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Synthetic lethality-an interaction between two genetic events through which the co-occurrence of these two genetic events leads to cell death, but each event alone does not-can be exploited for cancer therapeutics1. DNA repair processes represent attractive synthetic lethal targets, because many cancers exhibit an impairment of a DNA repair pathway, which can lead to dependence on specific repair proteins2. The success of poly(ADP-ribose) polymerase 1 (PARP-1) inhibitors in cancers with deficiencies in homologous recombination highlights the potential of this approach3. Hypothesizing that other DNA repair defects would give rise to synthetic lethal relationships, we queried dependencies in cancers with microsatellite instability (MSI), which results from deficient DNA mismatch repair. Here we analysed data from large-scale silencing screens using CRISPR-Cas9-mediated knockout and RNA interference, and found that the RecQ DNA helicase WRN was selectively essential in MSI models in vitro and in vivo, yet dispensable in models of cancers that are microsatellite stable. Depletion of WRN induced double-stranded DNA breaks and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models required the helicase activity of WRN, but not its exonuclease activity. These findings show that WRN is a synthetic lethal vulnerability and promising drug target for MSI cancers.

Mouse models are a tool for studying the mechanisms underlying complex diseases; however, differences between species pose a significant challenge for translating findings to patients. Here, we used single-cell transcriptomics and orthogonal validation approaches to provide cross-species taxonomies, identifying shared broad cell classes and unique granular cellular states, between mouse and human kidney. We generated cell atlases of the diabetic and obese kidney using two different mouse models, a high-fat diet (HFD) model and a genetic model (BTBR ob/ob), at multiple time points along disease progression. Importantly, we identified a previously unrecognized, expanding Trem2high macrophage population in kidneys of HFD mice that matched human TREM2high macrophages in obese patients. Taken together, our cross-species comparison highlights shared immune and metabolic cell-state changes.

Successful mapping of cancer dependencies requires conducting genetic and pharmacological screens in a diversity of cell models. However, existing model development approaches require long periods of culture time during which evolutionary pressures reduce heterogeneity. It also remains difficult to create long-term models of many cancers, greatly limiting the share of patient samples that can be studied. These limitations make it challenging to create large and diverse datasets for the discovery and validation of biomarker-vulnerability relationships. To enable high-throughput genetic and pharmacological screens in primary, including nondividing, cells without an intermediate model generation step, we are developing a label-free imaging-based platform of early living tissue perturbation. Here, we describe our efforts to establish an ex vivo cell-preservation and imaging system for malignant ascites from patients with advanced gastroesophageal (GE) cancer, whose prognosis remains poor and there is an urgent need for rapid evidence-based therapeutic discovery. First, we optimized a workflow to acquire and perturb cells within 24 hours of sample collection. We observed that incorporating microenvironmental factors by mixing ascites fluid with organoid media extends the preservation of cellular composition and viability. We next hypothesized that label-free microscopy can be a substitute for fluorescence-based labels which fade over time in live-cell imaging. To test this, we created a dataset consisting of over 1.0M cells from 14 samples (10 unique patients). Before seeding, we added fluorescence labels to annotate cell type and viability during imaging. We then trained predictive models to infer cell annotations based on brightfield morphological features only and observed an overall accuracy of 92% and 82% for cell identity and viability, respectively. Prediction of tumor cell fraction from label-free images alone showed strong correlation with tumor fractions estimated by flow cytometry. We also integrated single-cell RNA sequencing data to generate a candidate panel of 28 compounds which are predicted to exhibit antitumor activity via different mechanisms that are of relevance to our study cohort. We observe that label-free inference of compound activity showed strong correlation (R2 > 0.8) with fluorescent-based methods. We are now expanding the scale of our rapid screens and utilizing transcriptomics to link the molecular profile with response. Since our approach couples the timing of drug or genetic perturbation with the preservation of subcellular heterogeneity, it will serve as a strong foundation for preclinical studies. Importantly, our method substantially expands the fraction of samples that can be interrogated and will have application in other areas of need where material is limited or long-term model generation remains unsuccessful as is the case in many rare diseases. Citation Format: Mushriq Al-Jazrawe, Csaba Molnar, Niklas Rindtorff, Steven Blum, William Colgan, Maria Alimova, Sean Misek, Carmen Rios, Moony Tseng, James M. McFarland, Aviv Regev, Beth A. Cimini, Anne E. Carpenter, Adam Bass, Samuel J. Klempner, Jesse Boehm. Rapidly evaluating cancer dependencies by label-free imaging of zero-passage primary cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 639.

The decrease in the economic activity level around the world due to the COVID-19 pandemic spread has led to a sharp decrease in the crude oil price and provoked an oil war outbreak in the global energy market. The current situation has provoked the need for a total decrease in the crude oil production in the world. Considering that Russia is one of the main oil exporters on the world market, the need to determine the supply and demand levels for Russian oil is becoming relevant. The aim of the paper is to model predictive scenarios of Russian oil industry development, considering the specifics of the current economic environment given the COVID-19 pandemic. The multifactor correlation modeling method was used to form the system of indicators determining the level of demand and supply for Russian oil used and the total level of their influence. The functions determine the probability of implementing various scenarios of oil industry development depending on the predicted values of demand and supply. The three-sigma rule and the fuzzy sets method were used to estimate three scenarios of oil industry development for 2020–2021. Changes in revenues of the industry under the influence of forecast indicators of supply and demand for oil have been assessed and the probability of implementation of each of the scenarios has been reasoned. The results obtained are of a practical nature and can be used by government agencies, financial intermediaries, and scientists to diagnose Russian oil industry development. The results will be useful for oil companies to develop a strategy of open innovations for further design of the scientific information field for the effective functioning of the industry in complete uncertainty conditions.

Summary Drug repurposing has the advantage of identifying potential treatments on a shortened timescale. In response to the pandemic spread of SARS-CoV-2, we took advantage of a high-content screen of 3,713 compounds at different stages of clinical development to identify FDA-approved compounds that reduce mucin-1 (MUC1) protein abundance. Elevated MUC1 levels predict the development of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) and correlate with poor clinical outcomes. Our screen identifies fostamatinib (R788), an inhibitor of spleen tyrosine kinase (SYK) approved for the treatment of chronic immune thrombocytopenia, as a repurposing candidate for the treatment of ALI. In vivo, fostamatinib reduces MUC1 abundance in lung epithelial cells in a mouse model of ALI. In vitro, SYK inhibition by the active metabolite R406 promotes MUC1 removal from the cell surface. Our work suggests fostamatinib as a repurposing drug candidate for ALI., Graphical Abstract, Highlights Elevated MUC1 levels predict the development of acute lung injury (ALI) A high-content screen of 3,713 compounds identifies repurposing candidates R406 removes MUC1 from the apical surface of epithelial cells Fostamatinib treatment reduces MUC1 in a mouse model of lung injury, In a high-content screen, Kost-Alimova et al. identify R406, the active metabolite of fostamatinib, as an FDA-approved candidate repurposing compound for the reduction of MUC1 protein levels in lung epithelium in the setting of acute lung injury.

Successful mapping of cancer dependencies requires conducting genetic and drug screens on a diversity of models. However, the difficulty in generating long-term models of many cancers limits the share of patient samples that can be studied. Such long-term models have likely also lost the cellular heterogeneity present in the original tumor due to in vitro propagation. To overcome these limitations, we are developing image-based ex vivo cancer biosensors from early patient material. Using freshly received gastroesophageal cancer ascites, we are optimizing perturbation methods and utilizing single-cell transcriptomics and label-free microscopy to infer a subpopulation-specific vulnerability profile. We show that label-free microscopy can infer cell identity and viability in heterogeneous early patient samples. Additionally, early drug perturbation recapitulates observations made in established gastroesophageal cancer organoids. Successful implementation of ex vivo biosensors will expand the cancer dependency space by making perturbational studies accessible to more diverse samples, and by identifying and validating hits in a more immediate setting to the original tumor. Citation Format: Mushriq Al-Jazrawe, Csaba Molnar, Niklas Rindtorff, Pinar Eser, Sean Misek, Maria Alimova, Oana Ursu, William Colgan, Adel Attari, Natalie Tsang, Paula Keskula, Carmen Rios, Moony Tseng, Anne Carpenter, James McFarland, Adam Bass, Samuel Klempner, Jesse Boehm. Evaluating dependencies by rapid image-based ex vivo cancer biosensors [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-093.

Summary paragraph Synthetic lethality, an interaction whereby the co-occurrence of two or more genetic events lead to cell death but one event alone does not, can be exploited to develop novel cancer therapeutics1. DNA repair processes represent attractive synthetic lethal targets since many cancers exhibit an impaired DNA repair pathway, which can lead these cells to become dependent on specific repair proteins2. The success of poly (ADP-ribose) polymerase 1 (PARP-1) inhibitors in homologous recombination-deficient cancers highlights the potential of this approach in clinical oncology3,4. Hypothesizing that other DNA repair defects would give rise to alternative synthetic lethal relationships, we asked if there are specific dependencies in cancers with microsatellite instability (MSI), which results from impaired DNA mismatch repair (MMR). Here we analyzed data from large-scale CRISPR/Cas9 knockout and RNA interference (RNAi) silencing screens and found that the RecQ DNA helicase WRN was selectively essential in MSI cell lines, yet dispensable in microsatellite stable (MSS) cell lines. WRN depletion induced double-strand DNA breaks and promoted apoptosis and cell cycle arrest selectively in MSI models. MSI cancer models specifically required the helicase activity, but not the exonuclease activity of WRN. These findings expose WRN as a synthetic lethal vulnerability and promising drug target in MSI cancers.

SUMMARYKidney cancers are characterized by extensive metabolic reprogramming and resistance to a broad range of anti-cancer therapies. By interrogating the Cancer Therapeutics Response Portal compound sensitivity dataset, we show that cells of clear-cell renal cell carcinoma (ccRCC) possess a lineage-specific vulnerability to ferroptosis that can be exploited by inhibiting glutathione peroxidase 4 (GPX4). Using genome-wide CRISPR screening and lipidomic profiling, we reveal that this vulnerability is driven by the HIF-2α–HILPDA pathway by inducing a polyunsaturated fatty acyl (PUFA)-lipid-enriched cell state that is dependent on GPX4 for survival and susceptible to ferroptosis. This cell state is developmentally primed by the HNF-1β–1-Acylglycerol-3-Phosphate O-Acyltransferase 3 (AGPAT3) axis in the renal lineage. In addition to PUFA metabolism, ferroptosis is facilitated by a phospholipid flippase TMEM30A involved in membrane topology. Our study uncovers an oncogenesis-associated vulnerability, delineates the underlying mechanisms and suggests targeting GPX4 to induce ferroptosis as a therapeutic opportunity in ccRCC.HIGHLIGHTSccRCC cells exhibit strong susceptibility to GPX4 inhibition-induced ferroptosisThe GPX4-dependent and ferroptosis-susceptible state in ccRCC is associated with PUFA-lipid abundanceThe HIF-2α–HILPDA axis promotes the selective deposition of PUFA-lipids and ferroptosis susceptibilityAGPAT3 selectively synthesizes PUFA-phospholipids and primes renal cells for ferroptosis

SUMMARY Evidence that some high-impact biomedical results cannot be repeated has stimulated interest in practices that generate findable, accessible, interoperable, and reusable (FAIR) data. Multiple papers have identified specific examples of irreproducibility, but practical ways to make data more reproducible have not been widely studied. Here, five research centers in the NIH LINCS Program Consortium investigate the reproducibility of a prototypical perturbational assay: quantifying the responsiveness of cultured cells to anti-cancer drugs. Such assays are important for drug development, studying cellular networks, and patient stratification. While many experimental and computational factors impact intra- and inter-center reproducibility, the factors most difficult to identify and control are those with a strong dependency on biological context. These factors often vary in magnitude with the drug being analyzed and with growth conditions. We provide ways to identify such context-sensitive factors, thereby improving both the theory and practice of reproducible cell-based assays., Graphical Abstract, In Brief Factors that impact the reproducibility of experimental data are poorly understood. Five NIH-LINCS centers performed the same set of drug-response measurements and compared results. Technical and biological variables that impact precision and reproducibility and are also sensitive to biological context were the most problematic.

Acute myeloid leukemia (AML) is a highly aggressive disease with a high mortality rate that encompasses several genetically and clinically diverse hematological malignancies characterized by clonal expansion of transformed stem/progenitor cells with limited ability to differentiate into mature blood cells. Standard of care for AML has progressed minimally in the past 30 years for relapse/refractory AML, with survival rates of 65 years. Therefore, novel, highly effective therapeutics are needed for this population. Targeting bioenergetic susceptibilities is an exciting area of oncology therapeutics that is potentially applicable in AML. Our group and others have shown that AML blasts depend significantly on mitochondrial oxidative phosphorylation to meet their energy and biomass production demands. Through an extensive medicinal chemistry campaign IACS-10759 was identified as a potent, selective inhibitor of complex I of the electron transport chain with excellent PK and a suitable overall profile. In AML cell lines and primary AML blasts treated ex vivo, we observe a robust decrease in proliferation and a concomitant increase in apoptosis with EC50 values of less than 10 nM. Response to IACS-10759 in AML cells was associated with induction of a metabolic catastrophe that negatively impacted the cells' ability to sustain energy homeostasis, amino acid biosynthesis, and nucleotide production. In a primary AML patient derived xenograft model from a patient who was refractory to standard of care and salvage therapies, 42 days of IACS-10759 (QDx5/week) treatment at 10 mg/kg extended the median survival by greater than 2-fold. Inhibition of OXPHOS by IACS-10759 was confirmed in AML cell lines and PDX models by a decrease in oxygen consumption and significant changes in gene and protein expression, non-essential amino acids and nucleotides. Due to the robust response in AML cell lines, primary AML samples ex vivo, and in vivo efficacy in primary AML PDX models, IACS-10759 has been advanced through IND enabling studies with first-in-human studies targeted for the second quarter of 2016. Citation Format: Jennifer R. Molina, Marina Protopopova, Madhavi Bandi, Jennifer Bardenhagen, Christopher Bristow, Maria Alimova, Christopher Carroll, Edward Chang, Ningping Feng, Jason Gay, Mary Geck Do, Jennifer Greer, Sha Huang, Yongying Jiang, Marina Konopleva, Polina Matre, Zhijun Kang, Gang Liu, Timothy McAfoos, Pietro Morlacchi, Melinda Smith, Sonal Sonal, Jay Theroff, Quanyun Xu, Giulio Draetta, Philip Jones, Carlo Toniatti, M. Emilia Di Francesco, Joseph R. Marszalek. IACS-010759 is a novel inhibitor of oxidative phosphorylation that selectively targets AML cells by inducing a metabolic catastrophe. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-A15.

MTH1 is a protein that sanitizes oxidized dNTPs in the cell. It preferentially hydrolyzes 8-oxo-dGTP and 2-OH-dATP to their corresponding monophosphates and thereby prevents the incorporation of oxidized nucleotides into DNA or RNA. The functional result is a reduction in down-stream mutations, or DNA damage, thus preventing cell death. Recent publications suggest that MTH1 is a non-essential enzyme in normal cells, but is required for the survival of cancer cells as a consequence of being subjected to high levels of oxidative stress; hence its relevance as an oncology target. Gad et al., 2014 The interesting target rationale combined with a perceived high chemical tractability of the target resulting from availability of x-ray crystallographic information for the protein, led to a decision to undertake, in parallel, target validation, assay development and drug discovery. This effort resulted in the structure-based design of potent, cell active MTH1 small molecule inhibitors. This poster will describe the discovery and optimization of these inhibitors, and their use to evaluate the potential of MTH1 as an oncology target. This work was complemented by parallel genetic studies. Pharmacodynamic evaluation of target engagement using proximal biomarkers will be presented, as will phenotypic responses across a range of cancer cell lines. Citation Format: Elisabetta Leo, Alessia Petrocchi, Jennifer Bardenhagen, Maria Alimova, Xi Shi, Connor Parker, Naphtali Reyna, Matthew Hamilton, Edward Felix, Andrzej Mazan, Christian Dillon, Faika Mseeh, Joseph R. Marszalek, Carlo Toniatti, Giulio Draetta, Phil Jones, Richard T. Lewis. Identification of potent, cell active MTH1 inhibitors and their use in target validation studies. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr B48.

The SWI/SNF multi-subunit complex modulates chromatin structure through the activity of two mutually exclusive catalytic subunits, SMARCA2 and SMARCA4, which both contain a bromodomain and an ATPase domain. Using RNAi, cancer-specific vulnerabilities have been identified in SWI/SNF mutant tumors, including SMARCA4-deficient lung cancer, however, the contribution of conserved, druggable protein domains to this anticancer phenotype is unknown. Here, we functionally deconstructed the SMARCA2/4 paralog dependence of cancer cells using bioinformatics, genetic and pharmacological tools. We evaluated a potent and selective SMARCA2/4 bromodomain inhibitor (PFI-3) and characterized its activity in chromatin-binding and cell-functional assays focusing on cells with altered SWI/SNF status (e.g. Lung, Synovial Sarcoma, Leukemia, and Rhabdoid tumors). We demonstrated that PFI-3 is a cell-permeable probe capable of displacing ectopically expressed, GFP-tagged SMARCA2-bromodomain from chromatin, yet contrary to target knockdown, the inhibitor failed to display an antiproliferative phenotype. Mechanistically, the lack of pharmacological efficacy was reconciled by the failure of bromodomain inhibition to displace endogenous, full-length SMARCA2 from chromatin as determined by in situ cell extraction, chromatin immunoprecipitation (ChIP) and target gene expression and promoter occupancy studies. Using RNAi and cDNA complementation (bromodomain and ATPase-dead constructs), we identified the catalytic ATPase domain, and not the bromodomain of SMARCA2, as a relevant therapeutic target. Taken together, our complementary genetic and pharmacological studies exemplify a general strategy for bromodomain drug-target validation and in case of SMARCA2/4 highlight the requirement for drugging the more challenging helicase/ATPase domain affording potential synthetic-lethal treatment options to cancer patients with genetically defined alterations in SWI/SNF. Citation Format: Bhavatarini Vangamudi, Thomas Paul, Parantu K. Shah, Maria K. Alimova, Lisa Nottebaum, Xi Shi, Yanai Zhan, Elisabetta Leo, Harshad S. Mahadeshwar, Alexei Protopopov, Andrew Futreal, Trang N. Tieu, Mike Peoples, Alessia Petrocchi, Joseph R. Marszalek, Carlo Toniatti, Timothy P. Heffernan, Dominique Verhelle, Giulio Draetta, Dafydd Owen, Philip Jones, Wylie Palmer, Shikhar Sharma, Jannik N. Andersen. The SMARCA2/4 catalytic activity, but not the bromodomain, is a drug target in SWI/SNF mutant cancers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3528. doi:10.1158/1538-7445.AM2015-3528