Stanford University

NIH Research Projects · FY 2024 · 2023-07

Project Summary/Abstract There is a critical need to translate retinal ganglion cell (RGC) therapies from lab to clinic, particularly cell transplant therapies to repair degenerated eye tissues and restore visual function. RGC transplant has great potential in treating degenerative retinal and optic nerve diseases, but key pre-clinical studies are hampered by an inability to track transplanted cells. In this project, the candidate proposes to advance RGC transplant in treating glaucoma through longitudinal and non-invasive tracking of RGCs with the aid of nanoparticle-based optical coherence tomography (OCT) contrast agents. These nanoparticles are to be customized to label and visualize RGCs with a high spatial resolution. Longitudinal tracking of the RGCs in vivo could uncover the fate of the donor RGCs, increase our understanding of their behavior in the eye, and identify the factors that affect the treatment efficacy of RGC transplants. In this application, the PI first proposes to use spectral OCT signals of gold nanorods (GNRs) to maximize the contrast between donor RGCs and the retina in OCT imaging. Second, the PI proposes to examine the correlation between the OCT signals of GNRs and the fate of donor RGCs with both in vitro and in vivo assays. Third, the PI proposes to test the effects of cell number and injection location on the transplant success rate, and to leverage advanced imaging to optimize RGC transplantation. Overall, investigations in GNR-based OCT contrast agents for in vivo RGC tracking will gain us essential knowledge in the efficacy of RGC transplant and advance RGC transplant for glaucoma treatment. These data will contribute to the PI’s overall career goals, to investigate biomaterials that could track, support, and control therapeutic cells in vivo and to use these biomaterials to provide novel methods to treat otherwise incurable diseases. During the mentored phase of this award, the candidate will prioritize undertaking activities to increase understanding and gain hands-on training in the areas of OCT and glaucoma in the Department of Ophthalmology at Stanford, with support from the world-class Molecular Imaging Program and the outstanding Materials Science & Engineering Community at Stanford, and with the benefits of a close-knit and focused department and the multi- interdisciplinary collaborations and resources of the more comprehensive university.

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY Depression is the leading cause of disability worldwide and the leading cause of disease burden in the U.S. Up to a third of depressed individuals experience treatment-resistant depression, defined as the failure to achieve adequate improvement after two or more medication trials. A major advance in the field of psychiatry in the last 20 years is the development of a non-pharmacological option for treatment resistant depression using repetitive transcranial magnetic stimulation (rTMS). rTMS has proven an effective treatment modality for those with medication-resistant depression. While this represents a major advance, about half of patients do not benefit from rTMS for depression, and it is not clear why. One of the major impediments to optimizing rTMS and improving the percentage of patients who benefit from rTMS is a lack of understanding with regards to the basic mechanisms of how and why rTMS works. Prior work in this field has been limited by relying heavily on non-invasive measures of brain activity (functional MRI, EEG) and behavior to assess the underlying mechanisms of rTMS. These methods have inherent limitations in spatiotemporal resolution and despite several decades of research have not uncovered a satisfactory understanding of the mechanisms of action of rTMS in humans. The current proposal aims to apply a novel approach that combines invasive and noninvasive methods to evaluate the effects of rTMS with much higher spatiotemporal resolution than has been possible to date. Intracranial electrodes are surgically implanted for clinical reasons in epilepsy patients, and this proposal takes advantage of that unique ability to record directly from the human brain during the administration of stimulation protocols used to treat depression. The goal is to characterize the key signatures of the brain’s response to repeated doses of rTMS with an unparalleled combination of spatial and temporal resolution using intracranial recordings. We do this by evaluating the intracranial effects of focused electrical stimulation to maximize focality and minimize sensory effects (Aim 1), translate stimulation noninvasively by measuring the intracranial effects of rTMS (Aim 2), and translate intracranial recordings noninvasively using simultaneously measured scalp EEG (Aim 3). Our central hypothesis is that rTMS predictably changes evoked responses and oscillatory power locally and in downstream regions, and these changes accumulate across rTMS sessions in brain regions relevant to depression. If successful, this project will inform noninvasive EEG signatures of rTMS response that can be traced back to intracranial physiology. By relating scalp EEG signatures to reliable neural sources, these markers can be leveraged to optimize current treatments, develop new treatments, and overall markedly improve treatment efficacy.

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY/ABSTRACT Over 50% of long-term survivors of the Fontan operation with single ventricle congenital heart disease develop heart failure, for which standard therapies (ACE inhibitors, β-blockers) are largely ineffective. Thus, a major challenge in treating Fontan heart/circulation failure is in understanding its unique mechanisms that differentiate it from the more common acute ischemia-related heart failure and identifying new therapeutic targets. The overarching goal of this proposal is to develop new therapeutic targets to preserve heart function, and to identify biomarkers to detect heart/circulation failure earlier in the clinical course of patients with a Fontan circulation. We have previously identified chronic oxidative stress-induced mitochondrial injury as a major mechanism in Fontan failure. We hypothesize that oxidative stress induces cardiomyocytes to release damaged mitochondria that impair endothelial function in both the heart (local) and peripheral vasculature (plasma) in patients with Fontan failure. We examine this general question through the lens of cell-cell communication in the cardiovascular system. In Aim 1, we will evaluate the role of chronic non-ischemic oxidative stress in causing mitochondrial dysfunction in Fontan failure. We will use myocardial tissue to assess lipid peroxidation-induced mitochondrial dysfunction, correlate mitochondrial dysfunction with severity of clinical illness and how damaged mitochondria can be packaged and transported in extracellular vesicles to mediate cell-cell communication. In Aim 2, we will investigate whether lipid peroxidation-induced mitochondrial injury impairs cardiac vascular function. We will show that cardiac vascular dysfunction is a critical component of Fontan failure which may serve as a novel therapeutic target. We will assess endothelial mitochondrial dynamics in myocardial tissue from children with Fontan failure, assess cardiomyocyte and endothelial cell-cell communication via extracellular vesicles and phenotype the cardiac microvascular tree to assess for lipid peroxidation and cell death. In Aim 3, we will determine circulating biomarkers to monitor clinical status in children with and without Fontan failure and compare to control. We will show that circulating extracellular vesicles carrying oxidatively damaged mitochondria cause peripheral vascular endothelial dysfunction, determining the role of extracellular vesicles in initiating metabolic reprogramming, both locally and in distant organs. Using innovative approaches, including 3D human tissue imaging and high throughput quantitative proteomics, in a large cohort of patients with a Fontan circulation, we will test our hypothesis and examine the effectiveness of new mitochondrial-targeted therapies, including repurposing the FDA-approved small molecule elamipretide to target lipid peroxidation. Through better understanding of the unique mechanisms of Fontan failure, our team of clinicians and experts in mitochondrial and vascular biology are poised to develop new strategies for preventing and treating cellular energetic failure and vascular dysfunction.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY/ ABSTRACT Malaria is a leading cause of morbidity and mortality globally, responsible for the deaths of hundreds of thousands of individuals per year, primarily children and pregnant women. Effective control is hampered by the lack of a vaccine and continually emerging drug resistance. Most cases of severe malaria are caused by Plasmodium falciparum, which is an obligate intracellular parasite of human red blood cells (RBCs). Therefore, critical host factors may provide an untapped source of new therapeutic targets. Red blood cell invasion is a complex process that involves interactions between several parasite ligands and host receptors, but there remains a fundamental gap in knowledge regarding the functional role(s) of RBC host factors for P. falciparum. This gap in our knowledge is, in part, due to RBCs being terminally differentiated and lacking DNA, thereby precluding conventional genetic experimentation. To surmount this roadblock, we have recently developed CRISPR-Cas9-based methods to generate null mutants in primary human hematopoietic stem cells and efficiently differentiate them ex-vivo to mature cultured RBCs (cRBCs), opening new opportunities for functional analysis of these important cells. Our objective in this proposal is to comprehensively determine the specific roles and functions of two novel RBC host factors required for P. falciparum invasion, CD44 and CD55, which were recently identified from a forward genetic screen. Our central hypothesis, supported by strong preliminary data, is that these critical surface receptors play distinct yet synergistic roles to facilitate P. falciparum invasion through their interactions with parasite ligands and subsequent signaling to the host cell. In the first aim, we will determine the precise steps involving CD44 and CD55 in P. falciparum invasion of human RBCs using live cell imaging and advanced microscopy. In the second aim, avidity-based and proximity labeling proteomic approaches will be used to identify P. falciparum and RBC binding partners for CD44 and CD55. In the final aim, we will define host RBC signaling pathways activated by P. falciparum invasion, and test their dependence on CD44 and CD55. Together, these studies will generate a comparative understanding of the mechanistic roles of two novel host factors crucial for P. falciparum invasion. In addition to revealing new insights into the fundamental cell biology of Plasmodium invasion and human RBCs, this work will stimulate new therapeutic and vaccine approaches to treat one of the most important infectious diseases of humankind.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY / ABSTRACT Diabetes profoundly impairs the tissue repair process, leading to chronic non-healing wounds, which represent a leading cause of lower limb amputations. The role of vascular pathology in impaired diabetic wound healing (“under healing”) has been well established, and the role of external mechanical forces across wounds in promoting excessive scar formation (“over healing”) is similarly well studied. However, the mechanisms through which these countervailing systems interact within diabetic tissue to yield non-healing skin ulcers have yet to be thoroughly examined. During prior years of NIH-funded research, important contributions have been made to our knowledge of the critical role of vascular progenitor cells in normal and diabetic wound healing. These include the first studies on single cell analysis of diabetic subpopulations during wound healing in both mice and humans, which identified specific cell subtype depletions that contribute to impaired blood vessel formation and delayed healing. More recently, the role of mechanoresponsive fibroblast populations in driving excessive skin scarring and ineffective wound closure has been examined in similar pathologic states. To understand the effects of diabetes and mechanical force on cell population dynamics with greater precision, we have developed novel single cell techniques to identify critical perturbations in cell subpopulations. In this proposal, we will apply these emerging -omics technologies to characterize the behavior of cell populations in non-healing diabetic wounds. It is our fundamental hypothesis that local tissue mechanical forces contribute to the disruption of cellular ecology in diabetic wound healing and that mitigation of these forces can improve healing. To achieve this, we will first employ a novel multiplex approach to high-throughput single cell sequencing to evaluate changes to cell populations in human diabetic wounds healing under different mechanical environments (Specific Aim 1). We will then confirm the changes in human diabetic cell populations using animal models, while more precisely assessing the effect of skin tension on healing kinetics (Specific Aim 2), which will further clarify the functional role of these cells. Finally, we will use real world data (RWD) from electronic health records to evaluate the efficacy of therapies aimed at offsetting mechanical forces, in order to develop clinical models to guide treatment strategies (Specific Aim 3). Collectively, this work will enhance our understanding of diabetic wound biology and its interaction with the external mechanical environment, paving the way for future therapeutic approaches, while also providing generalizable clinical recommendations for force offloading therapies that can be readily applied to guide treatment decisions at wound centers across the United States. The studies described in this proposal reflect the multi-faceted approach to translational medical research that I hope to achieve moving forward in my career as a clinician scientist.

NIH Research Projects · FY 2026 · 2023-06

Uninsured patients are subject to catastrophic health expenditures, have higher rates of mortality, and far more limited availability of important healthcare resources (e.g., preventative or specialist care, rehabilitation, mental health) compared to insured patients. Uninsured individuals often defer care until treatment is urgently required, which can lead to debilitating disease, job loss and high medical bills. With more than 70% of uninsured patients unable to pay for their healthcare, U.S. hospitals and states are left to bear the brunt of uncompensated care ($42 billion). Hospital Presumptive Eligibility (HPE), a hospital-based emergency Medicaid program, is a successful solution to these problems. Patients enroll in temporary HPE healthcare coverage (up to 60 days), with an opportunity to sustain insurance by applying for Medicaid full coverage. Although HPE is a national Medicaid requirement, California is among the more comprehensive in terms of HPE eligibility. Among the 31 million remaining uninsured Americans, 10% are in California, the world’s 4th largest economy. During our previously funded R21, we collaborated with the California Department of Healthcare Services (DHCS) to create an innovative new dataset that tracks HPE enrollees across the state and follows them longitudinally to evaluate for Medicaid sustainment. Over 100,000 previously uninsured Californians enroll in HPE annually, up to 64% of whom sustain Medicaid at six-months. Inpatients, those requiring surgery or post-discharge health services are more likely to sustain insurance, with other groups less likely to sustain. Across hospitals, Medicaid sustainment ranges from 33-97%. Our preliminary data suggest that patient socio demographics, availability and training of hospital personnel and county-level engagement contribute to success of Medicaid sustainment after HPE enrollment. In response to PAR-20-310, investigation of modifiable predictors of Medicaid sustainment will guide our development of a DHCS, hospital and county-stakeholder informed “best practice” toolkit intervention for dissemination across hospitals, with the goal of reducing insurance-based differences. We will pursue 3 specific aims: (SA1) quantitatively characterize distribution of sustainment across hospitals and identify patient and hospital-level factors associated with Medicaid sustainment after HPE, (SA2) qualitatively identify hospital and county practices that promote or limit success Medicaid sustainment across varied settings, and (SA3) develop a stakeholder-informed best practice “toolkit” aimed at increasing Medicaid sustainment across hospitals and counties. Our goal by developing strategies for increasing sustained insurance coverage is to improve availability of care, clinical outcomes and financial health among otherwise uninsured patients.

NIH Research Projects · FY 2026 · 2023-06

Persistent poverty areas, a formal geographic classification developed by the United States Department of Agriculture and codified by Congress, is defined as an area with a poverty rate of 20% or higher across four consecutive ten-year time periods, spanning 30 years. Cancer rates are higher in these areas, and improving cancer outcomes in these areas requires transformational, multisector solutions that are co-created with the impacted communities. To address this challenge, we will form the Upstream Research Center, an innovative approach to provide practical policy-relevant solutions to the problems inherent in persistent poverty areas by leveraging state programs for Guaranteed Basic Income and the Earned Income Tax Credit (EITC). Our team science approach to this problem is supported by the unparalleled resources at Stanford University, the University of California, San Francisco and the University of California, Davis. Our work advances multiple conceptual and methodological innovations through two main research projects: 1) an ongoing partnership with the California Department of Social Services to access and evaluate a $35M intervention of Guaranteed Basic Income in persistent poverty areas with a focus on modifiable cancer risk factors and intermediate outcomes; 2) the impact of increases in income support through the EITC, which in California has a unique focus on lower income wage earners. Our Specific Aims are to: Aim 1. Build a collaborative community of residents in persistent poverty areas, policy makers, trainees, cancer and social science researchers and data scientists that co-create programs to address the fundamental impacts of low income, Aim 2. Evaluate the impact of income-based interventions in persistent poverty areas in Northern CA, Aim 3. Develop a mathematical model, with community input, that can assist in predicting long-term impacts of income-focused interventions on cancer incidence, providing community members, policy makers, and researchers with guidance on how best to eliminate the increased burden of cancer in persistent poverty areas, Aim 4. Develop and implement a career enhancement program that will facilitate the training and career development of interdisciplinary early-career scholars who are committed to advancing cancer research in persistent poverty areas and Aim 5. Implement innovative and collaborative cancer prevention and control programs identified through the Upstream Research Center research projects and our community partners to develop long-term sustainable strategies in our Northern CA Catchment Areas and across the Persistent Poverty Centers Network. Results from this novel groundbreaking work will lay the foundation for transformative approaches to address cancer prevention and control programs through capacity building and sustainable partnerships with policymakers, state and local agencies and community partners.

NIH Research Projects · FY 2025 · 2023-06

Abstract Age-related hearing loss is one of the most common conditions in the elderly. Many genetic factors for hearing loss have been identified, but many more remain to be identified; and our lack of knowledge about the mechanisms by which they cause hearing loss is a barrier that must be overcome if we are to develop methods for preventing (or reversing) age-related hearing loss. No model organism has contributed more than the laboratory mouse to improving human health, and mouse models have shaped our understanding of the mammalian auditory system. Mice with genetic mutations have been used to identify genes that are critical for auditory function, and for characterizing human genetic factors that cause hearing loss. A spontaneous hearing loss with an oligogenic basis develops in several well-studied inbred mouse strains (A/J, DBA/2J, MA/My, NOD/LtJ, NOR/LtJ, C57BR/cdJ, C57L/J). Our recently developed AI-based computational pipeline (GNNHap) identified four causative genetic factors for spontaneous hearing loss in three strains (A/J, DBA/2, NOD/LtJ). However, to accelerate the pace of genetic discovery for hearing loss, this project will enhance our AI by enabling it to analyze structural variant alleles present in the genomes of inbred strains, and by adding three computational capabilities for prioritizing candidate genes. The enhanced AI will be able to: (i) determine if alleles within the human homologues of identified mouse candidate genes were associated with hearing loss in human GWAS; (ii) analyze a phenotypic database to determine if a mouse line with a knockout of a candidate gene has impaired hearing; and (iii) analyze gene expression data in the Gene Expression Analysis Resource (gEAR) to determine whether identified candidate murine genes (and their human homologues) are expressed in the ear. The enhanced computational tool will then be used to identify genetic factors for hearing loss in four strains (MA/My, NOR/LtJ, C57BR/cdJ, C57L/J). Since it is critical to characterize genetic effector mechanisms, state of the art genome engineering is used to generate knockin (KI) mice, which have a reversion of a causative genetic factor for hearing loss to wild type. A detailed evaluation of these KI mice is performed to characterize the individual (and combined) effect of these mutations on hearing loss and cochlear morphology. Characterization of their genetic effector mechanisms will reveal how a set of interacting oligogenic factors produce a spontaneous hearing loss. As a stretch goal, we will use some of these KI mice to determine if we can develop a novel gene x environment model for noise- induced hearing loss.

NIH Research Projects · FY 2025 · 2023-06

Project Summary l The complexity of the human brain and lack of adequate models severely hinders our ability to understand mechanisms guiding neurodevelopment and neurodevelopmental disorders (NDDs), necessitating an innovative bioengineered approach for improving in vitro organotypic models of the human brain. Recent advances in stem cell-based neural organoids enable the formation of assembloids, which are fusions of organoids representing different brain regions. However, current approaches remain limited in the ability to properly recapitulate native brain cytoarchitecture and maturation within these organoids and also result in large heterogeneity due to the lack of a well-defined matrix. The proposed research seeks to resolve these critical issues by creating a reliable and reproducible in vitro environment for neural organoid culture to study aspects of neurodevelopment and NDDs that have been difficult to achieve with current platforms. To do this, I will 1) assess the effect of matrix biochemical cues for improving neural organoid architecture and maturation; 2) define the role of matrix stress relaxation and confinement on organoid growth; and 3) leverage the engineered hydrogel platform to study impaired interneuron migration in a disease model of 22q11.2 deletion syndrome (22q11DS). I hypothesize that the experiments described in my proposal will show that matrix-derived biochemical and biophysical signaling will allow for more robust neural organoid culture that better recapitulates the architecture and maturation of the human brain compared to conventional neural organoid models. I also hypothesize that fusion of 22q11DS neural organoids within engineered hydrogels will robustly demonstrate dysregulated interneuron migration mediated by the deletion of DCGR8. Of note, interneuron migration is a phenomenon that does not occur in murine systems and therefore cannot be studied using conventional murine models. To test this hypothesis, I will utilize a minimal matrix (HELP) to culture brain region-specific neural organoids derived from induced pluripotent stem cells (iPSCs) from healthy and 22q11DS patients. I will perform robust characterization of neural organoid architecture, maturation, and growth rate in response to tuning matrix biochemical and biophysical properties. I will also assess the ability of interneurons from 22q11DS patients to migrate into the dorsal forebrain by establishing a dorsal–ventral forebrain assembloid disease model. Together, these results will be critical for engineering a platform that is both permissive and instructive for robust and efficient neural organoid culture. In addition to expanding my scientific technical skills, my training plan includes development of mentorship, scientific writing, and presentation skills; training in research ethics; and enhancement of collaboration skills through a series of on-campus courses, workshops, and seminars as well as off-campus conferences. Altogether, this research proposal will empower me to become an independent, productive research scientist as I leverage the self- organizing capacity of stem cells and the tunable capacity of engineered materials to develop more human- relevant neural disease models.

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY Although we can readily determine a patient's genotype, we often cannot accurately predict their risk for disease or ascertain which of many variants of uncertain significance might underlie a pathology. Indeed, medically relevant phenotypes may emerge from the combination of thousands of polymorphisms. Complicating matters, the effects of genetic variants are not constant across individuals due to interactions with other variants in the genome and the environment. This project aims to build a fundamental understanding of which genetic variants give rise to complex traits and why. To do so, we will exploit a unique model system in the budding yeast Saccharomyces cerevisiae, in which we have already identified thousands of nucleotides that determine complex traits. These include regulatory variants that likely influence gene expression and many synonymous variants that, although often regarded as 'silent,' make substantial contributions to phenotype. Reversing typical functional genomics paradigms, we will examine the molecular consequences of known causal variants to identify the signatures that make them important to complex traits. We will focus on ascertaining the predictive power of functional measurements (such as nucleosome position, histone modification, gene expression level, and protein abundance) as a guide to the application of these technologies to patient- and tissue-specific genomics. In addition to examining these molecularly diverse linear contributors to phenotype, we will take advantage of a powerful genetic mapping panel (which contains more individuals than segregating polymorphisms) to begin dissecting the functional basis of gene ´ environment interactions and genetic background effects in complex traits. To chart this atlas of functionally important genetic variation, we will undertake the following specific aims: 1. Define the molecular impact of functional synonymous variants 2. Identify signatures of functional regulatory variants 3. Build integrative genotype-to-molecule-to-phenotype maps The inherent complexity of quantitative traits is a daunting problem that grows ever-more challenging with the growing catalog of variants of uncertain significance in the patient population. Using model systems in which the genotype-to-phenotype relationship can be comprehensively mapped is a powerful approach for understanding and building predictive models of which variants are likely to be causal. Indeed, linking changes in DNA both to their molecular consequences and their effects on cellular phenotypes is a central challenge in genetics that promises to allow the functional classification of never-before-seen mutations. Our approach will help to understand the fundamental structure of these relationships, with implications for genome reading and writing in medicine and biotechnology.

NIH Research Projects · FY 2024 · 2023-06

Abstract This project investigates a little-known physical property of ionizing radiation, which has the potential to increase the therapeutic ratio of radiation therapy (RT). Several decades ago, it was observed that ionizing radiation could nucleate gas nanobubbles (NBs) in water and other liquids. Seminal experiments revealed the presence of NB in irradiated water, which manifested as a decrease in the ultrasound power required to achieve acoustic cavitation. These results raise a crucial yet unanswered question: Does ionizing radiation nucleate NBs in vivo, inside irradiated tissues? Radiation is widely used in medicine. The premise that NBs may be nucleated in patients during diagnostic scans or radiation therapy is significant because NBs could induce biological effects. In addition, their presence in the tissues may lower the threshold for acoustic cavitation, which suggest a novel mechanism for increasing the efficacy of radiation therapy. The first Aim of this project is to gather rigorous and comprehensive evidence of NB nucleation in irradiated cells in vitro. Sensitive assays, including darkfield microscopy and ultrasound imaging, will be used to detect NBs in cells after exposure to ionizing radiation. This study will generate quantitative estimates of the efficiency of NB nucleation for different types of radiation, including their kinetics and stability under different conditions. The second Aim is to explore the use of radiation- induced NB to enhance the therapeutic efficacy of RT. Given that exogenously administered NBs are already used to increase the efficacy of high-intensity focused ultrasound (HIFU), intrinsically induced NBs nucleated during exposure to ionizing radiation should have similar enhancing effect for HIFU. Therapeutic efficacy of this combined treatment will be assessed by treating multicellular tumor spheroids sequentially with RT and HIFU, then quantitatively assessing the biological response of the cells. The proposed combination uses treatment modalities approved for use in humans and requires no extrinsic agents to be administered. This combination of radiation-induced NB nucleation and ultrasound-driven NB cavitation is a highly innovative and practical solution to the issue of treatment-resistant tumors.

NIH Research Projects · FY 2025 · 2023-06

Abstract Despite the great progress in recent decades, many types of cancer remain almost fatal. Pancreatic ductal adenocarcinoma (PDAC) is a remarkable example. One of the challenges is that the vast majority (95%) of PDACs are driven by mutations within a gene called KRAS, and these KRAS mutations are notoriously difficult to target with conventional drugs. The first generation of cancer drugs are based on small molecules, the second generation biologics (large biomolecules such as antibodies that specifically bind to cancer cells), and the latest generation cells (engineered to recognize and ablate cancer cells). Here our long-term goal is to demonstrate a new generation of therapeutics, using “circuits” as medicine. Circuits metaphorically refer to collections of biomolecules engineered to regulate each other and process information inside living cells. While conventional analyses output metrics to inform physicians, who then make therapeutic decisions, our circuits close the loop, and will serve as both the analytic and the therapeutic tools. It is a molecular and cellular analysis technology that queries living cells and actuates therapeutic outputs in real time without human intervention. Specifically, we will create circuits to program the immune system and emulate the “abscopal effect”, the occasional observation that distant tumors shrink when local tumors are treated, most likely due to the immune system learning the “signature” of the treated tumors and then extrapolating. We will first create the building blocks for such circuits: sensors that can interrogate whether a cell is in a cancerous state, actuators that can control the signals sent by cells to engage the immune system, and processors that connect the sensors and the actuators. These efforts will benefit from our experience of building circuits exclusively using proteins, which features technical advantages, such as ease of delivery and robustness of functionality in different cellular contexts, compared to more conventional ways of building circuits based on protein-DNA interactions. We will then assemble these building blocks into circuits, and quantify and optimize their operation in cultured cells. Leveraging our expertise in mouse models of PDACs, we will finally test these circuits’ efficacy in vivo. The premise is to program the outputs specifically from cancer cells to mobilize the immune system and then lyse these cells to grant the immune system access to all protein sequences that are uniquely present in cancer. These dead cancer cells will serve essentially as vaccines against other cells that exhibit similar protein sequence profiles. We will achieve this vaccination effect by either mimicking a specific type of cell death known to mobilize the immune system, or program the cancer cells to directly and artificially activate T cells – immune cells responsible for recognizing and ablating cancer cells. The expected outcomes of this proposal are not only preclinical evidence supporting a novel, powerful therapy for KRAS-driven PDAC, but also a proof of principle for the biomedical promise of synthetic biomolecular circuits for other recalcitrant types of cancer and beyond.

NIH Research Projects · FY 2025 · 2023-06

Families’ engagement in NICU care facilitates holding, skin-to-skin care, and human milk feeding, which improve neonatal survival and long-term infant development. However, there are many disproportionate structural barriers faced by marginalized families when visiting the NICU. Few studies have characterized these structural barriers and evaluated how they affect infant and parental disparities and outcomes. In this project, Dr. MK Quinn, hypothesizes that parents of children in the NICU from marginalized backgrounds are less likely to have access to paid family leave, childcare, transportation, and may encounter language barriers, and that this contributes racial, ethnic, and socioeconomic disparities in preterm infant health outcomes. This hypothesis will be addressed with two specific aims. First, to understand the barriers that families face to engaging in the care of their preterm infants in mixed methods study Dr. Quinn will identify barriers through key informant interviews of low-income families with preterm infants in the NICU. This rich qualitative data of parents’ experiences will inform the development of evidenced based theory of what is driving disparities in family visitation and engagement. This will be followed by a multicenter survey of parents with preterm infants in the NICU, in order to first understand the prevalence of these barriers and investigate how these barriers are experienced by marginalized groups. Second, Dr. Quinn will conduct an observational study of the health effects of the most salient barrier to care, paid family leave. For this analysis she will investigate how the implementation of California’s paid family leave policy contributed to racial and socioeconomic disparities in preterm infant care and outcomes. The results of this study will provide the groundwork for designing policy interventions to ensure families can engage in their preterm infant’s care, and ultimately, reduce inequities and improve preterm health outcomes. The sponsor for this research is Dr. Henry Lee, a neonatologist with expertise in health services research. The cosponsor, Dr. Jochen Profit, is a neonatologist with expertise in neonatal inequities. The advisory team includes Dr. Maya Rossin-Slater, an economist with expertise in family leave policy, Dr. Suzan Carmichael, an epidemiologist with expertise in perinatal health inequities, and Dr. Christine Morton, a sociologist with expertise in perinatal qualitative research. The research in this study in concert her training plan will provide Dr. Quinn a foundation in the study of neonatal health inequities and prepare her for a career continuing this research as an independent investigator.

NIH Research Projects · FY 2025 · 2023-06

Abstract Thyroid cancer patients with distant metastases or unresectable disease have poor likelihood of long-term survival. Radioactive iodine (RAI) can specifically and systemically eradicate malignant thyroid cancer cells that have spread throughout the body through metastasis. However, 5-15% of all thyroid cancer patients eventually progress to RAI-refractory status, which has the poorest prognosis of all thyroid cancer cases. Refractory disease occurs when thyroid tumor cells lose their innate ability to take up and concentrate RAI. Recent clinical studies have shown that kinase inhibitors and other drugs can reverse this effect by redifferentiating refractory tumor cells, thus restoring the cellular machinery required to concentrate RAI. However, this redifferentiation strategy remains challenging to optimize and deploy clinically. The reasons for this include the small number of patients eligible, the heterogeneity of the disease, the toxicity of targeted kinase therapies, and the lack of robust biomarkers. This project will develop papillary thyroid carcinoma organoids to study and individualize the use of redifferentiation agents to restore RAI uptake in RAI-refractory patients. In the first Aim, we develop a novel automated and high-throughput assay to measure RAI uptake in thousands of tumor organoid cultures. The assay will be optimized to achieve specific performance goals, including throughput, linearity, limit of detection, and reproducibility. In the second Aim, we will demonstrate the assay in a small pilot study of 10 patients. The panel of tumor organoids, which will include both RAI-sensitive and refractory disease, will be used to screen a library of relevant drugs on the basis of RAI uptake. Using the approach, we will optimize dosing and scheduling of the treatments towards the eventual goal of individualizing therapy to maximize efficacy while minimizing the adverse side effects of kinase inhibitors.

NIH Research Projects · FY 2026 · 2023-06

Project Abstract Lethal small molecules are powerful tools to discover and characterize new cell death mechanisms that may be useful for cancer treatment. Using small molecules, we have identified an unconventional form of non-apoptotic cell death that is distinct from apoptosis, ferroptosis, and other known forms of cell death. This lethal mechanism requires protein palmitoylation and involves the disruption of protein trafficking. In this research we propose to test the role of lipid metabolic enzymes that may positively or negatively regulate palmoptosis. One Aim of this research will focus on the lipid metabolic enzyme TECR (trans-2,3-enoyl-CoA reductase). We will test the hypothesis that TECR synthesizes palmitate that is used by protein palmitoylation enzymes to drive cell death via altered protein trafficking. A second Aim of this research will test the hypothesis that cell death is triggered by the disruption of phosphatidylcholine metabolism, which alters protein trafficking. A third Aim of this research will test the hypothesis that this new cell death mechanism can be activated in genetically engineered mouse models of cancer by a clinical drug candidate. While this cell death mechanism can be activated in diverse cancers, a major focus of the proposed studies is on sarcoma, which is highly sensitive to this lethal mechanism and for which new treatments are urgently needed. Together, these studies will define a new form of cell death and associated biochemical mechanisms that may be exploited for the treatment of sarcoma and other cancers.

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY/ABSTRACT The failure of surgery to provide a long-disease free survival interval to patients with resected pancreatic cancer is related to the inability to recognize occult tumor foci at metastatic or locoregional sites. For surgery to be effective, there is a critical need for real-time detection of small, sub-clinical metastases (if present) and for visualization of the tumor’s invisible infiltration along the boundaries of the planned resection. The overall objective of this application is to clinically validate the use of a fluorescently labeled anti-EGFR antibody, panitumumab-IRDye800CW (pan800), for the intraoperative detection of low-volume (1-3 mm3) pancreatic cancer tumor foci in vivo. The central hypothesis is that Near InfraRed (NIR) intraoperative imaging with pan800 will enable ultrasensitive detection of tumor deposits that would otherwise escape detection using current imaging technology and surgical inspection/palpation. In the proposed study, patients with pancreatic adenocarcinoma eligible for surgery will undergo infusion of pan800 2-5 days prior to surgery and NIR cameras will be used intraoperatively to detect 1-3 mm³ tumor foci. The following two specific aims will be pursued: 1) Determine the diagnostic accuracy of pan800 intraoperative fluorescent imaging to detect radiographically occult (i.e., unseen by the radiologist) pancreatic adenocarcinoma metastases; and 2) Determine the efficacy of pan800 fluorescent imaging to identify visibly occult (i.e., unseen by the surgeon) residual tumor foci at the post-surgical resection bed in vivo or at the margin of the resected specimen ex vivo. Under the first aim, the sensitivity and specificity of this intraoperative imaging modality to identify small, sub-radiologic peritoneal metastases will be documented. For the second aim, the incremental yield of this modality over conventional bright-field inspection in identifying otherwise invisible tumor foci at the resection bed or specimen margin will be demonstrated. The repurposing of readily available therapeutic EGFR antibodies to surgical imaging agents is not only safe and cost effective, but also highly innovative, in the applicant’s opinion, as it can challenge the status quo related to intraoperative pancreatic cancer detection, which has not fundamentally changed over several decades. The proposed research is significant because it will build upon the previously demonstrated efficacy of pan800 to detect pancreatic cancer in vivo, providing new opportunities for its continued development as a tool to enhance intraoperative staging, support decision making, increase the likelihood of complete tumor resection, and eventually improve clinical outcomes for patients with this highly lethal malignancy.

NIH Research Projects · FY 2025 · 2023-06

ABSTRACT Hundreds of thousands of mutations have been identified in cancer. However, the vast majority of cancer mutations lack functional biological characterization. Therefore, very little is known about their impact on gene function beyond in silico predictions. Developing experimental models to study the biological consequences of these mutations is a daunting challenge. We developed a technology called transcript-informed single cell CRISPR sequencing (TISCC-seq) that provides modeling of cancer mutations at single cell resolution. CRISPR engineering introduces cancer gene mutations into cells. Single-cell RNA sequencing (scRNA-seq) is a power tool for evaluating the genomic features of cancer. By combining these two approaches TISCC-seq has the potential for dramatic increases in parallelization and scalability of experimental cancer models. We use DNA base editors to introduce specific cancer mutations into target genes among individual cells. Single molecule nanopore sequencing of the cDNA target directly identifies the mutation in each cell. By integrating single cell long and short read sequence data, each cell’s newly introduced mutation is matched to the same cell’s gene expression data. We will develop TISCC-seq as a new single cell genomic platform for engineering cancer mutations into cell lines and primary tissue cultures. Single base mutations are the most commonly reported type of cancer genetic alteration. For Aim 1, we will develop TISCC-seq for highly multiplexed functional screening of substitution mutations at single cell resolution while matching the mutation genotype to the same single cell’s transcriptome. We will identify reported cancer mutations with known biological effects and others which are not characterized identified in colorectal or gastric cancer. Next, we will determine which of these mutations can be engineered using base editing methods. Then, we will deliver base editors and guide RNAs to engineer up to 500 substitution mutations across different cell lines and organoids. Post-editing, the cells will undergo scRNA-seq with both short and long-read platform. These data sets will be integrated to provide a single readout where the single cell mutation is matched to the corresponding cell’s gene expression. Alternative splicing is increasingly recognized as an important feature of cancer. Some cis-based cancer mutations occur in exon-intron junctions that lead to alternative splicing of mRNAs. For Aim 2, we will develop TISCC-seq as a method to evaluate this category of mutations. First, we will identify a set of 100 cancer genes that have cis-based mutations at exon-intron junctions as reported in colorectal or gastric cancer. We will increase the scalability of this process such that at least 500 of this class of mutations can be studied in parallel using an integrated long and short read sequencing. These mutations will be introduced across different cell lines and organoids. Overall, we will develop a new CRISPR genomic technology for highly multiplexed modeling of cancer mutations at single cell resolution and studying their biological effects.

NIH Research Projects · FY 2026 · 2023-05

Project Summary/Abstract: My laboratory research program in stochastic modeling and inference of evolutionary processes focuses on developing efficient methods for inference of evolutionary parameters from molecular data, and statistical tests for assessing evolutionary hypotheses. This proposal will focus on answering three fundamental questions in the study of evolutionary processes: Are the observed patters of genetic diversity the result of adaptive or non-adaptive evolution? What is the mode and strength of selection? How can we identify genomic regions undergoing selection? Whether adaptation, demography or local patterns of mutations are the sources of variation across populations, these forces influence the shape of the underlying genealogies and phylogenetic networks. Hence, assessing differences among genealogies provide information about differences in these forces, particularly among genealogies of different individuals, possibly living in different environments and times. We propose to approach these questions by defining new coalescent models of selection and exploiting a metric on the space of genealogies to define statistical tests. The computational advantage and the ease of biological interpretation, together with the mathematical properties of the proposed models and metric spaces, open the door to novel approaches for studying adaptation. Over the next five years, the Palacios laboratory will combine tools from combinatorial optimization, Bayesian inference, and coalescent theory to develop new coalescent models and tests applicable to studying the evolution of pathogens and other organisms.

NIH Research Projects · FY 2026 · 2023-05

PROJECT SUMMARY/ABSTRACT Degenerative cervical myelopathy (DCM) is the most common form of spinal cord (SC) injury in adults. DCM is characterized by multilevel degenerative changes in the cervical spine, causing SC compression and injury, which leads to worsening neurological dysfunction. Hand weakness and diminished coordination are more severe spinal pathology indicators, increasing the likelihood of spinal surgery. While restoring hand function is a primary goal of surgery, surgical management of DCM is challenging due to the low diagnostic certainty of the underlying pathology and lack of predictive factors to determine which patients may improve with surgery. The injury in DCM extends beyond the level of SC compression and affects the entire neuromuscular system. The interplay among the brain, SC, and muscles needs to be characterized to fully understand the mechanisms underlying hand dysfunction in DCM, the progression of DCM pathology, and the factors promoting recovery. Here we will use magnetic resonance imaging (MRI) to non-invasively characterize the brain, SC, and muscular mechanisms underlying hand weakness and diminished coordination in DCM. We will then combine brain, SC, and muscle measures to develop neuromuscular signatures of hand function and assess their value in predicting surgical outcomes in DCM. Our overarching hypothesis is that signatures of neuromuscular health will track the progression of DCM pathology and predict surgical recovery of hand function (less extensive brain, SC, and muscle injury will predict better surgical outcome). To accomplish this, we will enroll 60 right-handed DCM patients (age 40–80 years, 30 females, 30 males) with right hand weakness and diminished coordination, who are scheduled for surgery, and 60 age- and sex-matched healthy volunteers. We will perform simultaneous brain-SC fMRI using force-matching and finger-tapping tasks and resting-state functional connectivity to characterize the brain and SC mechanisms underlying hand dysfunction. We will also capture gray matter morphometry and white matter integrity along corticospinal pathways using methods developed and in use by our team. Then we will perform fat-water and diffusion tensor MRI of the right forearm providing measures of muscle volume and quality to characterize the downstream effects of SC injury on the forearm muscles. We will use multivariate machine-learning algorithms and the brain, SC, and muscle imaging to develop neuromuscular signatures of hand function by predicting grip strength and dexterity. We will then track clinical outcomes at 1-year post-surgery in the DCM patients, and we will assess the value of the pre-surgical signature responses for predicting surgical outcomes and establish clinical cutoffs. Validated neurobiologically-based predictors of surgical response could lead to earlier intervention in those likely to recover, prevent exposure to risks and complications in those unlikely to respond, and elucidate the factors underlying recovery to improve treatment.

NIH Research Projects · FY 2025 · 2023-05

ABSTRACT Childhood obesity remains highly prevalent and originates early in life. Efficacious early life interventions to prevent childhood obesity are lacking, particularly among populations most burdened by childhood obesity. Food insecurity - defined as lack of enough food for an active, healthy life – may play key upstream roles in etiologies of obesity through establishment of unhealthy dietary patterns and stress-related metabolic perturbations. Household food insecurity during the first 24 months of life is a risk factor for later childhood obesity. Professional organizations recommend integration of household food insecurity screening into routine pediatric primary care. Yet, a critical gap exists in identification of efficacious clinical interventions to reduce food insecurity. Another gap exists in understanding relationships between food insecurity and etiologies of obesity. Food FARMacia is a clinically based mobile food pantry intervention developed to address the high prevalence of food insecurity among pediatric patients. No randomized trials of a clinically-based mobile food pantry intervention in pediatric primary care exist. To understand the role of food insecurity in etiologies of childhood obesity, efficacious interventions to reduce food insecurity are needed. To test efficacy of the Food FARMacia intervention in a randomized clinical trial (RCT), feasibility of RCT procedures must first be established. The overall goal of this study is to perform a Phase IIb pilot and feasibility RCT of the Food FARMacia clinically based mobile food pantry intervention to promote healthy weight during infancy compared to an attention control over 6 months. We will recruit 70 families (randomized n = 35 infant-parent dyads per arm) with an infant age 6 to <18 months and food insecurity identified on routine electronic health record screening at pediatric primary care visits in our multi-site urban academic health care system. We will examine feasibility and acceptability of the RCT procedures and intervention components using quantitative and qualitative research methods. We will estimate the effects of the intervention on infant weight characteristics over time to inform a full-scale trial. We will explore potential mediators of intervention effects, including household food insecurity. Our multidisciplinary team has expertise in childhood obesity, nutrition, community-engaged, and population health research; clinical trials; qualitative research; and biostatistics. Results will immediately inform a full-scale Phase III RCT to test the efficacy of the Food FARMacia intervention on preventing childhood obesity. Results of a full-scale trial will also provide new information about relationships of household food insecurity during infancy and etiologies of obesity. If successful, this research will accelerate identification of scalable, efficacious clinical interventions to transform clinical care for reduction of food insecurity and promotion of healthy infant growth.

NIH Research Projects · FY 2026 · 2023-05

Project Summary: Defining Small Intestinal Microbial Landscapes To Improve Therapeutics For Gastrointestinal Disease Disease Relevance: Irritable Bowel Syndrome (IBS) is a chronic disorder characterized by altered bowel function (consistency and/or frequency) in additional to abdominal pain, effecting 7-16% of the US population and associated with an $1 billion of direct health care costs annually. This proposal seeks to better understand IBS and to develop more effective treatments for IBS. Candidate and Career Development Plan: My long-term goal is to become a fully independent physician scientist through leadership of a cutting-edge research program in human microbiota analysis and its association with clinical data complemented using a variety of tools (molecular genetics, metabolomics, gnotobiotic mouse models) to clarify mechanisms of action that will enable development of improved microbiota directed therapeutics for GI disease. Through my clinical training I am poised to become an expert in diagnosing and treating IBS, and through my previous research training am well equipped with the skills to perform high-resolution human and mouse immunology. To fully actualize my career goals of becoming an expert in microbiota-host interactions in IBS I will need to gain skills beyond my current knowledge base. This award will support the needed additional training in microbiota analysis, methods of clinical research, bacterial isolation and culturing, and gnotobiotic mouse models. Research Plan: The overarching research goal of this proposal is to move beyond feces, to define the site-specific microbial ecology of the human small intestine in IBS. We will construct a longitudinal map of intestinal microbiota and metabolites in humans with a swallowed, microbiota sampling capsule device. I have successfully employed this approach in healthy humans and the proposed research will expand sample collection to include IBS patient samples analyzed with microbiota sequencing, novel microbiota-focused metabolomics (Aim 1), and bacterial isolation and functional testing (Aim 2), with complementary studies in gnotobiotic mice (Aim 3) to define fundamental aspects of host- microbe interactions in the small intestine. Mentorship Team: To achieve these Aims, I have assembled a world class mentorship team with expertise in translational human microbiome studies (Justin Sonnenburg, primary mentor), isolation and study of bacteria from the human microbiome (KC Huang, co-mentor), and the treatment and study of IBS (Linda Nguyen, co-mentor). Environment and Institutional Commitment: Stanford University is a world leader in human microbiome studies and treating Gastroenterological(GI) disease. I will have access to mentorship, collaborators, and a breadth of resources that will provide an exceptional training environment. My mentorship team and the leadership within the Stanford Department of Medicine are committed to ensuring my success. The scientific training, skill acquisition, and career development under this award will allow me to become a fully independent physician scientist and leader in the translational microbiota science of GI disease.

NIH Research Projects · FY 2026 · 2023-05

Project Summary / Abstract Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer death worldwide. There is an unmet need for accurate, cost-efficient, and broadly accessible risk- stratification tools to identify patients at increased risk of recurrence , who are most likely to benefit from adjuvant therapy. Current standard-of-care risk stratification approaches are inadequate. Every CRC surgical candidate undergoes pathologic and radiologic evaluation of their tumor; these two modalities represent a rich, readily accessible and, thus far, underutilized resource for developing new risk-stratification tools. Deep learning (DL) has demonstrated great potential for augmenting physicians on an increasing range of diagnostic and prognostic tasks in pathology, radiology, and clinical medicine. We hypothesize that applying integrated DL-based analysis to multimodal (pathologic, radiologic, and electronic medical record (EMR)) data will yield greatly improved stratification of CRC patients for adjuvant treatment planning. We propose to build the first comprehensive, publicly-available, expert-annotated multimodal CRC dataset for deep learning, containing annotated CRC pathology whole-slide images (WSI), preoperative CT and MRI images, and structured clinical EMR data. Using this dataset, we will develop both single and multi-modality DL models for risk stratification of surgically-resectable (Stage I-III) CRC patients.To test our hypothesis, we will compare the performance of multi-modality models with that of single-modality models and existing methods of stratification. This project benefits from the complementary expertise and resources of a unique interdisciplinary team spanning the fields of machine learning, pathology, radiology, and oncology.

NIH Research Projects · FY 2026 · 2023-05

Project Abstract Major depression is the leading cause of ill health and disability worldwide according to the World Health Organization. Although significant progress has been made in understanding the disease and developing treatments, antidepressants, as the treatment mainstay, are effective for only about 50% of patients, in part due to the neurobiological and clinical heterogeneity in depression. Developing advanced data-driven techniques by leveraging machine learning with large-scale multimodal neuroimaging data from randomized clinical trials provides us a unique opportunity to explore brain biomarkers to identify treatment-predictive neurobiological phenotypes. Establishing such biomarkers is crucial for reducing the need for multiple drug trials and expediting remission by sharpening the search for treatment targets. However, integrative analysis of multimodal data for identifying biomarkers and differentiating individual responses to treatment in depression remains highly challenging and underexplored. In this proposal, we will develop new data-driven analytical tools to quantify multimodal moderators and signatures jointly from pre-treatment functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data for the prediction of treatment response to antidepressant medication. In Aim 1, we will identify multimodal moderators of treatment effect using data from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial. A canonical correlation analysis-based data-driven model will be designed to extract combined features that fuse together complementary information from both fMRI and EEG modalities. Intent-to-treat prediction linear mixed models will be used to probe multimodal moderators of antidepressant sertraline versus placebo treatment response. In Aim 2, we will build a supervised latent space model that unifies the feature fusion and predictive modeling and apply it to quantify multimodal brain signatures that can predict individual treatment responses to sertraline versus placebo medication. In Aim 3, we will recruit 50 depressed patients as an independent cohort undergoing sertraline treatment to optimize and validate the identified multimodal biomarkers. Both fMRI and EEG will be collected at baseline followed by treatment with the antidepressant medication sertraline (in a manner paralleling EMBARC procedures) and clinical assessment of outcomes. We will release the developed software tools and collected data to be publicly available to the research community to facilitate multimodal neuroimaging studies in other mental disorders.

NIH Research Projects · FY 2026 · 2023-05

Abstract: Sensorineural hearing loss affects 1.5 billion people worldwide, with the primary pathology being the irreversible loss of cochlear hair cells and supporting cells. Although hearing aids and cochlear implants can improve hearing, we currently lack the ability to reverse the underlying pathology of hearing loss-hair cell and supporting cell loss. Recent studies found that defined transcription factors can reprogram endogenous cochlear supporting cells to directly acquire a hair cell fate, however, the hair cells formed are limited both in number and degree of maturation. Moreover, this non-mitotic approach, coined direct transdifferentiation, leads to a loss of the overall supporting cell population. Thus, a better understanding of 1) mitotic regeneration of supporting cells and 2) how regenerated hair cells in the cochlea mature is critical. In this proposal, we will test whether singular or combinatorial application of transcription factors can replenish hair cells and supporting cells in the immature and mature mouse cochlea. In preliminary and recently published data using transgenic mouse models, we found that 1) greater epithelial ridge (GER) cells, instead of being a transient structure during development, migrate into the organ of Corti to regenerate lost supporting cells and mature to become the supporting cell subtype inner phalangeal cells, which are critical for the survival of inner hair cells, 2) damage induces GER cells to robustly proliferate and upregulate transcription factors associated with proliferation, 3) Atoh1 overexpression robustly induces new hair cell formation in the GER, which mature to become inner hair cell- and outer hair cell-like cells. The first aim will test the hypothesis that damage-responsive transcription factors promote mitotic regeneration in the neonatal and damaged mature cochlea. In the second aim, we will use regenerated hair cells in the GER as a model system to characterize the spatiotemporal features by which regenerated hair cells mature and then test whether the outer hair cell factor Ikzf2 enhances an outer hair cell fate. Moreover, we will examine the ability of combination of hair cell transcription factors to induce hair cell regeneration and maturation in the damaged mature cochlea. To gain an unbiased insight into the genetic signature of ectopic supporting cells and hair cells, the third aim will probe the transcriptomes of GER-derived hair cells and supporting cells. We will reveal their genetic landscape using bioinformatic approaches to define genes marking progenitors and regenerated supporting cells and hair cells and candidate genes driving regeneration. In summary, we will apply state-of-the-art technologies (live cell imaging, electrophysiology, snRNA-seq, inner ear surgery, viral transduction) to study the mechanisms of supporting cell and hair cell regeneration. We have assembled a team of experts who have worked together to collect promising preliminary data. At the end of this 5-year proposal, we will have determined 1) whether transcription factors can enhance cochlear regeneration 2) mechanisms dictating regeneration of supporting cells and hair cells in mammals.

NIH Research Projects · FY 2026 · 2023-05

ABSTRACT This proposal outlines a request to fund our multidisciplinary predoctoral training program, Stanford’s Translational Biomedical Imaging Instrumentation (TBI2) training program. Biomedical imaging technology continues to evolve at a rapid pace. Our mission is to train the next generation of researchers and inventors in translational biomedical imaging instrumentation in order to meet the national demand for highly skilled scientists in this field. At the national level, there persists a clear need for trained researchers in biomedical imaging instrumentation to fill positions in academia, industry, and government in order to fuel the cycles of innovation that ultimately impact human health. Our vision for achieving translational impact includes both bench to bedside (clinical translation) and bench to industry (translational entrepreneurship). Our vision is motivated by the career interests of our trainees, many of whom seek professional opportunities in academics and many of whom seek to translate their skills for translational impact by way of industry. Stanford University provides a highly innovative and unique multidisciplinary research environment in biomedical imaging instrumentation. The TBI2 faculty have an outstanding track record of innovation and translation that spans magnetic resonance imaging/spectroscopy, computed tomography, ultrasound, PET, molecular imaging, and optical imaging. Training in these modalities, plus exposure to hybrid imaging systems (X-ray/MR, PET/MR, and MR-guided focused ultrasound), will provide trainees with broad experience using advanced biomedical imaging technologies. Mentoring by our well-established research mentors and clinical co- mentors will provide opportunities to push developments towards translational applications in our adult and pediatric hospital settings. Parallel opportunites will provide experience in translational entrepreneurship to accelerate the entry of new technologies into industry for worldwide impact. Didactic training opportunities in the physics of medical imaging systems, image and signal processing, radiologic anatomy and physiology, advanced diagnostics, interventional procedures, and radiation therapy provide a rich learning environment. Furthermore, artificial intelligence and machine learning have been key technologies driving imaging innovation at Stanford for many years, and training in artificial intelligence and machine learning form a substantial emphasis of this new training program. It is woven across imaging modalities and includes both upstream and downstream applications. Trainees will also gain expertise in rigorous and reproducible experimental design, plus the ethical considerations of their research. TBI2 trainees that complete our training program will have a unique skill set that fullfills a distinct national need for researchers and leaders with expertise in advanced biomedical imaging instrumentation.