Yale University

NIH Research Projects · FY 2026 · 2026-05

One-third of patients with acute ischemic stroke (AIS) present to the emergency department (ED) with an unknown symptom onset time, making them ineligible for intravenous thrombolysis. Blood-based biomarkers predictive of time from symptom-onset, can make patients with unknown stroke onset times eligible for thrombolysis. Majority (>50%) of patients evaluated in the ED for acute neurological symptoms concerning for stroke, are also eventually diagnosed with not having stroke (stroke mimics) after comprehensive evaluation. Many stroke mimic patients also receive thrombolysis in the ED, posing a significant burden via healthcare resource utilization and exposing these individuals to unnecessary bleeding risk. Blood-based biomarkers that can differentiate stroke mimics from AIS, can potentially minimize unnecessary interventions and optimize resource allocation. Currently, no validated blood-based biomarker exists to address these urgent clinical gaps in acute stroke care. The goal of the STROKE-CLOCK study is to identify a blood-based biomarker panel capable of estimating stroke onset time and distinguishing early-onset AIS from stroke mimics. We will perform a single- site proteomics study using plasma samples collected in the ED, from patients who present with acute neurological symptoms concerning for stroke and have a clearly defined time of symptom onset. We will leverage plasma samples from the Emergency Medicine Specimen Biobank (EMSB) at Yale University and will include adults (age ≥18 years) presenting with a suspected stroke to the ED with a clearly defined onset time with blood (plasma) samples collected in the ED prior to any stroke intervention. We will perform mass spectrometry (MS)- based proteomics to identify and validate protein biomarkers that distinguish patients with early-onset AIS (≤4.5 hours) from late-onset AIS (>4.5 hours) (Aim 1) and distinguish early-onset AIS from stroke mimics within 4.5 hours (Aim 2). In both aims, we will first perform data-independent acquisition (DIA)-MS proteomics in a derivation cohort (2 groups, N=30/group) to nominate differentially enriched proteins (DEPs). We will then verify these in an independent set of samples (2 groups, N=30/group). Proteins nominated from untargeted studies will be validated on the same samples using targeted parallel reaction monitoring (PRM)-MS and then validated in an independent cohort of samples (2 groups, N=50/group). We will estimate performance metrics, including sensitivity, specificity, and negative and positive predictive values. Multivariable prediction models will be constructed, and performance of biomarker panels will be evaluated using area under the receiver operating characteristic curves. If successful, this R21 proposal will lay the foundation for future definitive studies on large- scale validation, temporal profiling, and clinical implementation of this biomarker panel to guide acute stroke triage and treatment decisions.

NIH Research Projects · FY 2026 · 2026-05

The Yale Center for Genome Analysis (YCGA) has been providing cutting-edge genomics analyses to support the fundamental research needs of over 1,000 Yale and non-Yale NIH-funded investigators. With a strong track record of advancing genomic technologies, enabling breakthrough scientific discoveries, and securing competitive NIH funding, YCGA has emerged as one of the leading genome centers. Currently, the Center provides integrated analyses in genomics, transcriptomics, and epigenomics. However, to fully support systems-level investigations and meet the growing demand for multiomics approaches, YCGA must expand its capabilities to include proteomics. Proteins are the primary effectors of cellular function and represent the downstream integration of genomic, epigenomic, and transcriptomic regulation. As such, proteomics is essential for a comprehensive understanding of human biology. While the genome provides a static blueprint, proteomics captures dynamic biological states that are critical to uncovering the mechanisms underlying health and disease. The proposed acquisition of the Olink platform will enable high-throughput, targeted proteomics analyses, filling a critical gap in YCGA’s service portfolio. This proposal is strengthened by (1) YCGA’s extensive user base, (2) the PI’s deep expertise, (3) and the Center’s proven success in deploying and integrating advanced “omics” technologies. Yale University has already invested substantially in the infrastructure, personnel, and automation systems required to support large- scale multiomics research. The addition of Olink proteomics will leverage this foundation to significantly expand the reach and impact of YCGA, enhancing NIH-funded research across a wide spectrum of biological and biomedical disciplines within and beyond the Yale community.

NIH Research Projects · FY 2026 · 2026-05

Project Summary This shared instrument grant requests funds for an Aurora CS for fluorescence-based cell sorting, to be installed at Yale University. Flow Cytometry is a critical resource for biomedical research. Nearly every discipline in the biologic sciences uses this technology that is critical for a variety of applications downstream of the sorting of cells. There is a growing demand for high-parameter flow cytometry at Yale to characterize biological samples as completely as possible. As the amount of published phenotypic information on distinct cell types and their subsets continues to increase, the number of parameters that is then needed to uniquely identify and distinguish diverse cell subset is likewise growing at a rapid pace. However, the number of cells within a sample can sometimes be small and as a result, an increasing number of studies require higher parameter panels during cell sorting to collect deep phenotypic information with small samples that cant also be analyzed separately at another instrument. For these reasons the Aurora CS is an ideal instrument to meet these needs because it 1) has full spectral detection with more than 60 sensitive detectors that generate spectral signatures that can be computationally “unmixed”, 2) enables measurement of over 30 cellular parameters simultaneously, 3) greatly improves the ability to distinguish multiple fluorescent proteins such as GFP, YFP or RFPs with overlapping emissions, or any other challenging dye combination, 4) identifies spectral signatures of unique cell-type specific autofluorescence that can then be computationally removed, solving a perennial problem with highly autofluorescent samples such as those derived from kidneys, lungs or intestines, and 5) further offers the ability to sort objects as small as 100 nm, such as EVs, synaptosomes or platelets. The requested equipment would replace a heavily used but aging BD FACSAria. The vendor will soon cease to offer service contracts on this model. Since this FACSAria is the only cell-sorting flow cytometer available in its building, any equipment breakdown could result in delays that would significantly impede ongoing research. It is critical that the existing instrument be replaced with a reliable cell-sorter that can be repaired in a timely fashion, preferably one that can be operated independently by investigators when staff is not available. The Aurora CS will serve as an ideal “future proof” cell sorter in a demanding location while addressing multiple other unmet needs on campus. Thus, the requested equipment will empower Yale researchers to interrogate complex biology with more challenging phenotypic panels, accelerating the pace of research while engendering greater insights and deeper knowledge.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract This is a career development award application for a dermatologist and physician-scientist studying the role of retroelements in Systemic Lupus Erythematosus (SLE). SLE is a highly morbid autoimmune disease with major manifestations that include disfiguring skin rashes as well as joint and kidney pathology. In the United States, it is estimated that over 200,000 patients have SLE. The pathogenesis of SLE remains incompletely understood. Of the implicated pathways, elevated antiviral type I interferon signaling as well as autoreactive T cells have been identified as possible mediators of disease, though the etiology of these antiviral signals as well as the antigenic targets of T cells are not well established. Prior work from our laboratory discovered antibodies targeting retroelements in patients with SLE which correlated with interferon gene expression signatures. We hypothesize that retroelements contribute to SLE through two distinct mechanisms: by inducing type I interferon responses and by serving as a source of autoantigens that trigger adaptive immunity. This proposal will (1) delineate gene and retroelement expression patterns and inflammatory cytokine levels in the peripheral blood and skin of SLE patients, (2) identify and phenotype retroelement-specific autoreactive CD4+ T cells, and (3) mechanistically evaluate immune responses targeting retroelements in the skin using genetic mouse models. Through characterization of these autoreactive T cell populations and correlation with gene, retroelement, and inflammatory protein levels, these studies will evaluate a previously undescribed pathway to autoimmunity with therapeutic potential. This proposal describes a rigorous five-year career development training program supporting my transition to an independent investigator. After completing my MD and PhD in Biochemistry and Molecular Biology, I continued my clinical and research training at Yale in the Investigative Dermatology Program which combines clinical dermatology residency training with protected research time. I have now embarked on an intensive immunology training program under the mentorship of Dr. Akiko Iwasaki, a pioneer and world leader in deciphering the complex interplay among viruses, innate immune recognition, and adaptive immunity. In addition to the intellectual development and practical laboratory-based training that I will continue to receive in Dr. Iwasaki's lab, I have developed a training program built on didactic coursework in immunology and computational biology. This plan is supported by the expertise of dedicated and experienced mentors with extensive domain knowledge in relevant disciplines. Yale School of Medicine, along with the Departments of Dermatology and Immunobiology, will provide the resources, support, and infrastructure to assist me in achieving the aims described in this proposal and my long-term goal of developing into an independent physician-scientist studying autoimmune skin disease.

NSF Awards · FY 2026 · 2026-05

This project will strengthen the foundations needed to make advanced language technologies more capable and reliable tools for science. Systems based on large language models can already help researchers search the literature, summarize prior work, answer technical questions, and suggest new hypotheses. Yet, these systems introduce problems in scientific settings: they may miss finding key publications, rely on weak or irrelevant evidence, present claims with unwarranted confidence, or offer persuasive but unfounded answers to questions that current scientific evidence does not yet support. These limitations can waste research time, mislead the scientific community, and reduce trust in methods that could otherwise help accelerate progress in scientific fields important to the Nation, including computer science, medicine, biology, and physics. This project addresses that need by developing the foundations required for more reliable language technologies for science: better ways to evaluate and understand capabilities of AI models for scientific tasks, better ways to adapt and advance their capabilities for this domain, and better ways to ensure that these models are reliable and their outputs are evidence-based and appropriately qualified. The project will generate openly available data, benchmarks, methods, software, and tutorials that can help researchers across institutions use these technologies more effectively and responsibly. It will also support graduate and undergraduate training, hands on research experiences, and activities that contribute to a strong future science and engineering workforce. The research will pursue three research thrusts. First, it will create new evaluation methods and frameworks for scientific tasks, including an evaluation framework for comparing systems on process-level and literature-grounded scientific reasoning, evidence retrieval, and long-form scientific analysis. This work will then provide evaluation testbeds for AI-based evaluators and measure and improve their alignment with domain experts. Second, it will develop new methods for adapting and advancing large language models in the scientific context. This includes compatible learning objectives to leverage the rich structure of scientific literature, building more powerful representations of scientific documents for retrieval and knowledge integration, and designing reasoning methods that can better integrate knowledge, as needed. Third, it will develop methods to improve reliability and control of language models in scientific domains, including techniques for aligning expressed confidence with actual uncertainty, recognizing when scientific questions are unanswerable or underspecified, and guiding systems toward more faithful, evidence grounded responses which is crucial in science. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-05

Project Summary Excessive cell growth contributes to senescence and is a hallmark of aging. In the innate immune system, monocyte distribution width (the standard deviation of the monocyte mean volume) has been proposed as a diagnostic marker for severe infection and early sepsis detection. Increased cell size is also associated with an exhaustion-like memory state. While both senescence and immune exhaustion can be pathogenic, they differ in their reversibility: senescence is characterized by an irreversible cell cycle arrest, whereas exhaustion in innate immune cells retains cell cycle activity and proliferative potential. It remains unclear how enlarged immune cells in an exhausted state can maintain immune surveillance without transitioning into senescence. Our unpublished work identifies a pathway regulated by the endocytic protein FBP17 that increases the cell size setpoint without inducing senescence. FBP17-deficient mast cells and macrophages remain proliferative despite their enlarged size. Similarly, exhausted monocytes subjected to repeated LPS stimulation in vitro exhibit both increased cell size and reduced FBP17 expression. In vivo, we also made a novel observation that monocytes isolated from aged mice with exhaustion-like memory signatures display reduced levels of FBP17, which strongly correlate with their enlarged size compared to monocytes from young mice. These findings suggest that cell enlargement does not inherently lead to proliferative arrest and that increases in cell size may be reversible. Using a single-cell microchannel system to monitor real-time cell growth and quantify size homeostasis, we further discovered that FBP17 knockdown cells increase their sizes through an "adder" growth mechanism. In this model, cells do not divide upon reaching a specific size threshold; instead, they add a fixed volume each generation. This behavior implies a form of transgenerational memory that depends on lineage age. We hypothesize that FBP17, along with the adder-based enlargement mechanism, plays a key role in enabling immune cells to grow without entering senescence. We aim to investigate how size increment is regulated via growth rate modulation, the molecular basis of intergenerational memory transmission, and whether this mechanism contributes to immune exhaustion memory. Understanding this non-canonical pathway of cell size regulation will offer novel strategies for reversing aging-associated cellular changes.

NIH Research Projects · FY 2026 · 2026-05

ABSTRACT Sickle cell disease (SCD) is a rare inherited multi-system blood disorder that affects about 100,000 persons in the US, almost all of whom are Black or African American. Most adults with SCD experience chronic pain (CP), i.e., pain on most days of the month for 6 months or more, and poor outcomes. SCD CP is further complicated by progressive end-organ damage, premature mortality, and enduring disparities in pain care. Given individual variability in the impact of CP, the National Pain Strategy conceptualized CP with substantial restriction of participation in work, social, or self-care activities as High-Impact Chronic Pain (HICP). We have, for the first time, examined HICP in SCD. Our work in three cohorts, including the pilot Sickle Pain Related Impact (SPiRit) study has shown that HICP is a high-risk CP phenotype in SCD, distinct from mild-bothersome CP (MBCP), and that HICP may be a dynamic state. Thus, we do not know who is at risk for sustained HICP and long-term risk of poor outcomes (Gap 1), and who to prioritize for treatment intensification and for resource limited and high-risk intensive therapies (e.g., gene therapy, hematopoietic cell transplant). Identifying risk factors for sustained HICP is also crucial as they are potential intervention targets to reduce disability (Gap 1). Lack of patient-centered endpoints to assess the efficacy and impact of interventions for SCD CP is another gap; current SCD clinical trial endpoints do not consider the perspective of, or preferences for pain endpoints among persons with lived experience of SCD CP (Gap 2). Further, there are no blood-based biomarkers specific to SCD CP that complement self-reported pain, which hinder regulatory approval of new SCD treatments (Gap 3). Our work has set the stage to address these critical gaps in a definitive way in an observational longitudinal study, SPIRit2. In SPiRIt2, we will follow 300 adults with SCD CP every 6-months for 2 years (Timepoints T1-T5). To identify persons at sustained high-risk, we propose a novel longitudinal risk group classification based on overall frequency of HICP or MBCP; higher frequency of HICP relative to MBCP will be considered ‘overall high-risk’, and higher frequency of MBCP (or no CP) relative to HICP will be considered ‘overall low-risk’. We propose three specific aims: In Aim 1, we will examine the long-term temporal stability of HICP, risk factors and long-term outcomes of HICP in SCD. In Aim 2, we will identify preferences for pain-related endpoints for interventional clinical trials among persons with SCD CP. In Aim 3, we will identify proteomic biomarkers of HICP, pain outcomes, and central sensitization in SCD. Completion of aims will shift paradigms with an evidence-based framework for future interventions for SCD CP thereby improving patient outcomes, and will translate beyond SCD to the study of HICP. The PI and investigator team have research and clinical expertise in SCD, SCD CP, longitudinal studies, patient reported outcomes, psychology, qualitative science, decision science, plasma-based proteomics, quantitative sensory testing, and biostatistical expertise in pain to complete the proposed aims.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract Myasthenia Gravis (MG) is an antibody-mediated autoimmune disease that impairs neuromuscular transmission through autoantibodies targeting proteins of the neuromuscular junction. However, up to 15% of clinically diagnosed MG patients are seronegative, lacking detectable autoantibodies in current diagnostic assays. This diagnostic gap delays diagnosis, treatment, and trial enrollment and highlights a critical unmet need for improved biomarkers in seronegative MG (SNMG). Emerging evidence suggests that some SNMG patients harbor pathogenic autoantibodies that escape detection due to low titers, non-canonical binding, or recognition of novel autoantigens. We hypothesize that autoreactive B cells in these patients, and more generally, in autoimmune diseases, undergo abnormal somatic evolution and maturation processes, leaving detectable molecular footprints in their B cell receptor (BCR) sequences that can be identified using advanced computational models. This project will develop and apply a multilevel computational and experimental strategy to uncover these hidden features. In Aim 1, we will build interpretable deep learning models, leveraging transformer architectures for anomaly detection, to identify BCR sequences enriched in autoimmune repertoires. We will develop interpretable methods to identify BCR features driving model predictions and incorporate uncertainty quantification to prioritize biologically meaningful candidates. In Aim 2, we will develop evolution-aware BCR models by integrating fine-tuned protein language models with clonal phylogenies to identify abnormal somatic hypermutation patterns and atypical B cell maturation trajectories. By comparing BCR repertoires from healthy individuals, autoimmune disease patients, and both seropositive and seronegative MG cases, we will uncover convergent features specifically enriched in autoimmune diseases and MG. In Aim 3, we will generate the first single-cell RNA/BCR sequencing dataset from a newly recruited SNMG cohort. Using our fast graph-based framework for modeling antibody-antigen interactions, we will perform structural modeling and in silico docking against a curated panel of known and putative MG autoantigens. Predicted antibody- antigen interactions will be experimentally validated using patient-derived samples. In summary, this project combines computational innovation with the generation of a new SNMG cohort and targeted experimental assays to detect autoreactive BCRs. Through deep learning, evolutionary modeling, and structural docking, we will identify repertoire features and atypical maturation patterns linked to autoreactivity. High-confidence predictions will be experimentally validated in patient samples, enabling biomarker discovery in SNMG, with broad implications for informing precision diagnostics across autoimmune diseases.

NIH Research Projects · FY 2026 · 2026-05

Applications of brain Positron Emission Tomography (PET) have been in place for over 40 years. The combination of quantitative PET systems with novel radiotracers has led to numerous imaging paradigms for understanding normal and pathological brain physiology and pharmacology. Brain-dedicated PET systems offer important advantages over currently available PET systems in terms of sensitivity and resolution. Funded by a BRAIN Initiative grant, we developed the NeuroEXPLORER (NX), an ultra-high performance brain PET system. To date, human results have produced exceptional image quality and the delineation of small brain nuclei. The system's performance derives from its long axial field of view, small crystal elements, depth of interaction measurement, and excellent time-of-flight resolution. This proposal takes the next steps to optimize system performance including accuracy and precision, expand on the capabilities for dynamic PET with tracer kinetic modeling, and demonstrate the real-world performance with a wide range of PET radiopharmaceuticals. The proposal includes the following Aims. Specific Aim 1: Optimize key aspects of the system performance and reconstruction methodology to maximize image quality and minimize noise. We will further optimize and improve rigid and non-rigid motion correction, investigate impact of detector crosstalk and corrections, and develop reconstruction methods with practical computation times. Specific Aim 2: Develop and extend the capabilities of the NX for dynamic analysis using tracer kinetic modeling. Our initial assessment of extracting image-derived input functions from the carotid arteries has been very successful, and we will further validate this approach against arterial blood samples with a large cohort study using multiple radiopharmaceuticals that are commonly used in research and have potential clinical impact. We will also develop and validate methods to estimate the radiopharmaceutical metabolite corrections using population modeling and kinetic analysis strategies. In addition, the ultra-high resolution and sensitivity of the NX allows the reassessment of optimal modeling methods, which will be explored for tracers with challenging spatiotemporal distributions. Specific Aim 3: Real-world performance of human brain scans. We will further develop our 3D printing methods to generate a full-brain phantom and use it to compare to other PET systems. We will facilitate access of this phantom to other sites with novel brain PET systems. To truly optimize NX human imaging, we will perform test/retest studies with multiple radiopharmaceuticals and compare NX images to those of a current state-of- the-art whole-body system (Siemens Vision). This work will demonstrate the significance of the NX's performance characteristics and enable harmonization with conventional PET/CT scanners. In addition, we will perform brain activation studies using functional PET in a paradigm targeting the olfactory system, which is highly relevant in the early manifestations of neurodegenerative disorders.

NIH Research Projects · FY 2026 · 2026-05

Project Summary Capturing the full allelic diversity in highly variable regions of the human genome requires large- scale sequencing efforts, yet current approaches face significant cost and privacy-related chal- lenges. The Human Pangenome Reference Consortium (HPRC) aims to expand its pangenome reference to 350 individuals by 2025, but scaling further remains difficult due to the high cost of long-read sequencing and barriers to data sharing across institutions. To address these challenges, our proposal brings together experts in genome assembly, genotyping, and privacy technologies to develop scalable and privacy-preserving methods for pangenome construction and analysis. Our specific aims include: developing co-assembly pipelines that leverage shared genetic variation to enable cost-efficient pangenome assembly from low-coverage sequencing data (Aim 1), creating privacy-preserving tools for utilizing pangenomes together with private or controlled-access data (Aim 2), and building production-grade software and resources to facilitate adoption of our tools by the genomics community (Aim 3). By enabling efficient, secure, and scalable pangenome con- struction, our work aims to accelerate population-scale pangenomics research and improve analysis of complex, multiallelic regions of the human genome.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract The acidity of the tumor microenvironment (TME), driven by hyperglycolytic tumor metabolism, represents a key mechanism by which cancers develop resistance to therapies. Metabolic reprogramming in glycolytic phenotypes overproduce H+ and lactate, but the function of intracellular machinery essential for glycolysis require an alkaline pHi. To support tumor survival and progression, H+/lactate are exported from glycolytic phenotypes into the TME, but paradoxically H+/lactate may also be imported into oxidative phenotypes for their metabolic needs, a mechanism termed “metabolic symbiosis” between glycolytic and oxidative phenotypes. In addition, CO2 produced during substrate oxidation also leads to extracellular acidification using enzymes like carbonic anhydrases (e.g., CAIX). One mechanism by which H+ and lactate is imported/exported is through proton- coupled transmembrane monocarboxylate transporters (MCTs). Thus, the difference between intracellular pH (pHi) and extracellular pH (pHe), called the transmembrane pH gradient (∆pH=pHi–pHe), is much larger in tumors than in normal tissue. Due to differences in metabolic reprogramming between glycolytic and oxidative phenotypes, we posit that ∆pH will be larger for glycolytic vs. oxidative phenotype. Targeting MCTs (such as MCT1 or MCT4) or CAIX has shown promising results as novel anti-cancer therapeutic strategies. We propose to develop an MR-based platform for high-resolution ∆pH imaging in glioblastoma multiform (GBM), an incurable and aggressive cancer with high resistance to chemotherapy, with increased expression levels of MCT1 and MCT4. Currently, there is a paucity of techniques that can provide simultaneous pHi and pHe imaging. Measuring both pHi and pHe is critical to differentiate between glycolytic and oxidative phenotypes. pHi can be imaged by MRI with Amine and Amide Concentration-Independent Detection (AACID), whereas pHe is imaged with an MRSI method called Biosensor Imaging of Redundant Deviation in Shifts (BIRDS). Our goals are to use unsupervised deep learning to improve the pHe resolution to match that of pHi resolution so that high- resolution ∆pH imaging enables differentiation of glycolytic vs. oxidative phenotypes, and then determine how their metabolic state is affected by treatment with MCT and/or CAIX inhibitors. The primary metabolic measures will be enhanced by clinical measures of tumor perfusion and cellularity, as well as tissue staining. First we will develop high resolution ∆pH imaging in rat brains with patient-derived xenografts, where pHe resolution will be improved using deep learning. Then we will apply high resolution ∆pH imaging to examine the effects of MCTs inhibition. Because Temozolomide (which inhibits DNA synthesis) and MCTs inhibition target different GBM progression mechanisms, we will compare the effect of MCTs inhibition with the standard GBM treatment with Temozolomide. Finally, we will determine if combined MCT/CAIX inhibition is more effective than separate MCT and CAIX treatments. This powerful MR imaging tool has high potential for translation to monitor tumor phenotypes and therapy response to inform treatment decisions for improved outcomes.

NIH Research Projects · FY 2026 · 2026-05

Research Summary Invasive aspergillosis (IA), primarily caused by Aspergillus fumigatus, is a life-threatening infection that predominantly affects immunocompromised individuals. Despite advancements in antifungal treatments, IA is associated with high mortality rates; for instance, among solid organ transplant recipients, mortality rates range from 65% to 92%, with IA contributing to approximately 9.3%–16.9% of all deaths within the first-year post- transplantation. A. fumigatus is also an important cause of fungal keratitis (FK), a site-threatening corneal infection that occurs in otherwise healthy patients that experience corneal trauma. As with IA, visual outcomes associated with FK are also poor, with 70% of all patients experiencing reduced or complete loss of vision in the affected eye. These statistics underscore the urgent need for novel therapeutic strategies for both pulmonary and corneal A. fumigatus infection. Pantothenate kinases are essential enzymes involved in the biosynthesis of coenzyme A (CoA and Acetyl-CoA (AcCoA) (The PCA pathway). Our studies have demonstrated that inhibition of PanK activity and the PCA pathway not only impedes fungal growth but also disrupts vacuolar function, compromising the pathogen's ability to detoxify antifungal agents. This dual mechanism suggests that PanK inhibitors can serve both as standalone drugs and as potentiators of existing antifungal drugs. We previously screened a library of 256,000 compounds against A. fumigatus AfPanK and identified pyrimidone triazoles (PTZs) as potent and selective inhibitors of this essential enzyme. Using structure-activity relationship (SAR) studies we designed and synthesized a focused library of 113 PTZ analogs. The goal of this R21/R33 proposal is to evaluate the biochemical activity, pharmacological properties and in vitro and in vivo efficacy of these compounds and identify potent dual-activity PTZ molecules to develop as novel antifungal agents against A. fumigatus infection. In the R21 phase, we will screen this focused library of PTZ analogs against purified AfPanK and a CDC collection of drug-sensitive and -resistant A. fumigatus clinical isolates. Potent candidate inhibitors will be further evaluated for their ability to augment the antifungal activity of clinically-approved anti-A. fumigatus agents including azoles, liposomal amphotericin B, and echinocandins. Transition milestones include the identification of lead compounds with defined inhibitory profiles and synergistic effects with existing drugs. In the R33 phase, we will conduct advanced in vitro efficacy and safety studies on the lead compounds, perform detailed pharmacological analyses, and assess the in vivo efficacy of lead compounds alone and in combination with approved antifungals using animal models of IA and FK A. fumigatus infections to validate their therapeutic potential. Successful completion of this project will yield novel AfPanK inhibitors that alone or when combined with approved antifungal drugs, can kill both sensitive and resistant A. fumigatus isolates. This therapeutic approach aims to reduce toxicity and improve treatment outcomes, potentially revolutionizing antifungal therapy.

NIH Research Projects · FY 2026 · 2026-05

Abstract Pathologic pathophysiology of Alzheimer Disease and related dementias (ADRDs). mislocalization and aggregation o TDP-43, an essential RNA/DNA-binding protein, is central to the of ALS, frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP), TDP-43 misregulation disrupts f and is a feature splicing, mRNA stability and transport, therebyimpairing neuronal function.Recent NMR and cryo-electron microscopy studies suggest that formation of TDP-43 fibrillar aggregates is facilitated by destabilization of an α-helical segment within the amyloidogenic core of TDP-43 C-terminal domain (CTD). This core region is necessary and sufficient for TDP- 43 aggregate formation in cells and in vivo, and is able to template aggregation of full-length TDP-43, suggesting a key role in regulating the structural transition of TDP-43 to amyloid-like conformations. We used a computational approach to generate novel peptides (50 residues in length) that exhibit enhanced α-helical secondary structure and bind to TDP-43's amyloidogenic core but resist β-sheet conversion. effectively that aggregate added enabling and engineered of This strategy caps the growth of fibrils and blocks further addition of TDP-43 monomers. Our preliminary data show co-expression of our top hit engineered peptides with TDP-43's aggregation-prone CTD reduce TDP-43 formation in mammalian cells and filter trap assay. In the next step of preclinical development, we a protein degradation motif to our engineered peptide, providing extra potential therapeutic efficacy by clearance of peptide-bound fibrils. The goal of this proposal is to examine target engagement, efficacy, potential off-target effects of our top ranked peptides in vitro and in vivo. We will test the hypothesis t hat our helical peptides function as: 1) novel capping agents that robustly bind and effectively inhibit growth TDP-43 fibrillar aggregates and2) bi-functional degraders of TDP-43 aggregates without adversely affecting physiologic function and localization of endogenous TDP-43. In Aim 1 we will evaluate our engineered helical peptides for target engagement and efficacy in reducing TDP-43 aggregates. Aim 2 will examine efficacy of engineered helical peptides for clearing TDP-43 aggregates in vivo and evaluate endogenous TDP-43 function. Upon successful completion, this project will determine whether our engineered helical peptides hold promise for further preclinical testing in mammalian in vivo models and opens avenues for targeting traditionally “undruggable” proteins.

NIH Research Projects · FY 2026 · 2026-05

Exploring the structural space underlying antibody-mediated Fc-effector functions Summary Viral fusion glycoproteins such as the HIV-1 envelope glycoprotein (Env) are conformationally dynamic to facilitate entry into cells while evading immune responses. It is therefore important to determine vulnerable viral fusion glycoprotein conformations that correlate with immune protection. While the stabilization of prefusion conformational states has led to success in the design of immunogens that elicit neutralizing antibody (nAb) responses, the structural correlates of antibody (Ab)-mediated Fc-effector functions are less well understood. Fc-effector functions describe the ability of the fragment crystallizable (Fc) region on antibodies to engage complement as well as human Fc receptors (FcR). Ab-dependent cellular cytotoxicity (ADCC) and Ab-dependent cellular phagocytosis (ADCP) functions augment broadly nAb efficacy and enhance infected cell clearance in vivo. Antibodies capable of mediating Fc-effector functions emerged as an immune correlate in the RV144 human vaccine trial. Moreover, Fc-effector functions play an important role in cure strategies targeting the HIV- 1 latently infected reservoir. Despite their increasingly recognized role in immune protection, the structural details that enable potent Fc-effector functions are largely unknown. To shed light onto this unknown structural space, we have established a cryo-electron microscopy platform to directly monitor how Abs-bound HIV-1 Env immune complexes are recognized by Fc receptors (FcR) in membranes. Specifically, we will utilize cryoET and single- particle cryoEM to observe the interactions between Abs-bound Env on virions and Fc gamma receptors (FcγRs) on plasma membrane blebs or virus-like particles (VLPs). We will study how two fundamentally different types of Abs, 1) broadly neutralizing Abs (bnAbs) that largely recognize the immunoevasive closed Env, and 2) non- neutralizing Abs (nnAbs) that bind highly conserved epitopes exposed on vulnerable open Env conformations, to engage FcγRs and mediate efficient Fc-effector functions. We aim to identify molecular features that define Fc potency. Our structural approach will be flanked by parallel functional assays. We will measure FcγR signaling, Ab-dependent phagocytosis of opsonized virions (ADP), ADCC, and ADCP) of infected cells using primary human effector cells. Thus, our comprehensive approach aims to determine correlates of Fc-effector function at the molecular and functional level.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY / ABSTRACT Cardiovascular disease (CVD) is the leading cause of mortality worldwide, disproportionately affecting older adults. Indeed, aging results in vascular stiffening and is the dominant risk factor for atherosclerosis. Although traditionally viewed as a disease of chronological aging, emerging evidence supports that CVD is driven by accelerated biological aging within the arterial wall. Among the cellular players involved, smooth muscle cells (SMCs) are pivotal in maintaining vessel integrity and contributing to atherosclerotic plaque structure. However, with aging, SMCs undergo epigenetic alterations particularly in DNA methylation that disrupt phenotypic plasticity, promote maladaptive remodeling, and compromise reparative functions. We recently reported that age is a key factor regulating SMC expansion in atherogenesis. Despite this central role, the biological age of SMCs and their potential for rejuvenation remain unexplored. To address this gap, our group has recently generated novel in vivo and in vitro SMC-specific epigenetic clocks using the Infinium Mouse Methylation platform. These clocks capture chronological aging of SMCs with high fidelity and provide a powerful platform to assess molecular and functional rejuvenation. We now leverage this tool to test the rejuvenation potential of transient epigenetic reprogramming with pluripotency factors OSKM (octamer-binding transcription factor 4 [OCT4], sex determining region Y-box 2 [SOX2], Kruppel-like factor 4 [KLF4], and c-MYC) to reverse SMC aging and mitigate CVD risk. Previous studies in the literature have briefly expressed pluripotency factors in other aged somatic cell types to reset epigenetic age and restore gene expression and functional capacities. Our central hypothesis is that transient epigenetic reprogramming of aged SMCs reverses molecular and functional hallmarks of aging, preserves cell identity, and mitigates vascular stiffness and atherosclerosis. In this R21 proposal, we aim to: 1) evaluate the effects of OSKM reprogramming on aged SMC function and epigenetic state in vitro and in vivo; and 2) determine how transient reprogramming alters vascular stiffness and atherosclerosis. By integrating DNA methylation profiling, gene expression analysis (including single cell RNA-sequencing), SMC and vascular functional assays and vascular disease models, this project will provide critical insights into the plasticity and therapeutic potential of aged SMCs. Our studies will serve as a foundation for novel vascular rejuvenation strategies and generate high impact preliminary data for subsequent R01 proposals focused on combating age-associated vascular disease.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY/ABSTRACT B cells are a key component of adaptive immune responses, and their differentiation from naive to long-lived antibody-secreting plasma cells provides us with protection from recurrent infections. Understanding the regulatory logic underlying B cell fate decisions, for example, the differentiation choices generating memory or plasma cells, offers the possibility of improved vaccination or immunotherapy strategies. Although B cell differentiation in humans cannot be directly observed, several computational methods have been proposed to infer regulatory networks from single cell transcriptomic data. However, existing transcriptional trajectory analysis approaches assume that the data contain cells representing a sufficient number of states along a continuum of dynamic changes. Applying such methods to B cell fate decisions is problematic since adaptive immune responses are spatially distributed, with cells migrating across many tissues (eg, lymph nodes, blood, and bone marrow), and are sampled at discrete time points often spanning days or weeks. Recent advances in high-throughput sequencing now allow for the simultaneous determination of the B cell antibody receptor (BCR) along with the cellular transcriptional profile at single cell resolution. The high variability of the BCR provides a “fingerprint” that can be used to identify the transcriptionally distinct descendants of each naive B cell (a “clone”). Further resolution of ancestor-descendant relationships can be accomplished through reconstruction of phylogenetic lineage trees based on somatic hypermutation patterns (mainly point mutations that accumulate through an enzymatically-driven process during adaptive immune responses). I propose to integrate B cell lineage trees with transcriptional trajectory analysis to resolve B cell differentiation processes across space and time. I will also improve methods for identification of clonally-related B cells by explicitly modeling B cell phylogenetic relationships as part of clonal analysis. Working closely with experimental collaborators, I will apply these methods to longitudinal human immune profiling data from multiple tissues. This will serve as method validation and may also provide knowledge that will lead to designing more effective vaccines or immunotherapies. These are early but critical steps in my long-term goal of connecting B cell migration and differentiation patterns to strategies for vaccination and other therapies.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY We propose to acquire an Avidion Cell Avidity analyzer from LUMICKS to support research on a broad range of biological questions at Yale University. It has long been understood that important physiological processes are regulated by the mechanical forces involved in cell interactions ranging from endothelial tight junctions to neuronal synapses to immune cell synapses. Yet, the ability to measure the strength of these interactions has been limited to highly technical, low throughput assays that probe only a single cell at a time. Less than a decade ago LUMICKS developed the z-Movi to measure cell-cell interaction strength on 100s of cells by acoustic force applied to a fluorescent cell interacting with a monolayer of cells on a glass plate. The PI, Samuel Katz, along with several other investigators at Yale have integrated this technology into our workflows and found it to provide meaningful measurements that accelerated our research. Based on this positive preliminary experience multiple other investigators have inquired about incorporating avidity measurements in their research programs, but the number of users that can complete an experiment on the current system each day is limiting. The recently developed LUMICKS Avidion has increased the throughput by an order of magnitude capable of approximately 200 measurements a day and two to three users. Moreover, it has expanded to four-color fluorescence in order to measure heterogenous cell populations and correlate Cell Avidity with other cell reporters. The automated nature of the Avidion with straightforward software for analysis further improves widespread usability. While this proposal nominally showcases 5 major users and 11 other users of this novel technology, multiple other investigators have expressed interest. The user base represents 12 different departments ranging from basic biologic inquiry to clinical translational uses. The requested instrument will be installed in a shared core facility at Yale, where it will support a large community of NIH-funded researchers studying cancer, autoimmunity, cardiovascular, neurodegenerative, inflammatory and other diseases. The absence of another commercially available or homemade alternative with the singular capabilities of the Avidion at Yale and the large NIH-funded userbase performing groundbreaking, high-impact research in a multitude of fields underscores the necessity for this advanced equipment.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY: Menopause is a pivotal life stage that brings about lasting changes in mental and cognitive functioning, potentially leading to profound negative effects on multiple life domains in females. During this period, many females may experience the worsening of depressive symptoms or onset of major depressive disorder (MDD), the most prevalent and disabling psychiatric disorder worldwide. Despite the fact that females comprise about half of the global population, evidence that neurochemical alterations observed during menopause may be associated with dementia onset, and higher rates of depression and dementia in females, there are currently no effective treatments targeting the mood and cognitive alterations experienced during menopause. Converging evidence from human clinical studies, postmortem analyses, and preclinical research suggests that both depression and menopause may alter the same brain mechanisms that are crucial for maintaining brain health, particularly through synaptic alterations as possible neurochemical mechanisms. Recent advancements in in vivo quantification of synaptic density in humans have made it possible to measure the density of synaptic vesicle glycoprotein 2A (SV2A), a widely expressed marker of synaptic density, using positron emission tomography (PET) imaging. Our prior studies have revealed that synaptic density is lower in individuals with MDD across young to middle adulthood. In the current study, we aim to conduct the first known in vivo human PET imaging study of how menopause affects synaptic density, whether MDD may exacerbate menopause-related alterations in synaptic density, and how these synaptic changes relate to objective and subjective measures of mood and cognition. Our preliminary data reveal significantly lower synaptic density in corticolimbic regions in post-menopausal females compared to their pre-menopausal counterparts. They further indicate substantially more pronounced deficits in synaptic density in post-menopausal females with MDD compared to pre-menopausal females with MDD, suggesting an acceleration of synaptic degradation. In the proposed study, we seek to confirm these findings in a large, well-characterized sample of females, incorporating a Research Domain Criteria (RDoC) approach to evaluate the role of menopause in moderating the relation between synaptic density and the full spectrum of mood and cognition. To assess the clinical significance of these changes, we will examine how menopause- and MDD-related changes in synaptic density are associated with functional neural (i.e., electroencephalography) and behavioral (i.e., clinical interview) measures of negative and positive valence and cognitive systems. Results of the proposed study will provide the first human in vivo data on the effects of menopause and MDD on brain synaptic density, and whether these changes may underlie the mood and cognitive alterations experienced in menopause. In doing so, they will help inform a modifiable, precision medicine-based target for treatments aimed at improving mood and cognitive alterations associated with this significant life change among females.

NIH Research Projects · FY 2026 · 2026-05

ABSTRACT People living with HIV face a significantly higher risk of developing non-Hodgkin’s lymphoma (NHL), which is the leading cause of cancer-related death in this population in the USA. Although the introduction of combination antiretroviral therapy has significantly decreased the incidence of NHL among PWH, it remains much higher than in the general population. Furthermore, individuals with HIV tend to be diagnosed with later-stage NHL and have worse prognoses than those without HIV. Thus, developing an effective strategy for earlier detection of NHL before symptomatic presentation, when cure rates are higher, is an especially important priority for people with HIV. This proposal aims to develop and validate a blood test to enable earlier detection of non-Hodgkin’s lymphoma in people with HIV, with the ultimate goal of improving NHL-survival rates in this population. We will measure altered methylation patterns of tumor-derived cell-free DNA (cfDNA) fragments in blood as biomarkers of lymphomagenesis. Specifically, we will noninvasively evaluate the hypermethylation of Epstein-Barr Virus (EBV) DNA and of gene promoters in infected B cell genomes which arise during the development of diffuse large B-cell lymphoma in people with HIV. This project is made possible by a liquid biopsy technology developed by our group, which permits efficient and comprehensive genome-wide profiling of hypermethylation patterns in cell-free DNA fragments derived from tumor cells. With access to crucial longitudinally banked plasma samples from a large cohort study of people with HIV, we are well-poised to evaluate changes in methylation of EBV DNA and the host B cell genome that occur prior to symptomatic diagnosis of lymphoma. Initial data indicate the assay's ability to detect lymphoma-specific methylation signals in pre-diagnosis plasma, often more than a year before diagnosis. This project will extend the analysis to a larger dataset, aiming to develop a predictive algorithm for early NHL detection. Key aims include characterizing the temporal order of methylation changes, evaluating algorithm sensitivity and specificity, and developing a longitudinal test to track personalized methylation signals over time. Ultimately, the project aims to develop an effective and practical approach for earlier detection of NHL, thereby improving clinical outcomes in people living with HIV.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Vascular diseases driven by endothelial dysfunction represent a major therapeutic challenge due to the lack of cell-specific delivery systems. While TGFβ-driven endothelial-to-mesenchymal transition (EndMT) has emerged as a key therapeutic target, current approaches are limited by off-target effects of systemic TGFβ inhibition. We have developed a novel HDL-mediated RNA delivery platform (C15-9- 900 LNP) that achieves unprecedented endothelial cell specificity through innovative ionizable lipid design. Our preliminary data demonstrate >90% targeting efficiency across multiple vascular beds, with exceptional manufacturing reproducibility at 2g scale, minimal inflammatory response, and established quality control parameters. This R21 ASCETTS proposal will advance platform development through two complementary aims. In Aim 1, we will establish critical quality attributes and manufacturing parameters through systematic evaluation of formulation conditions. Comprehensive particle characterization will include size, polydispersity index, and zeta potential analysis, complemented by quantitative biodistribution studies using endothelial lineage-traced mice. Advanced imaging and flow cytometry validation will confirm targeting specificity across multiple vascular beds. In Aim 2, we will demonstrate therapeutic efficacy using an established hypoxia- induced pulmonary hypertension model. We will evaluate the platform's ability to modulate TGFβ pathway signaling in pulmonary vascular endothelium, assess therapeutic outcomes through comprehensive hemodynamic and histological analyses, and establish clear translational parameters for clinical development. This platform technology represents a fundamental advance in targeted RNA therapeutics by enabling selective endothelial modification while minimizing systemic effects. Our systematic approach establishes standardized manufacturing parameters and analytical methods suitable for clinical translation. While initially focused on pulmonary hypertension, the platform creates a foundation for addressing multiple cardiovascular disorders where endothelial dysfunction plays a central role. Success in this R21 phase will accelerate therapeutic innovation through validated manufacturing processes and clear regulatory parameters.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY/ABSTRACT Intricate cytokine networks mediate effective immune responses and their subsequent return to homeostasis. Inflammatory stimuli trigger orchestrated responses to potential threats, and failure to return to homeostasis results in a pathogenic cytokine environment that can manifest as an inflammatory flare. Recurrent flares impart significant physical and psychological burden in patients of lifelong autoimmune and autoinflammatory diseases. Previously, we discovered mutation in the X-linked ETS transcription factor E74-like factor-4 (ELF4) to be causal of a cytokinopathy with a Behçet’s- and inflammatory bowel disease-like autoinflammatory syndrome in males, termed ‘Deficiency in ELF4, X-linked’ (DEX). We have previously established that ELF4 restrains hyper-cytokine secretion of IL-17, IFNγ and IL-1β upon activation in vitro and restrains systemic hypercytokinemia upon lipopolysaccharide (LPS) challenge in vivo. Through a bone marrow chimera system, I have demonstrated that ELF4 is not necessary for the development, or suppressive capacity of regulatory T cells at homeostasis, implicating alternative control mechanisms. ELF4 heterozygotes are somatic mosaics of ELF4-expressing and ELF4-deficient cells, that, interestingly are predominantly asymptomatic. Yet, recent evidence highlights that skewed X-inactivation may be responsible for newly discovered symptomatic ELF4 heterozygous variants, suggesting a critical threshold of wild-type cells may be necessary to restrain hypercytokinemia in the setting of DEX. Leveraging these insights and generating experimental cytokine flares in vivo, this proposal seeks to decode the cytokine machinery necessary to restore homeostasis after flares. We hypothesize that ELF4 functions as a key mediator of negative regulatory circuits supporting recovery after inflammatory insults, thereby resolving hypercytokinemia and preserving homeostasis. In Aim 1, I seek to determine the cell-intrinsic roles of ELF4 in tuning responses to anti-CD3/LPS induced cytokine flares, delineating the magnitude and dynamics of the cytokine codes during the perturbation and restoration of cytokine homeostasis. In Aim 2, I aim to examine the contribution of STAT1- and STAT3- inducing cytokines to feedback circuits during experimental cytokinopathy flares, to unravel the mechanisms by which ELF4-expressing cells functionally mitigate cytokinopathy resilience in the setting of ELF4- heterozygosity. The results of these investigations will not only guide our clinical approach to DEX patients but also broaden our fundamental understanding of the mechanisms of resilience to cytokinopathy.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract The human genome organization influences gene regulation. Aberrant nuclear structures observed in cancer and conservation of common features of genome organization, such as A/B compartments, topologically associated domains, and loops across mammalian evolution, further hint at its role in gene regulation. Yet scientists are only beginning to understand the sequence determinants and regulatory implications of nuclear DNA organization. Next-generation sequencing assays such as Hi-C, ATAC-seq, and RNA-seq assist in this task by measuring genome-wide biochemical activities. However, each of these three assays provides only a partial snapshot of regulatory interactions, and the lack of successful integration has hindered our understanding of the impact of nuclear organization on critical biological functions. The overarching goal of this proposal is to identify the functional consequences of variations in nuclear archi- tecture on transcriptional and post-transcriptional regulation and the role of this variation in human health and disease. Specifically, Aim 1 proposes to identify the sequence determinants of Hi-C contacts using novel deep learning models that predict Hi-C contacts from nucleotide sequences across 80 human tissues (K99 phase). Additionally, Aim 2 proposes to learn the rules of chromatin organization shared across evolution using a deep learning model for translating between Hi-C and ATAC-seq across 100 mammalian species (K99 phase). Finally, Aim 3 proposes to model the impact of variations in the nuclear organization on tissue-specific transcriptional and post-transcriptional regulation in humans using machine learning, long-read RNA-seq, and Hi-C (R00 phase). Together, this work will provide novel, open-source, and interpretable machine learning models to enable the discovery and quantification of the regulatory causes and functional consequences of nuclear DNA organization in healthy human tissues and misregulation of this architecture in disease. The models, resources, and skills learned during Aims 1 and 2 (K99 phase) will be used to accomplish Aim 3 during the R00 phase. The candidate aims to establish an independent research program that bridges the gap between experimental and computational research into genome architecture and gene regulation. She will receive the interdisciplinary training needed from her mentor, Dr. William Noble and her postdoctoral advisory committee, Drs. Erez Lieberman Aiden, William Greenleaf, Anshul Kundaje, and Sheng Wang. In addition, she will participate in career development activities offered through the University of Washington. Her research training, mentor, advisory committee, and academic environment will prepare her well as she transitions to an independent position as an academic researcher.

NIH Research Projects · FY 2026 · 2026-05

Therapeutic Rewiring of Colorectal Cancer BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer death and increasingly affects young adults. Our team has recently made paradigm-shifting discoveries in CRC oncology, biology and signalling, while also establishing proof-of-concept for therapeutic reprogramming and hyperactivation-induced lethality, pioneered the development of the first direct oncogene activator and novel receptor-targeting strategies, with extensive expertise in translating basic research into drug development. Our proposal now unites two key concepts under a single cancer rewiring project: 1) Hyperactivation — Emerging data suggest that many cancer cells are susceptible not only to inhibition of oncogenic signaling - but also overactivation of these same pathways. In CRC the three major signaling pathways that are dysregulated (WNT, MAPK and PI3K) all show evidence for this ‘Goldilocks’ (‘just right’) phenomenon. Moreover, emerging preclinical candidate therapeutics are poised to, for the first time, exploit these newfound vulnerabilities. 2) Cell-state Rewiring — CRC is also notable for the diverse sets of cell-states that drastically modulate the response to clinical therapeutics and likely will influence both response to chemotherapy, targeted pathway inhibition and pathway activators. We are similarly poised to rewire these states to enhance the response to existing and emerging therapies. AIM: Develop clinically tractable strategies using signalling activators and inhibitors to destroy cancer cells via hyperactivation and rewire cancer cells towards vulnerable cell-states. APPROACH: REWIRE-CAN (Reprogramming Epithelial WIRing to Eradicate CANcer) will address this Cancer Grand Challenge by: - DISCOVERING novel agents to modulate and hyperactivate oncogenic pathways (WP1) - DEVELOPING approaches to use novel signalling activators to treat cancer via signalling hyperactivation and cell-state rewiring (WP2) - TRANSLATING therapeutic rewiring strategies into preclinical and clinical proof-of-concept studies (WP3) METHODS: REWIRE-CAN will combine functional analysis of patient samples with advanced drug discovery, including functional genetic screens, clinical bio-specimens, patient-derived organoids, animal models, and custom single-cell signalling technologies. This integrated approach will define combinatorial signalling dependencies in human CRC and allow us to directly translate these findings into in vivo therapeutic studies prior to clinical application. IMPACT: REWIRE-CAN will harness novel signal activators and the unique signalling biology of CRC to create a roadmap for sensitising cancer cells to therapy through signalling rewiring. Our lasting impact will be to identify novel therapeutics for advanced CRC, supported by in vivo proof-of-concept and tractability towards clinical candidate development. REWIRE-CAN will develop much-needed new therapies for CRC and also act as an exemplar for emerging signalling activator therapy in cancer.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract Type 1 diabetes (T1D), which is characterized by T cell-mediated destruction of insulin-producing pancreatic beta cells, has a relatively well-defined genetic architecture that explains about 50% of inter-individual differences in disease risk. However, translating the genetic architecture into novel disease insights and therapies has lagged behind because its molecular and cellular mechanisms are incompletely understood. Studies have established a strong impact of T1D genetics on T cells, which supports the development of the only FDA-approved drug for delaying T1D-onset in high-risk individuals by targeting T cells. However, majority of individuals are non-responsive to this drug and/or develop disease regardless. The selective destruction of beta cells but no other endocrine cells that are embedded with beta cells in the islets implicates intrinsic beta- cell biology as a driver of T1D development. An emerging mechanism causing beta-cell destruction is noncanonical mRNA translation that generates neoantigens that act as autoantigens to invoke destruction by T cells. Accordingly, studies have elegantly demonstrated that insulin gene (INS) variation contributes to T1D risk by modulating the fidelity and efficiency of insulin mRNA translation in beta cells. In pursuit of our efforts to understand how genetics affect beta-cell biology and contribute to T1D, we overlayed T1D risk variants with variants that regulate gene expression and discovered genetic upregulation of RPS26 expression levels in human beta cells causally contributes to T1D risk. We further found that RPS26 expression is upregulated in beta cells from patients with T1D compared to control individuals. RPS26 is involved in mRNA translation and prior studies demonstrated that RPS26 protein can directly bind to certain mRNAs with features similar to that of insulin mRNA and orchestrate noncanonical translation. For instance, RPS26 has been shown to promote noncanonical translation of neurotoxic FMR1 mRNA bearing polymorphisms that are similar to those in the insulin mRNA. We herein hypothesize that genetic regulation of upregulation of RPS26 expression dysregulate translation efficiency and fidelity in beta cells, which impairs their vitality while enhancing immunogenicity in T1D. We will use genetic approaches to downregulate RPS26 expression and to induce T1D-related point mutations respectively in human beta cells and surrogate beta cells to understand the impact on beta-cell vitality, translation efficiency and fidelity, and immunogenicity. We will also use recombinant adeno-associated virus to specifically knockdown Rps26 in beta cells of autoimmune diabetes-prone NOD/ShiLtJ mice and investigate the impact on diabetes incidence. We will investigate the correlation between RPS26 genetic variation and markers of functional beta-cell mass in patients with T1D using the UK Biobank and the DCCT/EDIC study datasets. The findings from these studies are expected to shed light on novel mechanisms in beta cells contributing to their demise in T1D and inform drug targets for effective treatment of T1D.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY While immune checkpoint blockade therapies have revolutionized the treatment of cancer for patients, many remain unresponsive. There has been increased focus on factors outside of tumor-infiltrating CD8 T cells that contribute to treatment efficacy, particularly the role of helper CD4 T cells. In investigating this question, current studies have identified the CD4 subset, T follicular helper cells and their canonical cytokine Interleukin (IL)-21, to be an important driver of response, particularly to the CTLA-4 axis of immunotherapy. These studies, however, fail to define the precise location of IL-21 delivery for optimal CD8 T cell help or additional required factors, including the generation tumor-specific B cells. Based on preliminary data that tumor draining lymph nodes (tdLNs) contain a reservoir of IL-21 producing CD4 T cells outside of B cell follicles and that CTLA-4-mediated IL-21 production depends on a B cell antigen, I hypothesize that in order to optimally prime CD8 T cells to generate antitumor effectors and respond to CTLA-4, IL-21 production must occur outside of the B cell follicle in tdLNs and that this depends on the presence of tumor-specific B cells. To directly test this, I will pursue the following aims. For my first aim, I will define the factors that give rise to the subset of IL-21+ CD4 T cells in the extrafollicular zone of tdLNs. To accomplish this, I will spatiotemporally track the location, phenotype, and path of differentiation of IL-21-producing cells in tdLNs by cyclic immunofluorescence, flow cytometry, and single cell RNA sequencing. I will target genes predicted to be involved in this differentiation path using Cas9 ribonucleoprotein editing of tumor-specific CD4 T cells to modify their development and function. For my second aim, I will determine the role of IL-21 production on CD8 T cell effector function and anti-CTLA-4 therapeutic efficacy. To do this, I will eliminate the ability to produce IL-21 in tumor-specific CD4 T cells or remove B cells and determine the effects on CD8 T cell effector function and CTLA-4 blockade efficacy. I will then use adoptive transfer studies with a model of lung adenocarcinoma that is capable of generating IL-21+ TFH, HELLO, and one that is not, NINJA, to assess the requirement of CD4 interactions with tumor-specific B cells for CTLA-4 immunotherapy responses. Lastly, I will directly deliver tumor-specific CD4 T cells with ectopic IL-21 expression to NINJA tumor-bearing mice to overcome the requirement of B cells. I expect that my findings will uncover the necessary factors for productive IL-21 delivery within tdLNs and identify new strategies to generate IL-21 producing cells and reinvigorate CD8 T cells in ICB unresponsive tumors.