Nir Hacohen - US grants

DESCRIPTION (provided by applicant): In this proposal six NIH-funded faculty from the Broad Institute of MIT and Harvard request to purchase a Nanostring nCounterTM Analysis System. Nanostring is a new technology for multiplex measurement of up to 550 genes in cell lysates from any organism. The technology offers exceptional accuracy, reproducibility, and dynamic range, permits measurement in small cell numbers (as few as 2000 mammalian cells per sample), with minimal preparation steps (no enzymatic reactions), a medium throughput of samples, and a potentially low cost. It is thus complementary to whole-genome mRNA profiling with microarrays and enables measurement of transcriptional signatures in large numbers of samples, as well as in rare cell populations and paraffin-embedded clinical samples. In particular, the faculty will use Nanostring's nCounterTM to carry out unprecedented studies to decipher regulatory networks in mammalian immune cells, re-programming in multiple mammalian cell lineages, the regulatory roles of large non-coding RNAs (lincRNAs), and the evolution of gene regulation in yeasts. Preliminary data using an instrument on loan from Nanostring demonstrated that this technology generates quantitative, highly reproducible data with small numbers of cells. The nCounter system will be operated and maintained in the Genetic Analysis Platform (GAP) of the Broad Institute, where it will be accessible to all the major and minor users, as well as to a wider community of researchers from MIT and Harvard. A staff member, who is the leader of the expression profiling team in GAP and has extraordinary expertise in expression profiling technologies, is already available to operate and maintain the system and to instruct new users. This new equipment will enable cutting-edge research efforts supported by major NIH grants, including the NIH PIONEER and Innovator awards and U01, U54 and P01 program projects. It will also provide new capabilities for signature-based profiling to a large community of trainees and researchers at the Broad Institute, Harvard and MIT. Finally, it will help establish general methodologies for the use of signature- based profiling technologies applicable in organisms from bacteria to humans. PUBLIC HEALTH RELEVANCE: The proposed research addresses how systems of genes work together to carry out a function, and rather than investigating single genes, we will dissect entire networks of genes using an instrument that can track many genes at once in a very large number of samples. We will impact discovery in two ways: first, we will use it to define the circuits controlling gene regulation in cell differentiation and the immune response and to help us rationally select drug targets in autoimmune disease and cancer;second, our success would encourage similar studies in the biomedical community in organisms from bacteria to humans.

? DESCRIPTION (provided by applicant): A major challenge in human immunology is to develop tools for the unbiased analysis of immunity using low input samples from hundreds or thousands of patients. Current approaches have several limitations. First, tissue staining and flow cytometry are hard to scale up and only measure a small number of markers. Second, most genome/proteome-wide studies have focused on aggregated signals, such as mixtures of cells (PBMCs, whole tissues, tumors) that miss cell-type specific signals, or fluids, such as plasma, that combine secretions from billions of cells. Third, although unbiased studies of gene expression in purified immune cell types have shown success in discovery of disease predictors, it remains impractical to scale up such studies using conventional approaches for cell isolation such as flow cytometry or magnetic beads. What we urgently need are methods for unbiased profiling of purified cell types, which scale to large-scale human studies with low input samples. We propose to integrate two rapidly developing technologies -- microfluidics and sensitive RNA amplification -- into a compact device for highly multiplexed purification and RNA amplification of immune cell subsets. Such a major advance in unbiased measurements would advance our understanding of mechanisms and discovery of predictive markers for immune diseases. In preliminary data supporting this proposal, the Blainey lab has demonstrated a microfluidic device that can purify human immune cells using magnetic bead- based affinity purification, and separately, that can synthesize libraries for next generation sequencing (NGS). In parallel efforts, the Hacohen lab has developed low input RNA-seq protocols that work well on flow sorted immune cell types. These combined efforts support feasibility of a microfluidic system that couples cell purification with NGS library synthesis and enables sampling of all the major immune cell types from 1-5cc of blood. We propose to develop a microfluidics device to: (i) isolate immune cell subtypes directly from a mixture of cells; (ii) lyse purified cells; (iii) synthesize libraries for RNA-seq. We will demonstrate the utility of this technology in the analysis of primary human PBMCs from the blood of healthy subjects. Future applications to the clinic will focus, for example, on cross-sectional and longitudinal studies of autoimmune, infectious diseases, asthma, transplant and aging. Such studies are anticipated to lead to better understanding of immune responses and improvements in diagnosis, prognosis and therapeutics for human immune diseases. By creating the first scalable tools for unbiased analysis of cell states within the immune system, we hope to provide human immunologists the tools to study immune diseases at unprecedented depth.

? DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) have revealed thousands of genetic loci associated with common diseases. For each locus, a 'tag' single nucleotide polymorphism (SNP) has been identified along with dozens of additional SNPs in linkage disequilibrium. However, for many of these loci, the casual SNP(s) and the genes affected by the causal SNPs are not known. Since most SNPs fall in non-coding regions of the genome, and relatively little are known about the functions of these regions, it remains challenging to pinpoint the causal SNP based on its predicted impact on function. Despite the availability of non-coding genome annotation database and the development of computational approaches for narrowing down causal SNPs, most of the causal SNPs have not been validated, and there is an urgent need for large-scale validation of candidate SNPs. Two technological advances make it possible to address these needs and comprehensively validate thousands of candidate SNPs. First, DNA synthesis is now possible to perform in a parallel and cost-effective process, enabling the rapid generation of millions of DNA reporter constructs to test the impact of non-coding SNPs on reporter expression. Second, CRISPR-based genome editing tools are evolving at a fast pace, and are now able to directly alter non-coding sequences in the genome at medium- to high-throughput. The combination of these two methods to perturb DNA sequences and study the consequences provides a powerful approach highly suited to finding a small number of causal SNPs within a larger set of candidates. In a recent study from our group, we used these two approaches to pinpoint causal SNPs for a small number of genes in the immune system, providing a proof-of-principle for this proposal. We now extend this approach computationally and experimentally. First, we will develop a Bayesian hierarchical framework to integrate annotation datasets to help fine map and nominate causal SNPs for gene expression, and a meta-analysis approach to fine map causal GWAS SNPs based on validated eQTL SNPs. Second, using gene expression in immune cells as a proxy for disease, we will apply massively parallel reporter assays (MPRAs) and efficient genome engineering with CRISPR to test the impact of candidate GWAS SNPs on gene expression. Third, we will use these datasets to refine the computational models to better predict causal SNPs. Our datasets and models are expected to: (i) improve our ability to predict causal SNPs in any disease; (ii) lead us to deduce principles of genetic and functional variation in the immune system; (iii) reveal mechanisms underlying common human immune diseases.

A central challenge in cancer immunology is to explain inter-individual differences in spontaneous and immunotherapy-induced immunity, and then build on the explanatory mechanisms to enhance existing and develop novel immunotherapies. Based on studies across diverse cancers, a substantial increase in overall survival is observed for patients with higher densities of T cells in their tumors. However, what remains obscure is why some patients develop powerful immune responses while others have undetectable immunity. A series of recent studies reported that patients with high loads of tumor mutations are more likely to have durable responses to checkpoint blockade therapy ? for MSI+ CRC, lung cancer in smokers, and melanoma. The current hypothesis is that more mutations generate more neoantigens that provide unique targets for T cells to recognize tumors. Since mounting a strong immune response also requires stimulation of specialized pathogen sensors that drive innate immune response, we have hypothesized that potent tumor immunity may also depend on engagement of pathogen sensors. We recently discovered that damaged DNA is exported from nucleus to cytosol where it triggers the STING DNA-sensing pathway and thus induces cytokines, chemokines and subsequent immune responses, a finding observed recently by several groups independently. We propose that tumors with higher loads of damaged DNA could trigger intrinsic innate immune responses via STING and enhance protective anti-tumor immunity. Further supporting this hypothesis, we have identified 50 cancer cell lines that express a STING-dependent innate immune response constitutively. We thus hypothesize that tumors with higher loads of damaged DNA (or mutation rates) trigger DNA sensors within tumor cells, and induce innate immune responses that drive T or NK cell rejection of the tumor. This hypothesis synergizes well with the hypothesis that higher mutation rates produce more neoantigens, and explains the induction of both innate and adaptive immunity as a function of mutation rates and DNA damage. We propose to comprehensively test the role of damaged DNA in driving tumor immunity, using a combination of cell culture studies to study the role of damaged DNA in driving innate immune response (Aim 1); a mouse model to determine the impact of damaged DNA within a tumor on STING-dependent immune rejection of the tumor (Aim 2); and studies of human colorectal cancers and melanomas to test for associations between damaged DNA, local tumor immunity and clinical outcome (Aim 3). Since our long-term goal is to discover the mechanisms that explain variations in tumor immunity, we will employ an unbiased approach (Aim 3.2) to generate new hypotheses for how tumors drive or suppress immunity in human tumors with known outcome. Our studies are expected to help explain inter-individual variation in tumor immunity, address why immunotherapy succeeds or fails to control tumors, and inspire novel therapeutic targets.

ABSTRACT The kidney has developed a complex, three-dimensional architecture to serve its key functions, including excretion of waste substances, maintenance of the internal balance for fluid and salt, blood pressure control, and hormonal function. Understanding the roles of the individual renal cell types in these processes in health and disease is critical to develop novel targeted therapies. Extensive studies lead by this investigative group and others have started to identify molecular disease mechanism in renal biopsy tissues and helped to develop novel disease markers and therapies. However, up to now these studies were limited using biopsy tissue homogenates, making it difficult to discern the specific pathways activated in cell types. The PREcision Medicine through IntErrogation of Rna in the kidnEy (PREMIERE) Network will bring investigators from three leading biomedical research institutions with diverse, complementary expertise together. Our team has an established track record in working jointly to develop state of the art approaches in molecular analysis of renal disease. We will set out to mine our existing compendium of thousands of gene expression profiles from renal biopsy tissues to extract single cell signatures using advanced data mining tools. In parallel we will develop technologies in our laboratories towards single cell analysis of renal tissues and scale them down so that they can work on single cells extracted from small renal biopsies. These single cell profiles will be linked to the disease states of the patients. Key signatures associated with specific cells and diseases will be extracted and localized in the three dimensional context of the kidney using specific RNA staining techniques in the first phase of the project. In the second phase, the analytical strategies will be scaled up so that single cell profiles from specific groups of patients can be obtained in a robust and reproducible manner. To this end the PREMIERE investigators will work closely with the tissue procurement sites and the Central Hub of the KPMP, using their 20 years of experience in team science, so that at the end of the first KPMP funding cycle novel, cell type specific treatment targets are identified fueling the therapeutic pipelines of the future.

The dendritic cells (DCs) of the mammalian innate immune system are responsible for detection of microbial encounters and the initiation of inflammation and adaptive immunity. This central role of DCs in host physiology has attracted much attention, and these cells are the subject of active investigation. Despite the appreciation of the importance of DCs, there remain large and fundamental gaps in our knowledge of their mechanisms of regulation. For instance, DCs encode several receptors that detect bacterial lipopolysaccharides (LPS), yet the functions of only one (TLR4) have been examined extensively. Recent work by us and others have identified the LPS receptors CD14 and caspase-11 as being capable of inducing novel signaling pathways that proceed either upstream of TLR4 (CD14) or in parallel to TLR4 (caspase-11). The collective actions of CD14, TLR4 and caspase-11 are important for DC activation and host defense, yet their mechanisms of action are poorly defined. Thus, significant gaps in our knowledge exist to explain the earliest stages of DC interactions with bacteria. We also lack an understanding of how DCs interact with T cells at later stages of infection, yet it is clear that these interactions lead to profound changes in the activities of both cell types. Much of the research into these interactions has focused on how DCs promote changes in T cell activities. In contrast, we have a minimal understanding of how T cells influence the activity of DCs. In this application, we propose to fill these gaps in our knowledge of DC biology through forward genetic screening for novel regulatory factors in mice. This approach is facilitated by recent advances in genome editing provided by CRISPR-based technologies. A pipeline of gene discovery will be generated through the use of established and emerging FACS-based assays. These assays will be used in vivo and ex vivo to identify DCs that are deficient for regulators of DC interactions with microbes or T cells. All screens will depend on significant interactions between the informatics, mouse perturbation and CRISPR library Cores associated with this U19 application. Subsequent functional analysis of candidate regulatory proteins will be performed in collaboration with other investigators on this grant. The cumulative result of these efforts will be a series of novel gene sets that should define pathways and processes that explain numerous aspects of DC biology as they relate to host defense.