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Clinically-relevant cell type cross-talk identified from a human lung tumor microenvironment interactome

A. Gentles,A. Hui,Weiguo Feng,Armon Azizi,Ramesh Nair,David A. Knowles,Alice Yu,Youngtae Jeong,Alborz Bejnood,Erna Forgó,S. Varma,Yue Xu,Amanda Kuong,V. Nair,R. West,M. van de Rijn,Chuong D. Hoang,M. Diehn,S. Plevritis

Published 2019 in bioRxiv

ABSTRACT

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 performed 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 mapped the cell-specific differential expression of prognostically-associated secreted factors and cell surface genes, and computationally reconstructed cross-talk between these cell types to generate a novel resource we call the Lung Tumor Microenvironment Interactome (LTMI). Using this resource, we identified and validated a prognostically unfavorable influence of Gremlin-1 production by fibroblasts on proliferation of malignant lung adenocarcinoma cells. We also found 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. Summary RNA-seq profiling of sorted populations from primary lung cancer samples identifies prognostically relevant cross-talk between cell types in the tumor microenvironment.

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