Faculty Bibliography

The development of dendritic cells (DCs), including antigen-presenting conventional DCs (cDCs) and cytokine-producing plasmacytoid DCs (pDCs), is controlled by the growth factor Flt3 ligand (Flt3L) and its receptor Flt3. We genetically dissected Flt3L-driven DC differentiation using CRISPR-Cas9-based screening. Genome-wide screening identified multiple regulators of DC differentiation including subunits of TSC and GATOR1 complexes, which restricted progenitor growth but enabled DC differentiation by inhibiting mTOR signaling. An orthogonal screen identified the transcriptional repressor Trim33 (TIF-1γ) as a regulator of DC differentiation. Conditional targeting in vivo revealed an essential role of Trim33 in the development of all DCs, but not of monocytes or granulocytes. In particular, deletion of Trim33 caused rapid loss of DC progenitors, pDCs, and the cross-presenting cDC1 subset. Trim33-deficient Flt3⁺ progenitors up-regulated pro-inflammatory and macrophage-specific genes but failed to induce the DC differentiation program. Collectively, these data elucidate mechanisms that control Flt3L-driven differentiation of the entire DC lineage and identify Trim33 as its essential regulator.

Loss-of-function mutations in KEAP1 frequently occur in lung cancer and are associated with poor prognosis and resistance to standard of care treatment, highlighting the need for the development of targeted therapies. We previously showed that KEAP1 mutant tumors consume glutamine to support the metabolic rewiring associated with NRF2-dependent antioxidant production. Here, using preclinical patient-derived xenograft models and antigenic orthotopic lung cancer models, we show that the glutamine antagonist prodrug DRP-104 impairs the growth of KEAP1 mutant tumors. We find that DRP-104 suppresses KEAP1 mutant tumors by inhibiting glutamine-dependent nucleotide synthesis and promoting antitumor T cell responses. Using multimodal single-cell sequencing and ex vivo functional assays, we demonstrate that DRP-104 reverses T cell exhaustion, decreases T_regs, and enhances the function of CD4 and CD8 T cells, culminating in an improved response to anti-PD1 therapy. Our preclinical findings provide compelling evidence that DRP-104, currently in clinical trials, offers a promising therapeutic approach for treating patients with KEAP1 mutant lung cancer.

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-and-eosin-stained whole-slide images (WSIs). We trained an SSL Barlow Twins-encoder on 435 TCGA colon adenocarcinoma WSIs to extract features from small image patches. Leiden community detection then grouped tiles into histomorphological phenotype clusters (HPCs). HPC reproducibility and predictive ability for overall survival was confirmed in an independent clinical trial cohort (N=1213 WSIs). This unbiased atlas resulted in 47 HPCs displaying unique and sharing clinically significant histomorphological traits, highlighting tissue type, quantity, and architecture, especially in the context of tumor stroma. Through in-depth analysis of these HPCs, including immune landscape and gene set enrichment analysis, and association to clinical outcomes, we shed light on the factors influencing survival and responses to treatments like standard adjuvant chemotherapy and experimental therapies. Further exploration of HPCs may unveil new insights and aid decision-making and personalized treatments for colon cancer patients.

Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome¹. In bacteria, the relationship between the regulatory architecture of a gene and its expression is well understood for individual model gene circuits^2,3. However, a broader perspective of these dynamics at the genome scale is lacking, in part because bacterial transcriptomics has hitherto captured only a static snapshot of expression averaged across millions of cells⁴. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on the transcriptional response of each gene to its own replication, which we term the transcription-replication interaction profile (TRIP). Analysing single-bacterium RNA-sequencing data, we found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal the local regulatory context of a gene. Whereas the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, and this is shaped by factors such as intra-operon position and repression state. By revealing the underlying mechanistic drivers of gene expression heterogeneity, this work provides a quantitative, biophysical framework for modelling replication-dependent expression dynamics.

Pattern formation originates during embryogenesis by a series of symmetry-breaking steps throughout an expanding cell lineage. In Drosophila, classic work has shown that segmentation in the embryo is established by morphogens within a syncytium, and the subsequent action of the gap, pair-rule, and segment polarity genes. This classic model however does not translate directly to species that lack a syncytium - such as Caenorhabditis elegans - where cell fate is specified by cell-autonomous cell lineage programs and their inter-signaling. Previous single-cell RNA-Seq studies in C. elegans have analyzed cells from a mixed suspension of cells from many embryos to study late differentiation stages, or individual early stage embryos to study early gene expression in the embryo. To study the intermediate stages of early and late gastrulation (28- to 102-cells stages) missed by these approaches, here we determine the transcriptomes of the 1- to 102-cell stage to identify 119 embryonic cell states during cell fate specification, including 'equivalence-group' cell identities. We find that gene expression programs are modular according to the sub-cell lineages, each establishing a set of stripes by combinations of transcription factor gene expression across the anterior-posterior axis. In particular, expression of the homeodomain genes establishes a comprehensive lineage-specific positioning system throughout the embryo beginning at the 28-cell stage. Moreover, we find that genes that segment the entire embryo in Drosophila have orthologs in C. elegans that exhibit sub-lineage-specific expression. These results suggest that the C. elegans embryo is patterned by a juxtaposition of distinct lineage-specific gene regulatory programs each with a unique encoding of cell location and fate. This use of homologous gene regulatory patterning codes suggests a deep homology of cell fate specification programs across diverse modes of development.

Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome¹. In bacteria, the relationship between the regulatory architecture of a gene and its expression is well understood for individual model gene circuits^2,3. However, a broader perspective of these dynamics at the genome scale is lacking, in part because bacterial transcriptomics has hitherto captured only a static snapshot of expression averaged across millions of cells⁴. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on the transcriptional response of each gene to its own replication, which we term the transcription"“replication interaction profile (TRIP). Analysing single-bacterium RNA-sequencing data, we found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal the local regulatory context of a gene. Whereas the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, and this is shaped by factors such as intra-operon position and repression state. By revealing the underlying mechanistic drivers of gene expression heterogeneity, this work provides a quantitative, biophysical framework for modelling replication-dependent expression dynamics.

Mutations in genes encoding epigenetic regulators are commonly observed at relapse in B cell acute lymphoblastic leukemia (B-ALL). Loss-of-function mutations in SETD2, an H3K36 methyltransferase, have been observed in B-ALL and other cancers. Previous studies on mutated SETD2 in solid tumors and acute myelogenous leukemia support a role in promoting resistance to DNA damaging agents. We did not observe chemoresistance, an impaired DNA damage response, nor increased mutation frequency in response to thiopurines using CRISPR-mediated knockout in wild-type B-ALL cell lines. Likewise, restoration of SETD2 in cell lines with hemizygous mutations did not increase sensitivity. SETD2 mutations affected the chromatin landscape and transcriptional output that was unique to each cell line. Collectively our data does not support a role for SETD2 mutations in driving clonal evolution and relapse in B-ALL, which is consistent with the lack of enrichment of SETD2 mutations at relapse in most studies.

Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages: the trophectoderm, the epiblast and the primitive endoderm. Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements through which transcriptional regulators enact these fates remain understudied. Here, we characterize, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observe extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although distinct groups of genes are irresponsive to topological changes. In each lineage, a high degree of connectivity, or 'hubness', positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a predictive model for transcriptional regulation (3D-HiChAT) that outperforms models using only 1D promoter or proximal variables to predict levels and cell-type specificity of gene expression. Using 3D-HiChAT, we identify, in silico, candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments, we validate several enhancers that control gene expression in their respective lineages. Our study identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to comprehensively understand lineage-specific transcriptional behaviors.

UNLABELLED:Non-small lung cancers (NSCLC) frequently (∼30%) harbor KRAS driver mutations, half of which are KRASG12C. KRAS-mutant NSCLC with comutated STK11 and/or KEAP1 is particularly refractory to conventional, targeted, and immune therapy. Development of KRASG12C inhibitors (G12Ci) provided a major therapeutic advance, but resistance still limits their efficacy. To identify genes whose deletion augments efficacy of the G12Cis adagrasib (MRTX-849) or adagrasib plus TNO155 (SHP2i), we performed genome-wide CRISPR/Cas9 screens on KRAS/STK11-mutant NSCLC lines. Recurrent, potentially targetable, synthetic lethal (SL) genes were identified, including serine-threonine kinases, tRNA-modifying and proteoglycan synthesis enzymes, and YAP/TAZ/TEAD pathway components. Several SL genes were confirmed by siRNA/shRNA experiments, and the YAP/TAZ/TEAD pathway was extensively validated in vitro and in mice. Mechanistic studies showed that G12Ci treatment induced gene expression of RHO paralogs and activators, increased RHOA activation, and evoked ROCK-dependent nuclear translocation of YAP. Mice and patients with acquired G12Ci- or G12Ci/SHP2i-resistant tumors showed strong overlap with SL pathways, arguing for the relevance of the screen results. These findings provide a landscape of potential targets for future combination strategies, some of which can be tested rapidly in the clinic. SIGNIFICANCE/UNASSIGNED:Identification of synthetic lethal genes with KRASG12C using genome-wide CRISPR/Cas9 screening and credentialing of the ability of TEAD inhibition to enhance KRASG12C efficacy provides a roadmap for combination strategies. See related commentary by Johnson and Haigis, p. 4005.

Lung cancer treatment has benefited greatly through advancements in immunotherapies. However, immunotherapy often fails in patients with specific mutations like KEAP1, which are frequently found in lung adenocarcinoma. We established an antigenic lung cancer model and used it to explore how Keap1 mutations remodel the tumor immune microenvironment. Using single-cell technology and depletion studies, we demonstrate that Keap1-mutant tumors diminish dendritic cell and T cell responses driving immunotherapy resistance. This observation was corroborated in patient samples. CRISPR-Cas9-mediated gene targeting revealed that hyperactivation of the NRF2 antioxidant pathway is responsible for diminished immune responses in Keap1-mutant tumors. Importantly, we demonstrate that combining glutaminase inhibition with immune checkpoint blockade can reverse immunosuppression, making Keap1-mutant tumors susceptible to immunotherapy. Our study provides new insight into the role of KEAP1 mutations in immune evasion, paving the way for novel immune-based therapeutic strategies for KEAP1-mutant cancers.