Druggable Genome Research Articles

ANGI-14. DRUGGABLE GENOME CRISPR SCREEN IN 3D HYDROGEL DEVICES REVEALS TARGETABLE KINASES AND PHOSPHATASES IMPLICATED IN CYTOSKELETAL REORGANIZATION IN INVADING GBM CELLS

Abstract The invasive nature of glioblastoma cells into adjacent brain tissues is a key factor in its unfavorable prognosis. To decipher the mechanisms driving glioblastoma invasion, we developed microdissectable biomimetic 3D hydrogel invasion devices containing hyaluronic acid hydrogels decorated with integrin-binding peptides (RGD) and crosslinked with protease-cleavable crosslinkers. The ability to disassemble these devices and interrogate cells in the core vs. invasive fraction allows for high throughput screens. We thus performed a screen in GBM43 cells expressing CRISPR/Cas9 and a 13,250 gRNA library targeting the 2550 genes in the druggable human genome. Of seven initial hits from this screen, only two could be validated by single gene CRISPR and use of a drug to target the hit - ACP1 (also known as LMW-PTP) and Aurora Kinase B (AURKB). Integration of ChIP-seq and RNA-seq revealed no plausible transcriptional targets of ACP1 and AURKB that could drive invasion. Proximity labeling with the TurboID system identified CTTN (cortactin), an actin binding protein whose phosphorylation is integral to the formation of lamellipodia and invadopodia, as phosphorylated by AURKB and Ephrin A2 (EPHA2), whose dephosphorylation controls cell morphology, adhesion, migration and invasion by modifying the organization of the actin cytoskeleton and influencing the activities of integrins and intercellular adhesion molecules, as dephosphorylated by ACP1. These findings underscore the delicate balance between kinase and phosphatase activities in regulating the actin cytoskeleton broadly and at the cell’s front or “leading edge,” offering new therapeutic targets to disrupt the invasion that is a hallmark of glioblastoma.

Genome-wide association studies of ischemic stroke based on interpretable machine learning.

Despite the identification of several dozen genetic loci associated with ischemic stroke (IS), the genetic bases of this disease remain largely unexplored. In this research we present the results of genome-wide association studies (GWAS) based on classical statistical testing and machine learning algorithms (logistic regression, gradient boosting on decision trees, and tabular deep learning model TabNet). To build a consensus on the results obtained by different techniques, the Pareto-Optimal solution was proposed and applied. These methods were applied to real genotypic data of sick and healthy individuals of European ancestry obtained from the Database of Genotypes and Phenotypes (5,581 individuals, 883,749 single nucleotide polymorphisms). Finally, 131 genes were identified as candidates for association with the onset of IS. UBQLN1, TRPS1, and MUSK were previously described as associated with the course of IS in model animals. ACOT11 taking part in metabolism of fatty acids was shown for the first time to be associated with IS. The identified genes were compared with genes from the Illuminating Druggable Genome project. The product of GPR26 representing the G-coupled protein receptor can be considered as a therapeutic target for stroke prevention. The approaches presented in this research can be used to reprocess GWAS datasets from other diseases.

Arab founder variants: Contributions to clinical genomics and precision medicine.

Founder variants are ancestral variants shared by individuals who are not closely related. The large effect size of some of these variants in the context of Mendelian disorders offers numerous precision medicine opportunities. Using one of the largest datasets on Mendelian disorders in the Middle East, we identified 2,908 medically relevant founder variants derived from 18,360 exomes and genomes and investigated their contribution to the clinical annotation of the human genome. Strikingly, ∼34% of Arab founder variants are absent in gnomAD. We found a strong contribution of Arab founder variants to the identification of novel gene-disease links (n= 224) and the support/dispute (n= 81 support, n= 101 dispute) of previously reported candidate gene-disease links. The powerful segregation evidence generated by Arab founder variants allowed many ClinVar and Human Gene Mutation Database variants to be reclassified. Overall, 39.5% of diagnostic reports from our clinical lab are based on founder variants, and 19.41% of tested individuals carry at least one pathogenic founder variant. The presumptive loss-of-function mechanism that typically underlies autosomal recessive diseases means that Arab founder variants also offer unique opportunities in "druggable genome" research. Arab founder variants were also informative of migration patterns in the Middle East consistent with documented historical accounts. We highlight the contribution of founder variants from an under-represented population group to precision medicine and inform future prevention programs. Our study also sheds light on the added value of these variants in supplementing other lines of research in tracing population history. There is no funding for this work.

Atypical MAPKs in cancer.

Impaired kinase signalling leads to various diseases, including cancer. At the same time, kinases make up the majority of the druggable genome and targeting kinase activity has proven to be a successful first-line therapy for many cancers. Among the best-studied kinases are the mitogen-activated protein kinases (MAPKs), which regulate cell proliferation, differentiation, motility, and survival. However, the MAPK family also contains the atypical members ERK3 (MAPK6), ERK4 (MAPK4), ERK7/ERK8 (MAPK15), and NLK that are functionally and structurally different from their conventional family members and have long been neglected. Nevertheless, in recent years, important roles in carcinogenesis, actin cytoskeleton regulation and the immune system have been discovered, underlining the physiological importance of atypical MAPKs and the need to better understand their functions. This review highlights the distinctive features of the atypical MAPKs and summarizes the evidence on their regulation, physiological roles, and potential targeting strategies for cancer therapies.

Identifying genetically-supported drug repurposing targets for non-small cell lung cancer through mendelian randomization of the druggable genome.

Lung cancer is responsible for most cancer-related deaths, and non-small cell lung cancer (NSCLC) accounts for the majority of cases. Targeted therapy has made promising advancements in systemic treatment for NSCLC over the last two decades, but inadequate drug targets with clinically proven survival benefits limit its universal application in clinical practice compared to chemotherapy and immunotherapy. There is an urgent need to explore new drug targets to expand the beneficiary group. This study aims to identify druggable genes and to predict the efficacy and prognostic value of the corresponding targeted drugs in NSCLC. Two-sample mendelian randomization (MR) of druggable genes was performed to predict the efficacy of their corresponding targeted therapy for NSCLC. Subsequent sensitivity analyses were performed to assess potential confounders. Accessible RNA sequencing data were incorporated for subsequent verifications, and Kaplan-Meier survival curves of different gene expressions were used to explore the prognostic value of candidate druggable genes. MR screening encompassing 4,863 expression quantitative trait loci (eQTL) and 1,072 protein quantitative trait loci (pQTL, with 453 proteins overlapping) were performed. Seven candidate druggable genes were identified, including CD33, ENG, ICOSLG and IL18R1 for lung adenocarcinoma, and VSIR, FSTL1 and TIMP2 for lung squamous cell carcinoma. The results were validated by further transcriptomic investigations. Drugs targeting genetically supported genomes are considerably more likely to yield promising efficacy and succeed in clinical trials. We provide compelling genetic evidence to prioritize drug development for NSCLC.

Abstract Or121: Druggable Genome CRISPRi/a Screens in iPSC-Derived Cardiomyocytes Identify Therapeutic Targets for Doxorubicin-Induced Cardiotoxicity

Introduction: Doxorubicin is a highly effective chemotherapy drug whose therapeutic utility is significantly hampered by its life-threatening adverse cardiac effects. The need for strategies to mitigate these cardiotoxic effects without diminishing its efficacy against cancer is critical in cardio-oncology. Hypothesis: We hypothesize that through an integrated drug discovery pipeline, utilizing patient iPSC-derived cardiomyocytes (iCMs) and CRISPRi/a bidirectional pooled screens combined with small molecule screening and molecular docking, we can identify therapeutic targets that ameliorate doxorubicin-induced cardiotoxicity (DIC) while preserving its anticancer efficacy. Methods: Our approach included patient iPSC-derived cardiomyocytes (iCMs), CRISPRi/a bidirectional pooled screens targeting druggable genome (~2000 genes) to identify candidate genes implicated in DIC, and small molecule screening alongside molecular docking to find potential inhibitors. Notably, carbonic anhydrase 12 (CA12) was identified as a primary hit for its role in DIC. Results: The CRISPRi/a screens revealed several novel genes, including CA12, as potential contributors to DIC. Genetic inhibition of CA12 in iCMs enhanced cell survival, preserved sarcomere structure, and improved contractile function and calcium handling, effectively protecting against DIC. Furthermore, we discovered that a CA12 antagonist significantly attenuates DIC in both iCMs and mouse models. Mechanistic studies suggested that doxorubicin triggers CA12 activation, leading to a metabolic change towards glycolysis in cardiomyocytes, thereby exacerbating DIC by disrupting cellular metabolism and cardiac functions. Conclusions: Our findings propose a novel therapeutic avenue to safeguard against doxorubicin-induced cardiotoxicity through the targeting of CA12, offering new direction for the development of more refined anticancer therapies that minimize cardiotoxic risk. This study sets the stage of combining CRISPRi/a screen with iPSC technology for future drug discovery endeavors aimed at eliminating off-target cardiotoxicities of chemotherapy agents.

Identifying Potential Drug Targets for Keloid: A Mendelian Randomization Study

Keloids are a skin fibrosis disease characterized by troublesome symptoms, a varying degree of recurrence and inevitable side effects from treatments. Thus, identifying their drug targets is necessary. A two-sample MR analysis was conducted using proteins from the intersection of the deCODE database and "The Druggable Genome and Support for Target Identification and Validation in Drug Development" as the exposure variable. The outcome variable was based on recently published GWAS of keloids. SMR and colocalization analysis was employed to distinguish pleiotropy from linkage. Candidate targets underwent drug target analysis. The primary findings were validated through scRNA-seq data, Western Blot and immunofluorescence staining on keloids. Seven proteins were identified as potential drug targets for keloids. Among these proteins, HHIP, NTM, KLKB1, and CRIPTO showed positive correlations with keloids, while PLXNC1, SCG3 and PDGF-D exhibited negative correlations. Combined with the scRNA-seq data, NTM, PLXNC1, and PDGF-D were found highly expressed in the fibroblasts. NTM showed a significant increase in keloids as compared to normal scars. In accordance with the analysis, higher levels of protein expression of NTM in keloids compared to normal skin was observed. The identified proteins may be appealing drug targets for keloids treatment with a special emphasis on NTM.

Systematic druggable genome-wide Mendelian randomization identifies therapeutic targets for sarcopenia.

There are no effective pharmacological treatments for sarcopenia. We aim to identify potential therapeutic targets for sarcopenia by integrating various publicly available datasets. We integrated druggable genome data, cis-eQTL/cis-pQTL from human blood and skeletal muscle tissue, and GWAS summary data of sarcopenia-related traits to analyse the potential causal relationships between drug target genes and sarcopenia using the Mendelian Randomization (MR) method. Sensitivity analyses and Bayesian colocalization were employed to validate the causal relationships. We also assessed the side effects or additional indications of the identified drug targets using a phenome-wide MR (Phe-MR) approach and investigated actionable drugs for target genes using available databases. MR analysis identified 17 druggable genes with potential causation to sarcopenia in human blood or skeletal muscle tissue. Six of them (HP, HLA-DRA, MAP 3K3, MFGE8, COL15A1, and AURKA) were further confirmed by Bayesian colocalization (PPH4>90%). The up-regulation of HP [higher ALM (beta: 0.012, 95% CI: 0.007-0.018, P=1.2*10-5) and higher grip strength (OR: 0.96, 95% CI: 0.94-0.98, P=4.2*10-5)], MAP 3K3 [higher ALM (beta: 0.24, 95% CI: 0.21-0.26, P=1.8*10-94), higher grip strength (OR: 0.82, 95% CI: 0.75-0.90, P=2.1*10-5), and faster walking pace (beta: 0.03, 95% CI: 0.02-0.05, P=8.5*10-6)], and MFGE8 [higher ALM (muscle eQTL, beta: 0.09, 95% CI: 0.06-0.11, P=6.1*10-13; blood pQTL, beta: 0.05, 95% CI: 0.03-0.07, P=3.8*10-09)], as well as the down-regulation of HLA-DRA [lower ALM (beta: -0.09, 95% CI: -0.11 to -0.08, P=5.4*10-36) and lower grip strength (OR: 1.13, 95% CI: 1.07-1.20, P=1.8*10-5)] and COL15A1 [higher ALM (muscle eQTL, beta: -0.07, 95% CI: -0.10 to -0.04, P=3.4*10-07; blood pQTL, beta: -0.05, 95% CI: -0.06 to -0.03, P=1.6*10-07)], decreased the risk of sarcopenia. AURKA in blood (beta: -0.16, 95% CI: -0.22 to -0.09, P=2.1*10-06) and skeletal muscle (beta: 0.03, 95% CI: 0.02 to 0.05, P=5.3*10-05) tissues showed an inverse relationship with sarcopenia risk. The Phe-MR indicated that the six potential therapeutic targets for sarcopenia had no significant adverse effects. Drug repurposing analysis supported zinc supplementation and collagenase clostridium histolyticum might be potential therapeutics for sarcopenia by activating HP and inhibiting COL15A1, respectively. Our research indicated MAP 3K3, MFGE8, COL15A1, HP, and HLA-DRA may serve as promising targets for sarcopenia, while the effectiveness of zinc supplementation and collagenase clostridium histolyticum for sarcopenia requires further validation.

Abstract 4947: Uncovering the molecular basis for clinically relevant sphingolipidomic subtypes in acute myeloid leukemia

Abstract Acute myeloid leukemia (AML) has been extensively studied at the genomic level, resulting in various genomic classifications. Despite the progress, three key challenges remain: 1) a significant proportion of patients lack identified genomic features, 2) a discrepancy exists between genomic risk classification and clinical outcomes, and 3) many mutated targets remain non-druggable. There is an urgent need for an enhanced AML risk classification that goes beyond genomic aberrations to guide effective therapeutics. Recent research, including our own, has increasingly linked AML pathogenesis and therapeutic resistance with dysfunctional sphingolipid metabolism, a family of bioactive molecules crucial for cellular functions. In a recent manuscript, we identified two robust sphingolipidomic clusters in AML, characterized by reciprocal abundances of hexosylceramide (Hex) and sphingomyelin (SM) species (HexloSMhi, HexhiSMlo). These clusters correlate with latent transcriptional states and stratify patient groups in multiple independent datasets such as TCGA, and BeatAML, with the HexloSMhi cluster representing a high-risk subgroup associated with poor clinical outcomes. These findings underscore the role of sphingolipids in refining AML risk assessment and creating avenues for discovery and therapeutic intervention. However, the signaling states driving these sphingolipidomic clusters and the mechanisms elevating risk in the HexloSMhi cluster require further investigation. To identify regulatory genes for the AML subtypes, we constructed gene regulatory networks using differentially expressed genes. Focusing on the high-risk subtype, we identified highly connected genes ranked by connectivity, including KDM1A, GSK3β, LCK, and STAT5A. We found that higher STAT5A abundances in the HexloSMhi subtype, particularly correlated with pro-survival Bcl-xL proteins. Furthermore, we identified STAT5 protein abundance as a key variable associated with drug sensitivity from pharmacological screening with sphingolipid pathway inhibitors and AML therapeutics 30 AML cell lines and patient samples. This is encouraging as STAT5 is druggable as evidenced in the NIH-Pharos druggable genome database, and several small-molecule inhibitors are currently in clinical trials. Analysis of gene expression data suggest that STAT5 inhibition, through genetic or pharmacological means, downregulates cell cycle-related genes and significantly alters sphingolipid gene expression. Recent work by others indicates that sphingolipid-catalyzing enzymes regulate STAT5 activity in leukemias, with ceramides acting as a second messenger in cells. Taken together, this suggests a possibility of a positive feedback loop between sphingolipid homeostasis and activity of STAT5; the details of this interaction require further investigation. Citation Format: B Bishal Paudel, Su-Fern Tan, Johnson Ung, David Claxton, David J. Feith, Thomas P. Loughran, Kevin A. Janes. Uncovering the molecular basis for clinically relevant sphingolipidomic subtypes in acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4947.

Abstract 1936: KEAP1-NRF2 mediated resistance against KRASG12D inhibitor in pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer deaths in the US. Mutational activation of the KRAS oncogene is associated with 95% of PDAC and is essential for maintaining PDAC tumorigenic growth. Although inhibitors (sotorasib and adagrasib) targeting one KRAS mutation (G12C) have been approved for the treatment of KRASG12C-mutant lung cancer, the G12C mutation comprises less than 2% of KRAS mutations in PDAC. Recently, the clinical candidate KRASG12D-selective inhibitor MRTX1133 (G12Di) has been shown to potently suppress both activation of the RAF-MEK-ERK signaling pathway downstream of KRAS and tumorigenic growth of KRASG12D-mutant PDAC in vitro and in vivo. Since KRASG12D represents 40% of KRAS-mutant PDAC, G12D-selective inhibitors hold promise as an effective therapy for a significant fraction of PDAC patients. However, the efficacy of these inhibitors is hindered by persistent challenges related to both primary (innate) and acquired treatment-associated resistance, which curtails the long-term effectiveness of likely all KRAS inhibitors. Here, our studies focus on unraveling the mechanism of primary and acquired resistance to G12Di treatment in PDAC. We applied a loss-of-function CRISPR screen targeting the druggable genome on KRASG12D-mutant PDAC cells treated with a sublethal concentration of G12Di to identify genes that modulate G12Di sensitivity. We identified loss of genes (e.g., CBL, RB1, and PTEN) found previously in patients who relapsed on G12Ci treatment, providing validation of the screen. One gene also identified was KEAP1. KEAP1 is known as a substrate-specific adapter of an E3 ubiquitin ligase complex that promotes the degradation of NRF2, and the loss of KEAP1 is commonly associated with increased stability of NRF2, a transcription factor that promotes the transcription of many anti-oxidative stress and pro-cell survival genes. We found that knockout of KEAP1 significantly compromised the ability of G12Di to inhibit PDAC cell proliferation in vitro. KEAP1 loss was associated with upregulated expression of NRF2, and concurrent CRISPR knockout of NRF2 restored sensitivity of G12Di in PDAC. Interestingly, we determined that G12Di-resistant KEAP1-deficient PDAC cells exhibited high dependence on glutaminase (GLS), which converts glutamine to glutamate. We further discovered that combination treatment with a glutaminase inhibitor (CB-839) synergistically enhanced G12Di growth suppression not only of KEAP1-knockout but also of parental PDAC cells. In summary, our study establishes a role for KEAP1 loss as a mechanism that drives PDAC resistance to KRAS inhibitors and identifies GLS inhibition as a possible approach to overcome NRF2-driven resistance. Citation Format: Wen-Hsuan Chang, Addison G. Stamey, Andrew M. Waters, Kirsten L. Bryant, Adrienne D. Cox, Channing J. Der. KEAP1-NRF2 mediated resistance against KRASG12D inhibitor in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1936.

Abstract 6043: Discovery and characterization of a p300-selective degrader with potent anti-tumor activity in CBP mutant cancers

Abstract Although precision medicine strategies for the treatment of human cancers are clinically successful, they have also revealed that only a small fraction of cancers carry actionable alterations in oncogenic drivers. To expand the druggable genome while maintaining an emphasis on genetically targeted therapies, recent efforts have focused on exploiting synthetic lethal relationships. Paralogous protein pairs are particularly compelling targets in this context due to the clear mechanistic basis for the synthetic lethality. As such, functional genomics screens as well as work from Ogiwara et al. have shown compelling rationale for targeting the histone acetylase transferase p300 in the context of CBP-deficient cancer types. We discovered potent heterobifunctional degraders with demonstrated selectivity for p300 over CBP. Our compound exhibits degradation of p300 within 2 hours (DC50 < 10nM, Dmax > 90%) with minimal impact on CBP through 48 h (DC50 >1uM, Dmax = 30%). Utilizing CRISPR-generated isogenic cell lines depleted for either CBP or p300, we observed significant growth inhibition in CBP knockout (KO) cells (gIC50 = 17nM) with minimal impact on growth of p300 KO (gIC50 = >10uM) or parental wild-type cells (gIC50 > 10uM). This translated to downstream pharmacology, where we observed a rapid and potent inhibition of global H3K27 acetylation in the CBP deficient context but a significantly attenuated response in p300 deleted or parental cells. We subsequently employed computational methods to identify and characterize CBP alterations, defining a putative loss-of-function (LoF) phenotype and confirming this sensitivity pharmacologically in cancer cell types harboring these endogenous mutations. Results mirrored what we observed with CBP depletion in these endogenous CBP LoF cell lines, with potent growth inhibition seen in multiple cell lines including LK-2 (gIC50 = 8nM), H1703 (gIC50 = 9nM), and TE-8 cells (gIC50 = 23nM). To confirm the in vitro results in an in vivo setting, we evaluated the response in mice harboring H1703 xenografts. Once daily oral administration of our compound led to almost complete degradation of p300 within H1703 xenograft tumors, resulting in a pronounced inhibition of tumor growth. Lastly, we profiled p300 degradation in human bone marrow derived myeloid progenitor colony-forming assays where we observed a significant reduction in toxicity (IC50 = 3.9uM) compared to a dual CBP/p300 inhibitor (IC50 = 121nM) or degrader (IC50 = 16nM), supporting the hypothesis that a p300-specific mechanism will offer an improved therapeutic index while maintaining anti-tumor efficacy in a biomarker population Taken together, our results suggest that a p300-selective degrader has the potential to serve as an effective therapeutic modality in CBP-mutated cancers. Citation Format: Mike R. Russell, Cassandra L. Lowenstein, Xuqing Zhang, Jeremy Roach, Jianing Song, Rakesh Nagilla, Nathan Kendsersky, Shreyas Joshi, Peter Orth, Matt Tudor, Qiaolin Deng, Clemente Aguilar-Bonavides, Elham Behshad, Sudeep Banjade, Zhihua Sui, Corey Strickland, Larry Jolivette, Helai P. Mohammad. Discovery and characterization of a p300-selective degrader with potent anti-tumor activity in CBP mutant cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6043.

Abstract 641: SCD1 upregulation due to STK11/KEAP1 loss upregulates SLC7A11 and causes deregulation of fatty acid metabolism leading to ferroptosis evasion

Abstract Introduction: Non-small cell lung cancer (NSCLC) with co-occurring loss-of-function (LOF) mutations in serine/threonine kinase 11 (STK11) and Kelch-like ECH-associated protein1 (KEAP1) (SK) are notably aggressive and unresponsive to chemo and immunotherapy, in current care standards. Novel therapeutic strategies are in demand to improve the outcomes for SK co-mutant NSCLC patients. We reported earlier that SK LOF mutations enhance cell proliferation and tumor growth in xenograft lung cancer models. We also found the ferroptosis evasion genes are enriched, and targeting ferroptosis regulators is a therapeutic opportunity in SK co-mutant NSCLC. Methods: We used CRISPR/Cas9 gene editing to create stable knockouts of STK11 (SKO), KEAP1 (KKO) or both (DKO), non-targeting control (NTC) in two NSCLC lines. We performed an in vitro druggable genome library CRISPR screening in the same NSCLC lines. We performed kinase profiling and RNA-seq in the cell lines to depict the transcriptomic and proteomic landscape, followed by western blotting and qRT-PCR validation. We also performed BODIPY/C11 assay and lipidomics to explore the ferroptosis and metabolic landscape of SK co-mutant NSCLC models. Results: Stearoyl CoA desaturase-1 (SCD1) was the top CRISPR screen hit, a critical modulator of fatty acid metabolism and ferroptosis evasion. SCD1 expression is significantly higher in NSCLC tissue than adjacent normal tissue (p<0.0001), and high SCD1 expression correlates with poorer prognosis in patients with NSCLC (p=0.027). GSEA from the bulk RNA sequencing in SK co-mutant cells pre-and post-SCD1 inhibitor treatment showed SCD1 inhibition leads to upregulation of the glutathione and glutamic acid pathways compared to NTC cells. Moreover, SK co-mutant cells have a significantly higher expression of SLC7A11, enabling cystine uptake and subsequent conversion to cysteine, essential for maintaining redox balance and cell survival. Hence, SK co-mutant cells are more resistant to cysteine depletion than NTC cells. SCD1 inhibition causes a decrease in SLC7A11 expression exclusively in DKO cells. Eventually, SCD1 inhibition leads to global metabolomic changes in SK co-mutant cells, including key pathways involved in lipid and glucose metabolism. Finally, genetic and pharmacological inhibition of SCD1 prevents tumor growth and sensitizes DKO cells to ferroptosis inducers like erastin. Conclusions: Our findings highlight the importance of the SCD1-SLC7A11 axis in regulating ferroptosis in SK co-mutant models. Current data impact our understanding of ferroptosis in NSCLC and its ability to target SCD1 or ferroptosis in cancer treatment. Compounds such as inhibitors of SLC7A11 (Erastin/IKE) are safe to use with acceptable toxicity and established doses. Hence, our study will facilitate the translation of ferroptosis inducers or SCD1 inhibitors in clinical trials. Citation Format: Utsav Sen, Charles Coleman, Dan Hasson, Triparna Sen. SCD1 upregulation due to STK11/KEAP1 loss upregulates SLC7A11 and causes deregulation of fatty acid metabolism leading to ferroptosis evasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 641.

TBK1, a prioritized drug repurposing target for amyotrophic lateral sclerosis: evidence from druggable genome Mendelian randomization and pharmacological verification in vitro

BackgroundThere is a lack of effective therapeutic strategies for amyotrophic lateral sclerosis (ALS); therefore, drug repurposing might provide a rapid approach to meet the urgent need for treatment.MethodsTo identify therapeutic targets associated with ALS, we conducted Mendelian randomization (MR) analysis and colocalization analysis using cis-eQTL of druggable gene and ALS GWAS data collections to determine annotated druggable gene targets that exhibited significant associations with ALS. By subsequent repurposing drug discovery coupled with inclusion criteria selection, we identified several drug candidates corresponding to their druggable gene targets that have been genetically validated. The pharmacological assays were then conducted to further assess the efficacy of genetics-supported repurposed drugs for potential ALS therapy in various cellular models.ResultsThrough MR analysis, we identified potential ALS druggable genes in the blood, including TBK1 [OR 1.30, 95%CI (1.19, 1.42)], TNFSF12 [OR 1.36, 95%CI (1.19, 1.56)], GPX3 [OR 1.28, 95%CI (1.15, 1.43)], TNFSF13 [OR 0.45, 95%CI (0.32, 0.64)], and CD68 [OR 0.38, 95%CI (0.24, 0.58)]. Additionally, we identified potential ALS druggable genes in the brain, including RESP18 [OR 1.11, 95%CI (1.07, 1.16)], GPX3 [OR 0.57, 95%CI (0.48, 0.68)], GDF9 [OR 0.77, 95%CI (0.67, 0.88)], and PTPRN [OR 0.17, 95%CI (0.08, 0.34)]. Among them, TBK1, TNFSF12, RESP18, and GPX3 were confirmed in further colocalization analysis. We identified five drugs with repurposing opportunities targeting TBK1, TNFSF12, and GPX3, namely fostamatinib (R788), amlexanox (AMX), BIIB-023, RG-7212, and glutathione as potential repurposing drugs. R788 and AMX were prioritized due to their genetic supports, safety profiles, and cost-effectiveness evaluation. Further pharmacological analysis revealed that R788 and AMX mitigated neuroinflammation in ALS cell models characterized by overly active cGAS/STING signaling that was induced by MSA-2 or ALS-related toxic proteins (TDP-43 and SOD1), through the inhibition of TBK1 phosphorylation.ConclusionsOur MR analyses provided genetic evidence supporting TBK1, TNFSF12, RESP18, and GPX3 as druggable genes for ALS treatment. Among the drug candidates targeting the above genes with repurposing opportunities, FDA-approved drug-R788 and AMX served as effective TBK1 inhibitors. The subsequent pharmacological studies validated the potential of R788 and AMX for treating specific ALS subtypes through the inhibition of TBK1 phosphorylation.

The identification of small molecule inhibitors with anthelmintic activities that target conserved proteins among ruminant gastrointestinal nematodes.

Gastrointestinal nematode (GIN) infections are a major concern for the ruminant industry worldwide and result in significant production losses. Naturally occurring polyparasitism and increasing drug resistance that potentiate disease outcomes are observed among the most prevalent GINs of veterinary importance. Within the five major taxonomic clades, clade Va represents a group of GINs that predominantly affect the abomasum or small intestine of ruminants. However, the development of effective broad-spectrum anthelmintics against ruminant clade Va GINs has been challenged by a lack of comprehensive druggable genome resources. Here, we first assembled draft genomes for three clade Va species (Cooperia oncophora, Trichostrongylus colubriformis, and Ostertagia ostertagi) and compared them with closely related ruminant GINs. Genome-wide phylogenetic reconstruction showed a relationship among ruminant GINs structured by taxonomic classification. Orthogroup (OG) inference and functional enrichment analyses identified 220 clade Va-specific and Va-conserved OGs, enriched for functions related to cell cycle and cellular senescence. Further transcriptomic analysis identified 61 taxonomically and functionally conserved clade Va OGs that may function as drug targets for new broad-spectrum anthelmintics. Chemogenomic screening identified 11 compounds targeting homologs of these OGs, thus having potential anthelmintic activity. In in vitro phenotypic assays, three kinase inhibitors (digitoxigenin, K-252a, and staurosporine) exhibited broad-spectrum anthelmintic activities against clade Va GINs by obstructing the motility of exsheathed L3 (xL3) or molting of xL3 to L4. These results demonstrate valuable applications of the new ruminant GIN genomes in gaining better insights into their life cycles and offer a contemporary approach to discovering the next generation of anthelmintics.IMPORTANCEGastrointestinal nematode (GIN) infections in ruminants are caused by parasites that inhibit normal function in the digestive tract of cattle, sheep, and goats, thereby causing morbidity and mortality. Coinfection and increasing drug resistance to current therapeutic agents will continue to worsen disease outcomes and impose significant production losses on domestic livestock producers worldwide. In combination with ongoing therapeutic efforts, advancing the discovery of new drugs with novel modes of action is critical for better controlling GIN infections. The significance of this study is in assembling and characterizing new GIN genomes of Cooperia oncophora, Ostertagia ostertagi, and Trichostrongylus colubriformis for facilitating a multi-omics approach to identify novel, biologically conserved drug targets for five major GINs of veterinary importance. With this information, we were then able to demonstrate the potential of commercially available compounds as new anthelmintics.

Integrative analysis of noncoding mutations identifies the druggable genome in preterm birth.

Preterm birth affects ~10% of pregnancies in the US. Despite familial associations, identifying at-risk genetic loci has been challenging. We built deep learning and graphical models to score mutational effects at base resolution via integrating the pregnant myometrial epigenome and large-scale patient genomes with spontaneous preterm birth (sPTB) from European and African American cohorts. We uncovered previously unidentified sPTB genes that are involved in myometrial muscle relaxation and inflammatory responses and that are regulated by the progesterone receptor near labor onset. We studied genomic variants in these genes in our recruited pregnant women administered progestin prophylaxis. We observed that mutation burden in these genes was predictive of responses to progestin treatment for preterm birth. To advance therapeutic development, we screened ~4000 compounds, identified candidate molecules that affect our identified genes, and experimentally validated their therapeutic effects on regulating labor. Together, our integrative approach revealed the druggable genome in preterm birth and provided a generalizable framework for studying complex diseases.

Unveiling potential drug targets for lung squamous cell carcinoma through the integration of druggable genome and genome-wide association data.

Background: Lung squamous cell carcinoma (LSCC) is a major subtype of lung cancer with poor prognosis and low survival rate. Compared with lung adenocarcinoma, yet no FDA-approved targeted-therapy has been found for lung squamous cell carcinoma. Methods: To identify potential drug targets for LSCC, Summary-data-based Mendelian randomization (SMR) analysis was used to examine the potential association between 4,543 druggable genes and LSCC, followed by colocalization analysis and HEIDI tests to confirm the robustness of the result. Phenome-wide association study (PheWAS) explored potential side effects of candidate drug targets. Enrichment analysis and protein-protein interaction networks revealed the function and significance of therapeutic targets. Single-cell expression analysis was used to examine cell types with enrichment expression of druggable genes in LSCC tissue. Drug prediction included screening potential drug candidates and evaluating their interactions with targets through molecular docking. Results: This research has identified ten significant drug targets for LSCC through a comprehensive SMR analysis. These targets included (COPA, PKD2L1, CCR1, C2, CYP21A2, and NCSTN as risk factors, and CCNA2, C4A, APOM, and LPAR2 as protective factors). PheWAS demonstrated that C2, CCNA2, LPAR2, and NCSTN exhibited associations with other phenotypes at the genetic level. Then, we found four potentially effective drugs with the Dsigdb database. Subsequently, molecular docking indicated that favorable binding interactions between drug candidates and potential target molecules. In the druggability evaluation, five out of ten drug target genes have been used in drug development (APOM, C4A, CCNA2, COPA, and PKD2L1). Six out of ten druggable genes showed significant expression in LSCC tissues (COPA, PKD2L1, CCR1, C2, NCSTN, LPAR2). Besides, Single-cell expression analysis revealed that C2 and CCNA2 were primarily enriched in macrophages, while COPA and NCSTN were enriched in both macrophages and epithelial cells. Conclusion: Our research revealed ten potential druggable genes for LSCC treatment, which might help to advance the precise and efficient therapeutic approaches of LSCC.

Abstract C048: Inducible activation of sgRNA libraries in tumor xenografts empowers large-scale in vivo target discovery screens

Abstract CRISPR-mediated genome editing is a powerful approach to understanding disease biology, including identifying genes essential for cancer cell proliferation, immune evasion and survival. We routinely use the technology to identify novel therapeutic targets for cancer using both in vitro and in vivo tumor models, focusing on targets that are synthetic lethal with tumor suppressor gene loss. Large-scale CRISPR screens are often conducted using in vitro cell culture systems as in vivo ‘drop-out’ screens face several bottlenecks resulting in poor sgRNA library representation and low signal to noise ratio. These inherent limitations of in vivo screens occur because only a small fraction of the injected cells contribute to xenograft tumor formation, and because of the uneven clonal expansion due to heterogenous growth conditions in the tumor microenvironment. Hence, many in vivo screens are underpowered for statistical analysis, resulting in a high rate of ‘false negatives’ or ‘false positives’ unless a large number of animals are used or the size of the sgRNA library is greatly reduced to overcome sampling noise. Here, we validate a novel in vivo screening technology, CRISPR-StAR (Stochastic Activation by Recombination), that overcomes these challenges by (i) activating the sgRNA library in established tumors and (ii) generating internally matched-pair controls for each sgRNA using molecular barcodes to capture the history of each clone within the tumor. Using this clonal information, we developed a robust computational pipeline that extracts meaningful target sgRNA-level data from individual tumors, despite the random under-representation of the larger library. Statistical (down-sampling) analysis revealed that CRISPR-StAR has a resolution of 1,000 sgRNAs per tumor which reduces the number of animals required by 7-fold to traditional approaches. Consequently, we have performed several druggable genome screens (~30,000 sgRNA) using just 30-40 individual tumors and identified a catalog of tumor suppressor genes that, when lost, strongly promote tumor growth in vivo without affecting cell proliferation in vitro. This group of genes is enriched with epigenetic modifiers, in particular multiple members of the COMPASS family and the SWI/SNF chromatin remodeling complexes. These results validate CRISPR-StAR as a powerful in vivo functional genomics platform for high throughput target discovery screens. Citation Format: Silvia Fenoglio, James Tepper, Lauren Grove, Esther CH Uijttewaal, Alborz Bejnood, Yi Yu, Hsin-Jung Wu, Annabel Devault, Shangtao Liu, Binzhang Shen, Samuel R Meier, Ashley H Choi, Tenzing Khendu, Hannah Stowe, Minjie Zhang, Brian B Haines, Alan Huang, Jannik N Andersen, Xuewen Pan, Ulrich Elling, Teng Teng. Inducible activation of sgRNA libraries in tumor xenografts empowers large-scale in vivo target discovery screens [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C048.

Genome Wide siRNA Screen Identifies CGAS-Sting Pathway As a Pharmacological Target That Promotes Survival of Hematopoietic Stem Cells Deficient in Fanconi Genes

Introduction Fanconi anemia (FA) is a homozygous recessive genetic disorder due to mutation in the Fanconi family of genes. The disease is characterized by early onset bone marrow failure and a predisposition to cancer. The FA genes are involved in DNA damage sensing and repair. Mutation in these genes leads to heightened DNA damage and extreme sensitivity to cross-linking agents. Hematopoietic stem cells of FA patients are defective in differentiation and self-renewal, leading to stem cell exhaustion and bone marrow failure early in life. The current treatment for bone marrow failure is allogeneic stem cell transplant from healthy donors. Due to difficulties in finding matching donors and the inherent problems associated with allogeneic transplants, pharmacological therapies that delay or prevent bone marrow failure are of clinical importance. Other proposed therapies including TGF-b, metformin, and resveratrol have met with limited clinical success. Methodology: To identify genes that promote survival of FA cells we performed a genome wide siRNA screen using isogenic pair of cell line with FANCD2 deletions and its corrected counterpart using transfection of siRNA libraries targeting 18,119 genes from Human Drug Targets, Human Druggable Genome, and Human Genome libraries at 2000 cells/well in 384-well plates followed by cell viability measurement after 72 hrs. We measured IRF3 phosphorylation and expression of immune related genes to analyze the CGAS-STING pathway. Using peripheral blood and bone marrow derived CD34+ cells transduced with lentivirus expressing shRNA against FANCD2 we tested the effect of CGAS inhibitor in promoting CFU-GM and CFU-E. Results: A genome wide siRNA screen identified IRF7 as one of the top 5 hits whose diminished expression resulted in increased viability of F-D2 mutant PD20 cells. IRF7 along with IRF3 serve as downstream transcription factors including various Toll-like receptors, CGAS-STING pathways, and other pattern recognition innate immune receptors. Using pIRF3 as an activation readout for CGAS-STING pathway we identified that both FANCD2 and FANCA mutant cells have elevated pIRF3 levels. The elevated pIRF3 levels were further increased upon addition of mitomycin C (MMC) in FA mutant cells as compared to gene corrected cells. The pIRF3 levels decreased upon both genetic KD and small molecule inhibition of both CGAS and STING. In line with increased pIRF3 FA mutant cells showed increased gene expression of various interferon-regulated genes, which were then also reduced by CGAS inhibitor. Overexpression of RNAseH1 partially reduced pIRF3 levels in FA mutant cells indicating that the RNA:DNA hybrids whose levels are elevated in FA mutant cells is one of the ligands of CGAS. Most importantly 10µM of CGAS inhibitor RU.51 was able to rescue FA-A mutant cell line 6914 cells from low dose MMC-induced cell death showing that the sensitivity of FA mutant cells to DNA damaging agents was at least partially driven by CGAS-STING pathway. We then tested if the protective effect of CGAS inhibitor extended to human CD34+ cells deficient in FA genes. 20µM of RU.51 was able to rescue the CFU-GM and CFU-E defects of CD34+ cells carrying lentiviral integrated shRNA against FANCD2 to a level to that in cells expressing non-silencing shRNAs. Interferon-regulated gene expression was also elevated in the FANCD2-deficient CD34+ cells, which was reversed by treatment with cGAS inhibitor. Conclusions: It has previously been shown that FA patients have elevated TNF-alpha, IFN-gamma levels, and NFkbactivation, and interferon alpha administration hastens the onset of bone marrow failure in FA patients. Our results show that FA mutant cells have elevated CGAS-STING signaling resulting in heightened interferon gene expression. Elevated R-loop levels in FA cells act as trigger for the CGAS-STING pathway. CGAS inhibitor is able to rescue low dose MMC-induced cell death in FA mutant fibroblasts and also restores the CFU-GM and CFU-E forming ability of CD34+ cells. These results indicate that CGAS-STING pathway is a pharmacologically tractable target to reverse the hematopoietic stem cell exhaustion seen in FA patients.

Dex-Benchmark: datasets and code to evaluate algorithms for transcriptomics data analysis.

Many tools and algorithms are available for analyzing transcriptomics data. These include algorithms for performing sequence alignment, data normalization and imputation, clustering, identifying differentially expressed genes, and performing gene set enrichment analysis. To make the best choice about which tools to use, objective benchmarks can be developed to compare the quality of different algorithms to extract biological knowledge maximally and accurately from these data. The Dexamethasone Benchmark (Dex-Benchmark) resource aims to fill this need by providing the community with datasets and code templates for benchmarking different gene expression analysis tools and algorithms. The resource provides access to a collection of curated RNA-seq, L1000, and ChIP-seq data from dexamethasone treatment as well as genetic perturbations of its known targets. In addition, the website provides Jupyter Notebooks that use these pre-processed curated datasets to demonstrate how to benchmark the different steps in gene expression analysis. By comparing two independent data sources and data types with some expected concordance, we can assess which tools and algorithms best recover such associations. To demonstrate the usefulness of the resource for discovering novel drug targets, we applied it to optimize data processing strategies for the chemical perturbations and CRISPR single gene knockouts from the L1000 transcriptomics data from the Library of Integrated Network Cellular Signatures (LINCS) program, with a focus on understudied proteins from the Illuminating the Druggable Genome (IDG) program. Overall, the Dex-Benchmark resource can be utilized to assess the quality of transcriptomics and other related bioinformatics data analysis workflows. The resource is available from: https://maayanlab.github.io/dex-benchmark.

KSFinder-a knowledge graph model for link prediction of novel phosphorylated substrates of kinases.

Aberrant protein kinase regulation leading to abnormal substrate phosphorylation is associated with several human diseases. Despite the promise of therapies targeting kinases, many human kinases remain understudied. Most existing computational tools predicting phosphorylation cover less than 50% of known human kinases. They utilize local feature selection based on protein sequences, motifs, domains, structures, and/or functions, and do not consider the heterogeneous relationships of the proteins. In this work, we present KSFinder, a tool that predicts kinase-substrate links by capturing the inherent association of proteins in a network comprising 85% of the known human kinases. We also postulate the potential role of two understudied kinases based on their substrate predictions from KSFinder. KSFinder learns the semantic relationships in a phosphoproteome knowledge graph using a knowledge graph embedding algorithm and represents the nodes in low-dimensional vectors. A multilayer perceptron (MLP) classifier is trained to discern kinase-substrate links using the embedded vectors. KSFinder uses a strategic negative generation approach that eliminates biases in entity representation and combines data from experimentally validated non-interacting protein pairs, proteins from different subcellular locations, and random sampling. We assess KSFinder's generalization capability on four different datasets and compare its performance with other state-of-the-art prediction models. We employ KSFinder to predict substrates of 68 "dark" kinases considered understudied by the Illuminating the Druggable Genome program and use our text-mining tool, RLIMS-P along with manual curation, to search for literature evidence for the predictions. In a case study, we performed functional enrichment analysis for two dark kinases - HIPK3 and CAMKK1 using their predicted substrates. KSFinder shows improved performance over other kinase-substrate prediction models and generalized prediction ability on different datasets. We identified literature evidence for 17 novel predictions involving an understudied kinase. All of these 17 predictions had a probability score ≥0.7 (nine at >0.9, six at 0.8-0.9, and two at 0.7-0.8). The evaluation of 93,593 negative predictions (probability ≤0.3) identified four false negatives. The top enriched biological processes of HIPK3 substrates relate to the regulation of extracellular matrix and epigenetic gene expression, while CAMKK1 substrates include lipid storage regulation and glucose homeostasis. KSFinder outperforms the current kinase-substrate prediction tools with higher kinase coverage. The strategically developed negatives provide a superior generalization ability for KSFinder. We predicted substrates of 432 kinases, 68 of which are understudied, and hypothesized the potential functions of two dark kinases using their predicted substrates.