3D Enhancer-promoter networks provide predictive features for gene expression and coregulation in early embryonic lineages
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.
KEAP1 mutation in lung adenocarcinoma promotes immune evasion and immunotherapy resistance
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.
An Anterior Second Heart Field Enhancer Regulates the Gene Regulatory Network of the Cardiac Outflow Tract
BACKGROUND/UNASSIGNED:Conotruncal defects due to developmental abnormalities of the outflow tract (OFT) are an important cause of cyanotic congenital heart disease. Dysregulation of transcriptional programs tuned by NKX2-5 (NK2 homeobox 5), GATA6 (GATA binding protein 6), and TBX1 (T-box transcription factor 1) have been implicated in abnormal OFT morphogenesis. However, there remains no consensus on how these transcriptional programs function in a unified gene regulatory network within the OFT. METHODS/UNASSIGNED: RESULTS/UNASSIGNED: CONCLUSIONS/UNASSIGNED:Our results using human and mouse models reveal an essential gene regulatory network of the OFT that requires an anterior second heart field enhancer to link GATA6 with NKX2-5-dependent rotation and septation gene programs.
Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma
Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.
Digital spatial profiling to predict recurrence in grade 3 stage I lung adenocarcinoma
OBJECTIVE:Early-stage lung adenocarcinoma is treated with local therapy alone, although patients with grade 3 stage I lung adenocarcinoma have a 50% 5-year recurrence rate. Our objective is to determine if analysis of the tumor microenvironment can create a predictive model for recurrence. METHODS:Thirty-four patients with grade 3 stage I lung adenocarcinoma underwent surgical resection. Digital spatial profiling was used to perform genomic (n = 31) and proteomic (n = 34) analyses of pancytokeratin positive and negative tumor cells. K-means clustering was performed on the top 50 differential genes and top 20 differential proteins, with Kaplan-Meier recurrence curves based on patient clustering. External validation of high-expression genes was performed with Kaplan-Meier plotter. RESULTS:There were no significant clinicopathologic differences between patients who did (n = 14) and did not (n = 20) have recurrence. Median time to recurrence was 806 days; median follow-up with no recurrence was 2897 days. K-means clustering of pancytokeratin positive genes resulted in a model with a Kaplan-Meier curve with concordance index of 0.75. K-means clustering for pancytokeratin negative genes was less successful at differentiating recurrence (concordance index 0.6). Genes upregulated or downregulated for recurrence were externally validated using available public databases. Proteomic data did not reach statistical significance but did internally validate the genomic data described. CONCLUSIONS:Genomic difference in lung adenocarcinoma may be able to predict risk of recurrence. After further validation, stratifying patients by this risk may help guide who will benefit from adjuvant therapy.
Multiomic mapping of acquired chromosome 1 copy number and structural variants to identify therapeutic vulnerabilities in multiple myeloma
PURPOSE/OBJECTIVE:Chromosome 1 (chr1) copy number abnormalities (CNAs) and structural variants (SV) are frequent in newly diagnosed multiple myeloma (NDMM) and associate with a heterogeneous impact on outcome the drivers of which are largely unknown. EXPERIMENTAL DESIGN/METHODS:A multiomic approach comprising CRISPR, gene mapping of CNA and SV, methylation, expression, and mutational analysis was used to document the extent of chr1 molecular variants and their impact on pathway utilisation. RESULTS:We identified two distinct groups of gain(1q): focal gains associated with limited gene expression changes and a neutral prognosis, and whole-arm gains, which associate with substantial gene expression changes, complex genetics and an adverse prognosis. CRISPR identified a number of dependencies on chr1 but only limited variants associated with acquired CNAs. We identified seven regions of deletion, nine of gain, three of chromothripsis (CT) and two of templated-insertion (TI), which contain a number of potential drivers. An additional mechanism involving hypomethylation of genes at 1q may contribute to the aberrant gene expression of a number of genes. Expression changes associated with whole-arm gains were substantial and gene set enrichment analysis identified metabolic processes, apoptotic resistance, signaling via the MAPK pathway, and upregulation of transcription factors as being key drivers of the adverse prognosis associated with these variants. CONCLUSIONS:Multiple layers of genetic complexity impact the phenotype associated with CNAs on chr1 to generate its associated clinical phenotype. Whole-arm gains of 1q are the critically important prognostic group that deregulate multiple pathways, which may offer therapeutic vulnerabilities.
Loss of Notch signaling in skeletal stem cells enhances bone formation with aging
Skeletal stem and progenitor cells (SSPCs) perform bone maintenance and repair. With age, they produce fewer osteoblasts and more adipocytes leading to a loss of skeletal integrity. The molecular mechanisms that underlie this detrimental transformation are largely unknown. Single-cell RNA sequencing revealed that Notch signaling becomes elevated in SSPCs during aging. To examine the role of increased Notch activity, we deleted Nicastrin, an essential Notch pathway component, in SSPCs in vivo. Middle-aged conditional knockout mice displayed elevated SSPC osteo-lineage gene expression, increased trabecular bone mass, reduced bone marrow adiposity, and enhanced bone repair. Thus, Notch regulates SSPC cell fate decisions, and moderating Notch signaling ameliorates the skeletal aging phenotype, increasing bone mass even beyond that of young mice. Finally, we identified the transcription factor Ebf3 as a downstream mediator of Notch signaling in SSPCs that is dysregulated with aging, highlighting it as a promising therapeutic target to rejuvenate the aged skeleton.
Deep learning integrates histopathology and proteogenomics at a pan-cancer level
We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.
Haplodeficiency of the 9p21 Tumor Suppressor Locus Causes Myeloid Disorders Driven by the Bone Marrow Microenvironment
The chromosome 9p21 locus comprises several tumor suppressor genes including MTAP, CDKN2A and CDKN2B, and its homo- or heterozygous deletion is associated with reduced survival in multiple cancer types. We report that mice with germline monoallelic deletion or induced biallelic deletion of the 9p21-syntenic locus (9p21s) developed a fatal myelodysplastic syndrome/myeloproliferative neoplasm (MDS/MPN)-like disease associated with aberrant trabecular bone formation and/or fibrosis in the bone marrow (BM). Reciprocal BM transfers and conditional targeting of 9p21s suggested that the disease originates in the BM stroma. Single-cell analysis of 9p21s-deficient BM stroma revealed the expansion of chondrocyte and osteogenic precursors, reflected in increased osteogenic differentiation in vitro. It also showed reduced expression of factors maintaining hematopoietic stem/progenitor cells, including Cxcl12. Accordingly, 9p21s-deficient mice showed reduced levels of circulating Cxcl12 and concomitant upregulation of the pro-fibrotic chemokine Cxcl13 and osteogenesis- and fibrosis-related multifunctional glycoprotein Osteopontin (OPN)/Spp1. Our study highlights the potential of mutations in the BM microenvironment to drive MDS/MPN-like disease.
Cell-type-specific prediction of 3D chromatin organization enables high-throughput in silico genetic screening
Investigating how chromatin organization determines cell-type-specific gene expression remains challenging. Experimental methods for measuring three-dimensional chromatin organization, such as Hi-C, are costly and have technical limitations, restricting their broad application particularly in high-throughput genetic perturbations. We present C.Origami, a multimodal deep neural network that performs de novo prediction of cell-type-specific chromatin organization using DNA sequence and two cell-type-specific genomic features-CTCF binding and chromatin accessibility. C.Origami enables in silico experiments to examine the impact of genetic changes on chromatin interactions. We further developed an in silico genetic screening approach to assess how individual DNA elements may contribute to chromatin organization and to identify putative cell-type-specific trans-acting regulators that collectively determine chromatin architecture. Applying this approach to leukemia cells and normal T cells, we demonstrate that cell-type-specific in silico genetic screening, enabled by C.Origami, can be used to systematically discover novel chromatin regulation circuits in both normal and disease-related biological systems.