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ATR kinase inhibitors induce mitochondrial fission in CD8+ T cells and impair immune memory in vivo

The DNA damage response kinase ATR restrains CDK1 activity during S and G2 phases of the cell cycle, confining CDK1-driven processes to mitosis. ATR kinase inhibitors were originally developed to potentiate chemotherapy-induced DNA damage at stalled replication forks and to disrupt DNA damage-induced cell cycle checkpoints. Recent evidence, however, reveals that these inhibitors also disrupt cell cycle organization in cells that have not sustained any DNA damage. We show that ATR kinase inhibitors potently trigger unscheduled mitochondrial fission, causing loss of mitochondrial mass in actively dividing CD8+ T cells that persists in memory CD8+ T cells. Moreover, ATR inhibition during the peak of CD8+ T cell expansion in a mouse model of LCMV Armstrong infection impairs the formation of immune memory. These findings carry significant clinical implications. ATR kinase inhibitors are currently being evaluated in clinical trials in combination with chemotherapy, radiation, and immune checkpoint inhibitors in patients where anti-tumor immune responses are recognized as a determinant of durable response. Our results identify an unexpected consequence of ATR inhibition that disrupts cellular metabolism with broad implications for both preclinical research and clinical application.

cancer biology↗

Peripheral microbial metabolites as indicators of gut microbiome disruption: systematic review and meta-analysis

BackgroundGut microbiome disruption is often characterized by loss of obligate anaerobic bacteria, which may lead to altered production of microbial metabolites that can be detected peripherally. The application of widely used sequencing-based microbiome analyses to clinical settings is limited by cost, turnaround time, and challenges with patients with very low stool output. Since some products of strictly bacterial metabolism detectable in blood, peripheral metabolites may provide a potentially rapid and scalable indicator of gut microbiome composition and function. We performed a systematic review and meta-analysis of studies reporting circulating microbial metabolites and gut microbiome composition to evaluate whether peripheral microbial metabolites could identify gut microbiome perturbation. ResultsCandidate metabolites were identified systematically across an independent set of studies reporting metabolite-microbiome associations, enabling assessment of reproducibility across disease states and cohorts. We performed a meta-analysis of 19 human cohorts comprising 3242 participants with paired blood metabolite and stool microbiome data. Anaerobe depletion (obligate anaerobe relative abundance <0.70 by sequencing) was associated with decreased products of anaerobic microbial metabolism. Combinations of metabolites distinguished individuals with anaerobe-depleted microbiomes from those without. Circulating metabolite levels distinguished between cases and controls with similar performance as gut microbiome composition across a range of health/disease states, and changed markedly within patients experiencing gut anaerobe depletion after antibiotic exposure. ConclusionsCirculating microbial metabolites are potentially informative indicators of gut microbiome disruption and may serve as a rapid and method for patient stratification in clinical trials or acute care settings. ImportanceCirculating microbial metabolites represent a practical and scalable approach to detecting significant gut microbiome disruption, particularly loss of obligate anaerobes. Unlike stool-based sequencing, which can be logistically challenging and slow, blood-based metabolite profiling could be actionably integrated into existing clinical workflows. Our findings suggest metabolites capture compositional consequences of microbiome collapse, with performance comparable to direct microbiome profiling in distinguishing disease states. Enabling diagnostic enrichment and real-time monitoring of microbiome injury (e.g., during antibiotic use or critical illness) has potential implications for both clinical care and research, including selection of patients for investigation of microbiome-targeted therapies. With further validation, circulating metabolites could provide an accessible surrogate for gut microbiome composition in settings where sequencing is impractical.

microbiology↗

Reconstructing tumor trajectories during therapy through integration of multiple measurement modalities.

BackgroundAccurately determining changes in tumor size during therapy is essential to evaluating response or progression. However, individual imaging methodologies often poorly reflect pathologic response and long-term treatment efficacy in patients with estrogen receptor positive (ER+) early-stage breast cancer. Mathematical models that measure tumor progression over time by integrating diverse imaging and tumor measurement modalities are not currently used but could increase accuracy in measuring response and provide biological insights into cancer evolution. MethodsFor ER+ breast cancer patients enrolled on a neoadjuvant clinical trial, we reconstructed their tumor size trajectories during therapy by combining all available information on tumor size, including different imaging modalities, physical examinations and pathological assessment data. Tumor trajectories during six months of treatment were generated, using a Gaussian process and the most probable trajectories were evaluated, based on clinical data, using measurement models that account for biases and differences in precision between tumor measurement methods, such as MRI, ultrasound and mammograms. ResultsReconstruction of tumor trajectories during treatment identified five distinct patterns of tumor size changes, including rebound growth not evident from any single modality. These results increase specificity to distinguish innate or acquired resistance compared to using any single measurement alone. The speed of therapeutic response and extent of subsequent rebound tumor growth quantify sensitivity or resistance in this patient population. ConclusionsTumor trajectory reconstruction integrating multiple modalities of tumor measurement accurately describes tumor progression on therapy and reveals various patterns of patient responses. Mathematical models can integrate diverse response assessments and account for biases in tumor measurement, thereby providing insights into the timing and rate at which resistance emerges.

systems biology↗

Dose optimization of an adjuvanted peptide-based personalized neoantigen melanoma vaccine

The advancements in next-generation sequencing have made it possible to effectively detect somatic mutations, which has led to the development of personalized neoantigen cancer vaccines that are tailored to the unique variants found in a patients cancer. These vaccines can provide significant clinical benefit by leveraging the patients immune response to eliminate malignant cells. However, determining the optimal vaccine dose for each patient is a challenge due to the heterogeneity of tumors. To address this challenge, we formulated a mathematical dose optimization problem that aims to find the optimal personalized vaccine doses for a given fixed vaccination schedule, based on a previous mathematical model that encompasses the immune response cascade produced by the vaccine in a patient. To validate our approach, we performed in silico experiments on six patients with advanced melanoma. We compared the results of applying an optimal vaccine dose to those of a suboptimal dose (dose used in the clinical trial and its deviations). Our simulations revealed that an optimal vaccine may lead to a reduction in tumor size for certain patients, with higher initial doses and lower final doses. Our mathematical dose optimization offers a promising approach to determining the optimal vaccine dose for each patient and improving clinical outcomes.

systems biology↗

TigerAI: An AI-powered genetic evidence platform to support clinical development

Genetic evidence is a major determinant of clinical success in drug development, yet its aggregation has long relied on laborious human curation. Large language models (LLMs) have the potential to rapidly synthesize knowledge across biomedical resources, providing a route to scalable AI-driven genetic evidence generation. Here we develop a novel domain-grounded instruction framework to systematically evaluate GPT-5 for producing genetic evidence relevant to clinical trial success. Using 13,022 target-indication pairs from a comprehensive drug development database, we benchmark LLM-derived evidence against a recent exhaustive human expert-curated study. We find that GPT-5 yields genetic evidence that is at least as informative as expert curation for inferring clinical success, while substantially expanding coverage relative to traditional curation resources. Building on these results, we introduce TigerAI (https://tigerai.bio/), a dual-purpose platform for AI-powered genetic evidence that (i) benchmarks emerging state-of-the-art LLMs and (ii) provides an accessible service for querying reliable AI-generated genetic evidence. These contributions outline a practical, domain-grounded pathway for integrating AI-powered genetic evidence into drug development pipelines and for realizing the potential of LLMs to inform clinical success.

genetics↗

Oral Delivery of Kidney Targeting Nanotherapeutics for Polycystic Kidney Disease

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited renal disorder. Although a variety of candidate drugs have been found to modulate cystogenesis in animal studies, results from clinical trials have often been unfavorable due to low renal bioavailability and drug-induced side effects. To mitigate this, nanoparticles can be designed to deliver drugs directly to the target organ to increase effective dose while limiting off-target side effects. Unfortunately, there are no kidney-targeted nanomedicines clinically available, and most of the existing FDA-approved nanoparticles require intravenous administration which is not suitable for ADPKD that require lifelong therapy. To address this, we developed an oral drug delivery system using chitosan nanoparticles (CS-NP) that were loaded with peptide amphiphile micelles carrying metformin (met), an ADPKD drug candidate (CS-KM-met). We previously showed that CS-NP can shield met in the gastrointestinal tract; thus, we hypothesized that CS-NP could also enhance bioavailability of kidney-targeting micelles (KMs) upon oral administration. Specifically, we measured the loading capacity of KM-met in CS-NP, evaluated the stability of CS-KM-met under acidic conditions that mimic the gastric environment, and measured in vitro therapeutic effects. Upon oral administration in C57BL/6J mice, CS-KM-met showed significantly greater bioavailability and accumulation in the kidneys as compared to KM-met without CS-NP or free met for up to 24 hours. As such, CS-KM-met showed enhanced therapeutic efficacy in vivo upon oral administration in PKD mice (Pkd1fl/fl; Pax8-rtTA; Tet-O-Cre) compared to KM-met only. Herein, we demonstrate the potential of an oral delivery nanoformulation for the treatment of chronic kidney diseases such as ADPKD for the first time.

bioengineering↗

Mammalian orthoreovirus infection in human epidermal growth factor receptor 2 positive (HER2+) breast cancer cells

Mammalian orthoreovirus (MRV) is a clinically benign oncolytic virus which has been investigated for use in multiple cancer types, including breast cancer (BC). In human clinical trials, MRV has been shown to be safe, and multiple BC patients have shown partial responses to intratumoral and intravenous virus delivery. Combination therapies inclusive of MRV and current FDA approved BC chemotherapies are being investigated to target metastatic, early BC, and triple negative BC. Though MRV is being tested clinically, we still do not fully understand the highly variable patient responses to MRV therapy. One of the most aggressive BC subtypes is HER2+ BC, in which human epidermal growth factor receptor 2 (HER2) is dysregulated, resulting in increased growth, survival, and metastasis of cancer cells. FDA approved therapies, trastuzumab and pertuzumab, target HER2 to prevent signaling of the phosphoinositide 3-kinase (PI3K) pathway. However, recent findings show that accumulation of hypoxia inducible factor-1 alpha (HIF-1) in HER2+ BC cells contributes to trastuzumab resistance. In this work, we provide evidence that MRV infects, replicates in, and kills HER2 overexpressing cells. MRV infection is also found to have variable effects on signaling pathways that activate or are activated by HER2 expression. Finally, we show that MRV reduces HIF-1 accumulation in all the cell lines tested, including a HER2+ BC cell line. These studies provide further evidence that MRV holds promise for use in conjunction with trastuzumab to treat HER2+ BC patients.

microbiology↗

Fragment-Guided New Therapeutic Molecule Discovery and Mapping of Clinically Relevant Interactomes

Therapeutic interventions for complex diseases depend on the targeted modulation of key pathological pathways. While growing clinical needs continue to drive advancements in the drug discovery space, current strategies primarily rely on searching large volumes of chemical data without addressing the specific contributions of molecular features. Moreover, both clinicians and researchers recognize the need for improved drug discovery methods and characterization that could aid in clinical strategy selection. To address these challenges, we propose a new perspective on targeted therapy development as well as interactome mapping, utilizing molecular fragments. The present study focuses on therapeutic areas that represent emerging targets, namely JAK2 and GLP-1R, both of which have broad clinical potential. We developed a new self-adjusting neural network that enabled us to discover novel therapeutic candidates with improved in silico binding profiles, gain additional insights into drug-target binding that were not previously reported, and identify new metabolic trajectories. Importantly, our work revealed that even a small compound library can effectively generate lead candidates, expediting the search and exploration process. In addition, the fragment-guided bridging of chemical and biological spaces has revealed new opportunities for drug repurposing efforts and a means of improving the prediction of side effects. We concluded our study with insights into the recent high-profile clinical trial failure of danuglipron and how this could have been prevented with our methodology. Thus, building a robust in silico pipeline with integrated screening data can significantly reduce costs and guide therapy adoption. Furthermore, our proposed strategy highlights promising avenues for the discovery of new therapeutics and the development of clinical interventions. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/663848v3_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1db97a4org.highwire.dtl.DTLVardef@1c0a159org.highwire.dtl.DTLVardef@1a10711org.highwire.dtl.DTLVardef@d7016a_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

Restoration of β-globin expression with optimally designed lentiviral vector for β-thalassemia treatment in Chinese patients

{beta}-thalassemia is one of the most prevalent genetic diseases worldwide. The current treatment for {beta}-thalassemia is allogeneic hematopoietic stem cell transplantation (HSCT), which is limited due to lack of matched donors. Gene therapy has been developed as an alternative therapeutic option for transfusion-ependent {beta}-thalassemia (TDT). However, successful gene therapy for {beta}-thalassemia patients in China has not been reported. Here we present the results of preclinical studies of an optimally designed LV named LentiHBBT87Q in hematopoietic stem cells (HSCs) derived from Chinese TDT patients. LentiHBBT87Q was selected from a series of LVs with optimized backbone and de novo cloning strategy. It contains an exogenous T87Q {beta}-globin gene (HBBT87Q) driven by a specific reconstituted locus control region (rLCR) and efficiently express HBB mRNA and HBB protein in erythroblasts derived from cord blood (CB) HSCs. To facilitate clinical transformation, we manufactured clinical grade LentiHBBT87Q (cLentiHBBT87Q) and optimized its transduction procedure. Importantly, transduction of cLentiHBBT87Qrestored expression of HBB monomer and adult hemoglobin (HbA) tetramer to relatively normal level in erythroblasts from bone marrow (BM) HSCs of Chinese TDT patients, that carry the most common mutation types and cover various genotypes, including {beta}0/{beta}0. Furthermore, viral integration sites (VIS) of cLentiHBBT87Q were similar to other LVs safely used in previous clinical trials and the associated risk of tumorigenesis was not observed in cLentiHBBT87Q transduced HSCs through comprehensive analysis. Taken together, we have engineered the cLentiHBBT87Q that can restore {beta}-globin expression in the HSCs-derived erythroblasts of Chinese TDT patients with minimal risk on tumorigenesis, providing a favorable starting point for future clinical application.

cell biology↗

Boosting of SARS-CoV-2 immunity in nonhuman primates using an oral rhabdoviral vaccine

An orally active vaccine capable of boosting SARS-CoV-2 immune responses in previously infected or vaccinated individuals would help efforts to achieve and sustain herd immunity. Unlike mRNA-loaded lipid nanoparticles and recombinant replication-defective adenoviruses, replicating vesicular stomatitis viruses with SARS-CoV-2 spike glycoproteins (VSV-SARS2) were poorly immunogenic after intramuscular administration in clinical trials. Here, by G protein trans-complementation, we generated VSV-SARS2(+G) virions with expanded target cell tropism. Compared to parental VSV-SARS2, G-supplemented viruses were orally active in virus-naive and vaccine-primed cynomolgus macaques, powerfully boosting SARS-CoV-2 neutralizing antibody titers. Clinical testing of this oral VSV-SARS2(+G) vaccine is planned.

immunology↗

Single-Cell RNAseq Analysis Reveals Robust Anti-PD-1-Mediated Increase of Immune Infiltrate in Metastatic Castration-Sensitive Prostate Cancer

Compared to other malignancies, the tumor microenvironment (TME) of primary and castration-resistant prostate cancer (CRPC) is relatively devoid of immune infiltrates. While androgen deprivation therapy (ADT) induces a complex immune infiltrate in localized prostate cancer, both in animal models and humans, the TME composition of metastatic, castration-sensitive prostate cancer (mCSPC) is relatively unknown and the effects of ADT and other treatments are poorly characterized in this context. To address this challenge, we analyzed metastatic sites from patients enrolled on a phase 2 clinical trial (NCT03951831), in which men were treated with standard-of-care chemo-hormonal therapy with anti-PD-1 immunotherapy, at the single cell level. Longitudinal protein activity-based analysis of TME subpopulations identified immune subpopulations conserved across multiple metastatic sites, their dynamic, treatment-mediated evolution, and associated clinical response features. Our study revealed a therapy-resistant, transcriptionally distinct tumor subpopulation, which comprises an increasing number of cells in treatment-refractory patients, and identified several druggable targets in both tumor and immune cells as candidates to advance treatment and improve outcomes for patients with mCSPC.

cancer biology↗

Generation and benchmarking of a collection of hiPSC lines from Schizophrenia Patients with Diverse Clinical Profiles

Limited therapeutic advancements in Schizophrenia (SCZ) depend on the heterogeneous nature of the disorder, impacting drug development and clinical trials that assume uniform therapy response, neglecting individual genetic and epigenomic variability. Disease modeling using human induced pluripotent stem cells (hiPSCs) is ideally suited for precision medicine, enabling individualized treatment approaches. Here, we describe the generation of patient-specific lines from somatic cells of SCZ individuals with well-defined diverse clinical trajectories using a Sendai virus-based reprogramming system. Karyotypically and CGH-array validated, the generated hiPSCs expressed diagnostic markers and demonstrated functional pluripotency. Converting these hiPSCs into neural progenitor cells enables the identification of aberrant cellular phenotypes associated with specific pathologically relevant neural phenotypes. This collection of hiPSC lines serves as a platform for developing therapeutic compounds targeting neural populations, potentially addressing early-stage disease alterations.

neuroscience↗

Freshly Thawed Cryobanked Human Neural Stem Cells Engraft within Endogenous Neurogenic Niches and Restore Cognitive Function Following Chronic Traumatic Brain Injury

Human neural stem cells (hNSCs) have potential as a cell therapy following traumatic brain injury (TBI). While various studies have demonstrated the efficacy of NSCs from on-going culture, there is a significant gap in our understanding of freshly thawed cells from cryobanked stocks - a more clinically-relevant source. To address these shortfalls, the therapeutic potential of our previously validated Shef-6.0 human embryonic stem cell (hESC)-derived hNSC line was tested following long-term cryostorage and thawing prior to transplant. Immunodeficient athymic nude rats received a moderate unilateral controlled cortical impact (CCI) injury. At 4-weeks post-injury, 6x105 freshly thawed hNSCs were transplanted into six injection sites (2 ipsi- and 4 contra-lateral) with 53.4% of cells surviving three months post-transplant. Interestingly, most hNSCs were engrafted in the meninges and the lining of lateral ventricles, associated with high CXCR4 expression and a chemotactic response to SDF1alpha (CXCL12). While some expressed markers of neuron, astrocyte, and oligodendrocyte lineages, the majority remained progenitors, identified through doublecortin expression (78.1%). Importantly, transplantation resulted in improved spatial learning and memory in Morris water maze navigation and reduced risk-taking behavior in an elevated plus maze. Investigating potential mechanisms of action, we identified an increase in ipsilateral host hippocampus cornu ammonis (CA) neuron survival, contralateral dentate gyrus (DG) volume and DG neural progenitor morphology as well as a reduction in neuroinflammation. Together, these findings validate the potential of hNSCs to restore function after TBI and demonstrate that long-term bio-banking of cells and thawing aliquots prior to use may be suitable for clinical deployment. Significance StatementThere is no cure for chronic traumatic brain injury (TBI). While human neural stem cells (hNSCs) offer a potential treatment, no one has demonstrated efficacy of thawed hNSCs from long-term cryobanked stocks. Frozen aliquots are critical for multisite clinical trials, as this omission impacted the use of MSCs for graft versus host disease. This is the first study to demonstrate the efficacy of thawed hNSCs, while also providing support for novel mechanisms of action - linking meningeal and ventricular engraftment to reduced neuroinflammation and improved hippocampal neurogenesis. Importantly, these changes also led to clinically relevant effects on spatial learning/memory and risk-taking behavior. Together, this new understanding of hNSCs lays a foundation for future work and improved opportunities for patient care.

neuroscience↗

Quantitative MRI Measurements Capture Pancreatic Cancer and Stroma Reactions to New KRAS Inhibitor

PurposeIn pancreatic ductal adenocarcinoma (PDAC), KRAS mutations drive both cancer cell growth and formation of a dense stroma. Small molecule KRAS inhibitors (KRASi) represent a promising new treatment hence clinical tools that can assess early response, detect resistance and/or predict prolonged survival are desirable to understand clinical biology of KRASi. We hypothesized that diffusion-weighted MRI (DWI) can detect cell death while dynamic contrast enhanced MRI (DCE) and magnetization transfer ratio (MTR) imaging are sensitive to tumor microenvironment changes, and these metrics shed insights into tumor size change induced by KRASi treatment. Experimental DesignMultiple preclinical PDAC models including a genetically engineered mouse model (KPC) received MRTX1133, a KRASi specific for KRASG12D mutation. Quantitative imaging markers were corroborated with immunohistochemistry (IHC) analyses. ResultsSignificant increase of tumor apparent diffusion coefficient (a DWI metric) was detected as early as 48h and persisted to Day7 after initiation of KRASi treatment and was strongly correlated with cell death and reduced cellularity, resulting in greatly prolonged median survival in treated mice. Capillary perfusion/permeability (a DCE metric) exhibited an inverse relationship with microvascular density. Distinct responses of KRASG12C versus KRASG12D tumors to MRTX1133 were captured by the MRI metrics corroborated with IHC. When tumors developed resistance to MRTX1133, the imaging marker values exhibited a reversal from those of responding tumors. ConclusionsMultiparametric MRI provides early biological insights of cancer and stromal response to KRASi treatment and sets the stage for testing the utility of these clinically ready MRI methods in patients receiving KRASi therapy. Translational relevanceEmerging small molecule KRAS inhibitors (KRASi) represent a new class of therapy for PDAC. Clinical tools that can provide early biological insights of KRASi therapy are desirable. In PDAC models, we examined a clinically ready imaging protocol that combines MRI-based tumor size, diffusion-weighted MRI (DWI), dynamic contrast enhanced MRI (DCE), and magnetization transfer ratio (MTR) for detection of early response as well as acquired resistance to MRTX1133, a KRASi being evaluated in clinical trials. Our data show that DWI and DCE metrics provided key insights of significant cell death and tumor microenvironment changes underlying tumor size regression as early as 48 hours after KRASi treatment initiation. These MRI metrics also captured resistance to KRASi developed over prolonged treatment. This study has high translational relevance by employing clinically applied MRI methods, an investigational new drug and a genetically engineered mouse model that recapitulates salient features of human PDAC.

cancer biology↗

Cyclin-dependent kinase 9 inhibitors as oncogene signaling modulators in combination with targeted therapy for the treatment of colorectal cancer

BackgroundColorectal cancer (CRC) is the second deadliest cancer worldwide and new treatment options are urgently needed. Cyclin dependent kinase 9 (CDK9) promotes aberrant RNA transcription in cancer and is a promising target for cancer therapies. MethodsUsing CRC cell lines as well as newly established patient-derived organoid models of CRC, we studied the clinically promising CDK9 inhibitors (AZD4573, BAY1125152/VIP152/enitociclib, and NVP2) to determine their therapeutic potential. We investigated the efficacy and mechanisms of action through cell growth and cytotoxicity assays, RNAseq, immunoblotting, and IHC. ResultsWe found CDK9 inhibitors to be highly potent against CRC, through suppression of proliferation and induction of apoptosis. Our results demonstrated CDK9 inhibitors to be broadly active against a set of CRC models derived from a diverse patient population. Our mechanistic studies showed significant suppression of the Mitogen-active protein kinase (MAPK) signaling pathway due to CDK9 inhibitor treatment, suggesting that CDK9 inhibitor efficacy could be enhanced when combined with MAPK pathway inhibitors. As proof-of-concept, we found that CDK9 inhibitors and MEK inhibitors could be combined to synergistically suppress CRC growth and survival. ConclusionsCDK9 inhibitors show promising activity against patient-derived models of CRC. MAPK signaling is particularly suppressed by CDK9 inhibitors. Combining CDK9 inhibitors and targeted therapy against MAPK signaling pathway may be a viable strategy worthy of further investigation preclinically and clinically. State of translational relevanceNovel therapies for chemotherapy-refractory CRC remain urgently needed. Rapid validation of efficacy in appropriate translational models can provide the necessary rationale to test new therapies in clinical trials. Using newly established patient-derived organoids, we validate the preclinical efficacy of transcriptional CDK9 inhibitors against CRC. This is a therapeutic class that has been scarcely evaluated for efficacy against CRC. We found that CDK9 inhibitors potently inhibit patient-derived organoid models of CRC. Our mechanistic work also reveals that clinically achievable concentrations of CDK9 inhibitor treatment results in suppression of MAPK signaling. As proof-of-concept of the potential actionability of our findings, we demonstrate that CDK9 inhibitors can be combined with MEK inhibitors to synergistically suppress CRC growth. Our study provides new patient-derived CRC models as a resource available to others for therapeutic testing, as well as a roadmap for novel hypotheses about synergistic combination treatments using CDK9 inhibitors.

cancer biology↗

Single-cell-level digital twins for preterm birth prevention strategies

Digital twin models can accelerate therapeutic development by enabling low-risk testing of candidate interventions. In preterm labor (PTL), a major pregnancy complication where clinical trials face unique ethical and financial barriers, digital twins are especially valuable for evaluating new therapies targeting immune dysfunctions driving PTL. Yet, current models lack single-cell resolution, limiting detection of cell-type-specific mechanisms, off-target effects, and the design of personalized interventions. We present Simulated Immunome Modeling of Clinical Outcomes (SIMCO), a single-cell-level digital twin framework that models immunomodulatory treatment effects on the timing of labor using immunome-wide, single-cell simulations. SIMCOs digital twins are trained and validated on a newly generated mass cytometry atlas of the pregnant immunome exposed to nine candidate drugs preselected for PTL prevention. Applying SIMCO to an independent cohort of pregnant individuals, we simulate treatment effects on gestational length, screening for candidate drugs that delay labor timing and providing system-level mechanistic insight for each drug candidate. Tetrahydrofolate, maprotiline, and the combination of aspirin and lansoprazole emerged as top candidates for PTL prevention, delaying labor onset primarily through enhanced mTOR signaling in innate immune cells and attenuated JAK/STAT signaling in naive CD4 T cells. The codebase is available at https://github.com/ofondeur/SIMCO/.

immunology↗

Integrated serum proteomics and autoantibody analyses reveal a biomarker signature predictive of flare during biologic tapering in rheumatoid arthritis

BackgroundRheumatoid arthritis (RA) is a chronic immune-mediated inflammatory disease characterized by a heterogeneous clinical course with periods of remission and flare. Although biologic DMARDs (bDMARDs) have revolutionized RA treatment by enabling sustained disease control, their long-term use is associated with adverse effects and high costs, making dose tapering an attractive but clinically challenging strategy. The lack of reliable biomarkers to predict flare risk limits safe implementation of treatment de-escalation. This study aimed to identify novel circulating protein biomarkers associated with flare risk in RA patients undergoing bDMARDs tapering, useful to enable biomarker-guided treatment optimization strategies. MethodsA discovery proteomic analysis using mass spectrometry was performed on baseline serum samples from a subset of the OPTIBIO clinical trial (n=44), followed by validation in the full cohort (n=194) using ELISA. Functional pathway analysis explored biological processes associated with candidate biomarkers. In parallel, anti-cytokine autoantibodies were profiled using multiplex immunoassays. Logistic and Cox regression models were used to assess associations with flare risk. Predictive models integrating biomarkers and clinical variables were evaluated using receiver operating characteristic (ROC) analysis, sensitivity and specificity metrics, and decision curve analysis to assess clinical utility. ResultsMass spectrometry identified 806 proteins, of which 87 were differentially expressed at baseline between patients who flared and those who maintained remission during follow-up within the intervention (tapering) arm. Functional enrichment analysis highlighted immune-regulatory and innate immune pathways. Among the candidates, V-set immunoglobulin-domain-containing 4 (VSIG4) was validated as a biomarker associated with increased flare risk. Anti-interferon-{gamma} (anti-IFN{gamma}) autoantibodies were also associated with flare. A combined model including VSIG4, anti-IFN{gamma}, and the clinical variable DAS28-CRP improved predictive performance compared with clinical variables alone (AUC 0.76 vs 0.66), achieving significantly higher sensitivity. Decision curve analysis demonstrated higher net benefit of the combined model, indicating improved clinical decision-making. In a secondary analysis focused on patients with prolonged remission, representing the most suitable candidates for safe treatment tapering, the model performance further improved (AUC 0.84). ConclusionIntegration of novel serum proteomic and autoantibody biomarkers with clinical parameters improves prediction of flare during biologic tapering in RA and provides clinically relevant benefit for patient stratification. These findings support further development of biomarker-driven approaches for personalized treatment optimization strategies.

molecular biology↗

Inhibition of Neisseria gonorrhoeae complement-mediated killing during acute gonorrhoea is dependent upon the IgG2:IgG3 antibody ratio

Excessive binding of antibodies to the bacterial cell surface can paradoxically increase resistance of some Gram-negative pathogens to complement-mediated killing (CMK). We examined CMK of 336 Neisseria gonorrhoeae clinical isolates sampled from participants recruited to a clinical trial. Serum bactericidal assays revealed 3% (9/336) of the autologous participant sera that were tested inhibited CMK. Gonococci isolated from these participants were resistant to the autologous host serum, sensitive to a pool of healthy control sera (HCS) and protected by the host serum in a 1:1 mixture with HCS. Analysis of the clinical metadata showed that there were a significantly higher proportion of inhibitory sera found in participants with urethral infections and from men within the transmission network of men who have sex with women (MSW), when compared to the whole cohort. Following antibody purification from selected participants with inhibitory sera (5/9), IgG and IgM protected the autologous isolates from HCS-mediated killing. Only three of these isolates were protected by purified IgA. A closer examination of IgG subclasses using whole gonococcal cell ELISAs revealed a strong correlation between increased IgG2 binding and decreased IgG3 binding to the bacterial cell surface of isolates that were resistant to CMK. This suggests that IgG2 prevents bactericidal IgG3 from initiating CMK and that the IgG2:IgG3 ratio is important for determining either inhibition or killing of isolates. We therefore reveal a previously unreported mechanism by which inhibitory antibodies prevent CMK of N. gonorrhoeae.

microbiology↗