Faculty Bibliography
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Total Results:
109
Tumor-intrinsic LKB1-LIF signaling axis establishes a myeloid niche to promote immune evasion and tumor growth
Tumor mutations can influence the surrounding microenvironment leading to suppression of anti-tumor immune responses and thereby contributing to tumor progression and failure of cancer therapies. Here we use genetically engineered lung cancer mouse models and patient samples to dissect how LKB1 mutations accelerate tumor growth by reshaping the immune microenvironment. Comprehensive immune profiling of LKB1 -mutant vs wildtype tumors revealed dramatic changes in myeloid cells, specifically enrichment of Arg1 + interstitial macrophages and SiglecF Hi neutrophils. We discovered a novel mechanism whereby autocrine LIF signaling in Lkb1 -mutant tumors drives tumorigenesis by reprogramming myeloid cells in the immune microenvironment. Inhibiting LIF signaling in Lkb1 -mutant tumors, via gene targeting or with a neutralizing antibody, resulted in a striking reduction in Arg1 + interstitial macrophages and SiglecF Hi neutrophils, expansion of antigen specific T cells, and inhibition of tumor progression. Thus, targeting LIF signaling provides a new therapeutic approach to reverse the immunosuppressive microenvironment of LKB1 -mutant tumors.
PMCID:10370066
PMID: 37502974
ISSN: 2692-8205
CID: 5743132
Author Correction: Single-cell RNA sequencing reveals the effects of chemotherapy on human pancreatic adenocarcinoma and its tumor microenvironment
PMID: 37400453
ISSN: 2041-1723
CID: 5539082
Calcitonin Related Polypeptide Alpha Mediates Oral Cancer Pain
Oral cancer patients suffer pain at the site of the cancer. Calcitonin gene related polypeptide (CGRP), a neuropeptide expressed by a subset of primary afferent neurons, promotes oral cancer growth. CGRP also mediates trigeminal pain (migraine) and neurogenic inflammation. The contribution of CGRP to oral cancer pain is investigated in the present study. The findings demonstrate that CGRP-immunoreactive (-ir) neurons and neurites innervate orthotopic oral cancer xenograft tumors in mice. Cancer increases anterograde transport of CGRP in axons innervating the tumor, supporting neurogenic secretion as the source of CGRP in the oral cancer microenvironment. CGRP antagonism reverses oral cancer nociception in preclinical oral cancer pain models. Single-cell RNA-sequencing is used to identify cell types in the cancer microenvironment expressing the CGRP receptor components, receptor activity modifying protein 1 Ramp1 and calcitonin receptor like receptor (CLR, encoded by Calcrl). Ramp1 and Calcrl transcripts are detected in cells expressing marker genes for Schwann cells, endothelial cells, fibroblasts and immune cells. Ramp1 and Calcrl transcripts are more frequently detected in cells expressing fibroblast and immune cell markers. This work identifies CGRP as mediator of oral cancer pain and suggests the antagonism of CGRP to alleviate oral cancer pain.
PMCID:10341289
PMID: 37443709
ISSN: 2073-4409
CID: 5535282
Spatial transcriptomics stratifies psoriatic disease severity by emergent cellular ecosystems
Whereas the cellular and molecular features of human inflammatory skin diseases are well characterized, their tissue context and systemic impact remain poorly understood. We thus profiled human psoriasis (PsO) as a prototypic immune-mediated condition with a high predilection for extracutaneous involvement. Spatial transcriptomics (ST) analyses of 25 healthy, active lesion, and clinically uninvolved skin biopsies and integration with public single-cell transcriptomics data revealed marked differences in immune microniches between healthy and inflamed skin. Tissue-scale cartography further identified core disease features across all active lesions, including the emergence of an inflamed suprabasal epidermal state and the presence of B lymphocytes in lesional skin. Both lesional and distal nonlesional samples were stratified by skin disease severity and not by the presence of systemic disease. This segregation was driven by macrophage-, fibroblast-, and lymphatic-enriched spatial regions with gene signatures associated with metabolic dysfunction. Together, these findings suggest that mild and severe forms of PsO have distinct molecular features and that severe PsO may profoundly alter the cellular and metabolic composition of distal unaffected skin sites. In addition, our study provides a valuable resource for the research community to study spatial gene organization of healthy and inflamed human skin.
PMID: 37267384
ISSN: 2470-9468
CID: 5536642
A neonatal mouse model characterizes transmissibility of SARS-CoV-2 variants and reveals a role for ORF8
Small animal models have been a challenge for the study of SARS-CoV-2 transmission, with most investigators using golden hamsters or ferrets. Mice have the advantages of low cost, wide availability, less regulatory and husbandry challenges, and the existence of a versatile reagent and genetic toolbox. However, adult mice do not robustly transmit SARS-CoV-2. Here we establish a model based on neonatal mice that allows for transmission of clinical SARS-CoV-2 isolates. We characterize tropism, respiratory tract replication and transmission of ancestral WA-1 compared to variants Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), Omicron BA.1 and Omicron BQ.1.1. We identify inter-variant differences in timing and magnitude of infectious particle shedding from index mice, both of which shape transmission to contact mice. Furthermore, we characterize two recombinant SARS-CoV-2 lacking either the ORF6 or ORF8 host antagonists. The removal of ORF8 shifts viral replication towards the lower respiratory tract, resulting in significantly delayed and reduced transmission in our model. Our results demonstrate the potential of our neonatal mouse model to characterize viral and host determinants of SARS-CoV-2 transmission, while revealing a role for an accessory protein in this context.
PMID: 37230979
ISSN: 2041-1723
CID: 5508612
American journal of respiratory cell & molecular biology. 2023:68(5):523-536.DOI: 10.1165/rcmb.2022-0269OC
Hedgehog and PDGF Signaling Intersect During Postnatal Lung Development
Normal lung development critically depends on Hedgehog (HH) and Platelet-derived growth factor (PDGF) signaling, which coordinate mesenchymal differentiation and proliferation. PDGF signaling is required for postnatal alveolar septum formation by myofibroblasts. Recently, we demonstrated a requirement for HH in postnatal lung development involving alveolar myofibroblast differentiation. Given shared features of HH and PDGF signaling and their impact/convergence on this key cell type, we sought to clarify their relationship during murine postnatal lung development. Timed experiments revealed that HH inhibition phenocopies the key lung myofibroblast phenotypes of Pdgfa and Pdgfra knockouts during secondary alveolar septation. Utilizing a dual signaling reporter, Gli1IZ;PdgfraEGFP
PMID: 36693140
ISSN: 1535-4989
CID: 5419542
A neonatal mouse model characterizes transmissibility of SARS-CoV-2 variants and reveals a role for ORF8
Small animal models have been a challenge for the study of SARS-CoV-2 transmission, with most investigators using golden hamsters or ferrets 1,2 . Mice have the advantages of low cost, wide availability, less regulatory and husbandry challenges, and the existence of a versatile reagent and genetic toolbox. However, adult mice do not transmit SARS-CoV-2 3 . Here we establish a model based on neonatal mice that allows for transmission of clinical SARS-CoV-2 isolates. We characterize tropism, respiratory tract replication and transmission of ancestral WA-1 compared to variants alpha (B.1.1.7), beta (B.1.351), gamma (P.1), delta (B.1.617.2) and omicron (B.1.1.529). We identify inter-variant differences in timing and magnitude of infectious particle shedding from index mice, both of which shape transmission to contact mice. Furthermore, we characterize two recombinant SARS-CoV-2 lacking either the ORF6 or ORF8 host antagonists. The removal of ORF8 shifts viral replication towards the lower respiratory tract, resulting in significantly delayed and reduced transmission. Our results demonstrate the potential of our neonatal mouse model to characterize viral and host determinants of SARS-CoV-2 transmission, while revealing for the first time a role for an accessory protein this context.
PMCID:9558433
PMID: 36238716
ISSN: 2692-8205
CID: 5390862
Single-cell RNA sequencing reveals the effects of chemotherapy on human pancreatic adenocarcinoma and its tumor microenvironment
The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perform single-cell RNA sequencing on freshly collected human PDAC samples either before or after chemotherapy. Overall, we find a heterogeneous mixture of basal and classical cancer cell subtypes, along with distinct cancer-associated fibroblast and macrophage subpopulations. Strikingly, classical and basal-like cancer cells exhibit similar transcriptional responses to chemotherapy and do not demonstrate a shift towards a basal-like transcriptional program among treated samples. We observe decreased ligand-receptor interactions in treated samples, particularly between TIGIT on CD8 + T cells and its receptor on cancer cells, and identify TIGIT as the major inhibitory checkpoint molecule of CD8 + T cells. Our results suggest that chemotherapy profoundly impacts the PDAC TME and may promote resistance to immunotherapy.
PMCID:9925748
PMID: 36781852
ISSN: 2041-1723
CID: 5427092
Spatial Transcriptomics Stratifies Health and Psoriatic Disease Severity by Emergent Cellular Ecosystems [Meeting Abstract]
Background/Purpose: The skin is recognized as a window into the immunopathogenic mechanisms driving the vast phenotypic spectrum of psoriatic disease.
Method(s): To better decipher the cellular landscape of both healthy and psoriatic skin, we employed spatial transcriptomics (ST), a ground-breaking technology that precisely maps gene expression from histologically-intact tissue sections (Fig. 1A).
Result(s): Findings gleaned from computationally integrating our 23 matched lesional and non-lesional psoriatic and 7 healthy control samples with publicly-available single-cell ribonucleic acid (RNA) sequencing datasets established the ability of ST to recapitulate the tissue architecture of both healthy and inflamed skin (Fig. 1B) and highlighted topographic shifts in the immune cell milieu, from a predominantly perifollicular distribution in steady-state skin to the papillary and upper reticular dermis in psoriatic lesional skin. We also incidentally discovered that ST's ability to ascertain gene expression patterns from intact tissue rendered it particularly conducive to studying the transcriptome of lipid-laden cells such as dermal adipose tissue and sebaceous glands (Fig. 1C), whose expression profiles are typically lost in the process of tissue handling and dissociation for bulk and single-cell RNA seq. Unbiased clustering of pooled healthy and psoriatic samples identified two epidermal clusters and one dermal cluster that were differentially expanded in psoriatic lesional skin (p values <=0.05) (Fig. 1D); pathway analysis of these clusters revealed enrichment of known psoriatic inflammatory pathways (Fig. 1E). Unsupervised classification of skin-limited psoriasis and psoriatic arthritis samples revealed stratification by cutaneous disease severity or Psoriasis Area and Severity Index (PASI) score and not by presence or absence of concomitant systemic/synovial disease (Fig. 1F). Remarkably, this PASI-dependent segregation was also evident in distal, non-lesional samples and was driven by the dermal macrophage and fibroblast cluster and the lymphatic endothelium (Fig. 2A). Inquiry into the mechanistic drivers of this observed stratification yielded enrichment of pathways associated with key T cell and innate immune cell activation, B cells, and metabolic dysfunction (Fig. 2B). Finally, tissue scale computational cartography of gene expression revealed differences in regional enrichment of specific cell types across phenotypic groups, most notably upward extension of fibroblasts to the upper dermis in both lesional and non-lesional samples from mild psoriasis and restriction to the lower dermis in the moderate-to-severe psoriasis samples (Fig. 2C), suggesting that disease severity stratification may be driven by emergent cellular ecosystems in the upper dermis. Fig. 1. (A) Schematic of spatial transcriptomics study workflow. Four mm skin punch biopsies were obtained from healthy volunteers (n=3) and lesional and non-lesional skin from patients with psoriatic disease (n=11). Ten micron-thick sections were then placed on capture areas on the ST microarray slide, each containing molecularly barcoded, spatially encoded spots with a diameter of 50 microns and a center-to-center distance of 100 microns. (B) Side-by-side comparison of a hematoxylin-eosin (H&E) stained section of representative healthy, lesional, and non-lesional skin samples and the corresponding ST plots showed concordance of unbiased gene expression-based clustering with histologic tissue architecture. (C) Pathway analysis of the adipose cluster in healthy skin (cluster 2) confirmed upregulation of lipid-associated processes. Inset: Spots corresponding to the adipose cluster highlighted in yellow. (D) Wilcoxon rank sum test (results displayed as box plots) yielded statistically significant expansion of three clusters in lesional skin compared to both non-lesional and healthy skin-inflamed suprabasal epidermis (cluster 4), epidermis 2 (cluster 7), and inflamed dermis (cluster 10). HC=healthy control, L=lesional psoriatic skin, NL=non-lesional psoriatic skin. (E) Pathways enriched in clusters 4, 7, and 10. (F) Principal component analysis (PCA) plots demonstrating segregation of samples by severity of cutaneous disease in both lesional and non-lesional samples along the first principal component (right) that was not seen in the samples categorized according to presence or absence of arthritis (left). PsA=psoriatic arthritis, PsO=skin-limited psoriasis. Fig. 2. (A) PCA of lesional and non-lesional samples colored by disease severity in spatial clusters 1 (left) and 12 (right) revealed more discrete clustering. (B) Pathways significantly enriched in clusters 1 (left) and 12 (right) showed enrichment of pathways associated with key T cell and innate immune cell activation, B cells, and metabolic dysfunction (highlighted in red). (C) SpaceFold one dimension projection of cell distribution from an independently-generated single-cell RNA seq data set on aggregated ST lesional and non-lesional samples from mild (PASI-low) and moderate-severe (PASI-high) samples. Y-axis represents tissue position, starting with the lower dermis marked as position 0 to suprabasal epidermis marked as position 1. Dashed line represents epidermal-dermal junction, discerned by cell types in the basal epidermal layer (melanocytes and Langerhans cells). Fibroblast signatures (red arrows) were largely relegated to the lower dermis in the PASI-high group, but extended to the upper dermis in the PASI-low group. This striking difference in fibroblast localization was also noted in non-lesional PASI-high vs. PASI-low groups. In addition to fibroblasts, lymphatic, endothelial, myeloid, and T cells signatures (black arrows) were also observed in the upper dermis of lesional PASI-low samples, but were much lower in the dermis of PASI-low non-lesional and all samples in the PASI-high group. Interfollicular epidermis (IFE), hair follicle and infundibulum (HF/IFN), n= number of individual biopsies.
Conclusion(s): Thus, we have been able to successfully leverage ST integrated with independently-generated single-cell RNA seq data to spatially define the emergent cellular ecosystems of healthy and matched psoriatic lesional and non-lesional skin and in so doing, demonstrated the value of ST in unearthing the genetic groundwork at both the site of inflammation and in distal, clinically-uninvolved skin
Method(s): To better decipher the cellular landscape of both healthy and psoriatic skin, we employed spatial transcriptomics (ST), a ground-breaking technology that precisely maps gene expression from histologically-intact tissue sections (Fig. 1A).
Result(s): Findings gleaned from computationally integrating our 23 matched lesional and non-lesional psoriatic and 7 healthy control samples with publicly-available single-cell ribonucleic acid (RNA) sequencing datasets established the ability of ST to recapitulate the tissue architecture of both healthy and inflamed skin (Fig. 1B) and highlighted topographic shifts in the immune cell milieu, from a predominantly perifollicular distribution in steady-state skin to the papillary and upper reticular dermis in psoriatic lesional skin. We also incidentally discovered that ST's ability to ascertain gene expression patterns from intact tissue rendered it particularly conducive to studying the transcriptome of lipid-laden cells such as dermal adipose tissue and sebaceous glands (Fig. 1C), whose expression profiles are typically lost in the process of tissue handling and dissociation for bulk and single-cell RNA seq. Unbiased clustering of pooled healthy and psoriatic samples identified two epidermal clusters and one dermal cluster that were differentially expanded in psoriatic lesional skin (p values <=0.05) (Fig. 1D); pathway analysis of these clusters revealed enrichment of known psoriatic inflammatory pathways (Fig. 1E). Unsupervised classification of skin-limited psoriasis and psoriatic arthritis samples revealed stratification by cutaneous disease severity or Psoriasis Area and Severity Index (PASI) score and not by presence or absence of concomitant systemic/synovial disease (Fig. 1F). Remarkably, this PASI-dependent segregation was also evident in distal, non-lesional samples and was driven by the dermal macrophage and fibroblast cluster and the lymphatic endothelium (Fig. 2A). Inquiry into the mechanistic drivers of this observed stratification yielded enrichment of pathways associated with key T cell and innate immune cell activation, B cells, and metabolic dysfunction (Fig. 2B). Finally, tissue scale computational cartography of gene expression revealed differences in regional enrichment of specific cell types across phenotypic groups, most notably upward extension of fibroblasts to the upper dermis in both lesional and non-lesional samples from mild psoriasis and restriction to the lower dermis in the moderate-to-severe psoriasis samples (Fig. 2C), suggesting that disease severity stratification may be driven by emergent cellular ecosystems in the upper dermis. Fig. 1. (A) Schematic of spatial transcriptomics study workflow. Four mm skin punch biopsies were obtained from healthy volunteers (n=3) and lesional and non-lesional skin from patients with psoriatic disease (n=11). Ten micron-thick sections were then placed on capture areas on the ST microarray slide, each containing molecularly barcoded, spatially encoded spots with a diameter of 50 microns and a center-to-center distance of 100 microns. (B) Side-by-side comparison of a hematoxylin-eosin (H&E) stained section of representative healthy, lesional, and non-lesional skin samples and the corresponding ST plots showed concordance of unbiased gene expression-based clustering with histologic tissue architecture. (C) Pathway analysis of the adipose cluster in healthy skin (cluster 2) confirmed upregulation of lipid-associated processes. Inset: Spots corresponding to the adipose cluster highlighted in yellow. (D) Wilcoxon rank sum test (results displayed as box plots) yielded statistically significant expansion of three clusters in lesional skin compared to both non-lesional and healthy skin-inflamed suprabasal epidermis (cluster 4), epidermis 2 (cluster 7), and inflamed dermis (cluster 10). HC=healthy control, L=lesional psoriatic skin, NL=non-lesional psoriatic skin. (E) Pathways enriched in clusters 4, 7, and 10. (F) Principal component analysis (PCA) plots demonstrating segregation of samples by severity of cutaneous disease in both lesional and non-lesional samples along the first principal component (right) that was not seen in the samples categorized according to presence or absence of arthritis (left). PsA=psoriatic arthritis, PsO=skin-limited psoriasis. Fig. 2. (A) PCA of lesional and non-lesional samples colored by disease severity in spatial clusters 1 (left) and 12 (right) revealed more discrete clustering. (B) Pathways significantly enriched in clusters 1 (left) and 12 (right) showed enrichment of pathways associated with key T cell and innate immune cell activation, B cells, and metabolic dysfunction (highlighted in red). (C) SpaceFold one dimension projection of cell distribution from an independently-generated single-cell RNA seq data set on aggregated ST lesional and non-lesional samples from mild (PASI-low) and moderate-severe (PASI-high) samples. Y-axis represents tissue position, starting with the lower dermis marked as position 0 to suprabasal epidermis marked as position 1. Dashed line represents epidermal-dermal junction, discerned by cell types in the basal epidermal layer (melanocytes and Langerhans cells). Fibroblast signatures (red arrows) were largely relegated to the lower dermis in the PASI-high group, but extended to the upper dermis in the PASI-low group. This striking difference in fibroblast localization was also noted in non-lesional PASI-high vs. PASI-low groups. In addition to fibroblasts, lymphatic, endothelial, myeloid, and T cells signatures (black arrows) were also observed in the upper dermis of lesional PASI-low samples, but were much lower in the dermis of PASI-low non-lesional and all samples in the PASI-high group. Interfollicular epidermis (IFE), hair follicle and infundibulum (HF/IFN), n= number of individual biopsies.
Conclusion(s): Thus, we have been able to successfully leverage ST integrated with independently-generated single-cell RNA seq data to spatially define the emergent cellular ecosystems of healthy and matched psoriatic lesional and non-lesional skin and in so doing, demonstrated the value of ST in unearthing the genetic groundwork at both the site of inflammation and in distal, clinically-uninvolved skin
EMBASE:639965553
ISSN: 2326-5205
CID: 5513112
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 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.
PMID: 35709248
ISSN: 1095-9203
CID: 5268732
