Stanford University

NIH Research Projects · FY 2025 · 2021-05

Project summary Computational multi-scale modeling is a growing area of research that aims to link whole slide images and radiographic iamges with multi-omics molecular profiles of the same patients. Multi-scale modeling has shown its potential through its ability to predict clinical outcomes e.g. prognosis, and through predicting actionable molecular properties of tumors, e.g. the activity of EGFR, a major drug target in many cancers. Current applications are limited to study associations between imaging and molecular data, and predicting long term outcomes. No actionable information can be gained from multi-scale biomarkers yet. We propose to develop a multi-scale modeling framework to support treatment response, treatment monitoring and treatment allocation for patients with brain tumors, focusing on the most aggressive subtype of glioma, IDH wild-type high grade glioma. In Aim 1, we will develop informatics algorithms that integrate multi-scale data for treatment response. We will use our expertise in data fusion and develop novel approaches to integrate multi- scale data to predict first line treatment response. In Aim 2, we will develop algorithms that allow combining multi-scale data at diagnosis with multi-modal MR imaging data during treatment follow-up. We will focus on predicting treatment response and progression and whether we can predict these events earlier than radiologists can. In Aim 3, we will develop algorithms that use the multi-scale data to predict drug target activities and also suggest novel drugs for patients that become resistant to first line treatment. We will use a mixture of publicly available glioma multi-scale data sets totaling more than 1000 patients, and also 1600 retrospective and 150 prospective brain tumor patients from Stanford Medical Center. Combining these complementary data sources in a multi-scale framework for data fusion can have profound contributions toward predicting treatment outcomes by uncovering unknown synergies and relationships. More specifically, developing computational models integrating quantitative image features and molecular data to develop multi-scale signatures, holds the potential to translate in benefit to brain tumor patients by investigating biomarkers that accurately predict treatment response. Readily, because whole slide images and radiographic imaging is part of the routine diagnostic work-up of cancer patients and molecular data of brain tumors is increasingly being used in clinical workflows, therefore if reliable multi-scale signatures can be found reflecting treatment response, translation to clinical applications is feasible, including optimizing recruitment for clinical trials.

NIH Research Projects · FY 2025 · 2021-05

Project Summary/Abstract Cancer is the 2nd leading cause of death in US. Statistical designs and data analytics approaches are instrumental in recent development of more effective treatments for cancer. While successes like the I-SPY2 trial highlight the advancement, most oncology trials do not fully utilize powerful statistical innovations and there remains a lack of effective communications between oncologists and statisticians. To address these issues, we propose the Stat4Onc symposium which provides a unique platform for oncologists and statisticians to discuss and exchange ideas for pressing issues in cancer clinical trials, disease diagnosis, patient care, and decision making for drug development. This symposium will further drive innovations in statistical methodology and data analytics dedicated for oncology research and translate these innovations to research practice. It also provides a venue for trainees in oncology and statistics to learn inter-disciplinary collaborations. The symposium will be rotated among the four participating universities in a five- year funding period. The symposium is a three-day event, with first day of short courses relevant to the theme of the year, and then a two-day single-track scientific program. The symposium is inclusive, with respect to scientific expertise in oncology, statistics, regulatory and data sciences, to their professional associations from academia (faculty, staff, and students), biopharma and biotech industry, government agencies, and non-profit organizations, and to gender and ethnicity, in particular for the inclusion of underrepresented minority groups. The symposium size will be around 200 participants, allowing adequate and focused discussions. The symposium will be single tracked to allow participants to be in all the sessions. Keynote talks and all the sessions will have speakers from academic, government, and industry and with expertise in oncology and statistics. Trainees in both oncology and statistics disciplines will be supported for attending the symposium and offers opportunities to present in poster and mixer sessions. Symposium talks will be published in JCO Precision Oncology and New England Journal of Statistics in Data Science.

NIH Research Projects · FY 2025 · 2021-04

THERANOSTICS FOR PEDIATRIC BRAIN CANCER Glioblastoma (GBM) is the most frequently diagnosed primary malignant brain tumor in children with median survival of less than one year. Disease recurrence is common and is caused by the presence of glioma-initiating cells (GICs) that are unreceptive to conventional therapies, underscoring the urgent need for new therapeutic options. We aim to develop a novel strategy to specifically disrupt the lifeline of GICs, without causing toxic effects to the normal brain. The highly vascularized nature of GBMs and the critical function of the perivascular niche for nutritional supply of GICs have spurred much interest in novel vascular-disruptive agents (VDAs). Intravenously administered VDAs easily reach GBM vessels and do not rely on the enhanced permeability and retention effect, which can limit the delivery of macromolecules to the tumor tissue. VDA-mediated blood vessel disruption causes efficient drug delivery to the GIC niche and starvation of many tumor cells. In contrast to classical anti-angiogenesis drugs, VDAs not only disrupt the tumor vasculature, but also cause significant GIC apoptosis through direct cytotoxic effects. While being highly effective for cancer treatment, initial VDA formulations also caused significant toxicity to the normal brain. This is particularly concerning for children, as the developing brain is more vulnerable to toxic side effects compared to the adult brain. To solve this problem, we developed novel VDA-loaded theranostic (combined therapeutic and diagnostic) nanoparticles, which are specifically activated in brain tumors by matrix metalloproteinases 14 (MMP-14). The normal brain does not express MMP-14 and therefore, does not activate the theranostic drug, thereby creating highly effective cancer therapy without side effects. The major goal of our project is to develop MMP-14-activatable theranostic nanoparticles (TNPs) for curative treatment of GBM, without causing toxicity to the normal brain. The approach relies on the high prevalence of MMP-14 in GBM, a proven MMP-14-activatable prodrug strategy, and a nanocarrier platform based on FDA-approved iron oxide nanoparticles. We hypothesize that our TNPs will be converted to an active therapeutic agent only within MMP-14-expressing tumors, releasing the therapeutic drug azademethylcolchicine and causing significant antitumor effects. In addition, we postulate that the iron oxide nanoparticle moiety will allow real-time monitoring of drug accumulation and localization at tumors with magnetic resonance imaging (MRI). In aim 1, we will evaluate whether TNP dose and VDA payload affect VDA mediated vascular disruption, blood brain barrier (BBB) breakdown and cancer-specific toxicity. In aim 2, we will investigate the link between VDA-mediated tumor microvessel disruption, microvascular endothelial cell death and GIC death. TNPs hold the potential to substantially improving therapeutic efficacy whilst simultaneously reducing dose-limiting toxicities. Realizing our goal will uncover new targets and mechanisms for successful GBM therapy, eliminate or substantially reduce off-target toxicities and provide children with brain cancers with a much needed new treatment option.

NIH Research Projects · FY 2025 · 2021-04

Temporal lobe epilepsy (TLE) is the most common epilepsy in adults, and it is frequently refractory to current anti-epileptic drugs, with treatments often exerting a variety of debilitating side effects. A major barrier for the development of novel treatment strategies is our insufficient understanding of the precise cellular and circuit mechanisms underlying TLE. A centrally important but unresolved question in TLE concerns the mechanisms underlying the excessive, dysregulated production of action potentials at the axon initial segment (AIS) of excitatory principal cells (PCs). Synaptic control of AIS is provided by a unique, evolutionarily conserved, GABAergic cell-type, the axo-axonic cells (AACs). AACs form synaptic contacts exclusively with the AIS of PCs, placing AACs in a strategic position to control action potential generation. However, due to technical limitations, our knowledge about the in vivo function and regulation of AACs in the normal and epileptic hippocampus has been extremely limited. Here we propose to employ a combination of recent technical breakthroughs to test hypotheses about the in vivo functional effects, activity dynamics and efficacy of AAC- mediated control of AIS in mouse models of chronic TLE. The planned project will also determine if it is possible to mitigate epilepsy-related pathologically hyperactive circuits and cognitive deficits through interventions selectively directed at the AAC-dependent, endogenous GABAergic processes regulating AIS in chronic epilepsy. The proposed project aims to fill a major knowledge gap and address long-standing controversies concerning the interneuronal regulation of AIS in epilepsy by leveraging expertise in novel large- scale, high-resolution in vivo functional imaging techniques in combination with advanced electrophysiological, behavioral, optogenetic and computational modeling techniques in the CA1 region of the mouse hippocampus. It is anticipated that defining the function, regulation and therapeutic potential of AACs in TLE will have a significant impact by advancing our understanding of key circuit control mechanisms in chronic epilepsy and aid the future development of novel anti-epileptic treatment strategies.

NIH Research Projects · FY 2025 · 2021-04

Abstract Head and neck squamous cell carcinoma (HNSCC) is the 9th most common cancer globally. Studies have shown that tumor-induced suppression of the host immune system is critical to HNSCC progression and metastasis. Tumor secreted factors directly influence the expansion of myeloid-derived suppressor cells (MDSC), which have emerged as forefront mediators of cancer immune suppression. MDSC not only promote tumor growth by suppressing T cells within the tumor, but also facilitate metastasis by enhancing angiogenesis and pre-metastatic niche formation. The presence of expanded MDSC peripherally and within the tumor microenvironment has been associated with worse prognosis with definitive treatment and less response to anti-PD1 immune checkpoint therapy in HNSCC. Moreover, RT itself has been shown to increase MDSC level systemically. Therefore, investigating factors that facilitate MDSC expansion, recruitment and function is integral to developing novel therapies. We have previously shown that Galectin-1 (Gal-1) is induced by hypoxia and/or RT in HNSCC and its elevated expression in the tumor stroma correlated with poor prognosis. We have data indicating that Gal-1 expressing tumors harbor high levels of local and systemic MDSC, and that Gal-1 blockade (genetically or with antibodies) substantially reduced the number of MDSC throughout, independent of its effect on T cells. Moreover, Gal-1 blockade led to fewer metastases and less MDSC recruitment to metastatic sites. Despite extensive literature supporting Gal-1’s effect on T cells, very few studies have evaluated its relationship with MDSC. Based on our preliminary data, we hypothesize that tumor secreted Gal-1 can directly affect MDSC recruitment to the primary tumor while simultaneously promote metastases through MDSC driven pre-metastatic niche formation. In addition, RT-induction of Gal-1 secretion may lead to higher systemic MDSC noted in patients receiving RT. Therefore, Gal-1 blockade can decrease both local and systemic MDSC burden and enhance tumor response to both RT and immune check point therapy. We will test this hypothesis with the following specific aims: (1) To determine whether Gal-1 mediates the effect of RT on increasing MDSC level in the tumor and systemwide in HNSCC; (2) To discern the host versus tumor cell dependent factors mediating Gal-1’s induction of MDSC expansion systemwide and recruitment to the tumor microenvironment; (3) To determine whether MDSC mediate Gal-1’s effect on metastases and whether CXCR2 blockade decrease distant metastasis in Gal-1+ HNSCC, and (4) To determine whether CXCR2 inhibition is as effective as Gal-1 blockade when combined with RT and PD1 antibody in HNSCC and to characterize the immune cells involved in these treatments. While optimal Gal-1 targeting is being developed, clinical grade CXCR2 inhibitors exist and are being tested in trials for both cancer and non-cancer conditions. Our studies, if successful, will provide rationales for integrating CXCR2 inhibitor with RT and anti-PD1 therapy in Gal-1 overexpressing HNSCC.

NIH Research Projects · FY 2025 · 2021-04

Identifying how genetic variation leads to neurodevelopmental or psychiatric disorders provides new means to study, predict, prevent and treat disease. Identifying the immediate molecular consequences of disease- associated genetic variation has necessitated the development of large-scale, multi-tissue functional genomic resources. Projects such as GTEx, Roadmap Epigenomics Project and PsychENCODE have combined molecular QTL mapping and epigenomic maps in bulk tissues to interpret various disease-associated genetic variants. However, few colocalizations between molecular QTLs and traits have been robustly identified and few causal variants mapped. As tissues like the brain constitute 100s of cell-types, we hypothesize that existing maps may mask the contributions of disease-associated variation in less-abundant cell types. One extremely powerful approach to identify cell-type specific molecular effects and their relationship to genetic diseases is through application of chromatin accessibility data – these data both allow inference of causal cell types and provide base level resolution gene regulation. Our team has considerable expertise in connecting GWAS to molecular functions and predicting causal variants through use of chromatin accessibility data. We have additionally recently collaborated to generate a comprehensive, multi-individual map single cell ATAC- seq map (scATAC-seq) of six different brain regions to detect causal cell types and predict causal variants. This work has been recently demonstrated in our fine-mapping study of Alzheimer’s and Parkinson’s disease (Corces et al, bioRxiv, 2020) but has not been systematically applied to mental health disorders. We propose to develop statistical genetics and machine learning approaches that advance the use of scATAC-seq data to connecting mental health GWAS loci to specific cell types, mechanisms and causal variants. In Aim 1, we will assemble a pipeline that leverages region and cell type-specific scATAC-seq data to identify pathological cell types for 100s of mental health and brain-related traits. We will also enhance the detection of cell-type specific molecular mechanisms by extending and applying a novel GWAS/QTL colocalization approach. Throughout these activities, variants will be validated using massively-parallel reporter assays (MPRA). In Aim 2, we will develop sophisticated machine learning models that learn regulatory grammars and score variants across the allele frequency spectrum. Predicted causal variants in GWAS loci will be further assessed with MPRAs in Aim 1 and applied in Aim 3. In Aim 3, we will demonstrate how improved detection of causal variants using our single-cell informed models aids transferability of polygenic risk scores across populations. We will provide open resources and reproducible computational methods and pipelines that integrate single cell chromatin accessibility data from multiple brain regions. This will allow detection cell-type specific genetic effects and pathological cell types in mental health GWAS, establish robust causal links between variants, genes and disease, and improve prediction of disease risk.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY/ ABSTRACT This application focuses on the contribution of transplant hemorrhage-induced iron overload in the dysregulation of pulmonary macrophages (mɸs) and the promotion of invasive aspergillosis. Aspergillus fumigatus (Af) is a ubiquitous mold that releases airborne spores (conidia) and affects nearly 20 million people worldwide. One-in- three lung transplant recipients (LTRs) suffers from Aspergillus-related pulmonary disease. While lung transplantation can be a life-saving treatment for thousands of people, survival post-transplant is often limited by Af infection. To better understand the transplant (host)-Af (pathogen) relationship, we developed a murine orthotopic tracheal transplant (OTT) model of Af infection. We have shown that transplant rejection-mediated microhemorrhage increases tissue iron levels and determines Af invasion. However, the exact interaction between immunity, iron overload and infection are still poorly understood. Mɸs are the first line of defense against Af and are also central to restoring tissue iron homeostasis. Importantly, our preliminary results indicate that microhemorrhage-mediated iron overload: (i) profoundly impacts the ability of mfs to kill Af conidia through a defect in lysosomal acidification; (ii) the innate immune response is polarized toward a pro-inflammatory mɸs state that results in high levels of tissue damaging reactive oxygen species (ROS); and (iii) iron promotes mɸ ferroptosis. Ferroptosis is a newly recognized form of regulated cell death that results from the production of iron toxic lipid ROS. Ferroptosis was first recognized in cancer but is now known to contribute to Alzheimer’s and Parkinson’s disease, ischemia reperfusion injury, atherosclerosis, acute kidney injury and the response to acute hemorrhage. However, the role of ferroptosis in lowering the host’s defense against pathogens, if any, remains unknown. The proposed studies are designed to address these questions in terms of Af invasion. The central hypothesis is that transplant microhemorrhage-mediated iron overload induces mf ferroptosis and polarization into an unrestrained pro-inflammatory phenotype that promotes Af invasion. Specific aim 1 utilizes in vitro and in vivo experiments to investigate the concept that ferroptosis is dictated by mɸs polarization state and contributes to the inability of transplant mɸs to mitigate Af infection and studies the role of iron lowering agents and anti-ferroptotic drugs to decrease fungal invasion. Specific aim 2 uses state-of-art omics techniques to define iron induced Af proteases and tests the concept that fungal protease inhibition can mitigate ferroptosis and improve outcomes in the tracheal transplant model. Specific aim 3 studies the ability of alveolar mɸs isolated from human LTRs compared to non-lung transplants to kill Af conidia and correlates the ability of mɸs to kill conidia with mɸs-polarization state and ferroptosis, using mass cytometry. This aim will provide a direct translatability of the hypothesis that iron overload induces ferroptosis and a pro-inflammatory phenotype that promotes fungal invasion. Successful completion of these studies will allow for the discovery of a fundamental new biology and provide novel targets for the treatment of fungal infections.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY Pathogens have evolved to co-opt cellular functions to support their replication and spread while inactivating innate immune mechanisms that restrict their growth. Discovery and characterization of cellular components that regulate pathogenesis hold promise for revealing new approaches to treat infectious diseases. Enteroviruses (EVs) comprise a large genus of single-stranded RNA viruses of positive polarity whose members cause a number of important human diseases such as poliomyelitis, myocarditis, acute flaccid paralysis and the common cold. How EVs co-opt cellular functions to promote replication and cause pathogenesis is incompletely understood. Through robust, unbiased knockout screening approaches, we have discovered that the protein methyltransferase SETD3 is required for infection by a broad range of human EVs. We showed that enterovirus replication is severely hampered in human cells lacking SETD3 and that the block occurs during the RNA replication step. SETD3 is a methyltransferase that mono-methylates actin, thereby regulating actin function. However, we found that methyltransferase activity of SETD3 is not required for its role in viral replication indicating that enteroviruses’ reliance on SETD3 is independent of actin methylation. We further showed that SETD3 interacts with the viral nonstructural 2A protein of several enteroviruses. SETD3 is critically important for in vivo pathogenesis as we show that Setd3-/- mice are completely protected from lethal intracranial inoculation with EV-A71 in a neonate model. These findings demonstrate that SETD3 controls pathogenesis for a large class of viruses with a strong impact on human health including non-polio EVs that can cause severe neurological symptoms (EV-A71, EV-D68). In this application, we will determine the specific role of SETD3 in viral RNA replication, structurally characterize the interaction between SETD3 and 2A, and test the hypothesis that SETD3’s interactions with viral nonstructural proteins are a novel molecular mechanism by which EVs hijack cellular machinery to enable genome amplification. Furthermore, to study the in vivo role of SETD3 in a mouse model that recapitulates more faithfully the transmission cycle and pathogenesis of enteric enteroviruses, we will develop and apply an oral infection model of EV-A71 in immune-competent mice. Our results will provide details on the molecular mechanisms by which host factors promote enteroviral RNA replication, reveal how non- catalytic functions of methyltransferases act in microbial pathogenesis and uncover the in vivo role of SETD3 in promoting EV-A71 replication in diverse cell types involved in initial replication, systemic spread and ultimately in neuropathogenesis.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY / ABSTRACT Peripheral artery disease (PAD), characterized by diseased arteries to the limbs, affects 200 million people worldwide and 9 million people in the U.S. Chronic kidney disease (CKD) affects 20 million people in the U.S. and confers a markedly higher risk for PAD. Yet patients with CKD are less likely to have revascularization procedures and are more likely to undergo lower extremity amputation than patients without CKD. In addition to a high prevalence of traditional risk factors such as hypertension and diabetes mellitus, patients with CKD have other unique risk factors such as chronic inflammation or uremia, which in turn can lead to more aggressive PAD at a younger age. Therefore, patients with CKD need dedicated study. Our overarching goal is to help close these evidence gaps and address these limitations by harnessing the power of Optum Clinformatics Data Mart, which includes over 7 billion claims records on over 83 million unique lives from all 50 states spanning 2005-2019. Our secondary goal is to facilitate future PAD studies using real-world data by leveraging the power of natural language processing to improve our ability to accurately and automatically ascertain PAD from large electronic health record databases. Our innovative algorithm will be of particular importance among subgroups where clinical trial evidence is limited, such as in advanced CKD. Our proposal has the Specific Aims. Aim 1: To evaluate lower extremity revascularization in patients with non-dialysis- requiring CKD. We hypothesize that patients with CKD undergoing surgical versus endovascular revascularization will have longer initial hospitalization, but fewer subsequent major adverse limb events. AIM 2: To evaluate antiplatelet and anticoagulant medications after lower extremity revascularization in patients with non-dialysis-requiring CKD. We hypothesize that real-world patients with CKD treated with antiplatelet medications or direct oral anticoagulants after lower extremity revascularization will have higher rates of bleeding but lower rates of major adverse limb events. AIM 3: To develop an algorithm that accurately and automatically ascertains PAD from electronic health record databases. We hypothesize that a natural language processing-approach applied to diagnostic vascular testing reports will have better test performance (i.e. sensitivity, specificity, positive and negative predictive values) for identifying PAD than a traditional approach that uses administrative billing codes. Manual chart review will serve as the gold standard.

NIH Research Projects · FY 2025 · 2021-04

Project Summary Background: Malignant melanoma and pancreatic ductal adenocarcinoma (PDAC) typically spread to lymph nodes (LNs) prior to outgrowth in distant tissues. While metastasis to LNs is frequently attributed to passive drainage from tumor lymphatics, the mechanisms enabling LN metastasis and its functional role in tumor progression remain poorly understood. LNs are education hubs of the adaptive immune response and harbor the majority of potentially tumor-reactive lymphocytes. Recently, we discovered that in colonizing LNs, tumor cells induce tumor-specific immune tolerance through their interactions with leukocytes that subsequently circulate throughout the host, resulting in systemic tolerance that facilitates metastatic seeding of distant sites. Hypothesis and objective: We hypothesize that by targeting the induction of immune tolerance in LNs, we can both prevent distant metastasis and induce tumor regression. We will use multiple cutting-edge methods to identify the cellular and molecular mechanisms of LN tolerance induction and develop approaches for breaking it. These goals will be pursued in the following aims: Specific Aims: Aim 1: Identify the mechanisms by which lymph node metastases induce tumor-specific immune tolerance through their activation of immunosuppressive lymphocyte populations. Aim 2: Determine the role of epigenetic regulation in LN metastasis and tolerance induction. Aim 3: Investigate immunotherapeutic approaches targeting tumor immune tolerance in LNs. Study design and methods: Using high-content multiplexed microscopy, mass cytometry, photoconversion- based lineage tracing, TCR sequencing, and genetic mouse models of antigen presentation, we will dissect the cellular interactions in LNs that we hypothesize are responsible for tolerance induction and dissemination, and validate the findings in human tissues and datasets. LN metastatic tumor cells exhibit conserved and stable transcriptional profiles indicative of epigenetic reprogramming. We will assess the role of epigenetic alterations in conferring a pro-LN metastatic transcriptional signature using bisulfite sequencing and ATAC-seq, and employ T-ATAC-seq to elucidate changes in the epigenetic landscape within tolerized T cells that recognize tumor antigens. We will evaluate the ability of our novel immunostimulatory antibody conjugates, targeted specifically to LNs, to reprogram APCs in metastatic LNs, employ HDAC inhibitors to reprogram both malignant and lymphocyte populations away from tumor immune tolerance, and combine these strategies to elicit robust anti-tumor combination therapies in mouse models of melanoma and PDAC. Expected results and impact: Upon successful conclusion of this work, we will have identified the mechanisms by which LN metastasis induces systemic tolerance, and evaluated novel immunotherapeutic strategies to overcome these mechanisms.

NIH Research Projects · FY 2025 · 2021-04

ABSTRACT Surgery is common and appropriate postoperative pain management is critical as poor management can impair recovery and lead to adverse events, including prolonged opioid use and transition to chronic pain. Additional specific risks in elder surgical patients include delirium and falls. Currently prejudice rather than evidence guides the complex problem of elder perioperative pain management. Given the gravity of the US opioid epidemic, policy makers are quickly establishing rules and regulations for opioid prescribing. These policies are blanket regulations that neglect emerging evidence regarding the need for differential opioid prescriptions based on clinical and patient factors, particularly in elders. Currently, there lacks tools to identify elders at high risk for adverse pain outcomes. Such tools are needed to provide critical evidence on pain management to stakeholders and move the field away from pain treatment for the ‘average’ elder patient to pain treatment for an individual. In this grant, we propose an innovative approach to advance the systematic analysis of postoperative pain in elders. Our approach will develop scalable, open source risk stratification tools for adverse pain outcomes in elders. We will accomplish this work in three aims. First, we will develop clinical phenotypes to identify and extract key discriminating features necessary to assess postoperative pain using EHRs. Next, we will develop pain risk stratification models using machine learning, including deep learning, methods and tools based on phenotypes developed in Aim 1. Finally, we will validate our models externally at the VA and disseminate our work through open source libraries and public websites. This project will deliver validated risk-stratification tools derived from real world evidence to identify elder patients at high risk for adverse pain outcomes following surgery, which can potentially reduce prescribed opioids circulating in the community– a key to curbing the opioid epidemic.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY Relapse is the major cause of cancer related mortality in children with leukemia. Despite improvements in overall survival for children with B-cell progenitor acute lymphoblastic leukemia (ALL), for the 600 patients who will relapse each year, half will die of their disease. The high mortality of patients who relapse underscores the need for improved risk prediction and treatment strategies to prevent recurrent leukemia. Current approaches to relapse prediction are limited by insufficient accuracy, delayed prediction and the inability to make actionable treatment adjustments based on prediction information. To address these limitations, we applied a single-cell, high-parameter proteomic approach to ALL patient samples at the time of diagnosis, accurately predicting future relapse based on the presence of pre-B cells with activated signaling. This approach was 38% more accurate than standard of care relapse prediction methods. We propose that identifying relapse-predictive cells in ALL at the time of diagnosis using their distinguishing proteomic and genetic features will result in a clinical risk prediction model that is accurate, immediate, and actionable. This approach to relapse prediction will change the clinical paradigm of relapse risk in ALL to reduce the incidence of relapse itself. Using large multi-institutional, multimodal cohorts of molecularly and clinically annotated diagnostic patient samples, we will apply deep proteomic approaches to identify surface proteins uniquely expressed on relapse predictive pre-B cells enabling direct identification in a diagnosis sample. We will determine how genomic mutations associate with the presence of relapse predictive cells and examine their genomic mutational burden using single-cell exome sequencing. Finally, building on our data-driven, machine learning approaches, we will construct a diagnostic relapse predictor that is more accurate than standard of care models while informing on leukemia biology and targeted therapeutic options for patients at risk. This will enable a more precise approach to patient classification and treatment, reducing the number of children facing relapse and moving closer to precision medicine for children with ALL.

NIH Research Projects · FY 2025 · 2021-04

ABSTRACT: OVERALL The goal of this proposal is to form a Biomedical Technology Research Resource (BTRR) at SLAC National Accelerator Laboratory that involves a set of interrelated Technology Research and Development (TR&D) projects aimed at enhancing and developing the unique capabilities of the SLAC Linac Coherent Light Source (LCLS) for biomedical applications. The BTRR will enable structural biology experiments that are extremely difficult or impossible to perform at synchrotron (SR) or electron microscopy (cryoEM) facilities and will increase the availability of these capabilities to the broader structural biology community. The enabled experiments will facilitate paradigm-shifting advances on a wide variety of topics, including neurotransmission, signal transduction, cellular metabolism, transcription and viral infection. The proposed TR&Ds are tightly coupled with the research themes of the nine Driving Biomedical Projects (DBPs). These research themes focus on developments to visualize large complexes and membrane proteins, such as GPCRs and that provide accurate active site structures of metalloenzymes, such as ribonucleotide reductase and cytochrome c oxidase, and complex macromolecular machines, such as RNA polymerase-II. Finally, a common research area of all DBPs involve time-resolved (TR) studies that include research to follow dynamic processes involved in adenine riboswitch signaling, the transport mechanism of N. gonorrhoeae MtrF, antibiotic binding to β-lactamase and examination of interaction specificity of CypA variants. All DBPs hinge on highly efficient data collection methods, which are required for successful macromolecular crystallography (MC) experiments at X-ray FELs. The high peak brightness of an X-ray FEL pulse destroys the crystal volume exposed, bringing about sample refreshment challenges previously unknown to the MC SR community. As a result, the sample must be continually replenished throughout the experiment. As part of the TR&Ds, sample injectors that rapidly deliver crystals and sample solutions to the X-ray beam will be optimized and automated during LCLS experiments along with data analysis to gauge experimental success and optimize use of limited sample and beam time. Time resolved studies hinge on improvements to mixing injectors, laser activation and complementary spectroscopic methods. X-ray FEL beam time is scarce so careful characterization of samples and complex experimental setups prior to beam time is critical to ensure experimental success, in particular for complex time resolved measurements of sensitive metalloenzymes intermediates. Experimental design and testing, sample production, sample characterization (including spectroscopic analysis) and crystal quality screening are supported in the laboratory, at the Stanford Synchrotron Radiation Lightsource (SSRL) and during screening beam time at LCLS. Integrating with, and enhancing the existing programs at SSRL and LCLS, the BTRR will provide support, expertise and training to the biomedical community.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY/ABSTRACT Although endothelial keratoplasty is one of the most commonly performed transplant surgeries, it is unknown which technique provides optimal visual acuity outcomes while minimizing endothelial cell loss and complications. Post-operative endothelial cell counts have been shown to correlate with risk of subsequent graft failure, with significant cost to individual patients and society. Topical rho-kinase inhibitors such as ripasudil 0.4% may play an important role in maintaining endothelial health after keratoplasty. Here we propose the Descemet Endothelial Thickness Comparison Trial (DETECT), a randomized, outcome- masked, multi-center, four-arm clinical trial with a 2x2 factorial design. The purpose of this study is to determine differences in visual outcomes between two types of corneal transplant surgeries, ultrathin Descemet stripping automated endothelial keratoplasty (UT-DSAEK) and Descemet membrane endothelial keratoplasty (DMEK), and to determine the effect of rho-kinase inhibitors on endothelial cell counts after keratoplasty. Patients presenting to Oregon Health & Science University, Stanford University, NorthShore University HealthSystem, University of Maryland, and to Kaiser Permanente Northern California with endothelial dysfunction who are good candidates for either UT-DSAEK or DMEK will be eligible for inclusion. Participants will be randomized to one of four treatment groups in this 2x2 factorial design study: Endothelial Keratoplasty UT-DSAEK DMEK Adjuvant Topical Medication Ripasudil 0.4% UT-DSAEK + 0.4% ripasudil DMEK + 0.4% ripasudil Placebo UT-DSAEK + placebo DMEK + placebo This approach is innovative for a number of reasons including its testing of a novel treatment, ripasudil 0.4%, and the randomization of surgery, which is relatively rare. It is aligned with the priorities of the NEI, studying new high-resolution imaging techniques such as endothelial cell imaging, anterior-segment optical coherence and Pentacam Scheimflug imaging, to guide post-operative treatment and as potential surrogate trial endpoints in future trials. This world class team of collaborators have a proven track record for executing large NEI- funded trials in ophthalmology, and are well positioned to answer the two important questions presented in this proposal.

NIH Research Projects · FY 2025 · 2021-04

Alzheimer's disease (AD) is the most common neurodegenerative disorder in the United States that affects more than 5 million Americans. Synapses are the earliest affected component of the brain during AD pathogenesis, suggesting that the cognitive decline and neuronal loss in AD initiates with synaptic dysfunction. Despite much effort, however, no definitive understanding of AD pathogenesis is available, and no therapies that alleviate or even stop progression of AD are known. Genetic studies identified rare mutations in presenilin and in APP genes that cause early-onset familial AD (FAD), and described common variants in several genes, chiefly the ApoE and TREM2 genes, that predispose to sporadic AD, providing potential clues to AD pathogenesis. Presenilin mutations impair the activity of γ-secretase, an intramembranous protease that cleaves a large number of membrane proteins, including APP. Presenilin and APP mutations associated with FAD both enhance production of Aβ, a cleavage product of APP. Moreover, all AD patients suffer from an accumulation of Aβ in brain, leading to the `amyloid Aβ hypothesis' whereby AD is induced by Aβ amyloid accumulation in brain. However, therapies that prevent or even reverse Aβ accumulation in brain have not been effective in treating AD. Furthermore, ApoE and TREM2 are not directly related to Aβ, but seem to influence microglial function, inflammatory responses, and/or lipid metabolism. Indeed, alterations in lipid content are a prominent feature of AD brains, suggesting that Aβ may be related to AD pathogenesis in a manner that is not related to amyloid formation. Indeed, in preliminary experiments we observed that a chronic decrease γ-secretase activity, as would be observed with FAD- associated mutations of presenilin genes, causes a major decrease in synaptic transmission and an upregulation of cholesterol synthesis. Based on the all of these findings together, we here propose an interdisciplinary project that examines the role of changes in γ-secretase activity in synaptic function and lipid metabolism as a potential pathogenetic mechanism in AD. We describe four specific aims that will investigate the relationship of γ- secretase to synaptic transmission, the mechanism by which γ-secretase activity normally suppresses cholesterol synthesis, and the possibility that increased cholesterol synthesis induced by a chronic decrease in γ-secretase activity is responsible for the observed synaptic impairments. Moreover, the proposed specific aims will explore the possibility that ApoE4, the ApoE variant predisposing to AD, also acts by altering lipid metabolism in neurons. These experiments will adopt a multidisciplinary approach that will be carried out in human neurons and in mouse brains, and will combine cell biology, transcriptomics, CRISPR, and electrophysiology techniques to explore the underlying mechanisms. Among others, these experiments will contribute to our understanding of how presenilin mutations that cause FAD and impair γ-secretase activity affect synapses, and test the overall hypothesis that FAD-associated presenilin mutations and genetic ApoE variants predisposing to sporadic AD act by a sucommon pathway regulating neuronal cholesterol levels, which in turn influences synaptic function.

NIH Research Projects · FY 2025 · 2021-04

PROJECT SUMMARY The goal of cancer immunotherapy is to awaken the body’s anti-tumoral immune response to fight against all cancers in all patients. Our lab recently identified a key mechanism by which cancer cells are detected by our innate immune system. We now know that cancer cells, with intrinsic chromosomal instability, constantly secret the soluble small molecule 2’3’-cyclic-GMP-AMP (cGAMP). Acting as an immunotransmitter, extracellular cGAMP is taken up by surrounding tissues and immune cells to activate its receptor STING in a paracrine fashion, resulting in downstream anti-cancer immune responses. The importance of extracellular cGAMP is demonstrated by our finding that it is required for the curative effect of ionizing radiation in a murine model of breast cancer. Furthermore, we identified the extracellular enzyme ENPP1 as the only detectable hydrolase of extracellular cGAMP that blocks its signaling pathway. Therefore, we hypothesize that ENPP1 is an innate immune checkpoint that could be targeted to expand the reach of cancer immunotherapy. Although ENPP1 is cGAMP’s only hydrolase, it hydrolyzes extracellular ATP at comparable potency. Therefore, genetic and pharmacological tools that are based on complete ablation of ENPP1 activity cannot be used to distinguish the physiological role between extracellular cGAMP and ATP. Here, we propose selective genetic and chemical biology approaches: we will characterize genetic tools that selectively abolish ENPP1’s hydrolase activity toward extracellular cGAMP but not ATP (dENPP1cGAMP); in parallel we will develop substrate- specific ENPP1 inhibitors as tool compounds and potential immunotherapeutics. In Aim 1, we will fully characterize the kinetics, selectivity, and mechanisms of action of mutant dENPP1cGAMP, as well as the pathophysiology of dEnpp1cGAMP mice. In Aim 2, we will evaluate multiple tumor models in the dEnpp1cGAMP mouse strain to determine the physiological roles of extracellular cGAMP in controlling tumor growth and synergism with checkpoint blockers. In Aim 3, we will first characterize mechanism of substrate selectivity of our lead cGAMP-selective ENPP1 inhibitor and then use this inhibitor to harness the anti-tumoral effects of extracellular cGAMP. This proposal combines careful biochemical analyses with mouse genetics and tool compound development to address the role of extracellular cGAMP in cancer, with the goal of improving cancer immunotherapy.

NIH Research Projects · FY 2025 · 2021-04

Leveraging deep learning for markerless motion management in radiation therapy Project Summary Organ motion is a predominant limiting factor for the maximum exploitation of modern radiation therapy (RT). Adverse influence of the organ motion is aggravated in hypofractionated treatment because of protracted dose delivery. Current image guided RT often relies on the use of implanted fiducial markers (FMs) for online/offline target localization, which is invasive and costly, and introduces possible bleeding, infection and discomfort of the patient. In this project, we harness the enormous potential of deep learning and investigate a novel markerless localization strategy by combined use of a pre-trained deep learning model and kV X-ray projection or cone beam CT images. We hypothesize that incorporation of deep layers of image information allows us to visualize otherwise invisible target in real-time and greatly reduce the uncertainties in beam targeting. Specific aims of the project are to: (1) Develop a DL-based tumor target localization framework for image guided RT (IGRT); (2) Apply the DL-based strategy to localize prostate target on 2D kV X-ray projection and 3D CBCT images; and (3) Evaluate the potential clinical impact of the DL strategy for pancreatic IGRT. This study brings up, for the first time, highly accurate markerless target localization based on deep learning and provides a clinically sensible solution for IGRT of prostate and pancreas cancers or other types of cancers. Successful completion of this investigation will significantly advance the current beam targeting technique and provide radiation oncology discipline a powerful way to safely and reliably escalate the radiation dose for precision RT. Given its significant promise to optimally cater for inter- and intra-fractional uncertainties, the study should lead to substantial improvement in patient care and enables us to utilize maximally the technical capability of modern RT such as IMRT and VMAT. Given the dose responsive nature of various cancers and that the proposed method requires no hardware modification, this research should lead to a widespread impact on the management of neoplasmic diseases affected by organ motion.

NIH Research Projects · FY 2025 · 2021-03

PROJECT SUMMARY The immune system remarkably distinguishes between self and non-self/self-aberrant antigens, affording exquisite anti-tumor specificity and inhibition of tumorigenesis. However, tumor immunosurveillance is unfortunately opposed by tumor cell evasion of the immune response. Immune checkpoint blockade (ICB) targeting PD-1, PD-L1, CD40 and others, as well as adoptive cell transfer (CAR-T, bulk TILs) favorably modulate this equilibrium for therapeutic benefit. However, response rates are often incomplete, progressive disease is common, and predictive biomarkers are suboptimal. The development of next-generation immunotherapies has been hindered by a lack of in vitro models that functionally recapitulate syngeneic interactions between tumor and infiltrating immune cells. In response, we have developed organoid methods that culture primary human tumor biopsies together with their infiltrating immune components as a cohesive unit without reconstitution. These “patient-derived tumor organoids” (PDO) preserve tumor cells alongside endogenous T, B, NK cells and macrophages, robustly recapitulate the T cell receptor clonotype repertoire of the original tumor, and crucially, manifest tumor-infiltrating lymphocyte (TIL) expansion, activation and tumor cell killing in response to anti-PD-1/PD-L1 therapeutic antibodies (Cell, 2018). The PDO system thus represents a holistic organoid model of human tumor-immune interactions. Here, we leverage the PDO technique to investigate immunotherapeutic mechanisms and treatments in PD-1-responsive cutaneous squamous cell carcinoma (cSCC) and melanoma, exploiting pre- and post-treatment human biopsies and mouse models. Aim 1 hypothesizes that checkpoint inhibition induces a complex and sequential network response involving immune-tumor and immune-immune crosstalk. Thus, Aim 1 employs the ability to perform serial time-course sampling of PDOs to define a single cell RNA-seq network cellular crosstalk model of the early anti-PD-1-stimulated anti-tumor immune response over multiple acute time points typically inaccessible to clinical biopsies performed after months. Importantly, comparison of this immune propagation in responding versus non-responding mouse and human organoids will define nodal points conferring resistance. Aim 2 improves bulk TIL adoptive transfer immunotherapy by using PDOs as living bioreactors to enrich tumor-reactive mouse and human melanoma TILs by anti-PD-1 checkpoint inhibition, followed by testing of enhanced anti-tumor activity in vitro and in vivo. Lastly, Aim 3 performs a co-treatment trial comparing anti-PD-1 responses of pre-treatment biopsy cSCC PDOs to clinical outcomes. Further, post- treatment biopsy PDOs are re-challenged with anti-PD-1 and a novel agent inactivating PD-1 by dephosphorylation. We thus utilize the holistic PDO model preserving endogenous tumor epithelial and immune components en bloc to investigate and improve cancer immunotherapy via our team of Calvin Kuo (organoids), Mark Davis and Chris Garcia (tumor immunology) and Anne Chang and Dimitri Colevas (cSCC clinicians).

NIH Research Projects · FY 2025 · 2021-03

Project Summary: Worldwide, 844 million people are afflicted with liver disease, with mortality nearing 2 million deaths per year. Liver transplantation is the preferred treatment for selected cases but is limited by the availability of high-quality organs from young donors (<55 years old), and the morbidity associated with the operation. Cell-based therapy using primary human hepatocytes (PHHs) is a minimally invasive alternative for treatment of select liver pathologies where architecture is preserved but there are metabolic derangements, such as in acute liver failure and metabolic liver disease. Optimal metabolic function of the cells is critical for the success of cell-based therapies. However, PHH therapy is severely limited by the scarcity of donors, and the dramatic decrease in metabolic function of PHHs from older donors. Human hepatocyte-like cells (h-iHLCs) derived from human induced pluripotent stem cells (h-iPSCs) emerged as an alternative to PHHs for treatment of select liver conditions. H-iHLC have three benefits: (1) H-iHLCs are produced from an unlimited, renewable source: h-iPSCs. (2) They bypass ethical concerns associated with the use of embryonic stem cells. (3) They have the potential to prevent an allogeneic immune response following transplantation by utilizing the patients’ own cells. Although, the deleterious impact of age on the metabolic function has been described for PHHs, the impact of donor age on the metabolism in h-iHLCs has not been studied. Here, we aim to identify the donor age-associated changes in the overall metabolic profile of h-iHLCs by studying the transcriptome and proteome of h-iHLCs from young and old donors and compare the results to PHHs from the same donors. We will study in detail the expression and function of the cytochrome P450 (CYP450) superfamily in h-iHLCs and PHHs as a function of donor age. Age-related changes in DNA-methylation down-regulate metabolic function including CYP450 activity in PHHs. Therefore, we will study and attempt to modulate this regulatory mechanism in h-iHLCs with the goal to optimize the overall metabolic function including CYP450 activity in h-iHLCs. We will examine the therapeutic efficacy of the generated h-iHLCs in a murine model of acute liver failure by transplanting h-iHLCs into metabolic liver failure, tyrosemia type I (Fah¯′¯/Rag2¯′¯/Il2rg¯′¯ on NOD-strain background (FRGN)) mice. The results from this study will provide critical information about the impact of donor age on metabolism and its regulation in h-iHLCs and will (1) assist in selecting metabolically fit donors for allogeneic h-iHLCs transplantation, (2) allow future modulation of functional and regulatory mechanisms through alterations in reprogramming, differentiation and gene editing, to produce high-quality h-iHLCs with optimized metabolic function for allo- and autogeneic transplantation.

NIH Research Projects · FY 2025 · 2021-03

PROJECT SUMMARY/ABSTRACT PIs: Ash Alizadeh, M.D./Ph.D. & Maximilian Diehn, M.D./Ph.D. Classical Hodgkin lymphoma (HL) is among the most curable human malignancies. However, strategies to personalize HL therapies and to minimize long-term attendant toxicities of chemotherapy are currently limited to baseline risk factors and imaging. This is due to our incomplete understanding of targetable pathways and lack of good biomarkers. Because of the low fraction of malignant cells in tumor tissue and consecutive technical challenges, the landscape of HL is not well-defined. Our long-term goal is to study the ability of baseline and dynamic risk factors, including genetic mutations, circulating tumor DNA (ctDNA) and imaging studies (PET), to accurately predict treatment outcomes in HL patients, and to provide a basis for individualized precision medicine. Our central hypothesis is that clinical and biological heterogeneity in HL reflects distinct genomic features that are noninvasively measurable using ultrasensitive ctDNA techniques, and that refining early response assessment integrating interim PET and blood based methods improves prognostication. We will test our hypotheses via three specific aims: (1) To noninvasively define the genomic landscape of somatic variations in HL, and to determine the relationship of genomic variants with biological heterogeneity at initial disease presentation, (2) To associate molecular features at baseline and molecular response with ultimate therapeutic outcome, and to integrate clinical and molecular biomarkers in a personalized dynamic risk model for predicting HL outcomes, and (3) To functionally characterize novel mutations in Interleukin-4 receptor (IL4R) resulting in gain-of-function IL4/STAT6 signaling, and to test the utility of precision therapeutic targeting of these mutations. If successful, our project will lead to novel ways to select better therapies for patients at highest risk of failure, and to minimize toxicity for the majority of patients responding well to standard therapy. Our innovative approach, in which we will combine blood-based methods for genotyping and disease monitoring with imaging studies, will provide the basis for a personalized treatment approach in HL.

NIH Research Projects · FY 2026 · 2021-03

ABSTRACT Covalent post-translational protein modifications (PTMs) contribute to all aspects of cell physiology and are a major source of protein functional diversity in mammalian cells. Aberrant regulation of PTMs is a common feature of human diseases. Our research focuses on an important PTM: protein methylation occurring on lysine residues as well as on less common residues. Our overarching goal is to elucidate at a molecular level the physiologic roles for protein methylation signaling in the regulation of chromatin biology, epigenetics, protein synthesis, and other fundamental biological processes, and to understand how disruption in these mechanisms contributes to human disease. Within this research framework we will investigate the biology and function of enzymes that regulate histone methylation dynamics, with a focus on methylation at histone H3 lysine 36 (H3K36). Beyond histone methylation, there is a growing appreciation that a number of non-histone proteins, including several with clear roles in gene expression and signal transduction are lysine methylated. Indeed, there are likely more than seventy-five lysine methyltransferases in the human genome, and an increasing number of examples of alterations in these genes being linked to human disorders. Thus, it is likely that non- histone protein methylation dynamics plays a crucial role in physiology and in disease pathogenesis. We will explore the biology and function of non-histone protein methylation signaling pathways. In addition to lysine methylation, other residues like histidine are also methylated, though relatively little is known about these methylation modification network. We will explore the hypothesis that non-canonical protein methylation has an underappreciated and significant role in signal transduction, cell biology, and disease. For our studies, we will use a multi-disciplinary strategy that include biochemical, molecular, proteomic, genomic, genetic, chemical, cellular and mouse modeling approaches.

NIH Research Projects · FY 2025 · 2021-03

REPROGRAMMING MYELOID CELL METABOLISM TO PREVENT COGNITIVE AGING AND ALZHEIMER’S DISEASE SUMMARY The brain is highly vulnerable to aging, as demonstrated by the high prevalence of age-associated cognitive decline and Alzheimer’s disease (AD). Human genome-wide association studies demonstrate a dominant role for dysfunctional myeloid cells, which include brain microglia as well as peripheral monocytes/macrophages (Mo/Mph), in increasing risk of AD. Microglia lose their normal capacities to maintain immune homeostasis within the brain, provide trophic support to neurons, and clear misfolded proteins. Circulating factors in aged plasma influence microglial activation and are linked to age-associated cognitive decline. These observations point to a causal role of brain and/or systemic myeloid dysfunction in development of cognitive decline in aging and AD. In our recent studies, we have identified an important role for cellular bioenergetics in regulating immune responses in aging macrophages and microglia. Maintenance of homeostatic and healthy immune function requires robust glycolytic and mitochondrial metabolism to meet demand for energy and biosynthetic precursors. Indeed, our recent studies demonstrate that glycolysis and mitochondrial respiration are significantly suppressed in aging microglia and Mo/Mph, leading to an energy deficient state that promotes maladaptive pro-inflammatory responses and decreased phagocytic potential. In this proposal we will test whether reprogramming cellular metabolism in aging microglia and/or peripheral Mo/Mph by modulating a major inflammatory pathway, the PGE2 signaling pathway, is disease-modifying in aging and in AD model mice. There is a growing literature on how cellular metabolism regulates immune cell function, particularly in the areas of infection and cancer. This conceptual framework has not yet been applied to aging, nor has it been applied to cognitive aging and age- associated neurodegenerative diseases like AD. Our approach proposed here will answer several fundamental questions including: (1) whether myeloid metabolic deficits drive brain aging, (2) whether peripheral or brain myeloid compartments are critical in this process, and (3) whether targeting myeloid metabolism represents a new therapeutic approach for AD.

NIH Research Projects · FY 2025 · 2021-03

The National Cancer Institute has called for eliminating disparities in cancer morbidity and mortality through the use of Data Science. Gastric cancer remains one of the most unequally distributed cancers in the United States, with high burden among certain ethnic, racial, and immigrant groups. Identification of individuals at greatest risk for gastric cancer may allow for targeted risk attenuation programs, and improve health equity. Candidate and Career Development Plan: I am a board-certified Gastroenterologist and Master’s degree-trained epidemiologist at Stanford University who seeks to use data science to reduce disparities in cancer outcomes. Based on my training and experience, I have content expertise in gastrointestinal cancer diagnosis, and methodologic expertise in epidemiologic principles and observational study design. In order to achieve my long-term goal of becoming an independent investigator and national leader in cancer disparities research, I require additional quantitative skills (large data analytics, machine learning-based risk prediction, unstructured data extraction using natural language processing), qualitative skills (effective scientific communication, scientific leadership), and professional development. Research Plan: The overarching research aim of this proposal is to develop a PErsonalized Risk Score for gastrIc CancEr (PRECISE) using real-world clinical data sources. My overall hypothesis is that through use of advanced data analytics and deep learning methods, a highly-refined cohort of individuals at highest risk for gastric cancer can be identified. The Specific Aims of this proposal seek to address this hypothesis: (1) to build a personalized risk prediction model using regression, (2) to build a personalized risk prediction model using machine learning algorithms, and (3) to compare regression and machine learning models in electronic health records data. Achievement of these aims will produce a novel, personalized prediction score which will help identify individuals at high risk for gastric cancer and who may benefit from targeted risk attenuation programs. Mentorship Team: To achieve these Aims, I have assembled a world class mentorship team with expertise in epidemiology and health disparities research (Latha Palaniappan, primary mentor), machine learning and natural language processing in EHR data (Tina Hernandez-Boussard, co-mentor), and gastric cancer screening and prevention (Joo Ha Hwang, co-mentor). Environment and Institutional Commitment: Stanford University is a world leader in clinical informatics, epidemiology, and health services research. I will have access to a unique data core, which contains one of the most extensive and robust collections of curated clinical data in the world. My mentorship team is committed to ensuring the success of the proposal, and in developing me to become an independent investigator competitive for R-level grants.

NIH Research Projects · FY 2025 · 2021-03

Project Summary Understanding how a network of interconnected neurons receives, stores and processes information requires parallel and high quality recording of neuroelectric signals. Intracellular recording techniques such as patch clamp are invasive and limited to recording 1-2 cells. While extracellular multielectrode arrays can record multiple cells, they are pre-fabricated and thus can only probe fixed locations. Optical detection of electric activities provides the needed spatial flexibility. Calcium sensors such as GcaMP have a slow time response and not suitable to record fast-spiking pacemaker neurons such as dopaminergic neurons. Voltage-sensitive fluorescence proteins and dyes have much faster time response, but their recording time is usually limited by photobleaching. In this project, we will demonstrate an orthogonal approach of optical recording. This method, Electrochromic Optical Recording of Electric potentials (ECORE) makes use of a unique material property – optical absorption of an electrochromic film depends on applied voltages. We detect the optical reflection of an electrochromic film to read out cellular electrical activities. The method is truly label-free, i.e. free of any molecular probes that need to be incorporated into cells and perturb cellular physiology, and not limited by photobleaching or photo-toxicity. In preliminary work, we have built a sensitive optical setup that is able to detect the reflectivity change of the electrochromic film in response to electrical potentials as small as 10 microvolts. Indeed, we have used ECORE to successfully record single-cell action potentials in neurons, cardiomyocytes, and brain tissues. With this project, we plan to dramatically expand ECORE capabilities by developing a scanning ECORE platform for parallel detection and an ECORE microscope for subcellular measurement of neuroelectric activities. We will use ECORE to probe the functional connectivity of dopaminergic neurons in midbrain area. Accomplishment of this work will result in a new class of electrophysiological tools that can be used by other research groups.

NIH Research Projects · FY 2025 · 2021-03

PROJECT SUMMARY/ABSTRACT Cystic fibrosis (CF) is an autosomal recessive single-gene disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The most common mutation, termed ∆F508, occurs in ~85% of CF patients. Because the CFTR gene encodes for an anion transport protein, CFTR mutations alter electrolyte and water transport, resulting in dense, pathologic, mucous and other secretions. The most harmful effects of CFTR dysfunction occur in the respiratory system, with recurrent infections and inflammation of the upper and lower airways. Despite substantial progress with medical therapies, there remains a tremendous unmet need for improved, durable therapies for CF. For the past 3 years, our collaborative group of complementary scientists and physicians has determined to develop a novel, stem cell-based treatment strategy for patients suffering from CF. For several critical reasons, we directed our efforts to cell-based therapy of CF upper airway disease using ex vivo-expanded, primary human airway basal stem cells, termed ABCs. The first major milestone was to utilize CRISPR/Cas9 genome editing technology to efficiently correct the ∆F508 mutation in ABCs cultured from CF patients undergoing sinus surgery. This gene correction approach has led to significant restoration of chloride anion transport from 0-3% to 30-40% in ABCs. This encouraging, and newly published, development now provides a pre-clinical roadmap for re-introducing CFTR gene-corrected ABCs into in vivo contexts as a stem cell replacement therapy. In this proposal, we will rigorously determine the most efficient, biomaterial platform for ex vivo-to-in vivo transplant and engraftment of human ABCs, and assess the behavior of gene-corrected ABCs in the lab and live animal model using a microsurgical model system of upper airway transplantation that we have developed. The experiments outlined are essential pre-clinical steps in order to translate this approach to CF patients to generate an innovative and possibly transformative therapy for patients with CF, and the first stem cell-based therapy for human airway disease.