Faculty Bibliography

Clonal hematopoiesis (CH) is an aging-associated condition characterized by the clonal outgrowth of mutated pre-leukemic cells. Individuals with CH are at an increased risk of developing hematopoietic malignancies. Here, we describe a novel animal model carrying a recurrent TET2 missense mutation, frequently found in CH and leukemic patients. In a fashion similar to CH, animals show signs of disease late in life when they develop a wide range of myeloid neoplasms, including acute myeloid leukemia (AML). Using single cell transcriptomic profiling of the bone marrow, we show that disease progression in aged animals correlates with an enhanced inflammatory response and the emergence of an aberrant inflammatory monocytic cell population. The gene signature characteristic of this inflammatory population is associated to poor prognosis in AML patients. Our study illustrates an example of collaboration between a genetic lesion found in CH and inflammation, leading to transformation and the establishment of blood neoplasms.

PURPOSE/OBJECTIVE:Lung adenocarcinoma (LUAD) is a clinically heterogenous disease, which is highlighted by the unpredictable recurrence in low-stage tumors and highly variable responses observed in patients treated with immunotherapies, which cannot be explained by mutational profiles. DNA methylation-based classification and understanding of microenviromental heterogeneity may allow stratification into clinically relevant molecular subtypes of LUADs. EXPERIMENTAL DESIGN/METHODS:We characterize the genome-wide DNA methylation landscape of 88 resected LUAD tumors. Exome sequencing focusing on a panel of cancer-related genes was used to genotype these adenocarcinoma samples. Bioinformatic and statistical tools, the immune cell composition, DNA methylation age (DNAm age), and DNA methylation clustering were used to identify clinically relevant subgroups. RESULTS:Deconvolution of DNA methylation data identified immunologically hot and cold subsets of lung adenocarcinomas. Additionally, concurrent factors were analyzed that could affect the immune microenvironment, such as smoking history, ethnicity, or presence of KRAS or TP53 mutations. When the DNAm age was calculated, a lower DNAm age was correlated with the presence of a set of oncogenic drivers, poor overall survival, and specific immune cell populations. Unsupervised DNA methylation clustering identified 6 molecular subgroups of LUAD tumors with distinct clinical and microenvironmental characteristics. CONCLUSIONS:Our results demonstrate that DNA methylation signatures can stratify lung adenocarcinoma into clinically relevant subtypes, and thus such classification of LUAD at the time of resection may lead to better methods in predicting tumor recurrence and therapy responses.

Extracellular vesicles of endosomal origin, exosomes, mediate intercellular communication by transporting substrates with a variety of functions related to tissue homeostasis and disease. Their diagnostic and therapeutic potential has been recognized for diseases such as cancer in which signaling defects are prominent. However, it is unclear to what extent exosomes and their cargo inform the progression of infectious diseases. We recently defined a subset of exosomes termed defensosomes that are mobilized during bacterial infection in a manner dependent on autophagy proteins. Through incorporating protein receptors on their surface, defensosomes mediated host defense by binding and inhibiting pore-forming toxins secreted by bacterial pathogens. Given this capacity to serve as decoys that interfere with surface protein interactions, we investigated the role of defensosomes during infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). Consistent with a protective function, exosomes containing high levels of the viral receptor ACE2 in bronchoalveolar lavage fluid (BALF) from critically ill COVID-19 patients was associated with reduced intensive care unit (ICU) and hospitalization times. We found ACE2+ exosomes were induced by SARS-CoV-2 infection and activation of viral sensors in cell culture, which required the autophagy protein ATG16L1, defining these as defensosomes. We further demonstrate that ACE2+ defensosomes directly bind and block viral entry. These findings suggest that defensosomes may contribute to the antiviral response against SARS-CoV-2 and expand our knowledge on the regulation and effects of extracellular vesicles during infection.

Molecular classification has improved diagnosis and treatment for patients with malignant gliomas. However, classification has relied on individual assays that are both costly and slow, leading to frequent delays in treatment. Here, we propose the use of DNA methylation, as an emerging clinical diagnostic platform, to classify gliomas based on major genomic alterations and provide insight into subtype characteristics. We show that using machine learning models, DNA methylation signatures can accurately predict somatic alterations and show improvement over existing classifiers. The established Unified Diagnostic Pipeline (UniD) we develop is rapid and cost-effective for genomic alterations and gene expression subtypes diagnostic at early clinical phase and improves over individual assays currently in clinical use. The significant relationship between genetic alteration and epigenetic signature indicates broad applicability of our approach to other malignancies.

Mammalian cells autonomously activate hypoxia-inducible transcription factors (HIFs) to ensure survival in low-oxygen environments. We report here that injury-induced hypoxia is insufficient to trigger HIF1α in damaged epithelium. Instead, multimodal single-cell and spatial transcriptomics analyses and functional studies reveal that retinoic acid-related orphan receptor γt⁺ (RORγt⁺) γδ T cell-derived interleukin-17A (IL-17A) is necessary and sufficient to activate HIF1α. Protein kinase B (AKT) and extracellular signal-regulated kinase 1/2 (ERK1/2) signaling proximal of IL-17 receptor C (IL-17RC) activates mammalian target of rapamycin (mTOR) and consequently HIF1α. The IL-17A-HIF1α axis drives glycolysis in wound front epithelia. Epithelial-specific loss of IL-17RC, HIF1α, or blockade of glycolysis derails repair. Our findings underscore the coupling of inflammatory, metabolic, and migratory programs to expedite epithelial healing and illuminate the immune cell-derived inputs in cellular adaptation to hypoxic stress during repair.

Mitofusins reside on the outer mitochondrial membrane and regulate mitochondrial fusion, a physiological process that impacts diverse cellular processes. Mitofusins are activated by conformational changes and subsequently oligomerize to enable mitochondrial fusion. Here, we identify small molecules that directly increase or inhibit mitofusins activity by modulating mitofusin conformations and oligomerization. We use these small molecules to better understand the role of mitofusins activity in mitochondrial fusion, function, and signaling. We find that mitofusin activation increases, whereas mitofusin inhibition decreases mitochondrial fusion and functionality. Remarkably, mitofusin inhibition also induces minority mitochondrial outer membrane permeabilization followed by sub-lethal caspase-3/7 activation, which in turn induces DNA damage and upregulates DNA damage response genes. In this context, apoptotic death induced by a second mitochondria-derived activator of caspases (SMAC) mimetic is potentiated by mitofusin inhibition. These data provide mechanistic insights into the function and regulation of mitofusins as well as small molecules to pharmacologically target mitofusins.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. Here, we utilize two distinct and complementary machine learning methods of analyzing whole slide images (WSI) for predicting mutated BRAF. In the first method, WSI of melanomas from 256 patients were used to train a deep convolutional neural network (CNN) in order to develop a fully automated model that first selects for tumor-rich areas (Area Under the Curve AUC=0.96) then predicts for mutated BRAF (AUC=0.71). Saliency mapping was performed and revealed that pixels corresponding to nuclei were the most relevant to network learning. In the second method, WSI were analyzed using a pathomics pipeline that first annotates nuclei and then quantifies nuclear features, demonstrating that mutated BRAF nuclei were significantly larger and rounder nuclei compared to BRAF WT nuclei. Lastly, we developed a model that combines clinical information, deep learning, and pathomics that improves the predictive performance for mutated BRAF to AUC=0.89. Not only does this provide additional insights on how BRAF mutations affect tumor structural characteristics, machine learning-based analysis of WSI has the potential to be integrated into higher order models for understanding tumor biology.

Introduction: Gene rearrangements play a critical role in the development of brain tumors. RNA next-generation sequencing (NGS) panels cover a limited number of genes, are rarely successful in FFPE samples > 5 years old, and cannot detect rearrangements between genes and non-coding regulatory regions. We evaluated whole genome Hi-C NGS for detection of gene fusions and cryptic rearrangements.
Method(s): DNA was extracted from FFPE scrolls of 55 glial and non-glial brain tumors and processed using Arima-HiC+ FFPE Sample protocol, consisting of chromatin fragmentation, labeling, and re-ligation, followed by DNA purification and library preparation for paired-end Illumina sequencing with an average of 10X genome coverage (100M PE reads per sample). Data were analyzed using the Arima-SV pipeline using Juicer and HiCUP, SV detection using HiC-Breakfinder, loop calling using Juicer Tools, and integrative data visualization using Juicebox. Overexpression of putative driver genes was confirmed by immunohistochemistry.
Result(s): Hi-C libraries were prepared and sequenced from FFPE tissues including samples that failed RNA NGS. Hi-C successfully detected gene-gene fusions including actionable EML4-NTRK3, ETV6-NTRK3, fusions. We detected rearrangements missed by RNA NGS (i.e., complex MYBL1 rearrangement) or between non-coding regions and known cancer genes (i.e. PDL1, PAX5, NRAS, TERT, KAT6A, GATA6, and ARID1B). Since Hi-C data captures 3D genome structural features such as chromatin loops and topological domains, datasets were of high quality and capable of detecting up to 13,000 chromatin loops per tumor.
Conclusion(s): Genome-wide Hi-C NGS is successful in detecting gene fusions and cryptic rearrangements between coding and non-coding regions in archival FFPE tissue including degraded samples. Because Hi-C data captures 3D genome structures, these datasets simultaneously inform gene regulatory mechanisms that may play a role in oncogenesis or tumor progression. Whole-genome Hi-C NGS expands our ability to detect actionable and novel drivers, and potentially new therapeutic targets in a single NGS workflow

Embryos are diagnosed as mosaic if their chromosomal copy number falls between euploid and aneuploid. The purpose of this study was to investigate the impact of mosaicism on global gene expression. This study included 42 blastocysts that underwent preimplantation genetic testing for aneuploidy (PGT-A) and were donated for IRB approved research. Fourteen blastocysts were diagnosed as mosaic with Next-generation Sequencing (NGS). Three NGS diagnosed euploid embryos, and 25 aneuploid embryos (9 NGS, 14 array Comparative Genomic Hybridization, 2 Single Nucleotide Polymorphism array) were used as comparisons. RNA-sequencing was performed on all of the blastocysts. Differentially expressed genes (DEGs) were calculated using DESeq2/3.5 (R Bioconductor Package) with p < 0.05 considered significantly differentially expressed. Pathway analysis was performed on mosaic embryos using EnrichR with p < 0.05 considered significant. With euploid embryo gene expression used as a control, 12 of 14 mosaic embryos had fewer DEGs compared to aneuploid embryos involving the same chromosome. On principal component analysis (PCA), mosaic embryos mapped separately from aneuploid embryos. Pathways involving cell proliferation, differentiation, and apoptosis were the most disrupted within mosaic embryos. Mosaic embryos have decreased disruption of global gene expression compared to aneuploid embryos. This study was limited by the small sample size, lack of replicate samples for each mosaic abnormality, and use of multiple different PGT-A platforms for the diagnosis of aneuploid embryos.

ARID2 is the most recurrently mutated SWI/SNF complex member in melanoma; however, its tumor-suppressive mechanisms in the context of the chromatin landscape remain to be elucidated. Here, we model ARID2 deficiency in melanoma cells, which results in defective PBAF complex assembly with a concomitant genomic redistribution of the BAF complex. Upon ARID2 depletion, a subset of PBAF and shared BAF-PBAF-occupied regions displays diminished chromatin accessibility and associated gene expression, while BAF-occupied enhancers gain chromatin accessibility and expression of genes linked to the process of invasion. As a function of altered accessibility, the genomic occupancy of melanoma-relevant transcription factors is affected and significantly correlates with the observed transcriptional changes. We further demonstrate that ARID2-deficient cells acquire the ability to colonize distal organs in multiple animal models. Taken together, our results reveal a role for ARID2 in mediating BAF and PBAF subcomplex chromatin dynamics with consequences for melanoma metastasis.