Stanford University

NIH Research Projects · FY 2025 · 2021-08

Summary: One of the biggest gaps in our knowledge of the human gut microbiome is how microbes secure the energy and nutrients required to sustain their growth. This is an important deficit in light of the fact that microbial pathways produce short chain fatty acids like butyrate, indoles like indolepropionic acid, and amines like trimethylamine, all of which play a critical role in host physiology and disease. Understanding the metabolic processes that underlie why microbes make these molecules is critical for developing strategies to predictably control the metabolic output of the gut microbiota. Despite the importance of microbial metabolism in the gut to human physiology, we know very little about the nature of these metabolic pathways. A key gap in knowledge is how pathways for high abundance metabolites is linked to the physiology of commensal bacteria. Knowledge of these metabolic strategies is critical to developing strategies aimed at predictably modulating the metabolic output of the gut microbiota. One of the major challenges to studying the gut microbiota is that genetic tools are only available for a small subset of bacteria. Therefore, new tools are urgently needed to study the physiology and metabolism of genetically intractable microbes. In this project, we will use techniques in bacterial physiology and genetics to uncover how microbes in the gut capture energy from dietary nutrients, and how these processes contribute to drug-like small molecules that influence host physiology. We will also develop a new metabolomics approach to generate genome-wide maps of genetic determinants of microbial small molecules in genetically tractable and intractable gut bacteria. These studies will provide fundamental insights into several of the microbiome's core functions and will stimulate future avenues for inquiry into the human gut microbiome.

NIH Research Projects · FY 2024 · 2021-08

Project Summary / Abstract Targeted therapy for the treatment of non-small cell lung cancer (NSCLC) has greatly improved patient outcomes compared to traditional chemotherapy. However, it is estimated that up to 20% of lung cancer patients receive first-line therapy prior to EGFR mutational analysis, necessitating the need for a rapid and cheap blood-based circulating tumor (ct) DNA test for efficient therapy selection. Additionally, ctDNA can be useful for rebiopsy and monitoring of response to therapy or acquired resistance to therapy. We have successfully developed a highly multiplexable magneto-nanosensor assay for the detection of “hot spot” mutation panel for lung cancer [targeted therapy selection or therapy monitoring and prognosis.] Specific aims of the project are: 1) Validate ctDNA EGFR magneto-nanosensor assay accuracy and correlations to clinical outcome on expanded cohort. We hypothesize that our magneto-nanosensor assay can detect “hot spot” EGFR mutations Exon19 deletion, L858R, and T790M with high sensitivity and specificity in a large cohort of NSCLC patients. Additionally, this assay can be well suited for prognosis and therapy response monitoring. A follow-up blood draw 2 weeks after initiating TKI therapy can be highly predictive of progression free survival. Additionally, we hypothesize that frequent testing (every 2-3 months) on the magneto-nanosensor assay could be used in lieu of radiographic imaging if patient maintains favorable response, and that the magneto-nanosensor assay could detect progression of disease prior to imaging. 2) Develop an extensive ctDNA mutation panel assay on magneto-nanosensor arrays [for NSCLC treatment selection, monitoring, and prognosis.] We hypothesize that our previously developed EGFR ctDNA magneto- nanosensor mutation assay can be further expanded to include mutations relevant to third-generation TKI resistance mechanisms and mutations in other genes to better aid in NSCLC [treatment selection, monitoring, and prognosis.] In this aim, our goal is to develop a ctDNA mutation panel that can help identify treatment options for NSCLC patients, not only EGFR mutations but also including KRAS, BRAF V600E, ALK-EML4 fusions, and ROS1 fusions. [We aim to monitor patients throughout their treatment course for responsiveness and prognosis.] The expected outcomes of this project are clinical validation of a ctDNA EGFR magneto-nanosensor assay, expanding and multiplexing the existing EGFR assay to include KRAS, BRAF V600E, ALK-EML4 fusions, and ROS1 fusions, and utilizing the assay [for efficient therapy selection, prognosis, and/or response monitoring.]

NIH Research Projects · FY 2025 · 2021-08

Project Summary Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, with prevalence rates ranging from 5-10% globally. With rising diagnosis rates in the last two decades, childhood ADHD has become a significant social and financial burden to affected individuals, families, and society at large. ADHD is characterized by impairments in cognitive control, with adverse life-long consequences for academic and social functioning. Cognitive control requires dynamic engagement of proactive and reactive control processes, and aberrancies in these processes underlie behavioral deficits, including elevated response variability and slow stopping speed. A related line of research suggests that rewards may increase stopping speed and reduce response variability in ADHD, with some individuals even reaching similar performance as typically developing children (TDC). However, the cognitive and brain mechanisms underlying proactive and reactive control, their modulation by reward and relation to clinical symptoms in ADHD are unknown. Here we develop an innovative multi-componential cognitive, neuroscience, and computational framework to address this gap and advance fundamental understanding of dysfunctional brain circuits linking cognitive control and reward systems in children with ADHD. Recent progress in cognitive and computational neuroscience has demonstrated that cognitive control relies on dynamic brain states characterized by dynamic interactions in functional brain circuits. The proposed studies will rigorously test theoretical cognitive and neuroscience models of ADHD by examining reward modulation of proactive and reactive control as well as dynamic brain circuits involving cognitive control, default mode and reward systems in children with ADHD. We will integrate multiple high-impact lines of our ongoing research on cognitive control, children with ADHD, and brain circuit dynamics. Importantly, we will leverage multiple novel computational models to uncover dynamics of cognitive and brain processes. The proposed studies will: (1) investigate how reward modulates proactive and reactive control in children with ADHD, (2) determine how aberrations in reward modulation of proactive and reactive control are related to core clinical symptoms, (3) characterize dynamic brain circuits underlying reward modulation of proactive and reactive control in children with ADHD, (4) determine how reward modulation of dynamic brain circuits involving cognitive control and reward systems are related to core symptoms, (5) identify multivariate cognitive and neurobiological features for classification of childhood ADHD and prediction of core clinical symptoms of ADHD. The proposed studies will facilitate a deeper understanding of cognitive and brain mechanisms underlying reward modulation of cognitive control, which will facilitate developing more effective and precise intervention for childhood ADHD in the future. Our cognitive, neuroscience and computational framework developed here can be widely applied to study many psychiatric disorders that manifest similar cognitive deficits, such as schizophrenia and autism.

NIH Research Projects · FY 2025 · 2021-08

Abstract (Overall): Pancreatic Ductal Adenocarcinoma (PDAC) is a deadly disease whose mechanisms of development remain incompletely understood. Evidence suggests that pancreatic cancers may arise from acinar cells undergoing a process called acinar to ductal metaplasia (ADM) or from ductal cells to give rise to Pancreatic Intraepithelial Neoplasias (PanINs). How mutations or combinations of mutations promote PDAC development and the role of inflammation in the process still remains unclear. Moreover, interactions between immune cells, cancer- associated fibroblasts (CAFs) and cancer cells can promote PDAC development and progression, but much remains to be learned about how signaling between cells in the tumor microenvironment (TME) affects the stem cell compartment (`stemness') thought to underlie PDAC development and promotes immune evasion. Thus, multiple questions about fundamental mechanisms governing PDAC development persist. To address these challenges, our superb and highly interactive team will identify genetic and stromal (immune cells and CAFs) interactions and pathways that regulate the inception and progression of PDAC using innovative mouse models and human tissue-based approaches. We propose three Projects to address the following overall aims: 1. Identify the originating cell(s) and deconstruct genetic pathways underlying PDAC initiation 2. Discover immune signals that cross-talk with epithelial cells and CAFs to promote pancreas cancer development and stemness 3. Investigate the impact of tumor genetics on PDAC immunobiology and response to macrophage-targeted immunotherapy Effort on these projects will be organized through an Administrative and Biostatistics Core (A) and empowered by two Research Cores, focused on human tissue procurement (Core B), and use of high-dimensional imaging to measure cell and signaling interactions in tissues (CODEX; Core C). The participating investigators on this P01 lead teams that have collaborated productively for years and have generated compelling preliminary data that support the potential for unraveling the genetic and immune signaling mechanisms underlying PDAC development, and developing new immunotherapeutic strategies for PDAC, which has proven frustratingly resistant to immuno-based therapies. Our studies should broadly impact pancreas cancer biology and importantly, elucidate the reciprocal interactions between immune and non-immune compartments (epithelial, CAFs) in shaping the tumor microenvironment during disease evolution. accelerate discovery of novel diagnostic or preventive strategies for early-stage disease, or therapeutics for advanced PDAC.

NIH Research Projects · FY 2024 · 2021-08

PROJECT SUMMARY/ABSTRACT: In children with tracheostomy (an artificial airway placed for upper airway abnormalities or chronic illness progression), bacterial respiratory infections are the most common reason for hospital admission, accounting for over 4600 hospitalizations and $300 million in U.S. hospital charges each year. Despite being the most common reason for hospital admission, there is limited evidence for the treatment of bacterial tracheostomy-associated infections (bTRAINs; bacterial pneumonia and/or tracheitis) in children. The overall objective of the current application is to evaluate what factors influence clinicians to diagnose and treat suspected bTRAINs with antibiotics. Pseudomonas aeruginosa (Pa), a bacterium with limited oral antibiotic options, is a common cause of bTRAINs. Because Pa causes 60% of bTRAINs, some clinicians presumptively treat for Pa while awaiting test results. However, because Pa growth is also common in respiratory cultures from patients with tracheostomy without clinical bTRAIN symptoms, some clinicians do not use Pa-targeted antibiotics when Pa is recovered on respiratory culture. Our preliminary data demonstrates wide variations in hospital-level diagnostic testing and treatment care practices in this population that are not associated with clinical outcomes, common use of empiric Pa-targeted antibiotics, and absence of differential outcomes when Pa is detected, regardless of receiving Pa-targeted antibiotics. Through development of a consortium of five freestanding children's hospitals, we will prospectively collect data on 1500 hospitalizations in children with tracheostomy and complete the following specific aims: 1) To determine the impact of rapid respiratory viral testing on continued antibiotic treatment in children with suspected bTRAINs; 2) To identify clinical and laboratory factors associated with antibiotic overuse in children with tracheostomy treated for bTRAINs; and 3) To define the association between bacteria-discordant antibiotic coverage, culture results and clinical outcomes in children hospitalized with bTRAINs and Pa-positive respiratory cultures. This will be the first multicenter prospective study in respiratory infections in children with tracheostomy. Findings will provide the necessary groundwork to design and implement targeted intervention trials to address heterogeneity in bTRAIN diagnosis and management, which may lead to decreased broad-spectrum antibiotic exposure and better long-term outcomes in a vulnerable population with high healthcare utilization. The proposal is responsive to the current program announcement (PA-16-423) and the AHRQ's mission to promote appropriate antibiotic use by “improv[ing] the appropriateness of antibiotic selection” through identifying “factors influencing prescriber decisions about the use and choice of antibiotics” and by examining “the role of rapid diagnostics in improving antibiotic use, including how rapid diagnostics should be integrated into clinicians' decision making about antibiotic use.” This proposal also studies several AHRQ priority populations, including children, low income populations, individuals with disabilities, and individuals who need chronic health care.

NIH Research Projects · FY 2026 · 2021-08

Seizures are one of the most common reasons why bystanders call Emergency Medical Services (EMS) for a child, and current practice frequently fails due to under-dosing and delayed delivery of anti-seizure medication. Benzodiazepines, such as midazolam, given in the nose or as a muscular injection are the first line treatment for seizures. Unfortunately, one-third of actively seizing children have ongoing seizures on arrival to the emergency department (ED) because an inadequate and delayed dose of midazolam fails to stop seizures. Children who continue to seize have seizures that are harder to stop, and this puts them at risk for not breathing and having brain damage. Reducing this risk requires equipping paramedics with a simplified method for rapidly determining and administering a therapeutic dose of medication. Paramedics suggest simplifying midazolam dosing by eliminating the error-prone, sequential calculations required to determine a weight-based dose under stressful conditions. Standardized, age-based dosing may be simpler, faster and more effective, without compromising safety. The overall objective of the Pediatric Dose Optimization for Seizures in EMS (Pedi DOSE) study is to measure the impact of standardized EMS midazolam dosing on seizure treatment effectiveness and safety. To achieve this objective, we will conduct a large EMS trial to implement standardized, age-based midazolam dosing for pediatric seizures in 20 EMS systems nationally. We believe that implementation will stop more seizures before children arrive at EDs without increasing respiratory failure rates. The first aim of this study is to compare the impact of standardized EMS midazolam dosing relative to conventional dosing on seizure cessation. We hypothesize that giving a standardized midazolam dose based on age will allow paramedics to stop a child’s seizure faster than conventional dosing with current practice. The second aim of this study is to determine how often children stop breathing or ineffectively breathe after implementation of standardized EMS midazolam dosing. We hypothesize that standardized EMS midazolam dosing is associated with no difference in slow or absent breathing relative to conventional dosing with current practice. If this study demonstrates that standardized, age-based midazolam dosing is both safe and more effective than current practice, the potential impact of this study is a paradigm shift in the treatment of pediatric seizures that can be easily implemented in emergency medical services (EMS) systems across the country.

NIH Research Projects · FY 2025 · 2021-08

Racial/ethnic disparities in the quality of care provided to mothers and infants during the birth hospitalizations result directly in avoidable death and morbidity. Asian American and Pacific Islanders (AAPI) represent the fastest growing racial/ethnic group (25% living in California) and they experience significant disparities in several areas that are robust and merit policy and clinical attention. Unfortunately, research of AAPI populations suffers considerable limitations. First, few studies report on AAPI populations and those that do, usually aggregate to “Asian” or “Asian American and Pacific Islander”, masking the biological and sociocultural heterogeneity. Sec- ond, sociodemographic and neighborhood factors are rarely available for studies of hospital quality at childbirth. Third, lack of multilevel adjustment undermines the validity of comparative assessments of quality by penalizing hospitals that care for vulnerable populations. To understand disparities in care processes and outcomes for AAPI mother/infants, we will undertake a compre- hensive appraisal of the multilevel factors associated with quality of care during the birth hospitalization, promote fairer comparisons by making sociodemographic and neighborhood influences explicit; and assess key areas of quality using key performance metrics for care provided to mothers, low-risk newborns, and infants born very low-birth-weight (VLBW; <1500g). Innovative methods include leveraging our unique multilevel data sources to provide comprehensive assess- ments of hospital quality for AAPI populations with unprecedented granularity, assessing quality via key indi- vidual and composite measures, and using a mixed-methods approach to provide unique insights into the mechanisms by which sociocultural and neighborhood factors optimize or degrade quality. Specific aims: 1) Test for disparities in care processes and outcomes among AAPI mothers and infants and identify associations with patient and neighborhood level social risk factors; 2) Assess the impact of hospital performance on care processes and outcomes of AAPI maternal/infant popula- tions; and 3) Understand the birth and birth hospitalization experiences of AAPI populations alongside drivers of disparities in care processes and outcomes. An exceptional strength of our proposal is our ability to leverage the unique infrastructure of the California Peri- natal and Maternal Quality Care Collaboratives. Building on our prior work in linking complimentary high-quality clinical, administrative, and survey-based data sets containing multi-level factors, we will study a large popula- tion-scale AAPI sample of 1.6 million mothers and newborns (including ~8,000 VLBW infants) in 238 maternity hospitals and 138 neonatal intensive care units in California between 2011-23. Results of this proposal are expected to have an immediate positive impact because in leveraging our expertise as active quality improve- ment organizations, they are designed to identify pragmatic areas where hospitals and communities can improve.

NIH Research Projects · FY 2024 · 2021-08

Project Summary Pulmonary embolism (PE) is a leading cause of death in the United States. Risk stratification for acute PE treatment can reduce mortality. Risk scoring systems use clinical and laboratory electronic medical record (EMR) data. In addition, biomarkers on computed tomography imaging can identify which patients with PE are at high risk of death, independent of clinical data. Despite advances in clinical and image-driven scoring systems, improving outcomes in acute PE depends on implementation of patient-specific EMR and imaging data analytic prognostic models at the point of care. The promise of digital medicine stems in part from the hope that by digitizing health data, we can leverage computer information systems to understand and improve care. A method that can make use of these data to predict patient-specific outcomes could not only provide major benefits for patient safety and healthcare quality but also reduce healthcare costs. Unfortunately, most of this information is not yet included in predictive statistical models that clinicians use to improve care delivery. This is because traditional computational methods and techniques are insufficient at accurately analyzing such high volumes of heterogeneous data. The goal of this proposal is to develop an automated precision medicine approach to achieve point-of-care risk stratification for PE patient outcomes using a fusion deep learning strategy that can simultaneously analyze health records and imaging data. An ideal PE risk-scoring system would not only predict mortality, but also assess the risk for the many debilitating long-term consequences of acute PE. Such a system would, therefore, facilitate optimal management and would likely require intelligent use of clinical, laboratory, and imaging data together in order to provide accurate patient -specific risk scoring for multiple PE outcome measures. In order to build a robust model, we propose to apply distributed training of deep learning models across four large US healthcare institutions. By distributing the algorithm rather than the data, we avoid sharing individually identifiable patient information. If successful, this project will be the first endeavor to leverage diagnostic imaging (pixel) data in combination with structured and unstructured EMR data to predict outcomes. We have the ideal research team, experience, and methods to develop an automated risk-scoring system for acute PE patients. Using a powerful combination of clinical, laboratory, and imaging data, this system will provide patient-specific risk scoring for multiple PE outcome measures. Further, this project will foster multi- center collaborations, which will afford us the opportunity to investigate the generalizability of our approach to different populations of PE patients and to train, test, and ultimately deploy our automated predictive model in a variety of clinical environments.

NIH Research Projects · FY 2026 · 2021-08

PROJECT SUMMARY . Acute ischemic stroke is the leading cause of disability in the United States and the second-leading cause of death worldwide. AIS that involves a major cervical or cerebral artery is termed a large vessel occlusion, and recent landmark randomized studies found that endovascular thrombectomy is an effective treatment for ischemic stroke caused by large vessel occlusion of the internal carotid, middle, or anterior cerebral arteries (anterior circulation). However, up to 15% of large vessel occlusions occur in the vertebral or basilar arteries, and these posterior circulation stroke patients were largely excluded from modern endovascular thrombectomy trials. Clinical outcomes in patients with vertebral or basilar artery occlusions are often poor with severe disability or death occurring in 30-54% and 36-86% of patients, respectively. There are no prospective or randomized data designed to determine which imaging strategies should be used to guide thrombectomy treatment decisions in this understudied population. PRECISE (PeRfusion imaging to identify postErior CIrculation candidateS for thrombEctomy) is a prospective cohort study of patients with acute ischemic stroke due to occlusion of the vertebral or basilar artery within 24- hours of symptom onset. Patients will undergo CT or MRI cerebral perfusion imaging prior to endovascular thrombectomy treatment. The results of this study will determine if cerebral perfusion imaging can identify a subset of patients who are most likely to have a favorable outcome after thrombectomy treatment. PRECISE has the potential to improve the imaging evaluation of patients with acute ischemic stroke of the posterior circulation, to provide valuable prognostic information regarding thrombectomy efficacy in these patients, and to define sub-groups of patients who might benefit from future neuroprotective strategies.

NIH Research Projects · FY 2025 · 2021-07

Project Summary The Research Domain Criteria (RDoC) applies an integrative, dimensional approach anchored in circuit neuroscience, genes, molecules, and behaviors. The RDoC framework, currently only for research, ultimately aims at facilitating the development of psychiatric nosology (disorder-classification system) based upon primary behavioral functions and their associated biological features that the brain has evolved to carry out. Although the impetus behind RDoC is in the right direction, for greater efficacy of RDoC in clinical translation, a data-driven examination is needed to validate and refine the architecture of RDoC. Further, several key questions remain unanswered. First, as noted in the current RFA (RFA-MH-19-242), since the inception of RDoC, a thorough data-driven validation that broadly explores, compares, and validates the constructs within the framework has not been performed. Second, to increase clinical translation of the RDoC framework, it is essential to assess whether constructs within a domain consistently relate to similar dimensions of psychopathology. Thus, providing data-driven evidence for the convergent and discriminant validity of the RDoC framework in predicting psychopathology. Lastly, and perhaps more fundamentally, it is unclear whether carefully crafted behavioral paradigms are required to examine domain-specific features (behavioral or circuit- level) or task-free paradigms (e.g., resting-state) can be computationally employed to extract similar domain- specific features. The lack of task instructions in resting-state paradigms enhances compliance in clinical populations, makes data aggregation across sites straightforward, and could provide a higher cost-benefit ratio if a single resting-state scan can provide information that would otherwise require multiple, carefully crafted, domain-specific neuroimaging task scans. Here, we propose to mine, systemically and computationally, three large-scale datasets from the general population and diagnosed patient populations to answer critical questions regarding the validity of the RDoC framework. Specifically, we aim to examine whether: (1) within- domain constructs overlap more than do between-domain constructs; (2) within-domain constructs relate to similar dimensions of psychopathology; and (3) task-free paradigms (e.g., resting-state) can be mined to extract similar domain-specific information that is usually extracted using specific task-based paradigms. By addressing these three key questions, our central goal is to provide the much-needed bottom-up examination of the RDoC framework to pave a pathway for its refinement and translation. Our long-term goal is to develop new computational frameworks to generate converging insights for grounding psychiatric nosology in biological features. Altogether, without careful data-driven validation, the RDoC framework remains theoretical. Hence, we advocate for developing a computational backbone for the RDoC framework to validate the assumptions underlying RDoC and facilitate framework refinement for greater clinical translation.

NIH Research Projects · FY 2025 · 2021-07

Abstract Chronic musculoskeletal (MSK) pain affects the lives of over a quarter of youth, with societal costs exceeding $19.5 billion dollars in the U.S. each year. The impact of chronic MSK pain in adolescence is felt into adulthood and is a documented risk for opioid misuse. There are a number of efficacious behavioral interventions for adolescents with chronic pain, but many access-to-care barriers exist, highlighting the critical need to develop digitally delivered behavioral interventions to drastically increase reach. Graded exposure is a theory- driven, individually-tailored intervention for individuals with chronic pain targeting pain-related impairment by exposing patients to previously feared and avoided activities. This project seeks to develop and evaluate the feasibility and preliminary effectiveness of a digital exposure treatment (iGET Living) for adolescents with chronic musculoskeletal (MSK) pain and their parents, utilizing a sequential replicated and randomized single-case experimental design (SCED) and incorporating innovative technology for remote biomechanical assessment. The central hypothesis is iGET Living will be acceptable and feasible for youth with chronic MSK pain and their parents and will be effective at alleviating functional disability and pain-related distress. Agile research methods will allow for a rapid, iterative development and evaluation of the intervention, yielding a clinically useful solution. This proposal includes a comprehensive training plan under the guidance of mentors with expertise across study aims. Dr. Harrison will obtain specialized training in 1) user-centered design and agile development of digital interventions, 2) clinical research and trial execution, 3) intervention optimization, dissemination, and implementation science, 4) innovative, remote assessment of biomechanical function, 5) advanced qualitative and quantitative statistics, and 6) experiential learning in grant-writing. Research: Aim 1: In an iterative, user- experience design process, Dr. Harrison and her team will develop iGET Living for adolescents with chronic MSK pain and their parents. Data regarding comprehensiveness and acceptability will be collected via interviews with patients and parents. Clinicians specialized in pediatric chronic pain will provide feedback on how providers might integrate into practice, who they would refer, and potential barriers to utilization. Aim 2: Dr. Harrison will evaluate preliminary feasibility and effectiveness of iGET Living to reduce pain-related distress and functional disability utilizing SCED with multiple measures. Successful completion of these aims will provide the opportunity to rapidly evaluate treatment effectiveness and inform iterative development of iGET Living to prepare subsequent RCTs. The strong mentorship team, specialized career development training, and proposed research plan will allow Dr. Harrison to gain the expertise needed to seek R-level funding and achieve her long- term career goal of becoming an independent clinician-scientist with expertise in developing digital interventions for youth with chronic pain and their parents.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY This proposal aims to determine how cell growth triggers cell division, which is a fundamental question in cell and developmental biology. Its understanding will also greatly impact our knowledge of cancer, where this process is misregulated. It has long been known that cell growth triggers human cell division at the G1/S transition before DNA is replicated. But, although many key regulatory proteins linking cell growth to cell division are known, the molecular mechanisms mammalian cells use to control their size have remained poorly understood and have been based solely on the study of cells growing in culture. My laboratory recently made a breakthrough advance in understanding how growth triggers division. Contrary to expectations that growth would increase Cyclin D-Cdk4,6 activity, we found instead that cell growth dilutes the cell cycle inhibitor Rb to trigger division in cultured cells. Our discovery of the Rb dilution mechanism in cell culture raises three key questions which are the focus of this grant: 1. What is the molecular mechanism regulating Rb’s concentration dynamics that control cell size? 2. What is the function of Rb-based cell size control? 3. Do Rb dilution or other cell size control mechanisms link cell growth to cell division in vivo. We have begun to address the first question and our preliminary data indicate that the mechanism regulating the size-dependence of Rb concentration is translational. To further determine how this molecular mechanism works we will take an approach using reporters to identify the DNA-sequence element responsible and then the corresponding proteins regulating its function. To address the second question, we will take a mass spectrometry-based approach to measure how protein concentrations change with cell size across the proteome. Preliminary data indicate that proteins associated with senescence phenotypes increase in concentration in large cells. This suggests that cell size may be causal for senescence and cell size control functions to avoid this deleterious outcome. To address the final question to definitively test the Rb dilution and alternative models, we will perform a series of in vivo experiments. This is important because recent studies in cell culture have reported conflicting results about how animal cells control their size. To determine how animal cell growth triggers cell division in vivo, we propose to examine the mouse epidermis because it has a large population of proliferating stem cells whose division dynamics can be assayed using live- cell imaging. We will measure changes in keratinocyte cell size in a series of mouse lines in which the Rb family of genes has been conditionally deleted or over-expressed in the mouse epidermis. This will test our central hypothesis that Rb1 is crucial for cell size control in vivo. We will also use mouse genetics to test the alternative hypothesis that the p38 stress activated protein kinase controls cell size. Taken together, successful completion of these aims will have a big impact on understanding how cell growth triggers cell division. This is important because it allows cells to control their size, which is fundamental to cell physiology.

NIH Research Projects · FY 2026 · 2021-07

ABSTRACT Rapid advances in genomics have ushered in new opportunities for Mendelian disease discovery and diagnosis. In the last decade, exome and genome sequencing have moved from the research domain to clinical practice. These approaches have identified new disease genes and causative variants for ~30% of individuals suffering from a rare genetic disease. We believe that the systematic application of promising new genomics assays coupled with innovative computational approaches will foster discovery benefitting the 70% of symptomatic individuals without a genetic diagnosis. To this end we will apply long-read whole genome sequencing, RNA-sequencing, epigenomics assays, metabolomics and targeted in vitro and in vivo assays to evaluate a cohort of undiagnosed individuals suspected to have a Mendelian disorder. Our approach will be augmented through the development and application of computational strategies enabling improved gene and phenotype matching, integrative multi-omics analysis, and variant interpretation. This work is expected to establish a new frontier in Mendelian disease discovery. Our Mendelian Genomics Research Center (MRGC) team has developed key prior expertise and leadership in the use of diverse state-of-the-art experimental and computational methods for the diagnosis and discovery of Mendelian disorders. We hypothesize that the next phase of Mendelian genomics research will be defined by assessing and deploying the most effective `omics' strategies. We propose that ongoing and iterative integration of functional genomics data into the translational genomics toolkit will significantly increase discovery of new gene and variant disease associations beyond the capabilities of DNA-sequencing assays alone. To facilitate this, we will comprehensively study 400 individuals and their immediate family members (N= 900 total) with Mendelian disease where exome sequencing has not yielded a genetic diagnosis. These represent a select cohort of hard to solve cases intractable to DNA sequencing to date. In Aim 1, individuals recruited into the study will undergo short-read and long-read whole genome sequencing, RNA-seq, ATAC-seq and MethylC-seq across multiple commonly used cell/tissue types as well as metabolomics and lipidomics assays. This dataset will define a holistic view of emerging genomics approaches for Mendelian disease diagnosis and facilitate evaluation of the relative merits of each approach. In Aim 2, we focus on computational innovations that will improve integration of these multi-omics data in gene and variant interpretation by integrating functional genomics outliers and advanced statistical learning approaches. These methods will be applicable broadly across the MGRC and the world. In Aim 3, we apply state-of-the-art targeted approaches including massively-parallel reporter assays, induced-pluripotent stem cell functional genomics, CRISPR screens for modifier genes and engineered mouse models to detect and validate novel causal variants and genes. Work at our site will potentiate the broad impact of the MGRC by providing a platform for functional genomics research, validation and diagnosis in Mendelian disease.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY/ABSTRACT Malaria continues to result in more than 400,000 deaths annually, mainly in young African children. Effective immunity to malaria develops in endemic populations, but only after many repeated infections. Intermittent preventive treatment in pregnancy (IPTp) and childhood (IPTc) have emerged as strategies to decrease childhood morbidity and mortality, but there is concern that preventing malaria exposure early in life will delay the development of antimalarial immunity. However, data from our group suggests that interventions that selectively block the blood stage of malaria infection during this critical time may actually enhance antimalarial immunity. In this proposal, we will test the hypothesis that preventing blood-stage malaria antigenic exposure in utero and in young children with IPT enhances protective immunity to malaria by limiting malaria-induced immunoregulatory mechanisms. To test this hypothesis, we will take advantage of a unique opportunity to study children born to mothers enrolled in a funded clinical trial of different IPTp regimens in an area of eastern Uganda with very high malaria transmission intensity. In this parent study, 2757 pregnant women will be randomized to receive IPTp with sulfadoxine-pyrimethamine (SP, the poorly effective, current standard of care), the highly effective drug dihydroartemisinin-piperaquine (DP), or both SP+DP. We will leverage this parent study to enroll a birth cohort of 924 children who will be randomized at birth to receive no IPTc, IPTc with monthly DP to 1 year of age, or IPTc with monthly DP to 2 years of age. Children will be followed up to 4 years of age. This unique study design will allow us to determine whether effective prevention of blood-stage malaria exposure with DP-based IPT both in pregnancy and in infancy has lasting benefits for young children compared with the current standard of care. Our specific aims will be (1) to compare the incidence of malaria from birth up to 4 years of age among children born to mothers randomized to receive monthly IPTp with SP, DP, or DP+SP, (2) To compare the incidence of malaria from 2 up to 4 years of age among children randomized to receive no IPTc in infancy, monthly DP for the first year of life, or monthly DP for the first two years of life, and (3) To determine whether prevention of malaria with effective IPT leads to lower regulatory responses and enhanced innate and adaptive immune responses. By determining whether effective prevention of malaria with IPT during pregnancy and infancy leads to long-term, lasting benefits on infant health, this study could critically inform policy guidelines, including extending the use of IPT to settings where malaria transmission is year-round. These studies will also significantly improve our understanding of how preventing malaria early in life affects infant immune development and the acquisition of antimalarial immunity.

NIH Research Projects · FY 2025 · 2021-07

Project Summary Neuropsychiatric disorders are the single greatest cause of disability due to non-communicable disease worldwide, accounting for 14% of the global burden of disease. The current standards of care suffer from subjectivity, inconsistent delivery, and limited access with growing waitlists. New informatics solutions, in particular artificial intelligence (AI) that can port to more ubiquitous mobile health devices and that are not restricted for use in clinical settings, have great potential to complement or even replace aspects of the standards of care. We propose to develop a novel informatics solution for one of the most pressing mental health burdens, autism, which is up in incidence by more than 600% since 1990, among the fastest growing pediatric concerns today, and highly representative of many other neuropsychiatric conditions. We have invented a prototype mobile system called Guess What (guesswhat.stanford.edu) (GW) that turns the focus of the camera on the child through a fluid social engagement with his/her social partner that reinforces prosocial learning while simultaneously measuring the child’s developmental learning progress. At its simplest level, the GW app challenges the child to imitate social and emotion-centric prompts shown on the screen of a smartphone held just above the eyes of the individual with whom the child is playing. But more, as a home-based repeat-use system, GW uses computer vision algorithms and emotion classifiers integrated into gameplay to detect emotion in the child’s face via the phone’s front camera, automatically finding agreement with the displayed prompt, while capturing features such as gaze, eye contact, and joint attention. Preliminary work with more than 20 autistic children resulted in positive user feedback, evidence of high engagement for both the parents and children, and importantly, evidence of clinically meaningful gains in socialization. A single session produces 90 seconds of enriched social video and sensor data, opening up an exciting opportunity for the game play itself to passively generate labeled computer vision libraries that enable the development of better models with higher diagnostic precision going forward. Our proposed project will show that GW can (a.) serve as a mobile therapy that can be used repeatedly by families to target core deficits of autism while inherently tracking progress during use, and, (b.) serve as a distributed system to crowdsource the acquisition of new labeled image libraries for AI models that can automatically classify diagnostic features relevant to autism and extend to other sectors of mental health (and even beyond).

NIH Research Projects · FY 2025 · 2021-07

The mission of the Stanford Biophysics Program is to develop students with strong, interdisciplinary, quantitative approaches to meaningful biological problems, while establishing a rigorous atmosphere of high research conduct and ethics. To meet these goals, trainees participate in coursework, mentored primary research, and other activities designed to enhance their training; together these opportunities prepare graduates for the next step in their careers as part of the STEM workforce. The Program requires graduate-level coursework in physical and biological sciences, participation in seminar series and the retreat, and the development of a high level of proficiency in independent research. Faculty in this interdepartmental predoctoral training program come from >20 departments in the Schools of Humanities and Sciences, Medicine, Engineering, and the Stanford Synchrotron Radiation Laboratory. Student training and research centers on the application of physical and chemical principles and methods to biological problems, as well as the development of new methods. The quantitative relationship between molecular properties and higher-level cell/tissue properties is an increasing focus of the Program, as are emerging areas of quantitative cell and organ biology. Overall, this training program capitalizes on student backgrounds and interests in the physical sciences while fostering creative, collaborative, highly skilled approaches that span biological scales. Trainees are appointed upon admission to Stanford for up to 2 years; the 12 requested slots will generate class sizes of 8-10 through university and externally funded fellowships. The program currently has 70 students across all cohorts, with undergraduate backgrounds spanning physical science, biochemistry, and engineering. To maximize trainee retention, first-year advising by the Program Director and annual meetings with each student’s thesis committee ensure that a balanced academic program is tailored to the background of each student and that an acceptable level of performance is maintained. Required IDP meetings with the advisor ensure career development and RCR/R&R instruction; the latter is also provided through required coursework including a Statistics class and a variety of elective offerings. Students are heavily involved in program activities, establishing a cohesive community; the Program benefits from high levels of University support and engagement. The fundamental and applied research carried out by our trainees is the cornerstone for developing drugs targeted to specific molecules, for understanding the relationships between environmental stimuli and cell and tissue behavior, and for developing new methods for detecting and treating diseases including cancer and neurological pathologies.

NIH Research Projects · FY 2025 · 2021-07

This application seeks funding for 10 trainees within the Sarafan ChEM-H Chemistry-Biology Interface (CBI) predoctoral training program at Stanford University, aligned with the mission of the Sarafan ChEM-H institute. Sarafan ChEM-H was formed with the mission of bringing chemists, biologists, engineers and clinicians together to pursue a molecular level understanding of the principles underlying human health and to devise innovative disease interventions. The program’s primary mission is to cultivate interactions, thinking, and communication across the chemistry biology interface to enable innovations in the study and advancement of human health. The CBI Training Program will provide PhD students with an enriching community of peers and mentors from the Schools of Humanities and Sciences, of Engineering, and of Medicine. Graduate students in the program will be recruited from six PhD granting programs: Chemistry, Chemical Engineering, Chemical & Systems Biology, Biochemistry, Biology and Bioengineering. Appointed trainees are supported by the CBI Training Program for 2 years, usually the first- and second-year of graduate study. Mentors are affiliated across many departments and programs, including practicing physician scientists. Key components of the program are the incorporation of students during the first year of graduate study, first-year laboratory rotations, coursework in chemical biology, instruction in the responsible conduct of research and enhancing reproducibility, student and faculty seminars, and career development activities. Professional development activities include a career panel, conference presentations, communication training for outreach, and an annual retreat. Students will also receive instruction on developing strategies to translate molecular findings to humans. Anticipated trainee outcomes are peer-reviewed publications at the chemistry biology interface, conference presentations, receipt of external funding, and retention within the biomedical research workforce in a variety of academic and non-academic positions. Students trained in this program will be exposed to a wide range of scientific concepts and techniques, meet a variety of experts across the physical, life and medical sciences, and be uniquely situated to tackle challenges in human health from a molecular level perspective.

NIH Research Projects · FY 2025 · 2021-07

Project Summary/Abstract Colorectal cancer (CRC) is the second leading cause of cancer mortality in the United States, and obesity, which affects 40% of the population, not only increases the risk of developing CRC, but also increases CRC mortality through unknown mechanisms. Our preliminary studies demonstrate that CRC grows faster in mice rendered obese through a high fat diet (HFD), and that the tumor associated macrophages (TAMs) in these mice exhibit higher expression of the acid sensing receptor, GPR65, which is known to dampen the immune response. Moreover, in HFD-induced obese mice lacking GRP65, TAMs secrete more TNF-α and tumor growth is retarded. Given that TAMs but not normal tissue macrophages of obese mice exhibit increased GPR65, we examined the pH of the tumors in these mice and found them to be more acidic. On the basis of these findings, we hypothesize that excess lipids in the HFD alter tumor cell metabolism resulting in increased acid production, which potentiates GPR65 expression and signaling in TAMs, causing them to become immunosuppressive and promote tumor growth. To test this hypothesis we will pursue the following specific aims: 1) Determine the contribution of GPR65 signaling to TAM function and CRC growth under conditions of obesity by determining if the cAMP- PKA signaling axis, which functions downstream of GPR65, is activated in TAMs of obese mice and controls TNF-α production. We will also analyze GPR65 expression and the cytokine secretion capacity of macrophages from healthy blood donors and TAMs in CRC samples from non-obese and obese patients; 2) Identify the mechanism by which HFD promotes GPR65 signaling in CRC TAMs by testing the ability of HFD and oleic acid, a dietary triglyceride that is highly enriched in HFD tumors, to alter the oxidative potential, fatty acid oxidation capacity and acid production of human tumor cells via flow cytometry, CyTOF and Seahorse assays. We will also determine if a high-oleic-acid diet is sufficient to modify GPR65 expression and cytokine production by TAMs, and examine if tumor acidity is required for the blunted inflammatory response of TAMs; and verify the role of GPR65 in human macrophages and 3) Assess the effects of targeting GPR65 for tumor immunotherapy in obese and nonobese mice with CRC and other tumor types, namely hepatocellular carcinoma and melanoma, and assess the effects of checkpoint blocking antibodies on tumor growth and anti- tumor immunity in GPR65+ and GPR-/- mice bearing these tumors. The results of these studies are expected to not only reveal a critical mechanism responsible for accelerated tumor growth in the setting of obesity, but also identify a novel target for the treatment of these cancers.

NIH Research Projects · FY 2025 · 2021-07

Neural circuits are constructed by synapses that connect neurons into vast networks. Although many neural circuits have been characterized, the molecular and cellular mechanisms that build their synaptic architecture remain largely unknown. During synapse formation that establishes the synaptic architecture of neural circuits, bi-directional signaling via trans-synaptic adhesion molecules is thought to control assembly of synapses. Strikingly, genetic changes in trans-synaptic adhesion molecules often predispose to neuropsychiatric disorders, suggesting that dysfunction of the synaptic architecture of neural circuits contributes to neuropsychiatric disorders, although the nature of these impairments is poorly understood. Our preliminary data show that in hippocampal neurons, formation of subsets of excitatory synapses requires latrophilins (Lphns), a family of three postsynaptic adhesion-GPCRs. Different Lphns mediate establishment of distinct synapses even in the same neuron, suggesting that they are involved not only in constructing synapses, but also in determining their specificity. How Lphns mediate synapse formation, and to what extent their synapse-formation function involves GPCR signaling or adhesive interactions, remains unknown. Moreover, SNPs in the human Lphn3 gene (ADGRL3) downregulate Lphn3 expression robustly. The present application proposes to examine the signaling mechanisms that mediate Lphn-dependent synapse formation, to explore how Lphns determine synapse specificity, and to investigate how changes in Lphn3 expression change synaptic function. Specifically, the proposed experiments will test the overall hypotheses that (1) Lphns control synapse formation and maintenance by a GPCR-mediated mechanism involving locally restricted signaling, that (2) different Lphn isoforms control formation of distinct synapses via sequence-specific differences in their protein interactions and GPCR function, and that (3) changes in Lphn3 expression impair formation of a specific subset of synapses. Three Specific Aims will test these hypotheses, thus targeting key questions that are most relevant for understanding how neural circuits are wired and how impairment of neural circuits alter cognition. Using both mouse and human neurons as a model system, the project will pursue broadly interdisciplinary approaches in both mice and human neurons that range from biophysical studies of ligand-receptor complexes to cell-biological investigations of intracellular signaling to behavioral studies probing for cognitive changes. Thereby, this application will provide insight into how Lphns drive synapse formation in mice, and how decreased expression of Lphn3 predisposes to synaptic changes in human neurons. Addressing these questions is of paramount interest in basic and translational neuroscience because neural circuits that process the brain’s information are constructed by synapse formation, and dysfunction or imbalance of synaptic communication in neural circuits likely underlies the pathogenesis of neuropsychiatric disorders.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY We seek renewal of our predoctoral biotechnology training program, which has as trained more than 150 outstanding predoctoral students who have gone on to successful careers in academia, industry, government, and non-profit sectors. Our mission is to unite engineering, medicine, and the basic sciences into a cohesive, application-driven training environment that prepares trainees to become leaders in the rapidly evolving biotechnology field, and shape new efforts using biotechnology for prevention, diagnosis, and treatment of disease. Stanford provides an unusually rich environment, with colocated, nationally ranked schools devoted to basic science, engineering, and medicine, and a strong industrial presence from the surrounding Bay Area. We are leveraging this ecosystem to train talented pre-doctoral students who are becoming the next-generation of interdisciplinary global biotechnology innovators, and who will lead and invent the future with integrity and rigor. We are seeking training funding for 6 trainees per year for a period of 5 years. The program fuses faculty mentors and trainees from three schools across the University into a highly visible program that delivers a unique, applications oriented training experience focused on health-related biotechnology. Differentiating features of this program include full time industrial internships, quarterly field trips, deep interactions among trainees and academic and industrial mentors, and a focus in trainings that foster biotechnology innovation and leadership.

NIH Research Projects · FY 2026 · 2021-07

PROJECT SUMMARY / ABSTRACT OpenMM is a widely used toolkit for molecular simulation and modeling (>1.5 million downloads, >2400 citations, >1M deployed instances). Its Python API makes it widely popular as both an application (for modelers) and a library (for developers), while its C/C++/Fortran bindings enable major legacy simulation packages to use OpenMM to provide high performance on modern hardware. OpenMM has been used for probing biological questions that leverage the $20B global investment in structural data from the PDB at multiple scales, from detailed studies of single disease proteins to superfamily-wide modeling studies and large-scale drug development efforts in industry and academia. In addition to having a very large user base, OpenMM is an essential component of many high-impact projects, such as AlphaFold2 and Folding@home. The first period of this grant enabled OpenMM to transition toward a community governance and sustainable development model, build a highly popular quantum chemical dataset that has enabled the community to build accurate machine learning (ML) potentials that deliver QM-level accuracy, and integrate support for fast GPU-accelerated protein:ligand simulations that make use of these ML potentials but can still achieve fast near-molecular mechanics (MM) speeds. In the next period, we propose to build on these successes to generate much more extensive datasets, integrate multiple other ML potentials to greatly expand the application domain they can be used for, and further accelerate and parallelize these simulations. We also aim to integrate key methodological improvements to improve accuracy for drug discovery applications. To be maximally responsive to the continually growing needs of the large OpenMM user community, we also aim to onboard a new developer focused on implementing community-requested features. To ensure OpenMM remains highly relevant to the modern machine learning revolution, we will continue to expand the ability of OpenMM to interoperate with modern ML frameworks such as TensorFlow, PyTorch, and JAX.

NIH Research Projects · FY 2025 · 2021-07

Pharmacology is at a crossroads. Although technological advances in chemistry and biology have transformed drug discovery, our ability to develop new therapeutics has lagged behind our clinical needs. This gap reflects a disconnect between basic science discovery and translational research, and addressing this challenge will require scientists who can bridge these two areas. Toward this goal, the Stanford Molecular Pharmacology Training Program (MPTP) aims to empower predoctoral students across the biosciences with specialized training in drug discovery and development. The MPTP is founded on the rich history of pharmacology research and education at Stanford, and it now transcends conventional academic boundaries. Our training program draws upon an outstanding group of 26 highly collaborative Stanford faculty from multiple departments, and it builds upon the strength of SPARK, a translational research initiative that was created at Stanford in 2006. In addition to their independent research with MPTP faculty, our trainees receive formal course work in drug discovery, and they attend weekly presentations by SPARK-affiliated experts in pharma/biotech, patent law, venture capital, clinical medicine, and other areas related to therapeutic development. MPTP students also participate in summer biotech internships and clinical shadowing opportunities, supplementing their academic training with industrial and clinical experiences. These training activities are integrated with courses on the responsible conduct of research, rigor, and reproducibility, weekly student/faculty research forums, annual retreats, grant writing and science communication workshops, and outreach opportunities. Our predoctoral students are also encouraged to propose translational projects, which are reviewed and funded by SPARK on a competitive basis. These team-based projects provide hands- on, real-world experience in therapeutic development and direct interactions with industry veterans and experts. Our program carefully tracks student research progress, faculty mentorship, and program effectiveness to enable the MPTP to continually evolve to meet its educational mission. To train scientific leaders and innovators who will impact communities throughout the United States, we have also established recruitment and retention strategies to foster student diversity, leveraging Stanford resources and mobilizing the MPTP community. Through its innovative curriculum and partnerships with SPARK and industry, the MPTP will impart its students with rigorous training in basic science and an understanding of drug discovery and development. Graduates of our training program will be uniquely able to translate fundamental discoveries into clinical advances, and they will be well- positioned to become scientific leaders in academia, industry, government, and other sectors.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY Aging is the single greatest cause of disease and death worldwide, and rejuvenating the body by targeting biological aging processes therefore holds potential to simultaneously prevent multiple chronic diseases like cancer, heart disease, dementia, and diabetes. While decades of research has unveiled common hallmarks of aging, like mitochondrial dysfunction, inflammation, and loss of proteostasis, therapies targeting these hallmarks have elicited only modest rejuvenation in animal models. This may be in part because most aging studies have focused on only one or a few organs or cell types, with little to no temporal resolution, limiting our ability to interpret how and when aging impacts these interconnected systems. Recently, however, we have attempted such a systematic characterization of aging. Using bulk RNA-sequencing (RNA-seq) and single-cell RNA- sequencing (scRNA-seq) on dozens of mouse organs and cell types across the lifespan (termed Tabula Muris Senis), we discovered global and specific aging signatures throughout the body. But it remains unknown how, or if, rejuvenation paradigms affect these global aging pathways, or rather instigate nascent biochemical programs. The rational design of new therapeutics is therefore challenging. One method of rejuvenation which has garnered beneficial effects across organ systems is heterochronic parabiosis, in which a young and old mouse share a common circulation. Phenotypes like cognition, muscle strength, and bone repair have all shown functional improvement through exposure to young blood. Parabiosis research has largely focused on age-related changes to circulating proteins, and several have been determined to mediate at least some of the observed effects. However, such individual factors have yet to achieve robust rejuvenation throughout the body, likely in part due to an incomplete understanding of the effects of parabiosis on disparate organs and cells. Using our newly created Tabula Muris Senis data to represent normal aging, we investigated scRNA-seq changes in 3 tissues following parabiosis: gonadal and mesenteric adipose tissues, which undergo age-related gene expression changes prior to other organs, and liver, as hepatocytes were one of the first cell types observed to benefit from exposure to a young circulatory system. Interestingly, individual cell types vary greatly in their response to parabiosis, with vascular endothelial cells from all 3 tissues showing prominent transcriptomic changes consistent with normal aging genes. It is our hope that by expanding this analysis to scRNA-seq of 9 tissues, and to bulk RNA-seq of 21 tissues, we can discover signatures that will serve as the basis for identifying small molecules capable of robust rejuvenation and healthspan extension. As surgically intensive parabiosis is confounded by cell trafficking and simultaneous exposure to young and aged circulating factors, we further propose to compare parabiosis signatures to those derived from young plasma transfer, thereby uncovering aspects of rejuvenation specifically sensitive to alterations in plasma factors. Similar to our earlier datasets, all data will be made publically available.

NIH Research Projects · FY 2025 · 2021-07

ABSTRACT Lung cancer is a prevalent cancer type that leads to more deaths than the next four major cancer types combined. KRAS is one of the most frequent oncogenes in human lung cancer. Despite more than 30 years of biochemical and cell culture studies, as well as correlative studies on human tumors and clinical trials, therapeutic options for patients with oncogenic KRAS-driven tumors are just beginning to emerge. KRAS is often mutated at codons 12 and 13, but these mutations are diverse and these different mutant forms of KRAS have dramatically different biochemical features. By integrating conventional genetically-engineered mouse models and CRISPR/Cas9-based somatic genome engineering with quantitative genomics and mathematical modeling, we recently established CRISPR/Cas9-based approaches that enable the generation and quantitative analysis of multiple tumor genotypes in parallel in vivo. By employing homology directed repair in somatic cells, we induce a panel of oncogenic Kras variants, and uncovered an unexpectedly dramatic difference in oncogenic potential of different Kras variants in vivo. In addition to the diversity of different oncogenic KRAS variants, the compendium of important pathways downstream of oncogenic KRAS remains relatively poorly understood. The goals of this proposal are 1) to use genomic and pharmacological methods to generate a quantitative understanding of different signaling requirements in cancers driven by different Kras variants and 2) to uncover novel functional regulators of Kras-driven carcinogenesis. To understand the basis for the differential oncogenic potential of different oncogenic Kras variants, we will use our multiplexed genetic approaches to quantify the impact of increasing either overall Kras signaling or discrete downstream pathways on the in vivo tumorigenic potential of diverse oncogenic Kras variants. We will also use therapeutic treatments to uncover the requirement for sustained PI3K and Raf/Mek/Erk signaling in established lung tumors driven by diverse Kras variants. Finally, to expand our understanding of Kras-driven tumorigenesis beyond the canonical effect pathways, we will directly analyze the function of novel Kras-interacting proteins on lung tumor growth in vivo. By performing multiplexed genomic and pharmacologic analyses of oncogenic Kras signaling in cancer, we will uncover the molecular mechanisms that contribute to tumor growth driven by different variants of KRAS. We will define specific therapeutic sensitivities of lung tumors driven by diverse oncogenic mutations. Our proposed research is significant because it will uncover interesting new areas of biology, motivate genotype-directed clinical trials, and facilitate precision cancer therapy for lung cancer patients with KRAS- mutant tumors.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY / ABSTRACT Through decades of research, genome-wide association studies (GWAS) have identified heritable coding and noncoding single-nucleotide polymorphisms (SNPs) that lead to an increased risk of developing Alzheimer's disease (AD). However, the vast majority of these SNPs remain largely under-characterized, and their contribution to AD pathogenesis remains unclear, marking a critical roadblock to our understanding of AD genetics and pathogenesis. While SNPs within the APOE and TREM2 genes have identified vital nodes in AD biology, most AD-related SNPs reside within the noncoding genome, making their functional roles in the disease less clear. Co-inheritance of nearby SNPs (linkage disequilibrium) and the cell type-specificity of noncoding regulatory elements further complicate functional annotation of noncoding SNPs in AD. As part of the Alzheimer's Disease Sequencing Project Functional Genomics Consortium (ADSP FGC), this project will provide a robust and conclusive functional characterization of AD-related noncoding SNPs. To do this, we will first create a comprehensive single-cell atlas of gene expression and chromatin accessibility across a cohort of diverse clinico-pathologic states related to AD (Aim 1). Using these cell type-specific gene regulatory landscapes, we will develop and implement innovative machine learning and statistical genomics methods to predict functional noncoding, splicing, and coding SNPs (Aim 2). We will then validate these predictions using massively parallel reporter assays (MPRAs) and large-scale, scarless, single-base CRISPR editing of iPSCs followed by cell type-specific differentiations (Aim 3). Taken together (Aim 4), this project will pinpoint the functional SNPs and target cell types for dozens of AD-related risk loci and provide an unprecedented picture of the gene regulatory landscape of AD. This work will be performed as a joint collaboration between Stanford University and the Gladstone Institutes at UCSF. Our team, with many long-standing collaborations, has extensive experience in consortium science with long-term involvement in the Encyclopedia of DNA Elements, The Cancer Genome Atlas, and The Genotype-Tissue Expression Project. The proposed project is thus well- positioned to integrate into the highly collaborative ADSP Functional Genomics Consortium.