Oncogenic deubiquitination controls tyrosine kinase signaling and therapy response in acute lymphoblastic leukemia
Dysregulation of kinase signaling pathways favors tumor cell survival and therapy resistance in cancer. Here, we reveal a posttranslational regulation of kinase signaling and nuclear receptor activity via deubiquitination in T cell acute lymphoblastic leukemia (T-ALL). We observed that the ubiquitin-specific protease 11 (USP11) is highly expressed and associates with poor prognosis in T-ALL. USP11 ablation inhibits leukemia progression in vivo, sparing normal hematopoiesis. USP11 forms a complex with USP7 to deubiquitinate the oncogenic lymphocyte cell-specific protein-tyrosine kinase (LCK) and enhance its activity. Impairment of LCK activity leads to increased glucocorticoid receptor (GR) expression and glucocorticoids sensitivity. Genetic knockout of USP7 improved the antileukemic efficacy of glucocorticoids in vivo. The transcriptional activation of GR target genes is orchestrated by the deubiquitinase activity and mediated via an increase in enhancer-promoter interaction intensity. Our data unveil how dysregulated deubiquitination controls leukemia survival and drug resistance, suggesting previously unidentified therapeutic combinations toward targeting leukemia.
Single-cell RNA sequencing reveals distinct T cell populations in immune-related adverse events of checkpoint inhibitors
PD-1 is an inhibitory receptor in T cells, and antibodies that block its interaction with ligands augment anti-tumor immune responses. The clinical potential of these agents is limited by the fact that half of all patients develop immune-related adverse events (irAEs). To generate insights into the cellular changes that occur during anti-PD-1 treatment, we performed single-cell RNA sequencing of circulating T cells collected from patients with cancer. Using the K-nearest-neighbor-based network graph-drawing layout, we show the involvement of distinctive genes and subpopulations of T cells. We identify that at baseline, patients with arthritis have fewer CD8 TCM cells, patients with pneumonitis have more CD4 TH2 cells, and patients with thyroiditis have more CD4 TH17 cells when compared with patients who do not develop irAEs. These data support the hypothesis that different populations of T cells are associated with different irAEs and that characterization of these cells' pre-treatment has the potential to serve as a toxicity-specific predictive biomarker.
Lineage-coupled clonal capture identifies clonal evolution mechanisms and vulnerabilities of BRAFV600E inhibition resistance in melanoma
Targeted cancer therapies have revolutionized treatment but their efficacies are limited by the development of resistance driven by clonal evolution within tumors. We developed "CAPTURE", a single-cell barcoding approach to comprehensively trace clonal dynamics and capture live lineage-coupled resistant cells for in-depth multi-omics analysis and functional exploration. We demonstrate that heterogeneous clones, either preexisting or emerging from drug-tolerant persister cells, dominated resistance to vemurafenib in BRAFV600E melanoma. Further integrative studies uncovered diverse resistance mechanisms. This includes a previously unrecognized and clinically relevant mechanism, chromosome 18q21 gain, which leads to vulnerability of the cells to BCL2 inhibitor. We also identified targetable common dependencies of captured resistant clones, such as oxidative phosphorylation and E2F pathways. Our study provides new therapeutic insights into overcoming therapy resistance in BRAFV600E melanoma and presents a platform for exploring clonal evolution dynamics and vulnerabilities that can be applied to study treatment resistance in other cancers.
The impact of inflammation-induced tumor plasticity during myeloid transformation
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.
DNA methylation profiling identifies subgroups of lung adenocarcinoma with distinct immune cell composition, DNA methylation age, and clinical outcome
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.
ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection
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.
DNA methylation-based epigenetic signatures predict somatic genomic alterations in gliomas
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.
Interleukin-17 governs hypoxic adaptation of injured epithelium
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 HIF1Î± in damaged epithelium. Instead, multimodal single-cell and spatial transcriptomics analyses and functional studies reveal that retinoic acid-related orphan receptor Î³t+ (RORÎ³t+) Î³Î´ T cell-derived interleukin-17A (IL-17A) is necessary and sufficient to activate HIF1Î±. 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 HIF1Î±. The IL-17A-HIF1Î± axis drives glycolysis in wound front epithelia. Epithelial-specific loss of IL-17RC, HIF1Î±, 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.
Modulating mitofusins to control mitochondrial function and signaling
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.
Deep learning and pathomics analyses reveal cell nuclei as important features for mutation prediction of BRAF-mutated melanomas
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.