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IL-4 and IL-13 have non-redundant effects in olfaction, with loss of smell in mice evoked only by intranasal administration of IL-4, but not IL-13. IL-4-evoked pathophysiological effects on olfaction is independent of compromised structural integrity of the olfactory neuroepithelium. IL-4-IL-4Rα signaling modulates neuronal crosstalk with immune cells, suggesting a functional link between olfactory impairment and neuroinflammation. Abbreviations: IL, interleukin; KO, knock-out; wk, week; WT, wild-type., (© 2024 Sanofi and Regeneron Pharmaceuticals. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.)

Background: There is evidence of pathophysiologic diversity in chronic rhinosinusitis with nasal polyps (CRSwNP), but data characterizing the molecular endotypes of CRSwNP and their association with treatment are lacking., Objective: This study aimed to identify gene signatures associated with CRSwNP endotypes, clinical features, and dupilumab treatment response., Methods: Nasal brushing samples were collected from 89 patients randomized to dupilumab 300 mg every 2 weeks or placebo in the SINUS-52 trial (NCT02898454). Microarrays were used to identify transcriptional clusters and assess the relationship between gene expression and baseline clinical features and clinical response to dupilumab. Endotype signatures were determined using differential expression analysis., Results: Two distinct transcriptional clusters (C1 and C2) were identified, both with elevated type 2 biomarkers. At baseline, C2 patients had higher mean Nasal Polyp Score and higher type 2 biomarker levels than C1 patients. At week 24, significant improvements in clinical outcomes (dupilumab vs placebo) were observed in both clusters, although the magnitude of improvements was significantly greater in C2 than in C1, and more C2 patients demonstrated clinically meaningful responses. Gene set enrichment analysis supported the existence of 2 molecular endotypes: C2 was enriched in genes associated with type 2 inflammation (including periostin, cadherin-26, and type 2 cysteine protease inhibitors), while C1 was enriched in genes associated with T cell activation and IL-12 production., Conclusions: Two distinct gene signatures associated with CRSwNP clinical features were identified; the endotype signatures were associated with clinical outcome measures and magnitude of dupilumab response., Competing Interests: Disclosure Statement This study was sponsored by Sanofi and Regeneron Pharmaceuticals Inc. Disclosure of potential conflict of interest: K. Gayvert, J. Horowitz, J. D. Hamilton, and W. K. Lim are employees of Regeneron Pharmaceuticals Inc, and may hold stock and/or stock options in the company. M. Desrosiers reports clinical trial funding from AstraZeneca, GlaxoSmithKline, Probionase Therapies, and Sanofi; is an advisory board member of Regeneron Pharmaceuticals Inc and Sanofi; and is an equity holder in Probionase Therapies. T. M. Laidlaw is an advisory board member for GlaxoSmithKline, Novartis, Regeneron Pharmaceuticals Inc, and Sanofi. L. P. Mannent, K. Patel, and A. Jagerschmidt are employees of Sanofi and may hold stock and/or stock options in the company. N. Amin and S. Harel are former employees of Regeneron Pharmaceuticals Inc and may hold stock and/or stock options in the company., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Although recent efforts have led to the development of highly effective androgen receptor (AR)-directed therapies for the treatment of advanced prostate cancer, a significant subset of patients will progress with resistant disease including AR-negative tumors that display neuroendocrine features [neuroendocrine prostate cancer (NEPC)]. On the basis of RNA sequencing (RNA-seq) data from a clinical cohort of tissue from benign prostate, locally advanced prostate cancer, metastatic castration-resistant prostate cancer and NEPC, we developed a multi-step bioinformatics pipeline to identify NEPC-specific, overexpressed gene transcripts that encode cell surface proteins. This included the identification of known NEPC surface protein CEACAM5 as well as other potentially targetable proteins (e.g., HMMR and CESLR3). We further showed that cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) knockdown results in reduced NEPC tumor cell proliferation and migration in vitro . We provide in vivo data including laser capture microdissection followed by RNA-seq data supporting a causal role of CELSR3 in the development and/or maintenance of the phenotype associated with NEPC. Finally, we provide initial data that suggests CELSR3 is a target for T-cell redirection therapeutics. Further work is now needed to fully evaluate the utility of targeting CELSR3 with T-cell redirection or other similar therapeutics as a potential new strategy for patients with NEPC., Significance: The development of effective treatment for patients with NEPC remains an unmet clinical need. We have identified specific surface proteins, including CELSR3, that may serve as novel biomarkers or therapeutic targets for NEPC., (© 2023 The Authors; Published by the American Association for Cancer Research.)

The common γ chain (γc; IL-2RG) is a subunit of the interleukin (IL) receptors for the γc cytokines IL-2, IL-4, IL-7, IL-9, IL-15, and IL-21. The lack of appropriate neutralizing antibodies recognizing IL-2RG has made it difficult to thoroughly interrogate the role of γc cytokines in inflammatory and autoimmune disease settings. Here, we generated a γc cytokine receptor antibody, REGN7257, to determine whether γc cytokines might be targeted for T cell-mediated disease prevention and treatment. Biochemical, structural, and in vitro analysis showed that REGN7257 binds with high affinity to IL-2RG and potently blocks signaling of all γc cytokines. In nonhuman primates, REGN7257 efficiently suppressed T cells without affecting granulocytes, platelets, or red blood cells. Using REGN7257, we showed that γc cytokines drive T cell-mediated disease in mouse models of graft-versus-host disease (GVHD) and multiple sclerosis by affecting multiple aspects of the pathogenic response. We found that our xenogeneic GVHD mouse model recapitulates hallmarks of acute and chronic GVHD, with T cell expansion/infiltration into tissues and liver fibrosis, as well as hallmarks of immune aplastic anemia, with bone marrow aplasia and peripheral cytopenia. Our findings indicate that γc cytokines contribute to GVHD and aplastic anemia pathology by promoting these characteristic features. By demonstrating that broad inhibition of γc cytokine signaling with REGN7257 protects from immune-mediated disorders, our data provide evidence of γc cytokines as key drivers of pathogenic T cell responses, offering a potential strategy for the management of T cell-mediated diseases.

Drug target identification is a crucial step in development, yet is also among the most complex. To address this, we develop BANDIT, a Bayesian machine-learning approach that integrates multiple data types to predict drug binding targets. Integrating public data, BANDIT benchmarked a ~90% accuracy on 2000+ small molecules. Applied to 14,000+ compounds without known targets, BANDIT generated ~4,000 previously unknown molecule-target predictions. From this set we validate 14 novel microtubule inhibitors, including 3 with activity on resistant cancer cells. We applied BANDIT to ONC201-an anti-cancer compound in clinical development whose target had remained elusive. We identified and validated DRD2 as ONC201's target, and this information is now being used for precise clinical trial design. Finally, BANDIT identifies connections between different drug classes, elucidating previously unexplained clinical observations and suggesting new drug repositioning opportunities. Overall, BANDIT represents an efficient and accurate platform to accelerate drug discovery and direct clinical application.

Inhibition of oncogenes and reactivation of tumor suppressors are well-established goals in anticancer drug development. Unfortunately many oncogenes and tumor suppressors are not classically druggable, in that they lack a targetable enzymatic activity and associated binding pockets that small molecule drugs can be directed to. This is especially relevant for transcription factors, which have long been thought to be undruggable. To address this gap, we have developed and described CRAFTT, a broadly applicable computational drug-repositioning approach for targeting transcription factors. CRAFTT combines transcription factor target gene sets with drug-induced expression profiling to identify small molecules that can perturb transcription factor activity. Network analysis is then used to derive a modulation index (MI) and prioritize predictions.

CRISPR loci are a cluster of repeats separated by short "spacer" sequences derived from prokaryotic viruses and plasmids that determine the targets of the host's CRISPR-Cas immune response against its invaders. For type I and II CRISPR-Cas systems, single-nucleotide mutations in the seed or protospacer adjacent motif (PAM) of the target sequence cause immune failure and allow viral escape. This is overcome by the acquisition of multiple spacers that target the same invader. Here we show that targeting by the Staphylococcus epidermidis type III-A CRISPR-Cas system does not require PAM or seed sequences, and thus prevents viral escape via single-nucleotide substitutions. Instead, viral escapers can only arise through complete target deletion. Our work shows that, as opposed to type I and II systems, the relaxed specificity of type III CRISPR-Cas targeting provides robust immune responses that can lead to viral extinction with a single spacer targeting an essential phage sequence., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The transition from castration-resistant prostate adenocarcinoma (CRPC) to neuroendocrine prostate cancer (NEPC) has emerged as an important mechanism of treatment resistance. NEPC is associated with overexpression and gene amplification of MYCN (encoding N-Myc). N-Myc is an established oncogene in several rare pediatric tumors, but its role in prostate cancer progression is not well established. Integrating a genetically engineered mouse model and human prostate cancer transcriptome data, we show that N-Myc overexpression leads to the development of poorly differentiated, invasive prostate cancer that is molecularly similar to human NEPC. This includes an abrogation of androgen receptor signaling and induction of Polycomb Repressive Complex 2 signaling. Altogether, our data establishes N-Myc as an oncogenic driver of NEPC., (Copyright © 2016 Elsevier Inc. All rights reserved.)

In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population level, and a Human Immunodeficiency Virus (HIV) within host infection model. While the first has a low species count and few transitions, the second is more complex with a comparable number of species involved. The relative efficiency of each algorithm is determined based on computational time and degree of precision required. The numerical results suggest that all three algorithms have the similar computational efficiency for the simpler VRE model, and the SSA is the best choice due to its simplicity and accuracy. In addition, we have found that with the larger and more complex HIV model, implementation and modification of tau-Leaping methods are preferred.