University Of California, San Francisco

NSF Awards · FY 2025 · 2025-03

Cells contain complex networks of proteins that interact with each other in much the same way that electronic components interact in a circuit. Understanding how these circuits work has been a major goal in cell biology. Most tools available to researchers involve breaking molecular circuits, for example by removing one or more of the proteins in the network. This project will develop a method for adding new connections to the networks inside a cell, by implanting a physical electronic device that can interface with the cellular circuits, providing a completely new type of tool for studying how cells make decisions and carry out complex behaviors. If the project works, it could usher in a new era of convergence between molecular biology and microelectronics, with impacts on basic biology, biotechnology, and the semiconductor industry. Broad application of this approach will require a workforce with comprehensive understanding of both electronics and cell biology. A key broader impact of this project is that it will create an unprecedented opportunity for trainees from both electrical engineering and molecular cell biology labs to become cross-trained in both fields, via personnel exchange between research groups as well as pioneering interdisciplinary courses in cellular electronics. Another broader impact will be development of public outreach by showcasing new demonstrations at the Exploratorium science museum. This project is based on the hypothesis that intracellular signaling network models could be tested more rigorously, and networks reprogrammed to a wider range of behaviors, if it were possible to modify the links between nodes by introducing new functional connections between signaling proteins. It is difficult to create new connections between proteins using conventional molecular biology approaches. This project will develop a radical solution to address this problem by implanting microelectronic chips into living cells, which will sense kinase activities and/or monitor the concentration of second messenger molecules, and then trigger release of mRNA, siRNA, or small molecules to target specific signaling proteins, effectively “rewiring” the signaling pathway under electronic control. These chips will integrate biochemical sensors and actuators on a single chip, complemented by wireless communication and power delivery systems, controlled by onboard logic, all engineered to be of a size suitable for implantation into living cells. The device will incorporate nanofabrication techniques and advanced integrated circuit design to achieve a final chip size smaller than 100 µm by 100 µm, and 10 µm thick, allowing it to be accommodated within a single cell. The focus of this proposal is to conduct proof of concept experiments to determine the feasibility of this vision. At each step of the project’s progression, prototypes will be tested within living cells, using the giant amoeba Chaos carolinensis because of its large size and amenability for microsurgical implantation. Testing will be based on sensing and actuating easily-measured kinase molecules to allow verification of proper device function. This project was jointly funded by the Cellular Dynamics and Function program, along with the Systems and Synthetic Biology program in the Division of Molecular and Cellular Biosciences. Additional support was provided by the Communications, Circuits and Sensing Systems programs in the Division of Electrical, Communications, and Cyber Systems. 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 · 2025-03

PROJECT SUMMARY Twenty-four-hour intraocular pressure (IOP) assessment remains an unmet need in the clinical management of glaucoma. Among the devices that yield IOP measurements in millimeters of mercury, there is a 15-33% variance between true IOP and device output. Other devices lack the automation that facilitates IOP capture during undisturbed sleep. The ideal device would be non-invasive, accurate, and automated. Such a device would permit the exploration of the relationship between intraday IOP fluctuation and the pathogenesis of Primary Open Angle Glaucoma, the leading cause of irreversible blindness. It would also facilitate accurate screening, rapid diagnosis, and intuitive assessment of response to treatment. The overarching goal of the proposed research is to develop an accurate, safe, wearable IOP monitor. To accomplish this, we propose the following aims: Aim 1: Develop prototype of a contact lens based IOP sensor based on Atomic Force Microscopy. Aim 2: Develop an empirical model for the relationship between indentation measurements and IOP. Aim 3: Assess the effects of self-sensing cantilever indentation on the human corneal epithelium. The results of these experiments will inform prototype development with the goal of developing a wearable IOP monitor that accurately measures IOP with 0.1-1 mmHg precision. This instrument would improve the clinical management of glaucoma. ACTIVITIES RELATED TO DIVERSITY: THE RABB-VENABLE EYE RESEARCH CLUSTER INITIATIVE Recent studies have demonstrated the dire lack of diversity among ophthalmology faculty and trainees. There is a similar trend in the biomedical research workforce and the NIH clinical research training program only yielded five potential eye researchers in 15 years. During the grant funding period, we would like to: Objective 1: Expand URiM medical student recruitment to ophthalmology residency training programs. Objective 2: Support URiM medical students to complete a one-year research fellowship. Objective 3: Increase URiM ophthalmologist representation in the clinical translational research pipeline. Physician workforce diversity is a key component of mitigating healthcare disparities. This program will produce up to 25 potential eyes researchers during the 5-year funding period. We believe that building a core of physician scientists who can provide culturally sensitive care to underserved communities and lead the development and adoption of equitable healthcare delivery procedures and practices is necessary in ensuring greater health equity.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY The approach-avoid dichotomy is inherent in motivated behavior and animal survival; adaptive behavior requires these conflicting drives be appropriately weighed. In many human anxiety disorders, the approach- avoid calculation becomes maladaptive as individuals preferentially elect avoidance even when it is an inappropriate selection. At 32%, the lifetime prevalence of anxiety disorders is the greatest of any psychiatric illness in the United States, and current treatments are only effective in a subset of individuals—there is an unmet need for therapeutics that effectively ameliorate symptoms of anxiety. It is thought that the neural substrates underlying anxiety are conserved across phylogeny; therefore, understanding how non-human brains navigate approach-avoid conflicts can shed light on the mechanisms human brains use when faced with conflicts that contribute to the human anxiety state. The ventral hippocampus (vHPC) in rodents and the analogous structure in humans, the anterior hippocampus (aHPC), plays a central role in the approach-avoid calculation. Over a decade ago, simple lesion and manipulation experiments identified a functional gradient along the HPC axis; dorsal HPC was linked to spatial learning and memory, and vHPC was deemed a regulator of unconditioned avoidance responses. Since then, the development and use of innovative neuroscience tools has illuminated the extensive role vHPC, and particularly the vCA1 subregion, plays in coordinating a diverse array of approach-avoid behaviors. Still, one of the most well-studied properties of vCA1 is its capacity to represent experiences imbued with motivation to avoid; vCA1 encodes representations of innately anxiogenic environments, drives avoidance of these areas, and is necessary for many forms of fear learning. But the extent to which this circuitry contributes to avoidance behavior is unknown. One question that has been severely underexplored: how does vCA1 orchestrate avoidance of learned cues that predict aversive outcomes? Here, I describe how I will use circuit manipulation tools to determine the causal effect of vCA1 network activity on learned avoidance. I then describe how I will use microendoscopy technology to examine vCA1 network dynamics as animals learn to associate a neutral cue with an aversive outcome, and ultimately learn to avoid the cue. Given that maladaptive avoidance is relevant to the human anxiety state, findings from this research could provide direction for future therapeutic interventions. I will be conducting these experiments in the Kheirbek lab, where all the techniques necessary for my project have been previously setup and validated. The Kheirbek lab is located at the University of California, San Francisco, which is a world-renowned biomedical facility. I am well positioned to successfully complete the described project and graduate from UCSF as an impactful scientist.

NIH Research Projects · FY 2026 · 2025-02

Project Summary While causal genetic variants have been identified for many craniofacial syndromes, the functions of these genes in normal development and the mechanisms by which these variants lead to disease often remain unknown. Catel-Manzke syndrome (CMS) is a condition in which patients exhibit Pierre Robin Sequence (PRS), encompassing micrognathia and cleft secondary palate, together with limb and cardiovascular phenotypes and is caused by mutations in the dTDP-D-Glucose 4,6-dehydratase (TGDS)-encoding gene. The developmental and molecular functions of TGDS are unknown but our preliminary data indicate it may function in pathways impacting glycosaminoglycan metabolism. We have used next-generation CRISPR/Cas9 gene-editing approaches in mice to generate an allelic series that models CMS and enables the study of Tgds function in vivo. We propose a series of mouse genetic and quantitative morphometric assays to pinpoint the affected developmental processes, which we combine with unbiased transcriptomic, glycomic, and metabolomic approaches to build a foundation for understanding CMS etiology and Tgds developmental function. Completion of these studies will provide novel insights into the function of an unstudied gene, reveal the etiology of a craniofacial syndrome, and contribute to our fundamental understanding of how metabolic pathways regulate craniofacial development.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY/ABSTRACT The rationale for this grant is rooted in the observed disparities in the experiences and outcomes of UCSF students from historically underrepresented and marginalized (HUG) groups. Despite being academically indistinguishable from their majority peers in terms of GPA, publications, and time to degree, these students report higher rates of unhappiness and dissatisfaction, leading to lower participation in the scientific workforce upon graduation. We and others contend that the repeated emphasis on the negative experiences and unique difficulties encountered by these students has created a deficit focused thread of inquiry in which research continually identifies institutional mismatches and achievement gaps as compared to their well- represented peers. Arguably, identifying deficits does not account for the positive experiences and successes of these students, nor acknowledge that there are many historically underrepresented and marginalized students who elect and successfully complete higher STEM degrees, pursue STEM careers, or choose to use their STEM degrees in creative ways. Therefore, this proposal is guided by evidence in graduate education that points to the importance and effectiveness of social support programs that help HUG students successfully navigate the graduate school experience. The overarching mission of the proposed UCSF IMSD-T32 Program is to intentionally cultivate a community that values the experiences and perspectives of each HUG cohort and prepares fellows for academic and professional success as biomedical researchers. Training and activities proposed here will help IMSD Fellows’ academic and career success, because they will develop a strong sense of scientific identity through a series of co-curricular innovations that promote better alignment between personal and professional values, thus strengthening IMSD Fellows’ ability and desire to persist toward positions of scientific leadership. The program aims to foster scientific identity congruence and create a supportive academic environment that centers around community, belonging, identity, and organizational congruence. Key innovations include summer research rotation opportunities with programming to align personal and professional values, near-peer mentoring to foster mentorship skills, and initiatives to develop IMSD Fellows' agency and ownership in academic and career planning. By reinforcing anti-deficit framework and operationalizing campus resources for well-being, community building and career development, the proposed UCSF IMSD-T32 Program will provide frameworks for IMSD Fellows to create and measure their own pathways toward success.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY Deficits in speech production are highly prevalent in neurodevelopmental disorders (NDDs). They are some of the most debilitating of all deficits because they impair communication and there are not effective and efficient substitutes for speaking. In order to build our mechanistic understanding of the neurodevelopmental causes of speech impairments, we propose to study speech dysfunction in individuals with 16p11.2 deletions, which is one of the most common genetic etiologies of autism and is associated with related conditions such as epilepsy, motor impairment, sensory dysfunction, and most prominently, speech impairments, which affect an estimated 70-100% of individuals with this copy number variant. We will capitalize on data being collected for the ongoing UCSF Speech, Voice, and Communication (SVAC) study of speech in individuals with idiopathic autism for comparison groups, including speech-impaired autistic and typically developing participants, for the proposed cross-sectional study. We will enroll participants with 16p11.2 deletion syndrome and concurrently examine speech abilities, sensorimotor control of speech, and the neural processes that support these functions. This will allow us to build a mechanistic understanding of the potential causes of speech impairments in these populations. Our strong preliminary data suggest distinct mechanisms of impairment in speech-impaired individuals with autism without known genetic etiology and individuals with 16p11.2 deletion syndrome. Contrasting the more genetically and phenotypically homogenous group of individuals with 16p11.2 deletions with the more heterogeneous autism group will allow us to identify differences in neurobiology and sensorimotor control of speech that are specific to genetic impact via the deletion as opposed to being associated with broad neurodevelopmental differences. Thus, the proposed work will build our neurobiological and mechanistic understanding of speech impairments in neurodevelopmental disorders. This knowledge can be applied to uncover potential causal pathways of speech impairments and identify novel targets for intervention.

NIH Research Projects · FY 2026 · 2025-02

Project Summary Sepsis is an overwhelming, maladaptive, and lethal dysregulation of the immune response to infection. Annually, approximately 50 million people suffer from sepsis with 11 million resulting deaths worldwide. Age is one of the strongest risk factors for mortality from sepsis. Aging correlates with an overall reduction in the quality of immune response. The reasons behind age related immune decline are poorly understood, however, de-repression of transposable elements may play a role. Transposable elements (TEs) are repetitive, mobile, genetic elements that translocate, and amplify, themselves across a genome. Usually, they exist in a repressed state. However, their de-repression has been shown to result in accelerated aging phenotypes in mice and flies. Furthermore, we show de-repression of TEs in human immune cells can result from a genetic mutation in the AGO2 gene. This TEs de-repression results in activation of innate immune defenses in the form of interferon signaling. This phenomenon, known as viral mimicry, ultimately causes resting immune cells to exit quiescence in the absence of pathologic stimuli. TEs-mediated sterile activation of the interferon pathway is associated with immune aging. Notably, TEs located within immune genes are highly differentially expressed in sepsis. Furthermore, de-repressed TEs have been shown to affect human immune responses to infection. However, the relation between TEs expression and sepsis severity is poorly understood. We hypothesize that immune cell TEs de-repression in sepsis correlates with immune system aging, and with increased morbidity and mortality. Specifically, in Aim 1 we will investigate the dynamics of TEs de-repression as a function of age and sepsis. In Aim 2 we will employ machine learning to quantify immune aging and identify specific TEs, or families of TEs, that can predict immune aging or ICU outcomes such as mortality and secondary infections. In Aim 3 we will conduct whole exome sequencing on septic patient samples to identify mutations associated with high TEs expression. We will use CRISPR for reverse genetic experiments, in immortalized immune cells, to determine if mutations from septic patients, and candidate mutations such as AGO2 and SIRT6, lead to TEs de-repression. Finally, we will compare gene expression levels in cells with mutations giving TEs de-repression (ie: AGO2) to sepsis with high TEs expression using RNA-seq. Overall, these studies will investigate what role transposable elements may play in sepsis pathogenesis and maintenance. Results from this work could potentially shed light on genomic mechanisms underlying sepsis progression. Such mechanisms, should they exist, could suggest novel and personalized therapies similar to what is seen in cancer.

NIH Research Projects · FY 2026 · 2025-02

Project Summary/Abstract Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) remains a major global health problem, and the only licensed vaccine, Bacille Calmette-Guérin (BCG), lacks sufficient efficacy to control the TB pandemic. Therefore, development of effective TB vaccines is a high priority for controlling global TB. Since CD4 T cells are known to be important for protective immunity to TB, they have been the focus of TB vaccine development. Regardless of the mechanism, to be effective, vaccines must contain one or more antigens that can induce protective immune responses; not all antigens possess this potential, and some antigens can induce detrimental immune responses. Of ~4,000 Mtb proteins, ESAT-6 is among the most immunogenic, as it induces robust CD4 T cell responses in response to infection in multiple host species including humans, mice, and cattle. Consequently, ESAT-6 has been assumed be a valuable vaccine antigen, and it is included in multiple TB vaccines at various stages of development and testing. However, vaccines that contain ESAT-6 combined with other antigens have only modest efficacy even in animal models, and T cell responses to ESAT-6 in Mtb-exposed humans do not distinguish those with latent TB from those with active TB. These results are consistent with ESAT-6 acting as a decoy antigen that does not induce protective immunity to Mtb, and that may even interfere with optimal immunity. Determining if ESAT-6 serves a decoy antigen is important for vaccine design, since vaccination might enhance a decoy effect and limit vaccine efficacy. However, understanding the protective value of ESAT-6 and testing the decoy hypothesis have been impeded by the fact that ESAT-6 is also essential for Mtb virulence. Since traditional approaches have not been able to dissociate the role of ESAT-6 as a T cell antigen and its role in virulence, we took an innovative approach and generated transgenic mice whose CD4 T cells selectively lack the ability to respond to ESAT-6. We developed a novel strategy to express the I-Ab CD4 T cell epitope of ESAT-6 in the thymus so it is recognized as self during T cell development and causes deletion of ESAT-6-responsive CD4 T cells. We generated the mice and confirmed that they do not develop CD4 T cell responses to ESAT-6 during Mtb infection. With these (‘ESAT-6 tolerant’, or ‘6T’) mice, we can now determine the value of ESAT-6 as a CD4 T cell antigen without perturbing the function of ESAT-6 as a cell autonomous virulence determinant. In this project, we propose to determine whether CD4 T cell responses to ESAT-6 are beneficial, detrimental, or neutral in Mtb infection; we will determine whether ESAT-6 is a decoy antigen that alters recognition of other Mtb antigens; and we will test the hypothesis that ESAT-6 contributes to vaccine efficacy through mechanisms other than by serving as a T cell immunogen. Our findings will be valuable for guiding antigen selection in new TB vaccines and will either increase confidence that ESAT-6 is a valuable TB vaccine antigen or provide evidence that alternative antigens should be prioritized. The ESAT-6-tolerant mice we generated may also provide a new model for novel vaccine antigen discovery.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY Food insecurity is a critical driver of maternal and infant health and nutrition, including poor birth outcomes, suboptimal breastfeeding, perinatal depression and stress, and poor child growth and development. Pregnant women living with HIV are particularly vulnerable to food insecurity and face an excess risk of poor birth and infant outcomes. In sub-Saharan Africa, where both food insecurity and HIV are highly prevalent and a third of children under five are stunted, interventions to reduce food insecurity and malnutrition that are relevant for both women with and without HIV are needed. In rural settings in this region, small-scale farming is the primary source of livelihood, yet unpredictable rainfall, severe climate events, and limited irrigation hamper crop yields. Agricultural livelihood interventions are a promising approach to raising income, bolstering food security, and ultimately improving maternal and infant health and nutrition. Yet studies of agricultural interventions initiated in pregnancy are lacking despite the fact that in utero exposures crucially predict pregnancy and infant outcomes. The objectives of this proposal are to determine the effectiveness of an agricultural livelihood intervention on improving maternal and infant health when initiated in early pregnancy, and to understand factors that influence implementation of an agricultural intervention in the perinatal period, including the need for farming support when pregnancy impacts women’s capacity to work in the fields. We propose a hybrid effectiveness- implementation trial among 410 pregnant women enrolled at ≤20 weeks gestation, half living with HIV in western Kenya. Women will be randomized 1:1 the intervention or routine care. Those randomized to the intervention will receive guidance on obtaining farming support. Our central hypothesis is that by empowering pregnant women with skills and tools for sustainable farming and perinatal nutrition, the intervention will lead to improved maternal and infant health compared to control participants. We propose an HIV status neutral approach to optimize the generalizability and potential reach of this intervention. Also, because HIV stigma and poor health present additional barriers to empowerment and healthy behaviors, this intervention, which may reduce these barriers, has the potential to alleviate infant health disparities associated with maternal HIV. We propose the following aims: Aim 1: Determine the impact of the intervention on maternal, pregnancy and infant health outcomes, among women living with and without HIV and their newborns. Aim 2: Determine the impact of the intervention on empowerment, socioeconomic, and behavioral factors that may influence maternal and infant health. Aim 3: Identify attitudes, norms, processes, and resources that influence implementation outcomes and effectiveness of the intervention initiated in early pregnancy. This research will significantly advance scientific understanding of whether, how, and under what circumstances an agricultural intervention for pregnant women affects health.

NIH Research Projects · FY 2025 · 2025-01

Parkinson’s disease (PD) affects 1% of people over 60 years old, is highly disabling and represents a large economic burden. Therapeutic options include dopaminergic replacement and conventional DBS (cDBS) for advanced disease. However, cDBS therapy is currently unresponsive to the dynamic clinical states of patients, resulting in suboptimal control of symptoms during the day. Adaptive DBS (aDBS) seeks to solve this through personalized dynamic modulation of stimulation according to neural signals. Early studies of aDBS (completed by Drs Little, Starr and other research groups) provide proof-of-principle that aDBS can improve motor symptoms and reduce side-effects. Our team has also tested fully embedded, chronic naturalistic aDBS in a randomized, blinded study to show improvements in daytime motor symptoms and quality of life compared to cDBS. Further, we have also recently validated sleep stage specific Non Rapid Eye Movement (NREM) aDBS, that increased cortical slow waves (linked to slowed disease progression). However, full leveraging of these highly promising therapies is currently limited by 1) Lack of practical (minimally invasive) methods for chronic cortical recordings. 2) Complexity of programming aDBS due to a large parameter space. 3) Fluctuations in neural signals on multiple time scales, including circadian changes and long-term non-stationarity of signals. Our long-term goal is to advance aDBS from specialist research laboratories to real-world clinics through efficient, scalable implementation with the following advances: 1) Reduce risk and complexity of chronic cortical sensing by placing cortical leads in the subgaleal space rather than inside the cranium. 2) Utilize machine learning (ML) and data-driven biomarker and optimization techniques to minimize aDBS programming complexity. 3) Optimize aDBS across the full 24hr cycle - including sleep, with methods for long-term updating of aDBS settings. The study device will be the rechargeable, sensing and aDBS enabled, newly commercially available Medtronic Percept RC DBS system; connected to subgaleal frontal cortex leads and to directional basal ganglia leads. Our UG3 stage will support regulatory approval for Percept RC subgaleal aDBS. In UH3- 1, we will implant 24 PD patients, optimize cDBS, and identify subgroups for daytime and nighttime aDBS. In UH3-2 we will obtain in-clinic and at-home daytime naturalistic neural recordings and perform a blinded evaluation of data-driven chronic aDBS versus cDBS, for treatment of daytime motor fluctuations. In UH3-3, we will obtain in-clinic (sleep lab) and at-home nighttime naturalistic recordings and perform a blinded evaluation of chronic sleep aDBS versus cDBS, to improve NREM sleep duration and increase slow wave amplitude. We anticipate that these techniques will be the basis for a simple “turnkey” aDBS controller, to enable widespread, simple, scaleable and personalized aDBS for the full 24 hr. cycle in PD, and provide a rational foundation for adaptive neuromodulation in other neurological and psychiatric diseases.

NIH Research Projects · FY 2026 · 2025-01

Parkinson’s disease (PD) affects 1% of people over 60 years old, is highly disabling and represents a large economic burden. Therapeutic options include dopaminergic replacement and conventional DBS (cDBS) for advanced disease. However, cDBS therapy is currently unresponsive to the dynamic clinical states of patients, resulting in suboptimal control of symptoms during the day. Adaptive DBS (aDBS) seeks to solve this through personalized dynamic modulation of stimulation according to neural signals. Early studies of aDBS (completed by Drs Little, Starr and other research groups) provide proof-of-principle that aDBS can improve motor symptoms and reduce side-effects. Our team has also tested fully embedded, chronic naturalistic aDBS in a randomized, blinded study to show improvements in daytime motor symptoms and quality of life compared to cDBS. Further, we have also recently validated sleep stage specific Non Rapid Eye Movement (NREM) aDBS, that increased cortical slow waves (linked to slowed disease progression). However, full leveraging of these highly promising therapies is currently limited by 1) Lack of practical (minimally invasive) methods for chronic cortical recordings. 2) Complexity of programming aDBS due to a large parameter space. 3) Fluctuations in neural signals on multiple time scales, including circadian changes and long-term non-stationarity of signals. Our long-term goal is to advance aDBS from specialist research laboratories to real-world clinics through efficient, scalable implementation with the following advances: 1) Reduce risk and complexity of chronic cortical sensing by placing cortical leads in the subgaleal space rather than inside the cranium. 2) Utilize machine learning (ML) and data-driven biomarker and optimization techniques to minimize aDBS programming complexity. 3) Optimize aDBS across the full 24hr cycle - including sleep, with methods for long-term updating of aDBS settings. The study device will be the rechargeable, sensing and aDBS enabled, newly commercially available Medtronic Percept RC DBS system; connected to subgaleal frontal cortex leads and to directional basal ganglia leads. Our UG3 stage will support regulatory approval for Percept RC subgaleal aDBS. In UH3- 1, we will implant 24 PD patients, optimize cDBS, and identify subgroups for daytime and nighttime aDBS. In UH3-2 we will obtain in-clinic and at-home daytime naturalistic neural recordings and perform a blinded evaluation of data-driven chronic aDBS versus cDBS, for treatment of daytime motor fluctuations. In UH3-3, we will obtain in-clinic (sleep lab) and at-home nighttime naturalistic recordings and perform a blinded evaluation of chronic sleep aDBS versus cDBS, to improve NREM sleep duration and increase slow wave amplitude. We anticipate that these techniques will be the basis for a simple “turnkey” aDBS controller, to enable widespread, simple, scaleable and personalized aDBS for the full 24 hr. cycle in PD, and provide a rational foundation for adaptive neuromodulation in other neurological and psychiatric diseases.

NIH Research Projects · FY 2026 · 2025-01

ABSTRACT The University of California San Francisco's (UCSF) Advanced Research Careers (ARC) HUB is designed to provide comprehensive mentorship, training and career exploration for senior doctoral and postdoctoral scholars. The UCSF ARC HUB's initiatives are designed to equip scholars for a seamless transition into roles as research and teaching faculty or as researchers in the biotech sectors. Utilizing UCSF's established resources and proficiency in career and professional development, the program integrates evidence-based strategies rooted in career theory and proven methodologies aimed at doctoral and postdoctoral scholars. It provides platforms for both guided and self-directed information gathering related to the three career foci of the HUB. The HUB also offers innovative instruments for the identification and assessment of occupation related skills, knowledge, and competencies. Additionally, it gives access to extensive data on national and local workforce capacities, salary benchmarks, and growth projections. Scholars will be onboarded in cohorts, establish their peer coaching groups, and participate in a 3-day HUB Institute, providing them with a suite of professional development workshops and opportunities for networking. Coaches are senior faculty and biotech professionals trained in coaching and relevant career theory. The coaches will lead semi-structured monthly virtual meetups to discuss scholar progress as well as personal and professional issues related to scholars’ professional path and development. Finally, the program will provide monthly workshops on a variety of career related topics in the context of a four stage career development framework. These topics include Career Planning, Networking Strategies, Negotiation Skills, and Entrepreneurship and will be led by experienced professionals. Participants will also have access to career guidance professionals through the Office of Career and Professional Development at UCSF. The instruction and mentoring components of the program reflect the strengths-based approach designed to maximize informed career decision making, enhance career self-efficacy and optimize preparation and competitiveness for successful entry into the research workforce. As the program progresses and matures, we look to develop a robust alumni network that will enhance the training activities, as well as provide ongoing support, mentorship, and job opportunities.

NIH Research Projects · FY 2026 · 2025-01

Project Summary Variant effect prediction (VEP); the process of determining the impact of amino acid alterations in a protein sequence, remains a fundamental challenge across both clinical and research domains. Despite the extensive application of existing VEP methods, their overall impact is limited, with most variants labeled “variants of unknown significance”. This research project aims to overcome these limitations in VEP, harnessing the potential of protein language models (PLMs) which have already shown widespread success in other fields, and integrating complementary sources of information, as employed by current methodologies, to enhance the understanding and prediction of genetic variants' functional impact on proteins and complex traits. The specific aims include: 1) Enhancing the core functionality of VEP models by providing robust estimates of score uncertainty and experimentally validating whole haplotype effect scores, including predictions of epistatic interactions. 2) Improving VEP model performance by integrating PLMs with external information such as 3D structural and homology data and fine-tuning them on functional assays and clinical databases. 3) Improving the discovery and clinical interpretation of functional protein-altering variants by optimally utilizing computational annotations and analyzing whole haplotype data in the context of gene-trait associations and clinical settings. This research project builds upon our strong preliminary data of PLM-based variant effect prediction, which by multiple metrics has demonstrated best-in-class performance. By leveraging PLMs and a variety of external data, this project aspires to advance the field of variant effect prediction, enabling a more profound understanding of genetic alterations, and improving diagnostic and prognostic medical exome sequencing.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY For almost 50 years, blood-based therapies, such as autologous serum tears (ASTs), have been used in clinical ophthalmology to treat diverse ocular surface disorders including Sjogren's syndrome-related dry eye disease, persistent epithelial defects, chemical injury, recurrent erosion syndrome, superior limbic keratoconjunctivitis, neurotrophic keratopathy, limbal stem cell disease, cicatrizing conjunctivitis, and post-corneal cross-linking haze. It is theorized that serum has components that either replace those missing endogenously or modulate pathways to restore healthy function. However, to date, there has been no detailed molecular characterization of serum tears in the context of ocular surface disease. The poorly defined mechanism of serum tears in treating ocular surface disease leads to two important challenges in their clinical application: (1) the lack of a standard concentration for preparation, and (2) the inconvenient and costly process of obtaining ASTs. Thus, despite many clinical studies that demonstrate the ability of serum tears to improve both objective signs and subjective symptoms of ocular surface disorders, formulation and accessibility issues have limited its more widespread use. Our overall objective is to define the combinations of serum components (growth factors, signaling lipids, vitamins, etc.) that support corneal repair. We hypothesize that the effects of serum tears are due a simple combination of bioactive factors, some of which remain to be characterized, or the result of synergistic actions of serum components. Our studies seek to determine bioactive serum tear components and define synergism between components, and characterize the in vivo effects of blood-based tears in an ocular surface disease model. We anticipate this project will yield both translational insight to the clinical use of serum tears, and likely improve current formulation and accessibility issues which may allow for more widespread use. Furthermore, the identification and characterization of bioactive serum tear components is expected to reveal potential therapeutic targets for further exploration.

NSF Awards · FY 2025 · 2025-01

This project involves the creation of artificial intelligence (AI) models that make predictions about health events like substance use and stress-related blood pressure spikes using data from smartwatches like FitBit, Apple Watch, and other wearables. The innovation of this project comes from training personalized models that learn exclusively from each person’s wearable data. Recent advances in AI methods allow us to train these models to understand each user’s individual biosignals patterns related to heart rate, movement, and other signal recordings using large amounts of unlabeled data that are recorded when the user wears the device. This should, in theory, enable us to refine these models to learn to predict relatively complex recurring health outcomes like stress and blood pressure spikes using much fewer labeled examples than what would have previously been necessary. We will test this paradigm in two user studies related to stress-related hypertension and substance use detection. The status quo for machine learning consists of the development of a one-size-fits-all model which is usually trained on data coming from one group and tested on data from another disjoint group. However, the advent of self-supervised learning makes it possible to learn from vast unlabeled multimodal data streams recorded from a single individual, allowing for a pretrained model which learns feature representations which are specific to the baseline temporal dynamics of a single entity’s data streams. This project seeks to understand how such personalized self-supervised learning on multimodal data streams can be used to overfit, in a positive manner, a machine learning model to the unique patterns of an individual’s sensor readings, thus enabling model personalization and prediction of traditionally difficult or subjective targets. To make these artificial intelligence (AI) innovations practically useful and because these personalized models still require on the order of tens of annotations to converge, we propose to develop novel human-computer interaction (HCI) techniques which are tightly integrated into the AI workflow to facilitate reliable and effective yet minimal annotations of the adverse health event of interest from the end user. We will evaluate this paradigm on two separate health conditions with differing data types and nuances: (1) substance use and craving measurements and (2) stress-related hypertension, each predicted using multimodal passively collected consumer wearable and smartphone data streams. 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 2025 · 2025-01

PROJECT SUMMARY Dysfunctions in organelles such as the mitochondria and lysosomes are increasingly being appreciated to drive various forms of neurodegenerative diseases, such as the Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD). However, an integrated organelle proteome consortium in the field of AD/ADRD is lacking. To address this knowledge gap, an interdisciplinary team, consisting of Drs. Biao Wang and Danielle Swaney will form the Alzheimer's Disease Organelle Proteome Task (ADOPT), to quantitatively measure organelle proteome to provide in-depth knowledge of organelle homeostasis and function in the complex brain tissues during the disease progression of AD. This R03 proposal is a pilot phase of ADOPT, in which genetic organelle tagging approach will be utilized to enable rapid purification of lysosome from neurons in wild-type and AD brains from mouse models. A suite of mass spectrometry experiments will quantitatively measure organelle proteome, including protein abundance, post-translational modifications, and protein complexes. Computational modeling will determine lysosomal proteome homeostasis. This systems-to-function approach will shape new scientific paradigms in AD/ADRD research.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY/ABSTRACT This application presents a five-year mentored research and training plan that will prepare Dr. Sharon Chiang to be a leader in the field of hippocampal-cortical neuronal microcircuits in memory in epilepsy. Dr. Chiang completed her MD at Baylor College of Medicine and her PhD in Statistics at Rice University, where she was trained as a Bayesian statistician in the lab of Dr. Marina Vannucci, and is now a Clinical Fellow in Neurology at the University of California, San Francisco, in the Division of Epilepsy. Dr. Chiang's long-term career goal is to advance our understanding of the cellular circuits underlying memory in epilepsy and to investigate targeted manipulations to improve memory. This project will lay the basis of foundational studies for her independent research program focused on these aspects. Temporal lobe epilepsy (TLE) is the most common epilepsy in adults and affects more than 50 million people worldwide. There are no effective treatments for memory dysfunction in TLE, which stems from a lack of understanding of the fundamental mechanisms underlying memory impairment. Initially after an experience, the hippocampus repeatedly “replays” the memory at compressed timescales and transfers the memory to long-term storage in the neocortex. This replay of memories and the formation of a stable, long-term representation of the memory in the neocortex are critical to intact memory formation. Whether these critical elements are abnormal in TLE, and may be potential targets for manipulation, is unknown. This proposal leverages high-density, in vivo single neuron recordings in the hippocampus and neocortex in an experimental rat model of TLE, combined with real-time neurofeedback and electrical stimulation, to test the hypothesis that memory replay and formation of cortical memory-supporting neuronal ensembles are abnormal in TLE and that manipulations targeting these steps will improve memory. This work will generate fundamental knowledge about the role of two key neural circuitry steps in memory in TLE and may open avenues to new classes of targeted therapeutic manipulations. The proposed career development plan includes training in high-density flexible polymer probes, real-time neurofeedback, and electrical stimulation. Dr. Chiang will learn all of the skills needed for an independent research career, including mentoring/supervising trainees/staff, grant-writing, and scientific communication. She has assembled a world-class mentorship team with complementary expertise in hippocampal physiology, sharp- wave ripples, and memory (Primary mentor, Dr. Loren Frank); inhibitory microcircuits and closed-loop interventions in epilepsy (Scientific Advisor, Dr. Ivan Soltesz); rodent models of epilepsy and high-frequency oscillations (Scientific Advisor, Dr. Laura Ewell); electrical stimulation (Dr. Vikram R. Rao); neuroethics and rodent/human translation (Scientific Advisor, Dr. Daniel H. Lowenstein); and histopathology (Scientific Advisor, Dr. Cathryn Cadwell). Dr. Chiang, her mentors, and the Department of Neurology at UCSF are fully committed to this proposal and her development into an independent physician-scientist by the end of this training period.

NSF Awards · FY 2025 · 2025-01

The broader impact of this I-Corps project is the development of a contact lens-based device to monitor intraocular pressure (IOP). Glaucoma is the leading cause of irreversible blindness. It will affect nearly 5 million Americans and 112 million people worldwide by 2040. However, the emerging contact lens-based IOP monitors lack automation, lack accuracy with poor correlation to IOP, or induce significant tissue damage. This technology is an automated, wearable, IOP monitor capable of accurately assessing physiologic IOP fluctuation over 24 hours. Currently, continuous IOP monitoring is an unmet need in the clinical management of glaucoma. Current home devices designed to measure the pressure inside the eyes are incapable of providing automated measurements of the cornea for applications in IOP determination and surgery to correct vision. This device may be the first to describe the pathophysiology of primary open angle glaucoma as well as improve diagnostic accuracy and clinical outcomes. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a contact lens-based intraocular pressure (IOP) sensor. The cornea varies significantly with patient demographics, shape, and mechanical properties. This technology utilizes custom microelectromechanical systems (MEMS) self-sensing cantilevers to directly measure IOP-related changes in cornea thickness, radius of curvature, and Young’s modulus of elasticity. In addition, the device considers the demographics of each individual wearer as inputs into a computational model for IOP determination. The cantilevers are optimized to provide Δ 0.1 mmHg sensitivity without inducing clinically significant epithelial damage. The cantilever array is controlled to provide automated measurements and transmit data wirelessly to the electronic medical record. The contact lens is designed for ease of use, allowing the wearer to place the sensor and initiate the IOP monitoring session in the home setting. The prototype is currently under development to assess the effects of cantilever microindentation on corneal epithelium and the measurement principle. These findings will further refine the prototype for the first in-human clinical trials. 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 2025 · 2025-01

ABSTRACT Some individuals with behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA) syndromes are known to develop an intense, narrowed focus on specific activities, interests, and ideas, which together can be termed “rigid preoccupations” (RP). Examples of these behaviors include preoccupation with puzzles or games, collecting objects, dietary and exercise fads, religious or political adherence, clock watching, preoccupation with saving gasoline or electricity, and many others. Despite the very high early prevalence rates and clinical significance of RP behaviors in a subset of persons with dementia (PWD), particularly those with right temporal lobe dysfunction where RP symptom rates approach 90%, there is still no consensus in the field on the precise phenomenology of RPs from a behavioral neurology or neuropsychological perspective, and thus no agreement on how to measure them. The absence of validated measurement tools for comprehensively characterizing RP-related symptoms, and a lack of understanding of the fundamental neural circuitry involved in different presentations of this behavior, have hampered diagnosis and phenotyping, clinical research, clinical trial recruitment and monitoring, and clinical care of PWDs. For this study, we propose to perform a comprehensive evaluation of the phenomenology of RP symptoms using qualitative ethnographic methods, and to perform a chart review of archival research reports that can be analyzed in conjunction with functional MRI data. This work will set the foundation for later development of neurologically-grounded measures of RPs after this project. For Aim 1, we will perform a qualitative study to clarify the phenomenology of RPs using standard ethnographic methods. We will enroll 30 PWDs known to engage in RP behaviors, and will conduct interviews and home-based participant observation with them and their caregivers to elucidate their motivating emotions and thought processes. Interviewers will take observational field notes and conduct qualitative interviews with both PWDs and caregivers. Analytic memos will be constructed for each dyad to guide identification of themes. Transcribed interviews and field notes will be coded in ATLAS.ti, adding new codes as they emerge inductively. In parallel for Aim 2, we will perform a retrospective chart review of research visit summary reports from 200 PWDs (100 bvFTD/100 svPPA), quantifying evidence of RP behaviors and their associated cognitive and emotional processes. Data from the chart review will then be analyzed in conjunction with previously collected resting-state MRI scans to perform a preliminary examination of the neural basis of RP- associated features using functional connectivity and dynamic causal modeling approaches. Our goal is to understand the phenomenology of RP behavior in a data-driven manner using mixed-method approaches robust enough to capture the complexity of the internal cognitive and emotional processes involved, which will facilitate more meaningful hypotheses about the neurologic mechanisms underlying RPs and guide development of better measurement tools, facilitating advances in both research and clinical care.

NIH Research Projects · FY 2026 · 2025-01

PROJECT ABSTRACT: Prostate cancer is the most common cancer diagnosis in men, with approximately 300,000 new cases per year, marked by exceptionally heterogeneous prognosis across patients. We are now a decade into the era of clinically available genomic biomarker tests to improve clinical prognostic estimates and help guide decision-making after diagnosis of prostate cancer. Three RNA-based tests from prostate tissues are currently included in NCCN guidelines, and they have recently been joined by the first predictive biomarker derived from pathology artificial intelligence (PAI) analysis of standard H&E-stained cancer tissue. However, current genomic tests offer limited insights into tumor heterogeneity and biological variability, and little is understood of how PAI systems reflect the underlying biology, limiting their potential in advancing cancer research across patient sub-groups. The goal of this proposal is to apply two cutting-edge spatial proteogenomic technologies together with PAI to identify aspects of previously obscure biology which drive AI outcomes, and to explore and elucidate prostate cancer heterogeneity and prognosis at unprecedented depth. We will identify and validate, through micron-scale subcellular spatial analysis, novel genomic and proteomic markers of outcomes after prostate cancer treatment that can both explain and extend emerging pathology artificial intelligence (PAI) algorithms. We propose to 1) understand competitive and/or additive relationships between established standard-of-care genomic expression and PAI scores in predicting outcomes after radical prostatectomy, 2) employ spatial proteomics and transcriptomics to describe prostate cancer heterogeneity, local evolution, and cellular diversity at unprecedented detail; and to identify novel markers that can improve on both existing genomic scores and PAI, and 3) illuminate the black box of PAI—and build a better box by comparing subcellular proteogenomic and PAI convolutional features, and incorporating all these streams into next-generation AI algorithms. These platforms in concert will improve on our current ability to predict outcomes based on clinical and imaging parameters alone, and will yield novel insights into prostate cancer’s heterogeneity within patients, between individuals, and across diverse population groups. Overall, this study will greatly enhance our understanding of prostate cancer biology and heterogeneity within and between patients, and across critical sub-populations. We expect to generate next- generation artificial intelligence-based tools to drive a new level of personalized treatment for patients across the disease spectrum.

NIH Research Projects · FY 2026 · 2025-01

ABSTRACT The physiologic and neuropathologic processes in Alzheimer disease (AD) and Alzheimer disease related disorders (ADRD) are insidious and take decades to develop. Furthermore, the likelihood of developing AD/ADRD is influenced by the interplay of genetics and risk/resilience factors, especially cardiovascular disease (CVD) risk factors and social determinants of health (SDOH), that operate over the life course. Given that the new AD disease modifying therapies are believed to be most effective in the early stages, as well as the tremendous burden that AD/ADRD places on patients, caregivers, and society, it is imperative to identify the earliest manifestations of these diseases in order to offer better prevention/treatment, particularly in more diverse populations. The transition from midlife to early late-life offers an exciting and under investigated time period for early clinical AD/ADRD development and how this may differ according to race and sex. We propose to conduct a Year 40 (when participants have a mean age of 65) cognitive assessment and AD/ADRD adjudication among the ongoing Coronary Artery Risk Development in Young Adults (CARDIA) study in order to investigate this early late-life transition to clinical AD/ADRD and to determine underlying mechanistic pathways that may highlight prevention opportunities. CARDIA is uniquely positioned to address this line of investigation as it has repeated cognitive and brain MRI measures over the midlife period and is comprised of roughly equal numbers of Black and White participants who have been followed since their 20’s. We hypothesize that the early late-life period (when participants are in their 60s) is a critical window of opportunity to identify the transition to early clinical AD/ADRD and determine how this is influenced by early neurodegenerative (assessed by MRI, genetics, blood AD biomarkers and other factors) as well as vascular pathways (assessed by CVD, genetics, MRI and other factors). In turn, because CARDIA is balanced by race and sex, we will be in an excellent position to investigate disparities in the midlife to late-life transition to early AD/ADRD and whether mechanistic drivers differ by sex and race. We will also identify the life course predictors of this early AD/ADRD with a particular focus on comprehensive measures of SDOH and determine how SDOH also may influence proposed mechanistic pathways and their changes over time. Finally, as part of an exploratory aim, we will develop a prognostic model for AD/ADRD in the 60s incorporating life course risk factors, MRI measures, AD biomarkers, genetics and other data elements. This model will be essential for future risk prognostication as AD/ADRD drug development and prevention strategies advance and there is need to identify people as early as midlife in order to target primary prevention. Findings from this innovative study will provide highly relevant results to the field of AD/ADRD by providing critical information on the midlife to early late-life transition to AD/ADRD, the mechanistic pathways behind these changes, SDOH influences, and the underpinnings of health disparities for AD/ADRD.

NIH Research Projects · FY 2026 · 2025-01

Cancer immunotherapy is a new treatment modality that has revolutionized cancer care, providing benefits to many patients who previously had untreatable disease. However, we still do not fully understand how this breakthrough treatment works at a molecular level. Deep mutational scanning (OMS) is a new technique that enables the generation of large-scale libraries of mutants to understand how changes at the sequence level impact downstream protein phenotypes. Unlike previous, targeted mutagenesis techniques which were limited in the number of mutants that could be surveyed, OMS is capable of generating a comprehensive map of all potential amino acid change in a given protein. I will use OMS to profile how alterations to PD1, one of the key targets of cancer immunotherapy, impact myeloid cell function. A key limitation of existing OMS assays is the relatively coarse readouts, such as cell proliferation. In order to generate a richer characterization of each OMS mutant, I will couple it to single-cell RNA sequencing to enable fine grained readouts of cell state. I will then use the resulting data to train a large language model (LLM), a type of mathematical model that is capable of predicting the impacts of immunotherapy on cell state. This fellowship will give me the tools and techniques to advance my career, launching me on the path to becoming an independent investigator at an R 1 institution.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY/ABSTRACT Asthma is a chronic inflammatory airway condition with high global prevalence causing significant morbidity and mortality. Allergic, “type 2” (T2), inflammation is the defining feature of asthma in many patients. Type 2 T helper (Th2) cells and the airway epithelium, acting through the canonical T2 cytokines IL-4 and IL-13, have central roles in asthma. Polarization of T cells towards a Th2 phenotype via IL-4 stimulation creates a pool of Th2 cells that are a major source of IL-13 in the airways. Sustained airway epithelial exposure to IL-13 causes goblet cell metaplasia and stimulates the secretion of chemokines that recruit inflammatory cells to the lung. When left unchecked, these changes amplify over time, increasing disease severity and promoting exacerbations that carry high morbidity and mortality. The mechanisms that control the magnitude and duration of T2 signaling in asthma are not well understood. In this proposal, we seek to identify RNA regulatory circuits that drive persistent T2 inflammation in T cells and the airway epithelium. Post-transcriptional regulation is an important mechanism that allows cells to tune the intensity of inflammatory responses. Interactions between 3’ untranslated regions (UTRs) on mRNAs and RNA binding proteins (RBPs) are key to this regulatory level. RNA binding proteins interact with the 3’ UTRs, dictating transcript stability, degradation, and localization. These circuits give cells dynamic control over the flow of transcriptomic information into cellular actions. Post-transcriptional regulation is understudied in asthma and presents the potential to define novel mediators of T2 inflammation. Our lab recently identified the STAT6 3’ UTR as a potentially important post-transcriptional regulatory element in T2 high asthma. Signal transducer and activator of transcription 6 (STAT6) is a critical mediator of T2 gene expression programming, acting as a transcription factor in response to IL-4 and IL-13. The STAT6 3’ UTR has multiple regions with protein occupancy and contains a SNP (rs1059513) that is highly associated with asthma and allergy, suggesting regulatory control that may dictate sensitivity to IL-4 and IL-13. Through high resolution mapping, we seek to identify functional elements across the STAT6 3’ UTR and their role in regulating the T2 signaling intensity in T cells and the airway epithelium. We will assess how these functional elements control gene expression, cytokine secretion, and epithelial cell differentiation. We have also identified candidate RBP regulators of T2 inflammation in the airway epithelium which include IGF2BP3, ZFP36L1, and ZFP36L2. Using CRISPR activation and interference, we will evaluate how these proteins control IL-13 mediated gene expression, pathologic mucus accumulation, and airway epithelial cell differentiation. These studies will illuminate clinically relevant post-transcriptional circuits in asthma and nominate novel pathways for potential therapeutic targeting. This project will be completed through a postdoctoral fellowship at UCSF and will utilize comprehensive institutional support and resources to prepare the applicant for an independent research career.

NIH Research Projects · FY 2026 · 2025-01

Project Summary/Abstract Acute exacerbations in chronic obstructive lung disease (COPD) are often triggered by respiratory viral infections that leads to irreversible decline in lung function. Mechanistic insight into the pathophysiologic link between viral triggers and loss of lung structural cells could uncover therapeutic modalities to attenuate the frequent exacerbations in COPD patients that leads to significant morbidity and mortality. This proposal will interrogate how tissue factors in the lung alters the inflammatory niche associated with viral infections to suppress alveolar type 2 (AT2) stem cell in emphysema, a subtype of COPD characterized by the loss of alveolar epithelium. Our preliminary data demonstrate that fibroblast-specific deletion of Hhip, an emphysema susceptibility gene, promotes the accumulation of T cells with tissue residency features (tissue resident lymphocytes, or TRLs) in the alveoli and subsequent loss of AT2s after viral infections, suggesting that host factors in the lung can alter the inflammatory cascade after viral infections to suppress a lung stem cell reservoir. We go on to demonstrate that TRLs can directly suppress the self-renewal capacity of AT2s, which is in part mediated by the secretion of the antiviral cytokine, interferon gamma (IFNγ). Finally, we show that a highly clonogenic human AT2 subset characterized by basal interferon gene expression is lost in the lungs of emphysema patients concurrent with accumulation of TRLs. Utilizing a combination of novel genetic tools to trace and delete Hhip+ stromal cells, genetic model of IFNγ activation, human organoid platform, 3D high-content tissue imaging, single cell analysis of human lung stem cell subsets, and a novel pharmacologic reagent made in our lab to target TRL accumulation, this proposal will determine the mechanism by which stromal factors in the lung modifies TRL accumulation in response to viral infections and tobacco smoke, and how TRLs suppress AT2s in both mouse and human models. Furthermore, we will determine whether host factors that modify TRLs can be leveraged as pharmacologic therapy to attenuate the inflammation and stem cell loss associated with acute exacerbation in emphysema.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY Immunotherapies for cancer have revolutionized oncology, but most patients do not experience durable responses. Immune checkpoint inhibitors targeting PD-1 and PD-L1 are now FDA-approved for a wide variety of tumors, but non-invasive strategies to monitor response and identify mechanisms of resistance have not yet been developed. Such approaches would allow responsive patients to remain on therapy and potentially avoid the toxicity associated with other therapies, such as chemotherapy and radiation. In addition, early identification of resistance would allow for new precision medicine-based strategies to block those mechanisms and improve patient outcomes. We recently identified a novel mechanism of inflammation-mediated resistance to immune checkpoint inhibitors. Tumor cell production of the inflammatory cytokine IL-1a drives a suppressive circuit, resulting in the downstream production of G-CSF and CXCL1, which expand and recruit immunosuppressive neutrophils to the tumor microenvironment. In these tumors, immune checkpoint inhibitors do increase CD8 T cell infiltration in the tumor, but these CD8 T cells have poor cytotoxic function. Paradoxically, TNFa produced by T cells potentiates the resistance circuit by driving the production of higher levels of G-CSF and CXCL1, resulting in more neutrophil infiltration into the tumor. Blocking key elements of this circuit can synergize with checkpoint inhibitors to sensitize otherwise resistant tumors. Non-invasive imaging strategies to identify this mechanism of resistance early after therapy would allow patients to receive these combinations rapidly without waiting for evidence of disease progression by a radiographic scan. In this proposal, we will continue developing and will test such imaging strategies, including PET to measure granzyme B, which contributes to response, and neutrophil levels in the tumor, which contribute to resistance, early after treatment. We will also test novel implantable fluorescence sensors capable of measuring these parameters and reporting out their levels continuously in vivo. We will pair these molecular imaging approaches with high-parameter multiplexed ion beam imaging (MIBI) to measure up to 50 proteins simultaneously at subcellular resolution in tissue sections. We will utilize these techniques in established mouse models of response and resistance (Aim 1) and in a mouse model that exhibits variable responses (Aim 2). We will then determine whether early measurements after therapy enable rapid treatment modification for multiple tumor models with differing mechanisms of resistance, establishing imaging-based precision medicine for immunotherapy (Aim 3). These studies will collectively elucidate a novel mechanism of inflammation-mediated resistance to checkpoint inhibitors while developing molecular imaging approaches to measure these in real time early after treatment initiation. This study is in direct response to PAR-21-294, Molecular Imaging of Inflammation in Cancer, and will achieve the high-priority goals established by the NCI.