Which dataset
would you like to
analyze in BBrowser?

Species: m_fascicularis
Number of cells: 16331
Study size: 262MB

retina 
primates 
fovea 

Molecular Classification and Comparative Taxonomics of Foveal and Peripheral Cells in Primate Retina (foveal photoreceptor)

Yi-Rong Peng, Karthik Shekhar, Wenjun Yan, Dustin Herrmann, Anna Sappington, Gregory S. Bryman, Tavé van Zyl, Michael Tri. H. Do, Aviv Regev, Joshua R. Sanes

High-acuity vision in primates, including humans, is mediated by a small central retinal region called the fovea. As more accessible organisms lack a fovea, its specialized function and its dysfunction in ocular diseases remain poorly understood. We used 165,000 single-cell RNA-seq profiles to generate comprehensive cellular taxonomies of macaque fovea and peripheral retina. More than 80% of >60 cell types match between the two regions but exhibit substantial differences in proportions and gene expression, some of which we relate to functional differences. Comparison of macaque retinal types with those of mice reveals that interneuron types are tightly conserved. In contrast, projection neuron types and programs diverge, despite exhibiting conserved transcription factor codes. Key macaque types are conserved in humans, allowing mapping of cell-type and region-specific expression of >190 genes associated with 7 human retinal diseases. Our work provides a framework for comparative single-cell analysis across tissue regions and species.

Download bbrowser to analyze now

Species: m_fascicularis
Number of cells: 8376
Study size: 127MB

retina 
primates 
fovea 
peripheral retina 

Molecular Classification and Comparative Taxonomics of Foveal and Peripheral Cells in Primate Retina (peripheral photoreceptor)

Yi-Rong Peng, Karthik Shekhar, Wenjun Yan, Dustin Herrmann, Anna Sappington, Gregory S. Bryman, Tavé van Zyl, Michael Tri. H. Do, Aviv Regev, Joshua R. Sanes

High-acuity vision in primates, including humans, is mediated by a small central retinal region called the fovea. As more accessible organisms lack a fovea, its specialized function and its dysfunction in ocular diseases remain poorly understood. We used 165,000 single-cell RNA-seq profiles to generate comprehensive cellular taxonomies of macaque fovea and peripheral retina. More than 80% of >60 cell types match between the two regions but exhibit substantial differences in proportions and gene expression, some of which we relate to functional differences. Comparison of macaque retinal types with those of mice reveals that interneuron types are tightly conserved. In contrast, projection neuron types and programs diverge, despite exhibiting conserved transcription factor codes. Key macaque types are conserved in humans, allowing mapping of cell-type and region-specific expression of >190 genes associated with 7 human retinal diseases. Our work provides a framework for comparative single-cell analysis across tissue regions and species.

Download bbrowser to analyze now

Species: human
Number of cells: 47681
Study size: 2GB

Brain disorder 
autism 
spatial 
schizophrenia 
brain 

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

Kristen R. Maynard, Leonardo Collado-Torres, Lukas M. Weber, Cedric Uytingco, Brianna K. Barry, Stephen R. Williams, Joseph L. Catallini II, Matthew N. Tran, Zachary Besich, Madhavi Tippani, Jennifer Chew, Yifeng Yin, Joel E. Kleinman, Thomas M. Hyde, Nikhil Rao, Stephanie C. Hicks, Keri Martinowich, Andrew E. Jaffe

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-enriched expression signatures and refined associations to previous laminar markers. We overlaid our laminar expression signatures on large-scale single nucleus RNA-sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions in which morphological architecture is not as well defined as cortical laminae. Last, we created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research (http://research.libd.org/spatialLIBD).

Download bbrowser to analyze now

Species: human
Number of cells: 61405
Study size: 961MB

Immunology 
PBMC 
Primary Sjogren's Syndrome 

Single-Cell RNA Sequencing Reveals the Expansion of Cytotoxic CD4+ T Lymphocytes and a Landscape of Immune Cells in Primary Sjogren's Syndrome

Hong Xiaoping, Meng Shuhui, Tang Donge, Wang Tingting, Ding Liping, Yu Haiyan, Li Heng, Liu Dongzhou, Dai Yong, Yang Min

Objective: Primary Sjögren's syndrome (pSS) is a systemic autoimmune disease, and its pathogenetic mechanism is far from being understood. In this study, we aimed to explore the cellular and molecular mechanisms that lead to pathogenesis of this disease. Methods: We applied single-cell RNA sequencing (scRNA-seq) to 57,288 peripheral blood mononuclear cells (PBMCs) from five patients with pSS and five healthy controls. The immune cell subsets and susceptibility genes involved in the pathogenesis of pSS were analyzed. Flow cytometry was preformed to verify the result of scRNA-seq. Results: We identified two subpopulations significantly expand in pSS patients. The one highly expressing cytotoxicity genes is named as CD4+ CTLs cytotoxic T lymphocyte, and another highly expressing T cell receptor (TCR) variable gene is named as CD4+ TRAV13-2+ T cell. Flow cytometry results showed the percentages of CD4+ CTLs, which were profiled with CD4+ and GZMB+ staining; the total T cells of 10 patients with pSS were significantly higher than those of 10 healthy controls (P= 0.008). The expression level of IL-1β in macrophages, TCL1A in B cells, as well as interferon (IFN) response genes in most cell subsets was upregulated in the patients with pSS. Susceptibility genes including HLA-DRB5, CTLA4, and AQP3 were highly expressed in patients with pSS. Conclusions: Our data revealed disease-specific immune cell subsets and provided some potential new targets of pSS. Specific expansion of CD4+ CTLs may be involved in the pathogenesis of pSS, which might give valuable insights for therapeutic interventions of pSS.

Download bbrowser to analyze now

Species: human
Number of cells: 45114
Study size: 770MB

pan-cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Ovarian cancer)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 44024
Study size: 877MB

pan-cancer 
breast cancer 

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Breast cancer)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 44684
Study size: 802MB

pan-cancer 
colorectal cancer 

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Colorectal cancer)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 93575
Study size: 1GB

pan-cancer 
lung cancer 

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Lung cancer)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 65163
Study size: 1GB

pan-cancer 
lung cancer 
breast cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (T/NK cell)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 1962
Study size: 22MB

pan-cancer 
lung cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Mast cell)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 21880
Study size: 595MB

pan-cancer 
lung cancer 
breast cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Myeloid cell)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 17944
Study size: 398MB

pan-cancer 
lung cancer 
breast cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (B cell)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 3084
Study size: 100MB

pan-cancer 
lung cancer 
breast cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Dendritic cell)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 20363
Study size: 681MB

pan-cancer 
lung cancer 
breast cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Fibroblast)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

Species: human
Number of cells: 9476
Study size: 279MB

pan-cancer 
lung cancer 
breast cancer 
colorectal cancer 
ovarian cancer  

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling (Endothelial cell)

Junbin Qian, Siel Olbrecht, Bram Boeckx, Hanne Vos, Damya Laoui, Emre Etlioglu, Els Wauters, Valentina Pomella, Sara Verbandt, Pieter Busschaert, Ayse Bassez, Amelie Franken, Marlies Vanden Bempt, Jieyi Xiong, Birgit Weynand, Yannick van Herck, Asier Antoranz, Francesca Maria Bosisio, Bernard Thienpont, Giuseppe Floris, Ignace Vergote, Ann Smeets, Sabine Tejpar & Diether Lambrechts

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

Download bbrowser to analyze now

About 374 datasets