Identification Of Novel Drug Targets Research Articles

Identification of novel drug targets for Helicobacter pylori: structure-based virtual screening of potential inhibitors against DAH7PS protein involved in the shikimate pathway

Identification of novel drug targets for Helicobacter pylori: structure-based virtual screening of potential inhibitors against DAH7PS protein involved in the shikimate pathway

Identifying prothrombin and bone sialoprotein as potential drug targets for idiopathic pulmonary fibrosis

BackgroundIdiopathic Pulmonary Fibrosis (IPF) is a fatal disease with scarce therapeutic alternatives, which imposes a significant economic burden on society. The identification of novel drug targets is thus critically essential. Plasma proteins with discernible causal evidence hold promise as viable drug targets for this condition.MethodsWe performed a proteome-wide Mendelian randomization (MR) analysis to assess the causal effects of 4,907 circulating proteins from the deCODE study on the risk of IPF from the Finngen Database (2,018 cases vs. 373,064 controls). We further replicated the MR analysis in 1426 proteins from the ARIC study and IPF from the UK Biobank (1,369 cases vs. 435,866 controls). Then a series of analyses including Bayesian colocalization, Steiger filtering, and phenotype scanning were conducted to validate the credibility of the MR results. Subsequently, protein-protein interaction (PPI) analysis, pathway enrichment analysis, and druggability assessment were executed to elucidate the underlying mechanisms. Finally, the findings were corroborated using a bleomycin-induced pulmonary fibrosis mouse model.ResultsThe MR analysis bolstered by robust evidence of colocalization, indicated a significant positive association between Prothrombin and increased IPF risk (OR = 3.26,95%CI 1.75–6.07). Conversely, Bone Sialoprotein (IBSP) demonstrated an inverse association with IPF susceptibility (OR = 0.27,95%CI 0.14–0.55).ConclusionsThe integrative analysis suggests that Prothrombin and IBSP are promising candidates as potential drug targets for IPF. Additional clinical investigations are warranted to substantiate these findings.

In Silico Identification of Novel Drug Targets in the Honeybee Pathogen Paenibacillus larvae and Molecular Docking Studies

In Silico Identification of Novel Drug Targets in the Honeybee Pathogen <i>Paenibacillus larvae</i> and Molecular Docking Studies

Identification of novel drug targets for osteoarthritis by integrating genetics and proteomes from blood

BackgroundOsteoarthritis (OA) is a degenerative osteoarticular disease, involving genetic predisposition. How the risk variants confer the risk of OA through their effects on proteins remains largely unknown. Therefore, we aimed to discover new and effective drug targets for OA and its subtypes.MethodsA proteome-wide association study (PWAS) was performed based on OA and its subtypes genome-wide association studies (GWAS) summary datasets and the protein quantitative trait loci (pQTL) data. Subsequently, Mendelian randomization (MR) and colocalization analysis was conducted to estimate the associations between protein and OA risk. The replication analysis was performed in an independent dataset of human plasma pQTL data.ResultsThe abundance of seven proteins was causally related to OA, two proteins to knee OA and six proteins to hip OA, respectively. We replicated 2 of these proteins using an independent pQTL dataset. With the further support of colocalization, and higher ECM1 level was causally associated with a higher risk of OA and hip OA. Higher PCSK1 level was causally associated with a lower risk of OA. And higher levels of ITIH1, EFEMP1, and ERLEC1 were associated with decreased risk of hip OA.ConclusionOur study provides new insights into the genetic component of protein abundance in OA and a promising therapeutic target for future drug development.

Integrating genome-wide CRISPR screens and in silico drug profiling for targeted antidote development.

Numerous toxins threaten humans, but specific antidotes are unavailable for most of them. Although CRISPR screening has aided the discovery of the mechanisms of some toxins, developing targeted antidotes remains a significant challenge. Recently, we established a systematic framework to develop antidotes by combining the identification of novel drug targets by using a genome-wide CRISPR screen with a virtual screen of drugs approved by the US Food and Drug Administration. This approach allows for a comprehensive understanding of toxin mechanisms at the whole-genome level and facilitates the identification of promising antidote drugs targeting specific molecules. Here, we present step-by-step instructions for executing genome-scale CRISPR-Cas9 knockout screens of toxins in HAP1 cells. We also provide detailed guidance for conducting an in silico drug screen and an in vivo drug validation. By using this protocol, it takes ~4 weeks to perform the genome-scale screen, 4 weeks for sequencing and data analysis, 4 weeks to validate candidate genes, 1 week for the virtual screen and 2 weeks for in vitro drug validation. This framework has the potential to accelerate the development of antidotes for a wide range of toxins and can rapidly identify promising drug candidates that are already known to be safe and effective. This could lead to the development of new antidotes much more quickly than traditional methods, protecting lives from diverse toxins and advancing human health.

Hepatocyte aquaporin 8-mediated water transport facilitates bile dilution and prevents gallstone formation in mice

Although water channel aquaporin-8 (AQP8) has been implicated in hepatic bile formation and liver diseases associated with abnormal bile flow in human and animal studies, direct evidence of its involvement in bile secretion is still lacking. This study aimed to determine the role of AQP8 in bile secretion and gallstone formation. We generated various transgenic knock-in and knockout mouse models and assessed liver AQP8 expression by immunostaining and immunoblotting, hepatic bile secretion by cannulation of the common bile duct, cholesterol gallstone formation by feeding a high-fat lithogenic diet, and identified regulatory small molecules by screening the organic fractions of cholagogic Chinese herbs and biochemical characterization. We identified a novel expression pattern of AQP8 protein in the canalicular membrane of approximately 50% of the liver lobules. AQP8-deficient mice exhibited impaired hepatic bile formation, characterized by the secretion of concentrated bile with a lower flow rate and higher levels of bile lipids than that of wild-type littermates. AQP8-/- mice showed accelerated gallstone formation, which was rescued by AAV-mediated hepatic expression of AQP8 or AQP1. Moreover, we identified a small molecule, scutellarin, that upregulates hepatocyte AQP8 expression in vitro and in vivo. In AQP8+/+ mice, scutellarin significantly increased bile flow, decreased bile lipid concentrations, and prevented gallstone formation compared to AQP8-/- mice. Molecular studies revealed that scutellarin promoted the ubiquitination and degradation of HIF-1α, a transcriptional negative regulator of AQP8, by disrupting its interactions with HSP90. AQP8 plays a crucial role in facilitating water transport and bile dilution during hepatic bile formation, thereby mitigating gallstone formation in mice. Small-molecule intervention validated hepatocyte AQP8 as a promising drug target for gallstone therapy. The incidence of gallstone disease is high, and current drug treatments for gallstones are very limited, necessitating the identification of novel drug targets for developing new drugs with universal applicability. To our knowledge, this is the first study to provide direct evidence that hepatic water channel AQP8 plays a key role in bile dilution and gallstone formation. Modulation of hepatic water transport may provide a universal therapeutic strategy for all types of gallstone diseases.

Identification of novel drug targets to counteract efflux pump mediated multidrug resistance in Acinetobacter baumannii

The emergence of multidrug-resistant (MDR) Acinetobacter baumannii poses an escalating threat to the healthcare system worldwide. A significant factor contributing to increasing resistance is the overexpression of chromosomally encoded efflux pumps, which expel antibiotics from bacterial cells, thereby rendering treatments less effective. The efflux pumps not only mediate resistance to antibiotics through drug efflux but also work synergistically with other resistance mechanisms, thereby doubling the resistance. Despite their crucial role in antibiotic resistance, understanding of the structure, function, mechanisms of action, and regulation of efflux pumps remains limited, which is necessary for devising effective strategies to restore drug susceptibility and to combat MDR isolates. In this context, the present study evaluated the prevalence of efflux pump overexpression in clinical A. baumannii isolates using phenotypic and genotypic methods and identified potential therapeutic targets employing a network-based approach. A total of 172 A. baumannii isolates were collected and subjected to antibiotic susceptibility tests using the Kirby-Bauer disk diffusion method. All the isolates were found to be MDR, with 94.76 % showing resistance to carbapenems. Efflux pump overexpression was detected in 54.65 % of isolates using the Ethidium-Bromide Agar Cartwheel method, and efflux pump inhibitory activity was observed in 68.71 % of isolates using cyanide m-chlorophenylhydrazone (CCCP). A total of thirteen efflux pump genes were detected in the tested isolates using diagnostic PCR, which were considered for interaction network analysis using STRING. Clustering analysis of the merged network identified two highly interconnected clusters, each comprising functional partners crucial for efflux pump function and regulation. Key hub genes, including AdeB, AdeJ, AdeK, AdeC, macB, tolC, AIL80285.1, AdeR, and AdeS, were identified as primary targets due to their significant influence on the network. Additionally, 24 clustered genes were pinpointed as potential drug targets for developing novel therapeutics to combat the formidable challenge of efflux pump-mediated MDR in A. baumannii.

RELA-mediated upregulation of LINC03047 promotes ferroptosis in silica-induced pulmonary fibrosis via SLC39A14

Long non-coding RNAs play a key role in silicosis, a fatal fibrotic lung disease, and there is an urgent need to develop new treatment targets. Long intergenic non-protein-coding RNA 3047 (LINC03047) is associated with cancer, but its role and mechanism in the progression of silicosis require further elucidation. This study investigated the function of LINC03047 in the epithelial-mesenchymal transition (EMT) during silicosis progression. LINC03047 expression was upregulated in SiO2-treated BEAS-2B and A549 cells, promoting SiO2-induced ferroptosis and subsequent EMT. Moreover, knockdown of LINC03047 significantly decreased the expression of solute carrier family 39 member 14 (SLC39A14), a ferrous iron transporter, and inhibition of SLC39A14 alleviated the ferroptosis and EMT caused by LINC03047 overexpression. We further investigated that NF-κB p65 (RELA) was critical for LINC03047 transcription in SiO2-treated BEAS-2B and A549 cells. In vivo experiments showed that SLC39A14 deficiency improved SiO2-induced lipid peroxidation and EMT. Collectively, our study reveals the function of the RELA/LINC03047/SLC39A14 axis in SiO2-induced ferroptosis and EMT, thereby contributing to the identification of novel drug targets for silicosis therapy.

Unraveling the Roles of Neuropeptides in the Chemosensation of the Root-Knot Nematode Meloidogyne javanica.

The identification of novel drug targets in plant-parasitic nematodes (PPNs) is imperative due to the loss of traditional nematicides and a lack of replacements. Chemosensation, which is pivotal for PPNs in locating host roots, has become a focus in nematode behavioral research. However, its underlying molecular basis is still indistinct in such a diverse group of PPNs. To characterize genes participating in chemosensation in the Javanese root-knot nematode Meloidogyne javanica, RNA-sequencing of the second-stage juveniles (J2s) treated with tomato root exudate (TRE) for 1 h and 6 h was performed. Genes related to chemosensation in M. javanica mainly responded to TRE treatment at 1 h. Moreover, a gene ontology (GO) analysis underscored the significance of the neuropeptide G protein-coupled receptor signaling pathway. Consequently, the repertoire of putative neuropeptides in M. javanica, including FMRFamide-like peptides (FLPs), insulin-like peptides (ILPs), and neuropeptide-like peptides (NLPs), were outlined based on a homology analysis. The gene Mjflp-14a, harboring two neuropeptides, was significantly up-regulated at 1 h TRE treatment. Through peptide synthesis and J2 treatment, one of the two neuropeptides (MjFLP-14-2) was proven to influence the J2 chemotaxis towards tomato root tips. Overall, our study reinforces the potential of nematode neuropeptides as novel targets and tools for root-knot nematode control.

Functional Genomics and Insights into the Pathogenesis and Treatment of Psoriasis.

Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1-3% of the world's population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with Genome-Wide Association (GWAS) studies showing that many psoriasis risk genes lie along the IL-23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. This review is focused on the IL-23/Th17 axis, providing an insight into key cell types, cytokines, and intracellular signaling pathways involved. This includes examination of currently available biological treatments, time to relapse post drug withdrawal, and rates of primary/secondary drug failure, showing the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely to reduce the burden of disease for the longest period possible.

Identification of new potent NLRP3 inhibitors by multi-level in-silico approaches

Nod-like receptor protein 3 (NLRP-3), is an intracellular sensor that is involved in inflammasome activation, and the aberrant expression of NLRP3 is responsible for diabetes mellitus, its complications, and many other inflammatory diseases. NLRP3 is considered a promising drug target for novel drug design. Here, a pharmacophore model was generated from the most potent inhibitor, and its validation was performed by the Gunner-Henry scoring method. The validated pharmacophore was used to screen selected compounds databases. As a result, 646 compounds were mapped on the pharmacophore model. After applying Lipinski's rule of five, 391 hits were obtained. All the hits were docked into the binding pocket of target protein. Based on docking scores and interactions with binding site residues, six compounds were selected potential hits. To check the stability of these compounds, 100 ns molecular dynamic (MD) simulations were performed. The RMSD, RMSF, DCCM and hydrogen bond analysis showed that all the six compounds formed stable complex with NLRP3. The binding free energy with the MM-PBSA approach suggested that electrostatic force, and van der Waals interactions, played a significant role in the binding pattern of these compounds. Thus, the outcomes of the current study could provide insights into the identification of new potential NLRP3 inflammasome inhibitors against diabetes and its related disorders.

Identification of Novel Drug Targets for Alzheimer’s Disease by Integrating Genetics and Proteomes from Brain and Blood (P7-9.012)

Identification of Novel Drug Targets for Alzheimer’s Disease by Integrating Genetics and Proteomes from Brain and Blood (P7-9.012)

Abstract LB432: Identification of novel drug targets using the ADAPT biotargeting system on FFPE tissue from patients with glioblastoma multiforme

Abstract Glioblastoma Multiforme (GBM) is one of the most aggressive and lethal brain tumor types with a five-year survival rate of 6.9%. In 2023, more than 14,490 Americans were expected to receive a diagnosis. Although great progress has been achieved in protein target identification and treatment over the last few years, current treatment options are limited, and tumor recurrence occurs at a high rate due to treatment resistance. Aptamers, short single-stranded oligonucleotide ligands with high-affinity binding to molecular targets, are well suited tools for exploring novel targets in highly heterogeneous tumors with complex etiologies like GBM, where clinically relevant biomarkers are limited. In this study, aptamer-based cancer-specific drug target identification was performed by Adaptive Dynamic Artificial Polyligand Targeting (ADAPT) Biotargeting System. In short, a GBM-specific library was enriched through a Systematic Evolution of Ligands by EXponential enrichment (SELEX) process using micro dissected Formalin-Fixed Paraffin-Embedded (FFPE) tissues from GBM patients, along with whole body normal tissue for counterselection. Microdissection of tissue allows the partitioning of different types of cells to focus on specific cells of interest. The enriched libraries have been evaluated on clinical GBM and normal brain control samples through aptamer mediated tissue staining, resulting in preferential binding of enriched libraries compared to controls in the vast majority of GBM patients with little binding to normal brain samples. The final library was subsequently applied in an in-house developed library-based affinity pull-down assay using lysates from FFPE tissue of the same group of GBM patients and normal brain samples, followed by unbiased Mass Spectrometry for protein target identification. Combining the results from this proteomics analysis and data from the internal Whole Transcriptome Sequencing (WTS) database, we were able to identify several targets that are highly expressed in GBM and other cancer lineages. Antibody staining provided further validation of the expression levels and the cellular localization. The targets identified in this study include not only potential novel therapeutic targets, but also well-studied biomarkers and targets with available drugs already in clinical trials, demonstrating the platform has great potential for identifying high affinity binding and selectivity compared to traditional proteomics and other methods in drug target discovery. Citation Format: Xixi Wei, Myunggi An, Radhika Santhanam, Barbara Richardson, Lucas Vu, Justin Saul, Anna Walton, Michael Gee, Daniel Martin, Amanda Hubbard, Alexis Rodin, Matthew Rosenow, Tassilo Hornung. Identification of novel drug targets using the ADAPT biotargeting system on FFPE tissue from patients with glioblastoma multiforme [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB432.

A reconstructed genome-scale metabolic model of Helicobacter pylori for predicting putative drug targets in clarithromycin and rifampicin resistance conditions.

Helicobacter pylori is considered a true human pathogen for which rising drug resistance constitutes a drastic concern globally. The present study aimed to reconstruct a genome-scale metabolic model (GSMM) to decipher the metabolic capability of H. pylori strains in response to clarithromycin and rifampicin along with identification of novel drug targets. The iIT341 model of H. pylori was updated based on genome annotation data, and biochemical knowledge from literature and databases. Context-specific models were generated by integrating the transcriptomic data of clarithromycin and rifampicin resistance into the model. Flux balance analysis was employed for identifying essential genes in each strain, which were further prioritized upon being nonhomologs to humans, virulence factor analysis, druggability, and broad-spectrum analysis. Additionally, metabolic differences between sensitive and resistant strains were also investigated based on flux variability analysis and pathway enrichment analysis of transcriptomic data. The reconstructed GSMM was named as HpM485 model. Pathway enrichment and flux variability analyses demonstrated reduced activity in the ribosomal pathway in both clarithromycin- and rifampicin-resistant strains. Also, a significant decrease was detected in the activity of metabolic pathways of clarithromycin-resistant strain. Moreover, 23 and 16 essential genes were exclusively detected in clarithromycin- and rifampicin-resistant strains, respectively. Based on prioritization analysis, cyclopropane fatty acid synthase and phosphoenolpyruvate synthase were identified as putative drug targets in clarithromycin- and rifampicin-resistant strains, respectively. We present a robust and reliable metabolic model of H. pylori. This model can predict novel drug targets to combat drug resistance and explore the metabolic capability of H. pylori in various conditions.

Metabolic Signature of Warburg Effect in Cancer: An Effective and Obligatory Interplay between Nutrient Transporters and Catabolic/Anabolic Pathways to Promote Tumor Growth.

Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves the production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in the cancer-cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways that include amino acid metabolism, one-carbon metabolism, the pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of the expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates metabolic reprogramming, which has become a hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for the development of a new generation of therapeutics to treat cancer.

Post-translational modifications of Keap1: the state of the art.

The Keap1-Nrf2 signaling pathway plays a crucial role in cellular defense against oxidative stress-induced damage. Its activation entails the expression and transcriptional regulation of several proteins involved in detoxification and antioxidation processes within the organism. Keap1, serving as a pivotal transcriptional regulator within this pathway, exerts control over the activity of Nrf2. Various post-translational modifications (PTMs) of Keap1, such as alkylation, glycosylation, glutathiylation, S-sulfhydration, and other modifications, impact the binding affinity between Keap1 and Nrf2. Consequently, this leads to the accumulation of Nrf2 and its translocation to the nucleus, and subsequent activation of downstream antioxidant genes. Given the association between the Keap1-Nrf2 signaling pathway and various diseases such as cancer, neurodegenerative disorders, and diabetes, comprehending the post-translational modification of Keap1 not only deepens our understanding of Nrf2 signaling regulation but also contributes to the identification of novel drug targets and biomarkers. Consequently, this knowledge holds immense importance in the prevention and treatment of diseases induced by oxidative stress.

Identification of novel drug targets for Alzheimer’s disease by integrating genetics and proteomes from brain and blood

AbstractBackgroundGenome‐wide association studies (GWASs) have discovered numerous risk genes for Alzheimer’s disease (AD), but how these genes confer AD risk is challenging to decipher.MethodTo efficiently transform genetic associations into drug targets for AD, we employed an integrative analytical pipeline using proteomes in brain and blood by systematically applying proteome‐wide association study (PWAS), Mendelian randomization (MR) and Bayesian colocalization.ResultCollectively, we identified the brain protein abundance of 7 genes (ACE, ICA1L, TOM1L2, SNX32, EPHX2, CTSH, and RTFDC1) are causal in AD (P&lt;0.05/proteins identified for PWAS and MR; PPH4&gt;80% for Bayesian colocalization). The proteins encoded by these genes were mainly expressed on the surface of glutamatergic neurons and astrocytes. Of them, ACE with its protein abundance was also identified in significant association with AD on the blood‐based studies and showed significance at the transcriptomic level. SNX32 was also found to be associated with AD at the blood transcriptomic level.ConclusionOur current study results on genetic, proteomic and transcriptomic approaches has identified compelling genes, which may provide important leads to design future functional studies and potential drug targets for AD.

IFNγ Signaling in Acute Myeloid Leukemia Mediates Immunomodulation and Reveals Therapeutic Strategies

Background: Interferon gamma (IFNγ) is a critical cytokine known for its diverse roles in immune regulation, inflammation, and tumor surveillance. Studies have reported the dichotomous nature of IFNγ signaling in both the pathogenesis of cancer and immunotherapy response. However, its complex interplay with acute myeloid leukemia (AML) remains insufficiently understood. Methods: Three independent RNA-seq datasets were integrated to disentangle the IFNγ signaling in AML. We also performed single cell RNA sequencing (scRNA) on 20 newly diagnosed AML patients to discern relative contribution of cells and cellular communications for IFNγ signaling. Results: Single-sample gene set enrichment analysis was used to examine the transcriptional programs linked to IFNγ signaling in 672 newly diagnosed adult AML patients. We observed higher IFNγ signaling score in subgroups of patients including diploid with monocytic differentiation, inv16 core-binding-factor AML, and del7/7q. Notably, sorted CD34 + cells from 17 healthy donors had markedly lower levels of IFNγ signaling scores than did those from AML patients, making it a predominant feature in AML. Additionally, we found significant positive correlations between IFNγ signaling score and expression of its downstream targets HLA class 1 and 2 as well as T cell dysfunction score, T cell exhaustion score, and T cell senescence score, consistent with the fact that chronic IFNγ can drive T cell dysfunction. In scRNA, we observed that AML cells in patients with diploid monocytic AML had the highest expression of IFNγ signaling followed by del7/7q, while the non-monocytic, diploid AML cells had the lowest (Figure 1A). We then explored whether IFNγ signaling is differentially activated across the AML hierarchies and found the spectrum along the hierarchy with the primitive cells displaying significant higher IFNγ signaling than GMP while reaching the highest in Mono-like state. Transcription factor analysis revealed high regulon activity of interferon regulator factors (IRFs) in AML cells, with elevated levels of IRF1 and IRF5 regulons in del7/7q and del5/5q, respectively and elevated IRF8 regulon in diploid AML cells with monocytic differentiation, consistent with its role as a lineage-determinant factor promoting monocytic differentiation. Cell-cell interactions revealed IFNγ from CD8 T cells and NK cells as a top interaction to AML cells. These observations indicate that the activation levels of IFNγ signaling in AML cells are associated with distinct cellular states and hierarchies, and that disparate regulons of IFNγ signaling characterize distinct patient subgroups. The high level of IFNγ signaling in monocytic patient prompted us to assess its correlation with drug response as monocytic subclones are suggested to have inherent resistance to venetoclax. In BEAT-AML ex vivo drug test data, we found a strong positive correlation between IFNγ signaling score and venetoclax resistance, indicating that IFNγ signaling confers venetoclax resistance. This correlation was validated in an independent cohort. However, the IFNγ signaling score did not predict survival outcomes in our bulk cohort. Therefore, we defined a light weighted IFNγ signature to improve the prognostic sensitivity using the least absolute shrinkage and selection operator model. After regression, 47 genes related to survival were retained, forming a parsimonious IFNγ signature. The new parsimonious IFNγ score revealed a tight positive correlation with HLA class 1 and 2 scores. Importantly, this parsimonious IFNγ score was able to predict patient outcomes in our bulk cohort, whereby a higher score predicted worse survival (Figure 1B). Ultimately, these results suggest that the IFNγ pathway activation is associated with resistance to venetoclax-based therapy and can predict patient outcomes independently of known risk factors, making it a promising target for therapeutic intervention. Conclusions: Characterization of inflammation in AML using independent bulk and scRNA profiling led to the identification of novel drug targets and mechanisms of resistance to targeted therapy. We identified monocytic AML as having a unique microenvironment characterized by high IFNγsignaling in AML cells and immunosuppressive features. IFNγ signaling scores correlated strongly with venetoclax resistance. A parsimonious IFNγ gene signature demonstrated robust prognostic value.

New therapeutic targets to prevent benign prostatic enlargement and symptomatic progression to benign prostatic obstruction-ICI-RS 2023.

Benign prostatic enlargement (BPE) can impact lower urinary tract function due to its potential progression to benign prostatic obstruction (BPO). Treatment options include removal of the obstruction by surgery or through use of therapeutics designed to slow growth or reduce tissue stress imposed by muscular stromal components. Inflammation and development of fibrosis can also raise intrinsic tissue stress within the gland, further impacting obstruction. Outflow tract obstruction can also impact emission and ejaculation if the obstruction persists. This review summarizes an ICI-RS think tank considering novel drug treatments that might address BPO caused by progressive development of BPE, as well as manage decompensation changes to bladder function. Topics included recent advances in our understanding of pathological changes occurring to the prostate and other lower urinary tract tissues during progressive development of BPE, and how prevention or reversal might benefit from the identification of novel drug targets. These included contractile properties of prostatic tissues, the impact of BPE and its effects on bladder function, the deposition of intramural fibrotic tissue with protracted BPO, the role of inflammation in the development of BPE and its progression to BPO. In particular, we discussed current therapeutic options for treating BPE/BPO, and new therapeutic targets, what they treat and their advantage over current medications. Several new drug targets were identified, including soluble guanylate cyclase (sGC), the receptor for nitric oxide (NO•), and sGC activators that promotes sGC-mediated cGMP production when sGC is inactivated and unresponsive to NO•.

Comparative Analysis and Drug Target Identification of Human Kidney Cancer

Abstract: Kidney cancer, particularly renal cell carcinoma (RCC), is a significant global health concern characterized by its high morbidity and mortality rates. In this study, we employ a multifaceted approach to gain insights into the molecular mechanisms underlying kidney cancer and to identify potential drug targets for therapeutic intervention. To achieve this, we conducted a comprehensive comparative analysis of gene expression profiles in normal and cancerous kidney tissues, utilizing tools such as BLAST and gene analysis from the COSMIC database. This analysis allowed us to identify key genetic alterations and pathways associated with kidney cancer progression. Furthermore, molecular docking simulations were performed to predict potential drug candidates that could target specific proteins implicated in kidney cancer development. The aim was to prioritize molecules with high binding affinity and therapeutic potential. Additionally, cobalt analysis was utilized to investigate the metalloprotein content within kidney cancer cells, shedding light on potential metalloprotein targets for drug development.The results of this study provide valuable insights into the molecular basis of kidney cancer, offering a foundation for the identification of novel drug targets and the development of targeted therapies for this life-threatening disease. These findings contribute to our understanding of kidney cancer pathogenesis and may ultimately improve patient outcomes and the overall management of this challenging malignancy.