequency of partial effectiveness suggest that these measures alone fail to provide a full picture of overall efficacy. Methods: Using concentration-response data, we combined response effectiveness (EFF) and potency (AC50) into (a) a score characterizing the effect of a compound on a single cell line, S = log[EFF/AC50], and (b) a relative score, ΔS, characterizing the relative difference between a reference (e.g., non-tumor) and test (tumor) cell line. ΔS was applied to data from high-throughput screening (HTS) of a drug panel tested on NF1-/- tumor cells, using immortalized non-tumor NF1+/- cells as a reference. Results: We identified drugs with sensitivity, targeting expected pathways, such as MAPK-ERK and PI3K-AKT, as well as serotonin-related targets, among others. The ΔS technique used here, in tandem with a supplemental ΔS web tool, simplifies HTS analysis and may provide a springboard for further investigations into drug response in NF1-related cancers. The tool may also prove useful for drug development in a variety of other cancers.

Birinapant selectively enhances immunotoxin-mediated killing of cancer cells conditional on the IAP protein levels within target cells

Immunotoxins (ITs) target cancer cells via antibody binding to surface antigens followed by internalization and toxin-mediated inhibition of protein synthesis. The fate of cells responding to IT treatment depends on the amount and stability of specific pro-apoptotic and pro-survival proteins. When treated with a pseudomonas exotoxin-based immunotoxin (HB21PE40), the triple-negative breast cancer (TNBC) cell line MDA-MB-468 displayed a notable resistance to toxin-mediated killing compared to the epidermoid carcinoma cell line, A431, despite succumbing to the same level of protein synthesis inhibition. In a combination screen of ~1912 clinically relevant and mechanistically annotated compounds, we identified several agents that greatly enhanced IT-mediated killing of MDA-MB-468 cells while exhibiting only a modest enhancement for A431 cells. Of interest, two Smac mimetics, birinapant and SM164, exhibited this kind of differential enhancement. To investigate the basis for this, we probed cells for the presence of inhibitor of apoptosis (IAP) proteins and monitored their stability after the addition of immunotoxin. We found that high levels of IAPs inhibited immunotoxin-mediated cell death. Further, TNFα levels were not relevant for the combination's efficacy. In tumor xenograft studies, combinations of immunotoxin and birinapant caused complete regressions in MDA-MB-468tumor-bearing mice but not in mice with A431 tumors. We propose that IAPs constitute a barrier to immunotoxin efficacy which can be overcome with combination treatments that include Smac mimetics.

Phenotype plasticity and altered sensitivity to chemotherapeutic agents in aggressive prostate cancer cells

In 2023, approximately 288,300 new diagnoses of prostate cancer will occur, with 34,700 disease-related deaths. Death from prostate cancer is associated with metastasis, enabled by progression of tumor phenotypes and successful extracapsular extension to reach Batson's venous plexus, a specific route to the spine and brain. Using a mouse-human tumor xenograft model, we isolated an aggressive muscle invasive cell population of prostate cancer, called DU145J7 with a distinct biophysical phenotype, elevated histone H3K27, and increased matrix metalloproteinase 14 expression as compared to the non-aggressive parent cell population called DU145WT. Our goal was to determine the sensitivities to known chemotherapeutic agents of the aggressive cells as compared to the parent population. High-throughput screening was performed with 5,578 compounds, comprising of approved and investigational drugs for oncology. Eleven compounds were selected for additional testing, which revealed that vorinostat, 5-azacitidine, and fimepinostat (epigenetic inhibitors) showed 2.6-to-7.5-fold increases in lethality for the aggressive prostate cancer cell population as compared to the parent, as judged by the concentration of drug to inhibit 50% cell growth (IC50). On the other hand, the DU145J7 cells were 2.2-to-4.0-fold resistant to mitoxantrone, daunorubicin, and gimatecan (topoisomerase inhibitors) as compared to DU145WT. No differences in sensitivities between cell populations were found for docetaxel or pirarubicin. The increased sensitivity of DU145J7 prostate cancer cells to chromatin modifying agents suggests a therapeutic vulnerability occurs after tumor cells invade into and through muscle. Future work will determine which epigenetic modifiers and what combinations will be most effective to eradicate early aggressive tumor populations.

Breast Cancer Mutations HER2V777L and PIK3CAH1047R Activate the p21-CDK4/6-Cyclin D1 Axis to Drive Tumorigenesis and Drug Resistance

In metastatic breast cancer, HER2-activating mutations frequently co-occur with mutations in PIK3CA, TP53, or CDH1. Of these co-occurring mutations, HER2 and PIK3CA are the most commonly comutated gene pair, with approximately 40% of HER2-mutated breast cancers also having activating mutations in PIK3CA. To study the effects of co-occurring HER2 and PIK3CA mutations, we generated genetically engineered mice with the HER2V777L; PIK3CAH1047R transgenes (HP mice) and studied the resulting breast cancers both in vivo as well as ex vivo using cancer organoids. HP breast cancers showed accelerated tumor formation in vivo and increased invasion and migration in in vitro assays. HP breast cancer cells were resistant to the pan-HER tyrosine kinase inhibitor, neratinib, but were effectively treated with neratinib plus the HER2-targeted antibody-drug conjugate trastuzumab deruxtecan. Proteomic and RNA-seq analysis of HP breast cancers identified increased gene expression of cyclin D1 and p21WAF1/Cip1 and changes in cell-cycle markers. Combining neratinib with CDK4/6 inhibitors was another effective strategy for treating HP breast cancers, with neratinib plus palbociclib showing a statistically significant reduction in development of mouse HP tumors as compared to either drug alone. The efficacy of both the neratinib plus trastuzumab deruxtecan and neratinib plus palbociclib combinations was validated using a human breast cancer patient-derived xenograft with very similar HER2 and PIK3CA mutations to the HP mice. Further, these two drug combinations effectively treated spontaneous lung metastasis in syngeneic mice transplanted with HP breast cancer organoids. This study provides valuable preclinical data to support the ongoing phase 1 clinical trials of these drug combinations in breast cancer.

SIGNIFICANCE

In HER2-mutated breast cancer, PIK3CA mutation activates p21-CDK4/6-cyclin D1 signaling to drive resistance to HER2-targeted therapies, which can be overcome using CDK4/6 inhibitors.

Interpreting the Mechanism of Synergism for Drug Combinations Using Attention-Based Hierarchical Graph Pooling

Synergistic drug combinations provide huge potentials to enhance therapeutic efficacy and to reduce adverse reactions. However, effective and synergistic drug combination prediction remains an open question because of the unknown causal disease signaling pathways. Though various deep learning (AI) models have been proposed to quantitatively predict the synergism of drug combinations, the major limitation of existing deep learning methods is that they are inherently not interpretable, which makes the conclusions of AI models untransparent to human experts, henceforth limiting the robustness of the model conclusion and the implementation ability of these models in real-world human-AI healthcare. In this paper, we develop an interpretable graph neural network (GNN) that reveals the underlying essential therapeutic targets and the mechanism of the synergy (MoS) by mining the sub-molecular network of great importance. The key point of the interpretable GNN prediction model is a novel graph pooling layer, a self-attention-based node and edge pool (henceforth SANEpool), that can compute the attention score (importance) of genes and connections based on the genomic features and topology. As such, the proposed GNN model provides a systematic way to predict and interpret the drug combination synergism based on the detected crucial sub-molecular network. Experiments on various well-adopted drug-synergy-prediction datasets demonstrate that (1) the SANEpool model has superior predictive ability to generate accurate synergy score prediction, and (2) the sub-molecular networks detected by the SANEpool are self-explainable and salient for identifying synergistic drug combinations.

Targeting N-linked Glycosylation for the Therapy of Aggressive Lymphomas

Diffuse large B-cell lymphoma (DLBCL) can be subdivided into the activated B-cell (ABC) and germinal center B cell-like (GCB) subtypes. Self-antigen engagement of B-cell receptors (BCR) in ABC tumors induces their clustering, thereby initiating chronic active signaling and activation of NF-κB and PI3 kinase. Constitutive BCR signaling is essential in some GCB tumors but primarily activates PI3 kinase. We devised genome-wide CRISPR-Cas9 screens to identify regulators of IRF4, a direct transcriptional target of NF-κB and an indicator of proximal BCR signaling in ABC DLBCL. Unexpectedly, inactivation of N-linked protein glycosylation by the oligosaccharyltransferase-B (OST-B) complex reduced IRF4 expression. OST-B inhibition of BCR glycosylation reduced BCR clustering and internalization while promoting its association with CD22, which attenuated PI3 kinase and NF-κB activation. By directly interfering with proximal BCR signaling, OST-B inactivation killed models of ABC and GCB DLBCL, supporting the development of selective OST-B inhibitors for the treatment of these aggressive cancers.

SIGNIFICANCE

DLBCL depends on constitutive BCR activation and signaling. There are currently no therapeutics that target the BCR directly and attenuate its pathologic signaling. Here, we unraveled a therapeutically exploitable, OST-B-dependent glycosylation pathway that drives BCR organization and proximal BCR signaling. This article is highlighted in the In This Issue feature, p. 1749.

High-throughput screening identifies cell cycle-associated signaling cascades that regulate a multienzyme glucosome assembly in human cells

We have previously demonstrated that human liver-type phosphofructokinase 1 (PFK1) recruits other rate-determining enzymes in glucose metabolism to organize multienzyme metabolic assemblies, termed glucosomes, in human cells. However, it has remained largely elusive how glucosomes are reversibly assembled and disassembled to functionally regulate glucose metabolism and thus contribute to human cell biology. We developed a high-content quantitative high-throughput screening (qHTS) assay to identify regulatory mechanisms that control PFK1-mediated glucosome assemblies from stably transfected HeLa Tet-On cells. Initial qHTS with a library of pharmacologically active compounds directed following efforts to kinase-inhibitor enriched collections. Consequently, three compounds that were known to inhibit cyclin-dependent kinase 2, ribosomal protein S6 kinase and Aurora kinase A, respectively, were identified and further validated under high-resolution fluorescence single-cell microscopy. Subsequent knockdown studies using small-hairpin RNAs further confirmed an active role of Aurora kinase A on the formation of PFK1 assemblies in HeLa cells. Importantly, all the identified protein kinases here have been investigated as key signaling nodes of one specific cascade that controls cell cycle progression in human cells. Collectively, our qHTS approaches unravel a cell cycle-associated signaling network that regulates the formation of PFK1-mediated glucosome assembly in human cells.

Drug combinations identified by high-throughput screening promote cell cycle transition and upregulate Smad pathways in myeloma

Drug resistance and disease progression are common in multiple myeloma (MM) patients, underscoring the need for new therapeutic combinations. A high-throughput drug screen in 47 MM cell lines and in silico Huber robust regression analysis of drug responses revealed 43 potentially synergistic combinations. We hypothesized that effective combinations would reduce MYC expression and enhance p16 activity. Six combinations cooperatively reduced MYC protein, frequently over-expressed in MM and also cooperatively increased p16 expression, frequently downregulated in MM. Synergistic reductions in viability were observed with top combinations in proteasome inhibitor-resistant and sensitive MM cell lines, while sparing fibroblasts. Three combinations significantly prolonged survival in a transplantable Ras-driven allograft model of advanced MM closely recapitulating high-risk/refractory myeloma in humans and reduced viability of ex vivo treated patient cells. Common genetic pathways similarly downregulated by these combinations promoted cell cycle transition, whereas pathways most upregulated were involved in TGFβ/SMAD signaling. These preclinical data identify potentially useful drug combinations for evaluation in drug-resistant MM and reveal potential mechanisms of combined drug sensitivity.

Multiple therapeutic approaches of glioblastoma multiforme: From terminal to therapy

Glioblastoma multiforme (GBM) is an aggressive brain cancer showing poor prognosis. Currently, treatment methods of GBM are limited with adverse outcomes and low survival rate. Thus, advancements in the treatment of GBM are of utmost importance, which can be achieved in recent decades. However, despite aggressive initial treatment, most patients develop recurrent diseases, and the overall survival rate of patients is impossible to achieve. Currently, researchers across the globe target signaling events along with tumor microenvironment (TME) through different drug molecules to inhibit the progression of GBM, but clinically they failed to demonstrate much success. Herein, we discuss the therapeutic targets and signaling cascades along with the role of the organoids model in GBM research. Moreover, we systematically review the traditional and emerging therapeutic strategies in GBM. In addition, we discuss the implications of nanotechnologies, AI, and combinatorial approach to enhance GBM therapeutics.

CellMinerCDB: NCATS Is a Web-Based Portal Integrating Public Cancer Cell Line Databases for Pharmacogenomic Explorations

Major advances have been made in the field of precision medicine for treating cancer. However, many open questions remain that need to be answered to realize the goal of matching every patient with cancer to the most efficacious therapy. To facilitate these efforts, we have developed CellMinerCDB: National Center for Advancing Translational Sciences (NCATS; https://discover.nci.nih.gov/rsconnect/cellminercdb_ncats/), which makes available activity information for 2,675 drugs and compounds, including multiple nononcology drugs and 1,866 drugs and compounds unique to the NCATS. CellMinerCDB: NCATS comprises 183 cancer cell lines, with 72 unique to NCATS, including some from previously understudied tissues of origin. Multiple forms of data from different institutes are integrated, including single and combination drug activity, DNA copy number, methylation and mutation, transcriptome, protein levels, histone acetylation and methylation, metabolites, CRISPR, and miscellaneous signatures. Curation of cell lines and drug names enables cross-database (CDB) analyses. Comparison of the datasets is made possible by the overlap between cell lines and drugs across databases. Multiple univariate and multivariate analysis tools are built-in, including linear regression and LASSO. Examples have been presented here for the clinical topoisomerase I (TOP1) inhibitors topotecan and irinotecan/SN-38. This web application provides both substantial new data and significant pharmacogenomic integration, allowing exploration of interrelationships.

SIGNIFICANCE

CellMinerCDB: NCATS provides activity information for 2,675 drugs in 183 cancer cell lines and analysis tools to facilitate pharmacogenomic research and to identify determinants of response.

Conditional lethality profiling reveals anticancer mechanisms of action and drug-nutrient interactions

Chemical screening studies have identified drug sensitivities across hundreds of cancer cell lines but most putative therapeutics fail to translate. Discovery and development of drug candidates in models that more accurately reflect nutrient availability in human biofluids may help in addressing this major challenge. Here we performed high-throughput screens in conventional versus Human Plasma-Like Medium (HPLM). Sets of conditional anticancer compounds span phases of clinical development and include non-oncology drugs. Among these, we characterize a unique dual-mechanism of action for brivudine, an agent otherwise approved for antiviral treatment. Using an integrative approach, we find that brivudine affects two independent targets in folate metabolism. We also traced conditional phenotypes for several drugs to the availability of nucleotide salvage pathway substrates and verified others for compounds that seemingly elicit off-target anticancer effects. Our findings establish generalizable strategies for exploiting conditional lethality in HPLM to reveal therapeutic candidates and mechanisms of action.

High-throughput approaches to uncover synergistic drug combinations in leukemia

We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

The recent progress of deep-learning-based in silico prediction of drug combination

Drug combination therapy has become a common strategy for the treatment of complex diseases. There is an urgent need for computational methods to efficiently identify appropriate drug combinations owing to the high cost of experimental screening. In recent years, deep learning has been widely used in the field of drug discovery. Here, we provide a comprehensive review on deep-learning-based drug combination prediction algorithms from multiple aspects. Current studies highlight the flexibility of this technology in integrating multimodal data and the ability to achieve state-of-art performance; it is expected that deep-learning-based prediction of drug combinations should play an important part in future drug discovery.

High-throughput and targeted drug screens identify pharmacological candidates against MiT-translocation renal cell carcinoma

BACKGROUND

MiT-Renal Cell Carcinoma (RCC) is characterized by genomic translocations involving microphthalmia-associated transcription factor (MiT) family members TFE3, TFEB, or MITF. MiT-RCC represents a specific subtype of sporadic RCC that is predominantly seen in young patients and can present with heterogeneous histological features making diagnosis challenging. Moreover, the disease biology of this aggressive cancer is poorly understood and there is no accepted standard of care therapy for patients with advanced disease. Tumor-derived cell lines have been established from human TFE3-RCC providing useful models for preclinical studies.

METHODS

TFE3-RCC tumor derived cell lines and their tissues of origin were characterized by IHC and gene expression analyses. An unbiased high-throughput drug screen was performed to identify novel therapeutic agents for treatment of MiT-RCC. Potential therapeutic candidates were validated in in vitro and in vivo preclinical studies. Mechanistic assays were conducted to confirm the on-target effects of drugs.

RESULTS

The results of a high-throughput small molecule drug screen utilizing three TFE3-RCC tumor-derived cell lines identified five classes of agents with potential pharmacological efficacy, including inhibitors of phosphoinositide-3-kinase (PI3K) and mechanistic target of rapamycin (mTOR), and several additional agents, including the transcription inhibitor Mithramycin A. Upregulation of the cell surface marker GPNMB, a specific MiT transcriptional target, was confirmed in TFE3-RCC and evaluated as a therapeutic target using the GPNMB-targeted antibody-drug conjugate CDX-011. In vitro and in vivo preclinical studies demonstrated efficacy of the PI3K/mTOR inhibitor NVP-BGT226, Mithramycin A, and CDX-011 as potential therapeutic options for treating advanced MiT-RCC as single agents or in combination.

CONCLUSIONS

The results of the high-throughput drug screen and validation studies in TFE3-RCC tumor-derived cell lines have provided in vitro and in vivo preclinical data supporting the efficacy of the PI3K/mTOR inhibitor NVP-BGT226, the transcription inhibitor Mithramycin A, and GPNMB-targeted antibody-drug conjugate CDX-011 as potential therapeutic options for treating advanced MiT-RCC. The findings presented here should provide the basis for designing future clinical trials for patients with MiT-driven RCC.

Highly Parallel Tissue Grafting for Combinatorial In Vivo Screening

Material- and cell-based technologies such as engineered tissues hold great promise as human therapies. Yet, the development of many of these technologies becomes stalled at the stage of pre-clinical animal studies due to the tedious and low-throughput nature of in vivo implantation experiments. We introduce a 'plug and play' in vivo screening array platform called Highly Parallel Tissue Grafting (HPTG). HPTG enables parallelized in vivo screening of 43 three-dimensional microtissues within a single 3D printed device. Using HPTG, we screen microtissue formations with varying cellular and material components and identify formulations that support vascular self-assembly, integration and tissue function. Our studies highlight the importance of combinatorial studies that vary cellular and material formulation variables concomitantly, by revealing that inclusion of stromal cells can "rescue" vascular self-assembly in manner that is material-dependent. HPTG provides a route for accelerating pre-clinical progress for diverse medical applications including tissue therapy, cancer biomedicine, and regenerative medicine.

mTOR inhibition overcomes RSK3-mediated resistance to BET inhibitors in small cell lung cancer

Small cell lung cancer (SCLC) is a recalcitrant malignancy with limited treatment options. Bromodomain and extraterminal domain inhibitors (BETis) have shown promising preclinical activity in SCLC, but the broad sensitivity spectrum limits their clinical prospects. Here, we performed unbiased high-throughput drug combination screens to identify therapeutics that could augment the antitumor activities of BETis in SCLC. We found that multiple drugs targeting the PI-3K-AKT-mTOR pathway synergize with BETis, among which mTOR inhibitors (mTORis) show the highest synergy. Using various molecular subtypes of the xenograft models derived from patients with SCLC, we confirmed that mTOR inhibition potentiates the antitumor activities of BETis in vivo without substantially increasing toxicity. Furthermore, BETis induce apoptosis in both in vitro and in vivo SCLC models, and this antitumor effect is further amplified by combining mTOR inhibition. Mechanistically, BETis induce apoptosis in SCLC by activating the intrinsic apoptotic pathway. However, BET inhibition leads to RSK3 upregulation, which promotes survival by activating the TSC2-mTOR-p70S6K1-BAD cascade. mTORis block this protective signaling and augment the apoptosis induced by BET inhibition. Our findings reveal a critical role of RSK3 induction in tumor survival upon BET inhibition and warrant further evaluation of the combination of mTORis and BETis in patients with SCLC.

Machine Learning Informs RNA-Binding Chemical Space

Small molecule targeting of RNA has emerged as a new frontier in medicinal chemistry, but compared to the protein targeting literature our understanding of chemical matter that binds to RNA is limited. In this study, we reported Repository Of BInders to Nucleic acids (ROBIN), a new library of nucleic acid binders identified by small molecule microarray (SMM) screening. The complete results of 36 individual nucleic acid SMM screens against a library of 24 572 small molecules were reported (including a total of 1 627 072 interactions assayed). A set of 2 003 RNA-binding small molecules was identified, representing the largest fully public, experimentally derived library of its kind to date. Machine learning was used to develop highly predictive and interpretable models to characterize RNA-binding molecules. This work demonstrates that machine learning algorithms applied to experimentally derived sets of RNA binders are a powerful method to inform RNA-targeted chemical space.

SULT1A1-dependent sulfonation of alkylators is a lineage-dependent vulnerability of liver cancers

Adult liver malignancies, including intrahepatic cholangiocarcinoma and hepatocellular carcinoma, are the second leading cause of cancer-related deaths worldwide. Most individuals are treated with either combination chemotherapy or immunotherapy, respectively, without specific biomarkers for selection. Here using high-throughput screens, proteomics and in vitro resistance models, we identify the small molecule YC-1 as selectively active against a defined subset of cell lines derived from both liver cancer types. We demonstrate that selectivity is determined by expression of the liver-resident cytosolic sulfotransferase enzyme SULT1A1, which sulfonates YC-1. Sulfonation stimulates covalent binding of YC-1 to lysine residues in protein targets, enriching for RNA-binding factors. Computational analysis defined a wider group of structurally related SULT1A1-activated small molecules with distinct target profiles, which together constitute an untapped small-molecule class. These studies provide a foundation for preclinical development of these agents and point to the broader potential of exploiting SULT1A1 activity for selective targeting strategies.

Inhibition of HSP 90 is associated with potent anti-tumor activity in Papillary Renal Cell Carcinoma

Background

There is no universally accepted treatment for patients with advanced papillary renal cell carcinoma (PRCC). The presence of activating mutations in MET, as well as gain of chromosome 7, where the MET gene is located, are the most common genetic alterations associated with PRCC, leading to the clinical evaluation of MET tyrosine kinase inhibitors (TKIs) in this cancer. However, TKIs targeting MET selectively, as well as multitargeted TKIs with activity against MET demonstrate modest efficacy in PRCC and primary and secondary treatment failure is common; other approaches are urgently needed to improve outcomes in these patients.

Methods

High throughput screening with small molecule libraries identified HSP90 inhibitors as agents of interest based on antitumor activity against patient derived PRCC cell lines. We investigated the activity of the orally available HSP90 inhibitor, SNX2112 in vitro, using 2D/3D PRCC cell culture models and in vivo, in mice tumor xenograft models. The molecular pathways mediating antitumor activity of SNX2112 were assessed by Western blot analysis, Flow cytometry, RNA-seq analysis, Real Time qPCR and imaging approaches.

Results

SNX2112 significantly inhibited cellular proliferation, induced G2/M cell cycle arrest and apoptosis in PRCC lines overexpressing MET. In contrast to TKIs targeting MET, SNX2112 inhibited both MET and known downstream mediators of MET activity (AKT, pAKT1/2 and pERK1/2) in PRCC cell lines. RNAi silencing of AKT1/2 or ERK1/2 expression significantly inhibited growth in PRCC cells. Furthermore, SNX2112 inhibited a unique set of E2F and MYC targets and G2M-associated genes. Interestingly, interrogation of the TCGA papillary RCC cohort revealed that these genes were overexpressed in PRCC and portend a poor prognosis. Finally, SNX-2112 demonstrated strong antitumor activity in vivo and prolonged survival of mice bearing human PRCC xenograft.

Conclusions

These results demonstrate that HSP90 inhibition is associated with potent activity in PRCC, and implicate the PI3K/AKT and MEK/ERK1/2 pathways as important mediators of tumorigenesis. These data also provide the impetus for further clinical evaluation of HSP90, AKT, MEK or E2F pathway inhibitors in PRCC.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02416-z.

Zanubrutinib plus salvage chemotherapy for relapsed or refractory diffuse large B-cell lymphoma

Introduction

Relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL) has poor clinical outcomes when treated with conventional salvage chemotherapy. Monotherapy using zanubrutinib, a selective Bruton's tyrosine kinase (BTK) inhibitor, has achieved modest antitumor effect in R/R DLBCL. Here we aimed to evaluate the efficacy and safety of zanubrutinib plus salvage chemotherapy in R/R DLBCL patients.

Methods

We retrospectively reviewed R/R DLBCL patients who were administered with zanubrutinib plus salvage chemotherapy in our center between January, 2019 and December, 2021. Targeted panel sequencing of 11 lymphoma-related genes was performed on 8 patients with poor responses to zanubrutinib-based chemotherapy.

Results

27 R/R DLBCL patients were enrolled. Median age at this study was 59 years (range, 15-72). The best overall response rate (ORR) was 74.1% and complete remission rate was 33.3%. With a median follow-up of 11 months (range, 1-17), the median progression-free survival (PFS) was 8.1 months, and the overall survival (OS) was not achieved. The most common grade-3/4 adverse events were neutropenia (70.4%), thrombocytopenia (66.7%), and febrile neutropenia (33.3%). In multivariate analysis, early treatment and overall response after chemotherapy were independent favorable prognostic factors for PFS. Overall response after chemotherapy was an independent favorable factor for OS. Among the 8 patients with poor response to zanubrutinib-based treatment, the majority of patients had NOTCH2 mutations (n=8, 100%) and TP53 mutations (n=7, 87.5%). However, these patients achieved an ORR of 75% at 3 months after CD19-CAR-T cell therapy (including 4 cases of complete remission and 2 cases of partial remission). With a median follow-up of 9 months from CAR-T cell infusion (range, 1-16 months), the median PFS was 14.5 months, and the median OS was not reached.

Conclusion

With high efficacy and manageable tolerability, zanubrutinib plus salvage chemotherapy may be a potential treatment option for R/R DLBCL. CAR-T cell therapy may be a priority strategy for these poor responders to BTKi-based treatment.

Preclinical assessment of synergistic efficacy of MELK and CDK inhibitors in adrenocortical cancer

BACKGROUND

Adrenocortical cancer (ACC) is a rare and aggressive cancer with dismal 5-year survival due to a lack of effective treatments. We aimed to identify a new effective combination of drugs and investigated their synergistic efficacy in ACC preclinical models.

METHODS

A quantitative high-throughput drug screening of 4,991 compounds was performed on two ACC cell lines, SW13 and NCI-H295R, based on antiproliferative effect and caspase-3/7 activity. The top candidate drugs were pairwise combined to identify the most potent combinations. The synergistic efficacy of the selected inhibitors was tested on tumorigenic phenotypes, such as cell proliferation, migration, invasion, spheroid formation, and clonogenicity, with appropriate mechanistic validation by cell cycle and apoptotic assays and protein expression of the involved molecules. We tested the efficacy of the drug combination in mice with luciferase-tagged human ACC xenografts. To study the mRNA expression of target molecules in ACC and their clinical correlations, we analyzed the Gene Expression Omnibus and The Cancer Genome Atlas.

RESULTS

We chose the maternal embryonic leucine zipper kinase (MELK) inhibitor (OTS167) and cyclin-dependent kinase (CDK) inhibitor (RGB-286638) because of their potent synergy from the pairwise drug combination matrices derived from the top 30 single drugs. Multiple publicly available databases demonstrated overexpression of MELK, CDK1/2, and partnering cyclins mRNA in ACC, which were independently associated with mortality and other adverse clinical features. The drug combination demonstrated a synergistic antiproliferative effect on ACC cells. Compared to the single-agent treatment groups, the combination treatment increased G2/M arrest, caspase-dependent apoptosis, reduced cyclins A2, B1, B2, and E2 expression, and decreased cell migration and invasion with reduced vimentin. Moreover, the combination effectively decreased Foxhead Box M1, Axin2, glycogen synthase kinase 3-beta, and β-catenin. A reduction in p-stathmin from the combination treatment destabilized microtubule assembly by tubulin depolymerization. The drug combination treatment in mice with human ACC xenografts resulted in a significantly lower tumor burden than those treated with single-agents and vehicle control groups.

CONCLUSIONS

Our preclinical study revealed a novel synergistic combination of OTS167 and RGB-286638 in ACC that effectively targets multiple molecules associated with ACC aggressiveness. A phase Ib/II clinical trial in patients with advanced ACC is therefore warranted.

Oncogenic RAS commandeers amino acid sensing machinery to aberrantly activate mTORC1 in multiple myeloma

Oncogenic RAS mutations are common in multiple myeloma (MM), an incurable malignancy of plasma cells. However, the mechanisms of pathogenic RAS signaling in this disease remain enigmatic and difficult to inhibit therapeutically. We employ an unbiased proteogenomic approach to dissect RAS signaling in MM. We discover that mutant isoforms of RAS organize a signaling complex with the amino acid transporter, SLC3A2, and MTOR on endolysosomes, which directly activates mTORC1 by co-opting amino acid sensing pathways. MM tumors with high expression of mTORC1-dependent genes are more aggressive and enriched in RAS mutations, and we detect interactions between RAS and MTOR in MM patient tumors harboring mutant RAS isoforms. Inhibition of RAS-dependent mTORC1 activity synergizes with MEK and ERK inhibitors to quench pathogenic RAS signaling in MM cells. This study redefines the RAS pathway in MM and provides a mechanistic and rational basis to target this mode of RAS signaling.

RAS mutations are commonly found in multiple myeloma (MM). Here, the authors show that oncogenic RAS mutations activate mTORC1 signalling in MM and combining mTORC1 and MEK/ERK inhibitors synergize to improve survival in preclinical models.

Interfering B cell receptor signaling via SHP-1/p-Lyn axis shows therapeutic potential in diffuse large B-cell lymphoma

Background

Diffuse large B cell lymphoma (DLBCL) is an aggressive and molecularly heterogeneous non-Hodgkin’s lymphoma. The B cell receptor (BCR) signaling pathway in DLBCL emerges as a new drug target. Protein phosphatase SHP-1 negatively regulates several oncogenic tyrosine kinases and plays a tumor suppressive role.

Methods

The direct SHP-1 agonists were used to evaluate the potential therapeutic implication of SHP-1 in DLBCL. Immunohistochemical staining for SHP-1 was quantified by H-score. The SHP-1 phosphatase activity was determined using tyrosine phosphatase assay. In vitro studies, including MTT, western blot analysis and cell apoptosis, were utilized to examined biological functions of SHP-1.

Results

Oral administration of SHP-1 agonist showed the potent anti-tumor effects compared to a selective Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib in mice bearing U2932 xenografts. SHP-1 agonist increased SHP-1 activity as well as downregulated p-Lyn in vivo. Here, we demonstrated that immunohistochemical staining for SHP-1 expression was positive in 76% of DLBCL samples. SHP-1 agonist exerted anti-proliferative and apoptotic effects compared with ibrutinib in DLBCL cells. Mechanistically, SHP-1 agonist decreased BCR signaling, especially p-Lyn, and led to apoptosis.

Conclusions

These data suggest that SHP-1 negatively regulates phosphorylation of Lyn, and targeting SHP-1/p-Lyn using SHP-1 agonist has therapeutic potential for treatment of DLBCL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00518-0.

A quantitative high-throughput screen identifies compounds that lower expression of the SCA2-and ALS-associated gene ATXN2

CAG repeat expansions in the ATXN2 (ataxin-2) gene can cause the autosomal dominant disorder spinocerebellar ataxia type 2 (SCA2) as well as increase the risk of ALS. Abnormal molecular, motor, and neurophysiological phenotypes in SCA2 mouse models are normalized by lowering ATXN2 transcription, and reduction of nonmutant Atxn2 expression has been shown to increase the life span of mice overexpressing the TDP-43 (transactive response DNA-binding protein 43 kDa) ALS protein, demonstrating the potential benefits of targeting ATXN2 transcription in humans. Here, we describe a quantitative high-throughput screen to identify compounds that lower ATXN2 transcription. We screened 428,759 compounds in a multiplexed assay using an ATXN2-luciferase reporter in human embryonic kidney 293 (HEK-293) cells and identified a diverse set of compounds capable of lowering ATXN2 transcription. We observed dose-dependent reductions of endogenous ATXN2 in HEK-293 cells treated with procillaridin A, 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG), and heat shock protein 990 (HSP990), known inhibitors of HSP90 and Na+/K+-ATPases. Furthermore, HEK-293 cells expressing polyglutamine-expanded ATXN2-Q58 treated with 17-DMAG had minimally detectable ATXN2, as well as normalized markers of autophagy and endoplasmic reticulum stress, including STAU1 (Staufen 1), molecular target of rapamycin, p62, LC3-II (microtubule-associated protein 1A/1B-light chain 3II), CHOP (C/EBP homologous protein), and phospho-eIF2α (eukaryotic initiation factor 2α). Finally, bacterial artificial chromosome ATXN2-Q22 mice treated with 17-DMAG or HSP990 exhibited highly reduced ATXN2 protein abundance in the cerebellum. Taken together, our study demonstrates inhibition of HSP90 or Na+/K+-ATPases as potentially effective therapeutic strategies for treating SCA2 and ALS.