Tumor progression is the major cause of death in cancer patients. Due to their higher chromosomal instability and other genomic alterations, tumors evolve rapidly in response to therapeutic interventions and other external pressures. The immune system is our first line of defense against cancer and its interaction with cancer cells can both constrain and promote tumor growth and metastasis. A heterogeneous tumor consists of subclones with different characteristics. During tumor progression the anti-tumor immune activity removes subclones that express highly immunogenic antigens and leaves behind cancer cells with high immune escape or immunosuppressive properties. This process is called tumor immunoediting. Studying tumor progression requires reliable in vivo models that effectively capture the intricacies and complexities of this process. During the 1970s, Isaiah Fidler demonstrated that repeated passaging of cancer cells in mice can be used to emulate metastatic progression. This in vivo selection model has been used by many different research groups (including us) to model tumor progression in a number of cancer models. Our group has utilized these in vivo selection models to study cell autonomous mechanisms of tumor progression. More recently, however, we have come to realize that by leveraging these in vivo-selection models we can focus on studying non-cell autonomous mechanisms. Building on this notion, here, we propose a generalization of in vivo selection that models the role of the immune system in shaping tumor evolution. Our “immune selection” model takes advantage of a panel of genetic mouse models with various degrees of immunocompetency to serve as hosts for established syngeneic tumor cell lines. We utilized these ‘immuno-selected’ derivatives, in conjunction with cutting-edge tools in genetic engineering and single-cell genomics, to study the tumor-immune co-evolution. We discovered that the interferon response pathway lies at the heart of tumor immune evasion. Additionally, we have uncovered novel molecular pathways responsible for conferring resistance to both antitumor immunity and immunotherapies. Targeting these pathways holds significant therapeutic potential, particularly when used in conjunction with immune checkpoint blockades (ICBs) and other forms of immunotherapy. The second part of this thesis is focused on utilizing machine learning and computational tools to identify important molecular mechanisms in small RNA secretion. We developed ExoGRU, a deep-learning model for predicting secretion probabilities of small RNAs based on their primary sequence. We used ExoGRU to (i) identify mutations that abrogate the secretion of known cell-free small RNAs, and (ii) predict high confidence sets of synthetic sequences that are secreted or retained. We also used independent experimental approaches to validate our model’s prediction abilities. We discovered that the molecular signature needed for small RNA secretion lies in its primary sequence. Furthermore, we identified both previously known and novel RNA binding proteins (RBPs) crucial for facilitating this secretion. In both projects discussed, we demonstrate the effectiveness of in vivo, high-throughput, multi-omics and computational tools in uncovering novel mechanisms, particularly in the evolution of tumor immunity and RNA secretion, areas traditionally challenging to explore with conventional methods.

Human disease risk has been linked to hundreds of variants in our DNA. Understanding of these unbiased genetic associations has long held the promise of revealing insights into disease mechanisms. However, disease-risk variants overwhelmingly reside in non-coding sequences – long stretches of our chromosomes that we still know relatively little about. Here I develop new tools and methodologies to understand genetic risk for disease for a critical autoimmunity locus, IL2RA. I first demonstrate that CRISPR activation can be adapted for high throughput enhancer screens. By tiling CRISPR-activation across the super-enhancer within the IL2RA locus, I systematically map functional IL2RA enhancers in the disease-associated non-coding sequences. Undertaking a genetic perturbation approach, I dissect how distinct IL2RA enhancers regulate immune cell function as well as shape risk of autoimmunity in vivo. Using CRISPR-engineered enhancer deletion mice and human immune cells I identified two novel IL2RA enhancers; a maintenance enhancer that controls IL2RA expression in anti-inflammatory regulatory T cells and a disease-associated IL2RA enhancer that controls the timing of IL2RA induction in pro-inflammatory immune cells. Having discovered enhancers that regulate IL2RA in different contexts I interrogated their effects in an in vivo model of autoimmune disease. Deletion of the conserved stimulation-responsive enhancer that harbors a human variant protective against T1D completely protected non-obese diabetic (NOD) mice from diabetes. This work decodes a critical autoimmunity association, develops a cis-regulatory framework at the IL2RA locus, and causally links IL2RA gene regulation to autoimmunity. The tools and strategies developed in these studies can be used to decode disease-associated loci in the human genome.

Chimeric antigen receptors (CARs) repurpose natural signaling components to retarget T cells to refractory cancers but have shown limited efficacy in persistent, recurrent malignancies. Here, we introduce “CAR Pooling”, a multiplexed approach to rapidly identify CAR designs with clinical potential. Forty CARs with signaling domains derived from a range of immune cell lineages were evaluated in pooled assays for their ability to stimulate critical T cell effector functions during repetitive stimulation that mimics long-term tumor antigen exposure. Several domains were identified from the tumor necrosis factor (TNF) receptor family that have been primarily associated with B cells. CD40 enhanced proliferation, whereas B-cell activating factor receptor (BAFF-R) and transmembrane activator and CAML interactor (TACI) promoted cytotoxicity. These functions were enhanced relative to clinical benchmarks after prolonged antigen stimulation, and fell into distinct states of memory, cytotoxicity, and metabolism. BAFF-R CAR T cells were enriched for a highly cytotoxic transcriptional signature previously associated with positive clinical outcomes. Additionally, we observed that replacing the 4-1BB intracellular signaling domain with the BAFF-R signaling domain in a clinically validated B-cell maturation antigen (BCMA)-specific CAR resulted in enhanced activity in a xenotransplant model of multiple myeloma. Together, these results show that “CAR Pooling” is a general approach for rapid exploration of CAR architecture and activity to improve the efficacy of CAR T cell therapies.  

A central goal of genetics is to define the phenotypic consequences of genetic perturbations. Single-cell CRISPR screens such as Perturb-seq (pooled single-cell RNA-sequencing CRISPR screens) represent an emerging tool to systematically construct genotype-phenotype maps by pairing high-dimensional genetic perturbations with rich phenotypic readouts in single cells. However, to date, these screens have been deployed at a limited scale.

The first chapter of this thesis addresses a major technological hinderance to the scalable application of Perturb-seq: reliance on indirect indexing of single-guide RNAs (sgRNAs). I present direct-capture Perturb-seq, a versatile screening approach in which expressed sgRNAs are sequenced alongside single-cell transcriptomes. Direct-capture Perturb-seq enables detection of multiple distinct sgRNA sequences from individual cells and thus allows pooled single-cell CRISPR screens to be easily paired with combinatorial perturbation libraries that contain dual-guide expression vectors. I then demonstrate the utility of this approach for high-throughput investigations of genetic interactions and, leveraging this ability, dissect epistatic interactions between cholesterol biogenesis and DNA repair. Using direct capture Perturb-seq, I also show that targeting individual genes with multiple sgRNAs per cell improves the efficacy of CRISPR interference and activation, facilitating the use of compact, highly active CRISPR libraries for large-scale single-cell screens. Last, I show that hybridization-based target enrichment permits sensitive, specific sequencing of informative transcripts from single-cell RNA-seq experiments.

The second chapter builds on the first chapter by applying direct capture Perturb-seq and multiplexed CRISPR interference (CRISPRi) to perform the first genome-scale Perturb-seq screens. From these data, I yield a blueprint for the construction and analysis of rich genotype-phenotype maps. I show that genes can be clustered by transcriptional phenotypes across many essential cellular processes and reveal new roles for poorly characterized genes in ribosome biogenesis, transcription, and respiration. Beyond clustering genes, these data enable in-depth dissection of the functional consequences of genetic perturbations on a remarkable array of complex, composite phenotypes—including RNA processing, differentiation, and chromosomal instability. Leveraging this ability, I comprehensively identify genetic drivers and consequences of aneuploidy, and I uncover unanticipated perturbation-specific regulation of the mitochondrial genome. This thesis establishes Perturb-seq as a scalable tool for the principled exploration of multidimensional cellular behaviors, gene function, and regulatory networks.

T cells constitute an essential component of the adaptive immune response toimmunogenic antigens both endogenous and exogenous such as those from allergens or viral infections. We present here two studies of T cells, one in which we investigate a non-coding RNA circuit in the control of cytotoxic T cells and one in which we characterize allergen reactive T helper cells in human allergic asthmatic subjects. Proper activation of cytotoxic T cells via the T cell receptor and the costimulatory receptor CD28 is essential for adaptive immunity against viruses and intracellular bacteria. Through biochemical analysis of RNA:protein interactions, we uncovered a novel non-coding RNA circuit regulating cytotoxic T cells composed of the long non-coding RNA (lncRNA) Malat1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) and the microRNA family miR-15/16. miR-15/16 is a widely and highly expressed miRNA family important for cell proliferation and survival. miR-15/16 also play important roles in T cell responses to viral infection, including the regulation of antigen-specific T cell expansion and T cell memory. Comparative Argonaute-2 high throughput sequencing of crosslinking immunoprecipitation (AHC) combined with gene expression profiling in normal and miR-15/16- deficient T cells revealed a network of several hundred direct miR-15/16 targets, many with functional relevance for T cell activation, survival and memory formation. Among these targets, the long non-coding RNA Malat1 contained the largest absolute magnitude miR-15/16- dependent AHC peak in T cells. This binding site was also among the strongest lncRNA:miRNA interactions detected in the T cell transcriptome. We used CRISPR targeting with homology directed repair to generate mice with a 5-nucleotide mutation in the miR-15/16 binding site in Malat1. This mutation interrupted Malat1:miR-15/16 interaction, and enhanced the repression of ixother miR-15/16 target genes, including CD28. Interrupting Malat1 interaction with miR-15/16 decreased cytotoxic T cell activation, including the expression of IL-2 and a broader CD28- responsive gene program. Accordingly, Malat1 mutation diminished memory cell persistence following LCMV Armstrong and Listeria monocytogenes infection. This study marks a significant advance in the study of lncRNAs in the immune system by ascribing cell-intrinsic, sequence- specific in vivo function to Malat1. These findings have implications for T cell-mediated immunity, as well as lung adenocarcinoma and other malignancies where Malat1 is overexpressed. Beyond cytotoxic T cells, T helper cells can differentiate into distinct states marked by stereotypical cytokine expression. In the context of allergic diseases type 2 helper T cells which produce the type 2 cytokines, IL-5, IL-4, and IL-13 can become pathogenic and contribute to a consistently elevated level of type 2 inflammation. In asthma, the lung is the primary site of aberrant inflammation and understanding how this tissue responds to allergens is key. In this study, human subjects were locally exposed to allergen via bronchoscopy. We then assayed the immunological and cellular state of these bronchoscopy samples by multiple high dimensional ‘omic’ technologies: RNAseq, Cytof, and scRNAseq. We then define heterogeneity across these allergic subjects corresponding to type 2 high and type 2 low individuals. In the type 2 high individuals we find that inflammatory monocyte derived populations enter the lung and induce the expression of inflammatory chemokines CCL3, CCL17, and CCL22 likely contributing to increased inflammation in the lung. Further, through scRNAseq we are able to identify Th2 cells recruited specifically by the allergen challenge. In a subset of individuals we could identify TCR clones which were allergen reactive and expanded in the blood post allergen challenge. Indicating that, while these cells are rare in the lung, dampening their function systemically may lead to decreased local inflammation in the lung as well. Understanding all these facets of allergic inflammation in this detailed way is essential for proper clinical understanding of asthma as well as the potential development of novel therapeutic strategies.

The identification of autoantigens remains a critical challenge for understanding and treating autoimmune diseases. Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantigen discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation with autoimmunity.The first chapter of this thesis explores autoantigen discovery in the disease Autoimmune polyendocrine syndrome type 1 (APS1), a rare monogenic form of autoimmunity that presents as widespread autoimmunity with T and B cell responses to multiple organs. Importantly, autoantibody discovery in APS1 can illuminate fundamental disease pathogenesis, and many of the antigens found in APS1 extend to common autoimmune diseases. Here, I applied PhIP-Seq to sera from an APS1 cohort and discovered multiple common antibody targets. These novel autoantigens exhibit tissue-restricted expression, including expression in enteroendocrine cells and dental enamel. Using detailed clinical phenotyping, novel associations between autoantibodies and organ-restricted autoimmunity are described, including between anti-KHDC3L autoantibodies and premature ovarian insufficiency, and between anti-RFX6 autoantibodies and diarrheal-type intestinal dysfunction. These data highlight the utility of PhIP-Seq for interrogating antigenic repertoires in human autoimmunity and the importance of antigen discovery for improved understanding of disease mechanisms. In the second chapter, I discuss and address how despite several successful implementations of PhIP-Seq for autoantigen discovery, current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. I develop and validate a high throughput extension of PhIP-seq in the context of monogenic and acquired autoimmune disease, including APS1, IPEX, patients with RAG1/2 deficiency, Kawasaki Disease, multisystem inflammatory syndrome in children, and finally, mild and severe forms of COVID19. These scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel, autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with a RAG1/2 deficiency, one of which had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.

Regulatory T cells (Tregs) are required to control immune responses and maintain homeostasis, but are a significant barrier to anti-tumor immunity. Conversely, Treg instability, characterized by loss of the master transcription factor Foxp3 and acquisition of pro-inflammatory properties, can promote autoimmunity and/or facilitate more effective tumor immunity. A comprehensive understanding of the pathways that regulate Foxp3 could lead to more effective Treg therapies for autoimmune disease and cancer. Despite improved functional genetic tools that now allow for systematic interrogation, dissection of the gene regulatory programs that modulate Foxp3 expression has not yet been reported. In this study, we developed a CRISPR-based pooled screening platform for phenotypes in primary mouse Tregs and applied this technology to perform a targeted loss-of-function screen of ~490 nuclear factors to identify gene regulatory programs that promote or disrupt Foxp3 expression. We discovered several novel modulators including ubiquitin-specific peptidase 22 (Usp22) and ring finger protein 20 (Rnf20). Usp22, a member of the deubiquitination module of the SAGA chromatin modifying complex, was discovered to be a positive regulator that stabilized Foxp3 expression; whereas the screen suggested Rnf20, an E3 ubiquitin ligase, can serve as a negative regulator of Foxp3. Treg-specific ablation of Usp22 in mice reduced Foxp3 protein and created defects in their suppressive function that led to spontaneous autoimmunity but protected against tumor growth in multiple cancer models. Foxp3 destabilization in Usp22-deficient Tregs could be rescued by ablation of Rnf20, revealing a reciprocal ubiquitin switch in Tregs. These results reveal novel modulators of Foxp3 and demonstrate a screening method that can be broadly applied to discover new targets for Treg immunotherapies for cancer and autoimmune disease.