scholarly journals Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

2020 ◽  
Author(s):  
Jaewon J. Lee ◽  
Vincent Bernard ◽  
Alexander Semaan ◽  
Maria E. Monberg ◽  
Jonathan Huang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Single Cell ◽  
Rna Sequencing ◽  
Clinical Decision Making ◽  
De Novo ◽  
Ex Vivo ◽  
Ductal Adenocarcinoma ◽  
Precision Oncology ◽  
Single Cell Rna Sequencing

AbstractPrecision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. However, the long-term fidelity of recently deployed ex vivo preclinical platforms, such as patient-derived organoids (PDOs) remains unknown. Through single-cell RNA sequencing (scRNA-seq), we identify substantial transcriptomic evolution of PDOs propagated from the parental tumor, which may alter predicted drug sensitivity. In contrast, scRNA-seq is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast (CAF) subclasses, and predicts for a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. While PDOs continue to enable prospective therapeutic prediction, our analysis also demonstrates the complementarity of using orthogonal de novo biopsies from PDAC patients paired with scRNA-seq to inform clinical decision-making.Statement of SignificanceThe application of single-cell RNA sequencing to diagnostic pancreatic cancer biopsies provides in-depth transcriptomic characterization of the tumor epithelium and microenvironment, while minimizing potential artifacts introduced by an intervening ex vivo passaging step. Thus, this approach can complement the use of patient-derived organoids in implementing precision oncology.

scholarly journals Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

2020 ◽  
Author(s):  
Jaewon Lee ◽  
Vincent Bernard ◽  
Alexander Semaan ◽  
Maria Monberg ◽  
Jonathan Huang ◽  
...  
Keyword(s):  
Single Cell ◽  
Clinical Decision Making ◽  
De Novo ◽  
Ex Vivo ◽  
Clinical Decision ◽  
Ductal Adenocarcinoma ◽  
Cancer Associated Fibroblast ◽  
Parental Tumor

Abstract Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. However, the long-term fidelity of recently deployed ex vivo preclinical platforms, such as patient-derived organoids (PDOs), remains unknown. Through single-cell RNA sequencing (scRNA-seq), we identify substantial transcriptomic evolution of PDOs propagated from the parental tumor, which may alter predicted drug sensitivity. In contrast, scRNA-seq is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast (CAF) subclasses, and predict a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. While PDOs continue to enable prospective therapeutic prediction, our analysis also demonstrates the complementarity of using orthogonal de novo biopsies from PDAC patients paired with scRNA-seq to inform clinical decision-making.

scholarly journals Single-cell RNA sequencing reveals ex vivo signatures of SARS-CoV-2-reactive T cells through ‘reverse phenotyping’

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David S. Fischer ◽  
Meshal Ansari ◽  
Karolin I. Wagner ◽  
Sebastian Jarosch ◽  
Yiqi Huang ◽  
...  
Keyword(s):  
T Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Ex Vivo ◽  
Severe Disease ◽  
Human Leukocyte ◽  
Cell Receptor ◽  
Single Cell Rna Sequencing

AbstractThe in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for ‘reverse phenotyping’. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.

scholarly journals MBRS-46. CHARTING NEOPLASTIC AND IMMUNE CELL HETEROGENEITY IN HUMAN AND GEM MODELS OF MEDULLOBLASTOMA USING scRNAseq

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii406-iii406
Author(s):  
Andrew Donson ◽  
Kent Riemondy ◽  
Sujatha Venkataraman ◽  
Ahmed Gilani ◽  
Bridget Sanford ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Immune Cell ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Cell Heterogeneity ◽  
Transcriptomic Data ◽  
Single Cell Rna Sequencing ◽  
Transcript Profiles

Abstract We explored cellular heterogeneity in medulloblastoma using single-cell RNA sequencing (scRNAseq), immunohistochemistry and deconvolution of bulk transcriptomic data. Over 45,000 cells from 31 patients from all main subgroups of medulloblastoma (2 WNT, 10 SHH, 9 GP3, 11 GP4 and 1 GP3/4) were clustered using Harmony alignment to identify conserved subpopulations. Each subgroup contained subpopulations exhibiting mitotic, undifferentiated and neuronal differentiated transcript profiles, corroborating other recent medulloblastoma scRNAseq studies. The magnitude of our present study builds on the findings of existing studies, providing further characterization of conserved neoplastic subpopulations, including identification of a photoreceptor-differentiated subpopulation that was predominantly, but not exclusively, found in GP3 medulloblastoma. Deconvolution of MAGIC transcriptomic cohort data showed that neoplastic subpopulations are associated with major and minor subgroup subdivisions, for example, photoreceptor subpopulation cells are more abundant in GP3-alpha. In both GP3 and GP4, higher proportions of undifferentiated subpopulations is associated with shorter survival and conversely, differentiated subpopulation is associated with longer survival. This scRNAseq dataset also afforded unique insights into the immune landscape of medulloblastoma, and revealed an M2-polarized myeloid subpopulation that was restricted to SHH medulloblastoma. Additionally, we performed scRNAseq on 16,000 cells from genetically engineered mouse (GEM) models of GP3 and SHH medulloblastoma. These models showed a level of fidelity with corresponding human subgroup-specific neoplastic and immune subpopulations. Collectively, our findings advance our understanding of the neoplastic and immune landscape of the main medulloblastoma subgroups in both humans and GEM models.

scholarly journals Critical changes in hypothalamic gene networks in response to pancreatic cancer as found by single-cell RNA sequencing

2022 ◽  
pp. 101441
Author(s):  
Christian Huisman ◽  
Mason A. Norgard ◽  
Peter R. Levasseur ◽  
Stephanie M. Krasnow ◽  
Monique G.P. van der Wijst ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Single Cell ◽  
Rna Sequencing ◽  
Gene Networks ◽  
Single Cell Rna Sequencing

scholarly journals Integrated Single-Cell RNA-Sequencing Analysis of Aquaporin 5-Expressing Mouse Lung Epithelial Cells Identifies GPRC5A as a Novel Validated Type I Cell Surface Marker

Cells ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 2460 ◽  
Author(s):  
Masafumi Horie ◽  
Alessandra Castaldi ◽  
Mitsuhiro Sunohara ◽  
Hongjun Wang ◽  
Yanbin Ji ◽  
...  
Keyword(s):  
Cell Surface ◽  
Single Cell ◽  
Rna Sequencing ◽  
Surface Marker ◽  
Mouse Lung ◽  
Type I ◽  
Cell Markers ◽  
Lung Epithelial ◽  
Single Cell Rna Sequencing

Molecular and functional characterization of alveolar epithelial type I (AT1) cells has been challenging due to difficulty in isolating sufficient numbers of viable cells. Here we performed single-cell RNA-sequencing (scRNA-seq) of tdTomato+ cells from lungs of AT1 cell-specific Aqp5-Cre-IRES-DsRed (ACID);R26tdTomato reporter mice. Following enzymatic digestion, CD31-CD45-E-cadherin+tdTomato+ cells were subjected to fluorescence-activated cell sorting (FACS) followed by scRNA-seq. Cell identity was confirmed by immunofluorescence using cell type-specific antibodies. After quality control, 92 cells were analyzed. Most cells expressed ‘conventional’ AT1 cell markers (Aqp5, Pdpn, Hopx, Ager), with heterogeneous expression within this population. The remaining cells expressed AT2, club, basal or ciliated cell markers. Integration with public datasets identified three robust AT1 cell- and lung-enriched genes, Ager, Rtkn2 and Gprc5a, that were conserved across species. GPRC5A co-localized with HOPX and was not expressed in AT2 or airway cells in mouse, rat and human lung. GPRC5A co-localized with AQP5 but not pro-SPC or CC10 in mouse lung epithelial cell cytospins. We enriched mouse AT1 cells to perform molecular phenotyping using scRNA-seq. Further characterization of putative AT1 cell-enriched genes revealed GPRC5A as a conserved AT1 cell surface marker that may be useful for AT1 cell isolation.

scholarly journals Pancreatic cancer is marked by complement-high blood monocytes and tumor-associated macrophages

2021 ◽  
Vol 4 (6) ◽  
pp. e202000935
Author(s):  
Samantha B Kemp ◽  
Nina G Steele ◽  
Eileen S Carpenter ◽  
Katelyn L Donahue ◽  
Grace G Bushnell ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Rna Sequencing ◽  
Gene Expression Signature ◽  
Ductal Adenocarcinoma ◽  
Specific Gene ◽  
Sequencing Analysis ◽  
Tumor Associated Macrophages ◽  
Primary Tumors ◽  
Single Cell Rna Sequencing

Pancreatic ductal adenocarcinoma (PDA) is accompanied by reprogramming of the local microenvironment, but changes at distal sites are poorly understood. We implanted biomaterial scaffolds, which act as an artificial premetastatic niche, into immunocompetent tumor-bearing and control mice, and identified a unique tumor-specific gene expression signature that includes high expression of C1qa, C1qb, Trem2, and Chil3. Single-cell RNA sequencing mapped these genes to two distinct macrophage populations in the scaffolds, one marked by elevated C1qa, C1qb, and Trem2, the other with high Chil3, Ly6c2 and Plac8. In mice, expression of these genes in the corresponding populations was elevated in tumor-associated macrophages compared with macrophages in the normal pancreas. We then analyzed single-cell RNA sequencing from patient samples, and determined expression of C1QA, C1QB, and TREM2 is elevated in human macrophages in primary tumors and liver metastases. Single-cell sequencing analysis of patient blood revealed a substantial enrichment of the same gene signature in monocytes. Taken together, our study identifies two distinct tumor-associated macrophage and monocyte populations that reflects systemic immune changes in pancreatic ductal adenocarcinoma patients.

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