UCSF

Head and neck squamous cell carcinoma (HNSCC) affects approximately 890,000 patients worldwide each year, primarily as a result of tobacco and alcohol use or infection with high-risk strains of human papillomavirus (HPV). Despite current therapeutic strategies including surgery, radiation, chemotherapy, immunotherapy, and targeted therapy, the mortality rate remains at approximately 50%. HNSCC tumors exhibit significant genetic heterogeneity, characterized by a high frequency of point mutations and somatic copy number alterations (CNAs). While numerous genomic loci affected by CNAs have been identified, their mechanistic contributions to tumorigenesis remain incompletely understood. Early and frequent genetic alterations in HNSCC include the loss of tumor suppressors within the INK4/ARF locus (9p21.3), particularly CDKN2A, in conjunction with TP53 mutations. The INK4/ARF locus contains several genetic elements, with point mutations predominantly targeting p16. However, about one-third of patient tumors exhibit homozygous deletions of the entire region, representing an additional mode of inactivation. In addition to INK4/ARF loss, two of the most commonly deleted loci in HNSCC involve CSMD1 (8p23.2) and LRP1B (2q22.1). Although these genes have been implicated as tumor suppressors in other cancers, their role in HNSCC is unclear. One of the major challenges in studying large-scale chromosomal deletions has been the difficulty of recreating them in an appropriate model system. Here, I describe two different approaches for generating large deletions (~1.7 kb – 1.2 Mb) in primary human keratinocytes using CRISPR/Cas9 via transfection and electroporation. These approaches enabled creating targeted deletions within CSMD1 and LRP1B, as well as performing a functional dissection of the INK4/ARF locus to evaluate the roles of its genetic elements and various gene inactivation mechanisms. My results indicated that CSMD1 and LRP1B deletions were passenger events in the contexts examined, with no clear evidence supporting a pathogenic role in HNSCC tumorigenesis. I propose that alterations in these genes are more likely to represent common fragile sites. Furthermore, analysis of the INK4/ARF locus indicated that p16 was the essential tumor suppressor within this region, with point mutations and deletions exhibiting comparable biological outcomes. Additionally, there was no evidence that other genetic elements within the locus such as the regulatory domain (RD) element, p15, or p14 contribute to HNSCC tumorigenesis. These results have implications for future disease modeling as well as targeting the most critical pathways for therapeutic approaches.

Large-scale scATAC-seq experiments are challenging because of their costs, lengthy protocols, and confounding batch effects. Several sample multiplexing technologies aim to address these challenges, but do not remove batch effects introduced when performing transposition reactions in parallel. We demonstrate that sample-to-sample variability in nuclei-to-Tn5 ratios is a major cause of batch effects and develop MULTI-ATAC, a multiplexing method that pools samples prior to transposition, as a solution. MULTI-ATAC provides high accuracy in sample classification and doublet detection while eliminating batch effects associated with variable nucleus-to-Tn5 ratio. We illustrate the power of MULTI-ATAC by performing a 96-plex multiomic drug assay targeting epigenetic remodelers in a model of primary immune cell activation, uncovering tens of thousands of drug-responsive chromatin regions, cell-type specific effects, and potent differences between matched inhibitors and degraders. MULTI-ATAC therefore enables batch-free and scalable scATAC-seq workflows, providing deeper insights into complex biological processes and potential therapeutic targets.

While large-scale sequencing efforts have focused on the mutational landscape of the coding genome, the vast majority of cancer-associated variants lie within non-coding regions. In the context of tumor progression, these regions may harbor key regulatory drivers, yet an integrated method to discover and interrogate functional regions remains unexplored. In chapter 1, we present an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Applying this framework to sequencing data from a large prostate cancer patient cohort revealed a large set of candidate drivers. We use (i) in silico analyses, (ii) massively parallel reporter assays, and (iii) in vivo CRISPR interference screens to systematically validate mCRPC drivers. One found enhancer region, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. SF3A1 and CCDC157 promote tumor growth in vivo. We nominate a number of transcription factors, notably SOX6, to regulate expression of SF3A1 and CCDC157. Our integrative approach enables the systematic detection of non-coding regulatory regions that drive human cancers. Outside of cis-acting genomic regulatory elements that can play a driving role in driving cancer, the broad reprogramming of the cancer genome leads to the emergence of molecules that are specific to the cancer state. We previously described orphan non-coding RNAs (oncRNAs) as a class of cancer-specific small RNAs with the potential to play functional roles in breast cancer.

progression. Expanding upon this idea, in chapter 2, we report a systematic and comprehensive search to identify, annotate, and characterize cancer-emergent oncRNAs across 32 tumor types. We leverage large-scale in vivo genetic screens in xenografted mice to functionally identify driver oncRNAs in multiple tumor types. We not only discover a large repertoire of oncRNAs, but also find that their presence and absence represent a digital molecular barcode that faithfully captures the types and subtypes of cancer. Importantly, we discover that this molecular barcode is partially accessible from the cell-free space as some oncRNAs are secreted by cancer cells. In a large retrospective study across 192 breast cancer patients, we show that oncRNAs can be reliably detected in the blood and that changes in the cell-free oncRNA burden captures both short-term and long-term clinical outcomes upon completion of a neoadjuvant chemotherapy regimen. Together, our findings establish oncRNAs as an emergent class of cancer-specific non-coding RNAs with potential roles in tumor progression and clinical utility in liquid biopsies, providing the first tumor-naive minimum residual disease monitoring approach for breast cancer.Lastly, we explore the utilization of intrinsic transcriptional noise encoded within the cell as a mechanism of tumor proliferation and resistance in the face of unfamiliar microenvironments. More specifically, intratumoral heterogeneity (ITH) is recognized as a driver of therapeutic resistance and fatal cancer recurrence. ITH occurs at both a genetic and transcriptional level and enables tumor cells to adapt to variable environmental pressures, such as hypoxia, immune surveillance, and targeted molecular therapy. In chapter 3, through integrating in silico analysis of BRCA TCGA-RNA-Seq data, in vivo CRISPRi screens, and in vitro single-cell transcriptomics, we identify RNF8 and MIS18A as drivers of transcriptional heterogeneity. Modulating expression of these two genes impacts cellular fitness, chemotherapeutic sensitivity, and metastatic potential in a proportional manner, underscoring their roles in driving cancer progression. Analysis of human breast cancer patient data reveals that increased expression of

these genes correlates with detrimental survival outcomes. This study expands our understanding of transcriptional regulators of ITH and their potential as therapeutic targets.In summary, this thesis explores broadly how regulatory elements—encompassing enhancers, non-coding RNAs, and chromatin organizers—can drive cancer progression, shape tumor heterogeneity, and offer new avenues for clinical biomarker development and therapeutic intervention.

Computational drug discovery is an active area of biophysics research due to the difficulties in estimating the free energy changes of small molecules binding to proteins. Considering the large search space of drug-like molecules, any estimates of binding must be fast as well as accurate. In this dissertation, I present new tools and models to improve computational drug discovery. The first project (Chapter 2) involves converting an expert-curated hierarchical database into a statistical potential for rapidly evaluating torsion strain in docked ligand poses. The second project concerns better understanding a new mode of ligand binding. New cryogenic electron microscopy (cryo-EM) structures of positron emission tomography (PET) radiotracers bound to protein fibrils show long, symmetric stacks of ligands within the fibrils. We present SymDOCK (Chapter 3) for accurately docking molecules to protein fibrils in symmetric, interacting stacks at a fast enough rate for large-scale docking. To better understand the effects on experimental observables from ligand-ligand interactions and entropy from the number of sites, we derive a new model for symmetric ligand binding to protein fibrils (Chapter 4). We lastly attempt to use our new tools and models to prospectively dock molecules against Alzheimer’s Disease tau fibrils (Chapter 5), where preliminary experimental results show some of our predicted hits do bind to the protein.

The peritoneal cavity (PerC) is an important site for immune responses to infection and cancer metastasis. Yet few ligand–receptor axes are known to preferentially govern immune cell accumulation in this compartment. GPR34 is a lysophosphatidylserine (lysoPS)-responsive receptor that frequently harbors gain-of-function mutations in mucosa-associated B cell lymphoma. Here, we set out to test the impact of a GPR34 knock-in (KI) allele in the B-lineage. We report that GPR34 KI promotes the PerC accumulation of plasma cells (PC) and memory B cells (MemB). These KI cells migrate robustly to lysoPS ex vivo, and the KI allele synergizes with a Bcl2 transgene to promote MemB but not PC accumulation. Gene expression and labeling studies reveal that GPR34 KI enhances PerC MemB proliferation. Both KI PC and MemB are specifically enriched at the omentum, a visceral adipose tissue containing fibroblasts that express the lysoPS-generating PLA1A enzyme. Adoptive transfer and chimera experiments revealed that KI PC and MemB maintenance in the PerC is dependent on stromal PLA1A. These findings provide in vivo evidence that PLA1A produces lysoPS that can regulate GPR34-mediated immune cell accumulation at the omentum.

The immune system is complex, dynamic, and absolutely critical to maintain human health. The immune system comprises an enormous breadth of cell types, each able to respond to numerous extracellular environments. We have lacked adequate tools to dissect the mechanisms maintaining immune homeostasis through regulation of diverse cellular identities and stimulation responses. Human genetics has revealed key genes required to prevent immune dysfunction and many genomic loci associated with immune disease1,2. However, natural constraint, statistical power limitations, and lack of causal data hinder genetic association studies, preventing the identification of all key regulators and limiting conclusions about the relationships between regulatory genes 3–5. Experimental manipulation of gene expression with CRISPR provides the ability to investigate the structure and function of immune regulatory systems without the inherent limitations of association studies6.

In the T cell compartment, distinct lineages must respond to diverse signals to mount effective immune responses and maintain homeostasis, but the dynamic regulatory circuits that respond to extracellular cues in primary human cells remain poorly defined. To reveal the regulators of a core immune gene, IL2RA, expressed dynamically across the T cell compartment and required to prevent immune disease, we applied pooled CRISPR KO screens across cellular contexts7–10. We defined critical context specific regulators of IL2RA expression as well as regulators that affect the overall rest and activation state of the cell. One regulator in particular, MED12, coordinated gene regulatory networks required to maintain both T cell rest and activation. CRISPR ablation of MED12 blunted the cell state transitions between rest and activation and protected from activation-induced cell death, revealing a previously unappreciated gene regulatory mechanism governing T cell activity.

The effects of genetic variation on complex traits act mainly through changes in gene regulation. Although many genetic variants have been linked to target genes in cis, the trans-regulatory cascade mediating their effects remains largely uncharacterized. In a separate study, we investigated the function of and relationship between transcription factors associated with immune disease which are categorized as inborn errors of immunity (IEI) genes. We formed a large regulatory network consisting of regulators of IL2RA, IEI genes, and transcription factors without known immune disease associations1,11. These connections revealed shared paths and novel regulatory nodes that enable control over specific immune traits.

As a whole, this thesis work uses gene perturbation in distinct human T cell populations under different conditions to discover critical mechanisms regulating cell type and state specific gene expression. Detailed gene regulatory maps resulting from these studies, coupled with functional immune assays and biochemical data, provide new insights into human genetic variants linked to immune dysfunction and have potential to predict new modification strategies that enhance immunotherapies for the betterment of human health.

Aberrant DNA methylation is a hallmark of many cancers. As such, there has been substantial interest in the development of anti-cancer strategies which modulate epigenetic programs associated with alterations in DNA methylation. In acute myeloid leukemia (AML), decitabine is a clinically-approved DNA hypomethylating agent used for a subset of high-risk patients with poor prognoses. Despite the clinical use of this drug, and clear evidence of a clinical benefit for this patient cohort, the mechanisms by which decitabine acts as an anti-cancer agent through perturbing DNA methylation remains poorly understood. In this research, we describe our approach using functional genomics and multiomics to examine the mechanisms by which decitabine acts to kill cancer cells in the context of AML. More specifically, our results unexpectedly reveal RNA dynamics as key regulators of DNA hypomethylation induced cell death in AML. Specifically, we show that RNA decapping quality control promotes cellular resistance to DNA hypomethylation, and conversely, we also observe that RNA methylation promotes cellular sensitivity to DNA hypomethylation. Overall, our findings linking RNA dynamics to DNA methylation suggests new levels of cellular integration between RNA and DNA regulatory biology that may aid in the design of future therapeutic strategies.

Chronic pain disorders are among the top causes of global disability, presenting unique therapeutic challenges due to their complex pathophysiology and inherently subjective nature. Recent advances in non-invasive imaging, particularly magnetic resonance imaging (MRI), offer unprecedented opportunities to investigate the mechanisms underlying chronic pain conditions. This dissertation advances our understanding through three interconnected studies employing functional connectivity approaches: First, we develop a novel graph- theoretical model that predicts brain functional connectivity patterns from white matter structural architecture, providing insights into both healthy and diseased brain function. Second, using cross-decomposition analysis, we reveal previously uncharacterized relationships between distributed somatosensory patterns extracted from body map data and resting-state functional brain networks in chronic lower back pain patients. Finally, we extend functional connectivity principles to the knee, identifying distinct patterns of cartilage thickness change over 8 years that correlate with osteoarthritis progression and risk factors. Together, these works demonstrate the utility of connectivity-based approaches in understanding chronic pain across multiple biological scales.

Autism Spectrum Disorders (ASD) are a set of neurodevelopmental disorders with complex biology. The identification of ASD risk genes from exome-wide association studies and de novo variation analyses has enabled mechanistic investigations into how ASD-risk genes alter development. Most functional genomics studies have focused on the role of these genes in neurons and neural progenitor cells. However, roles for ASD risk genes in other cell types are largely uncharacterized. There is evidence from postmortem tissue that microglia, the resident immune cells of the brain, appear activated in ASD. Here, we used CRISPRi-based functional genomics to systematically assess the impact of ASD risk gene knockdown on microglia activation and phagocytosis. We developed an iPSC-derived microglia-neuron coculture system and high-throughput flow cytometry readout for synaptic pruning to enable parallel CRISPRi-based screening of phagocytosis of beads, synaptosomes, and synaptic pruning. Our screen identified ADNP, a high-confidence ASD risk genes, as a modifier of microglial synaptic pruning. We found that microglia with ADNP loss have altered endocytic trafficking, remodeled proteomes, and increased motility in coculture.

Lamin A processing is highly regulated, and necessary for proper assembly of the nuclear lamina facilitating its role in nuclear structure and chromatin organization. Pre-lamin A is first farnesylated, and then a short c-terminal peptide is cleaved to produce mature lamin A. O-GlcNAc Transferase (OGT), a glucose sensitive post-translational modification enzyme, has been identified as a potential regulator of lamin A. To explore the role of OGT in lamin A biogenesis, we examined the effects of variation in OGT levels, small molecule inhibition of OGT, and measured tail cleavage efficiency. Mutation of an OGT binding site and O-GlcNAc sites reduced tail cleavage efficiency suggesting that O-GlcNAcylation promotes lamin A processing. However, variation in OGT dose or inhibition of its activity did not alter endogenous lamin A abundance and distribution and did not disrupt differentiation. Likewise, another X-linked gene product, emerin, interacts with lamin A and is O-GlcNAc modified. As the sole developmental difference between XX and XY mESCs is that XX mESC must undergo X-chromosome inactivation (XCI), high expression of X-linked gene products, like emerin, may aid in regulation of XCI. However, perturbations to emerin in XX mESCs do not cause changes in XCI or disrupt epiblast differentiation. These results shed light onto the role of the nuclear lamina and lamin associate proteins in XCI. Additionally, our findings add to our understanding of the regulatory process behind lamin A cleavage and identify a potential link between glucose metabolism and lamina function.