A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk.
Journal
Genome biology
ISSN: 1474-760X
Titre abrégé: Genome Biol
Pays: England
ID NLM: 100960660
Informations de publication
Date de publication:
07 05 2020
07 05 2020
Historique:
received:
04
06
2019
accepted:
15
04
2020
entrez:
9
5
2020
pubmed:
10
5
2020
medline:
2
4
2021
Statut:
epublish
Résumé
Tumors comprise a complex microenvironment of interacting malignant and stromal cell types. Much of our understanding of the tumor microenvironment comes from in vitro studies isolating the interactions between malignant cells and a single stromal cell type, often along a single pathway. To develop a deeper understanding of the interactions between cells within human lung tumors, we perform RNA-seq profiling of flow-sorted malignant cells, endothelial cells, immune cells, fibroblasts, and bulk cells from freshly resected human primary non-small-cell lung tumors. We map the cell-specific differential expression of prognostically associated secreted factors and cell surface genes, and computationally reconstruct cross-talk between these cell types to generate a novel resource called the Lung Tumor Microenvironment Interactome (LTMI). Using this resource, we identify and validate a prognostically unfavorable influence of Gremlin-1 production by fibroblasts on proliferation of malignant lung adenocarcinoma cells. We also find a prognostically favorable association between infiltration of mast cells and less aggressive tumor cell behavior. These results illustrate the utility of the LTMI as a resource for generating hypotheses concerning tumor-microenvironment interactions that may have prognostic and therapeutic relevance.
Sections du résumé
BACKGROUND
Tumors comprise a complex microenvironment of interacting malignant and stromal cell types. Much of our understanding of the tumor microenvironment comes from in vitro studies isolating the interactions between malignant cells and a single stromal cell type, often along a single pathway.
RESULT
To develop a deeper understanding of the interactions between cells within human lung tumors, we perform RNA-seq profiling of flow-sorted malignant cells, endothelial cells, immune cells, fibroblasts, and bulk cells from freshly resected human primary non-small-cell lung tumors. We map the cell-specific differential expression of prognostically associated secreted factors and cell surface genes, and computationally reconstruct cross-talk between these cell types to generate a novel resource called the Lung Tumor Microenvironment Interactome (LTMI). Using this resource, we identify and validate a prognostically unfavorable influence of Gremlin-1 production by fibroblasts on proliferation of malignant lung adenocarcinoma cells. We also find a prognostically favorable association between infiltration of mast cells and less aggressive tumor cell behavior.
CONCLUSION
These results illustrate the utility of the LTMI as a resource for generating hypotheses concerning tumor-microenvironment interactions that may have prognostic and therapeutic relevance.
Identifiants
pubmed: 32381040
doi: 10.1186/s13059-020-02019-x
pii: 10.1186/s13059-020-02019-x
pmc: PMC7206807
doi:
Substances chimiques
GREM1 protein, human
0
Intercellular Signaling Peptides and Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
107Subventions
Organisme : NCI NIH HHS
ID : U54 CA209971
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001085
Pays : United States
Organisme : NCI NIH HHS
ID : U01CA154969
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA224309
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR003142
Pays : United States
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