scholarly journals Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution

2019 ◽  
Author(s):  
Abdel Nasser Hosein ◽  
Huocong Huang ◽  
Zhaoning Wang ◽  
Kamalpreet Parmar ◽  
Wenting Du ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Ductal Adenocarcinoma ◽  
Cell Populations ◽  
Specific Cell ◽  
Cell Heterogeneity ◽  
Mesenchymal Transition

AbstractBackground & AimsPancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression. The progression of PDA is a highly complex and dynamic process featuring changes in cancer cells and stromal cells; however, a comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression.MethodsWe employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models.ResultsOur data indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor progression. We also found distinct populations of macrophages with increasing inflammatory features during PDA progression. In addition, we noted the existence of three distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts are dynamically regulated by epigenetic mechanisms.ConclusionThis study systematically outlines the landscape of cellular heterogeneity during the progression of PDA. It strongly improves our understanding of the PDA biology and has the potential to aid in the development of therapeutic strategies against specific cell populations of the disease.

scholarly journals Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15739-e15739
Author(s):  
Abdel Nasser Hosein ◽  
Huocong Huang ◽  
Zhaoning Wang ◽  
Kamalpreet Parmar ◽  
Wenting Du ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Genetically Engineered ◽  
Cellular Heterogeneity ◽  
Ductal Adenocarcinoma ◽  
Cell Populations ◽  
Specific Cell ◽  
Cell Heterogeneity ◽  
Mesenchymal Transition

e15739 Background: Pancreatic ductal adenocarcinoma (PDA) is a major cause of cancer-related death with limited therapeutic options available. This highlights the need for improved understanding of the biology of PDA progression. The progression of PDA is a highly complex and dynamic process featuring changes in cancer cells and stromal cells; however, a comprehensive characterization of PDA cancer cell and stromal cell heterogeneity during disease progression is lacking. In this study, we aimed to profile cell populations and understand their phenotypic changes during PDA progression. Methods: We employed single-cell RNA sequencing technology to agnostically profile cell heterogeneity during different stages of PDA progression in genetically engineered mouse models. Results: Our data indicate that an epithelial-to-mesenchymal transition of cancer cells accompanies tumor progression. We also found distinct populations of macrophages with increasing inflammatory features during PDA progression. In addition, we noted the existence of three distinct molecular subtypes of fibroblasts in the normal mouse pancreas, which ultimately gave rise to two distinct populations of fibroblasts in advanced PDA, supporting recent reports on intratumoral fibroblast heterogeneity. Our data also suggest that cancer cells and fibroblasts are dynamically regulated by epigenetic mechanisms. Conclusions: This study systematically outlines the landscape of cellular heterogeneity during the progression of PDA. It strongly improves our understanding of the PDA biology and has the potential to aid in the development of therapeutic strategies against specific cell populations of the disease.

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 Synovial single-cell heterogeneity, zonation, and interactions: a patchwork of effectors in arthritis

Rheumatology ◽  
2021 ◽  
Author(s):  
Barbora Schonfeldova ◽  
Kristina Zec ◽  
Irina A Udalova
Keyword(s):  
Rheumatoid Arthritis ◽  
Single Cell ◽  
Cell Signalling ◽  
Synovial Cell ◽  
Cellular Heterogeneity ◽  
Cell Populations ◽  
Single Cell Level ◽  
Cell Heterogeneity ◽  
Cell Level ◽  
Peripheral Neurons

Abstract Despite extensive research, there is still no treatment that would lead to remission in all patients with rheumatoid arthritis as our understanding of the affected site, the synovium, is still incomplete. Recently, single-cell technologies helped to decipher the cellular heterogeneity of the synovium; however, certain synovial cell populations, such as endothelial cells or peripheral neurons, remain to be profiled on a single-cell level. Furthermore, associations between certain cellular states and inflammation were found; whether these cells cause the inflammation remains to be answered. Similarly, cellular zonation and interactions between individual effectors in the synovium are yet to be fully determined. A deeper understanding of cell signalling and interactions in the synovium is crucial for a better design of therapeutics with the goal of complete remission in all patients.

scholarly journals Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

2019 ◽  
Author(s):  
Gabriela S. Kinker ◽  
Alissa C. Greenwald ◽  
Rotem Tal ◽  
Zhanna Orlova ◽  
Michael S. Cuoco ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines ◽  
Human Tumors ◽  
Model Systems ◽  
Cellular Heterogeneity ◽  
Specific Cell ◽  
Rna Seq ◽  
Mesenchymal Transition

AbstractCultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

scholarly journals Single-cell analysis of pancreatic ductal adenocarcinoma identifies a novel fibroblast subtype associated with poor prognosis but better immunotherapy response

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Yu Wang ◽  
Yiyi Liang ◽  
Haiyan Xu ◽  
Xiao Zhang ◽  
Tiebo Mao ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Immune Cells ◽  
Poor Prognosis ◽  
Single Cell Analysis ◽  
Treatment Options ◽  
Objective Response ◽  
Complete Response ◽  
Ductal Adenocarcinoma

AbstractThe current pathological and molecular classification of pancreatic ductal adenocarcinoma (PDAC) provides limited guidance for treatment options, especially for immunotherapy. Cancer-associated fibroblasts (CAFs) are major players of desmoplastic stroma in PDAC, modulating tumor progression and therapeutic response. Using single-cell RNA sequencing, we explored the intertumoral heterogeneity among PDAC patients with different degrees of desmoplasia. We found substantial intertumoral heterogeneity in CAFs, ductal cancer cells, and immune cells between the extremely dense and loose types of PDACs (dense-type, high desmoplasia; loose-type, low desmoplasia). Notably, no difference in CAF abundance was detected, but a novel subtype of CAFs with a highly activated metabolic state (meCAFs) was found in loose-type PDAC compared to dense-type PDAC. MeCAFs had highly active glycolysis, whereas the corresponding cancer cells used oxidative phosphorylation as a major metabolic mode rather than glycolysis. We found that the proportion and activity of immune cells were much higher in loose-type PDAC than in dense-type PDAC. Then, the clinical significance of the CAF subtypes was further validated in our PDAC cohort and a public database. PDAC patients with abundant meCAFs had a higher risk of metastasis and a poor prognosis but showed a dramatically better response to immunotherapy (64.71% objective response rate, one complete response). We characterized the intertumoral heterogeneity of cellular components, immune activity, and metabolic status between dense- and loose-type PDACs and identified meCAFs as a novel CAF subtype critical for PDAC progression and the susceptibility to immunotherapy.

scholarly journals Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution

JCI Insight ◽  
2019 ◽  
Vol 4 (16) ◽  
Author(s):  
Abdel Nasser Hosein ◽  
Huocong Huang ◽  
Zhaoning Wang ◽  
Kamalpreet Parmar ◽  
Wenting Du ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cellular Heterogeneity ◽  
Ductal Adenocarcinoma

scholarly journals Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets

2019 ◽  
Author(s):  
Haruka Ozaki ◽  
Tetsutaro Hayashi ◽  
Mana Umeda ◽  
Itoshi Nikaido
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cellular Heterogeneity ◽  
Specific Cell ◽  
Read Coverage ◽  
Cell Heterogeneity ◽  
Sequencing Data ◽  
Rna Transcription ◽  
Link Type ◽  
Single Cell Rna Sequencing

AbstractBackgroundRead coverage of RNA sequencing data reflects gene expression and RNA processing events. Single-cell RNA sequencing (scRNA-seq) methods, particularly “full-length” ones, provide read coverage of many individual cells and have the potential to reveal cellular heterogeneity in RNA transcription and processing. However, visualization tools suited to highlighting cell-to-cell heterogeneity in read coverage are still lacking.ResultsHere, we have developed Millefy, a tool for visualizing read coverage of scRNA-seq data in genomic contexts. Millefy is designed to show read coverage of all individual cells at once in genomic contexts and to highlight cell-to-cell heterogeneity in read coverage. By visualizing read coverage of all cells as a heat map and dynamically reordering cells based on diffusion maps, Millefy facilitates discovery of “local” region-specific, cell-to-cell heterogeneity in read coverage, including variability of transcribed regions.ConclusionsMillefy simplifies the examination of cellular heterogeneity in RNA transcription and processing events using scRNA-seq data. Millefy is available as an R package (https://github.com/yuifu/millefy) and a Docker image to help use Millefy on the Jupyter notebook (https://hub.docker.com/r/yuifu/datascience-notebook-millefy).

scholarly journals A Cancer Cell Cluster Marked by LincRNA MEG3 Leads Pancreatic Ductal Adenocarcinoma Metastasis

2021 ◽  
Vol 11 ◽  
Author(s):  
Hong Pan ◽  
Huanrong Diao ◽  
Wen Zhong ◽  
Taifang Wang ◽  
Ping Wen ◽  
...  
Keyword(s):  
Single Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Metastasis ◽  
Epithelial Mesenchymal Transition ◽  
Critical Role ◽  
Marker Gene ◽  
Differentially Expressed Gene ◽  
Ductal Adenocarcinoma ◽  
Multiple Cancer ◽  
Mesenchymal Transition

Pancreatic ductal adenocarcinoma (PDAC) is a highly devastating disease with poor prognosis and rising incidence worldwide. Late detection and particularly aggressive characteristics are the major challenges that lead to therapeutic failure of this disease. A well described gene program and core regulators are yet to be discovered to drive the metastasis of the PDAC cells. As the development of single cell omics technologies including single cell RNA-sequencing (scRNA-seq), detailed characterization of the cellular composition of solid tumors and their microenvironments are well elaborated. In the current study, we accessed a recently published scRNA-seq dataset on primary and metastatic PDAC tissues and subset the tumor cells. By comparative analysis, we profiled the differentially expressed gene programs of primary and metastatic PDAC and found several long intergenic non-coding RNAs (LincRNAs) in top genes. The PDAC cancer cells showed some heterogeneity and were divided into four major subclusters based on gene profiles, one of which was mostly contributed by metastatic PDAC. Interestingly, this subcluster was remarkably marked by one of the above LincRNAs, MEG3, and exhibited significantly increased Epithelial–Mesenchymal-Transition (EMT) signatures. Ingenuity Pathway Analysis (IPA) on the signature genes of this subcluster gave multiple cancer metastasis associated and EMT signaling pathways, suggesting a critical role of this cluster in leading tumor cell metastasis. Taken together, this study displayed a PDAC cancer subcluster and its marker gene, biologically targeting of which might significantly attenuate the metastasis of tumor and might be a potential strategy for the therapeutic treatment of cancer.

scholarly journals A Comparative Endocrine Trans-Differentiation Approach to Pancreatic Ductal Adenocarcinoma Cells with Different EMT Phenotypes Identifies Quasi-Mesenchymal Tumor Cells as Those with Highest Plasticity

Cancers ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 4663
Author(s):  
Paula M. Schmidtlein ◽  
Clara Volz ◽  
Rüdiger Braun ◽  
Isabel Thürling ◽  
Olha Lapshyna ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Cell Lines ◽  
Human Pancreatic Cancer ◽  
Ductal Adenocarcinoma ◽  
Β Cell ◽  
Differentiation Potential ◽  
Mesenchymal Transition ◽  
Endocrine Differentiation ◽  
Pancreatic Cancer Cells

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and therapy-resistant cancer types which is largely due to tumor heterogeneity, cancer cell de-differentiation, and early metastatic spread. The major molecular subtypes of PDAC are designated classical/epithelial (E) and quasi-mesenchymal (QM) subtypes, with the latter having the worst prognosis. Epithelial–mesenchymal transition (EMT) and the reverse process, mesenchymal-epithelial transition (MET), are involved in regulating invasion/metastasis and stem cell generation in cancer cells but also early pancreatic endocrine differentiation or de-differentiation of adult pancreatic islet cells in vitro, suggesting that pancreatic ductal exocrine and endocrine cells share common EMT programs. Using a panel of PDAC-derived cell lines classified by epithelial/mesenchymal expression as either E or QM, we compared their trans-differentiation (TD) potential to endocrine progenitor or β cell-like cells since studies with human pancreatic cancer cells for possible future TD therapy in PDAC patients are not available so far. We observed that QM cell lines responded strongly to TD culture using as inducers 5′-aza-2′-deoxycytidine or growth factors/cytokines, while their E counterparts were refractory or showed only a weak response. Moreover, the gain of plasticity was associated with a decrease in proliferative and migratory activities and was directly related to epigenetic changes acquired during selection of a metastatic phenotype as revealed by TD experiments using the paired isogenic COLO 357-L3.6pl model. Our data indicate that a QM phenotype in PDAC coincides with increased plasticity and heightened trans-differentiation potential to activate a pancreatic β cell-specific transcriptional program. We strongly assume that this specific biological feature has potential to be exploited clinically in TD-based therapy to convert metastatic PDAC cells into less malignant or even benign cells.

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