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A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk.

ABSTRACT: 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.

SUBMITTER: Gentles AJ

PROVIDER: S-EPMC7206807 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk.

Gentles Andrew J AJ Hui Angela Bik-Yu AB Feng Weiguo W Azizi Armon A Nair Ramesh V RV Bouchard Gina G Knowles David A DA Yu Alice A Jeong Youngtae Y Bejnood Alborz A Forgó Erna E Varma Sushama S Xu Yue Y Kuong Amanda A Nair Viswam S VS West Rob R van de Rijn Matt M Hoang Chuong D CD Diehn Maximilian M Plevritis Sylvia K SK

Genome biology 20200507 1

<h4>Background</h4>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.<h4>Result</h4>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, immu ...[more]

PMID: 32381040

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Project description:BackgroundVarious studies highlighted that immune cell-mediated inflammatory processes play crucial roles in the progression and treatment of hepatocellular carcinoma (HCC). However, the immune microenvironment of HCC is still poorly characterized. Exploring the role of immune-related genes (IRGs) and describing the immune landscape in HCC would provide insights into tumor-immune co-evolution along HCC progression.MethodsWe integrated the datasets with complete prognostic information from the Cancer Genome Atlas (TCGA) database and GEO DataSets (GSE14520, GSE76427, and GSE54236) to construct a novel immune landscape based on the Cibersort algorithm and reveal the prognostic signature in HCC patients.ResultsTo describe the tumor microenvironment (TME) in HCC, immune infiltration patterns were defined using the CIBERSORT method, and a prognostic signature contains 5 types of immune cells, including 3 high-risk immune cells (T.cells. CD4. memory. resting, Macrophages.M0, Macrophages.M2) and 2 low-risk immune cells (Plasma. cells, T.cells.CD8), were finally constructed. A novel prognostic index, based on prognostic immune risk score (pIRG), was developed using the univariate Cox regression analyses and LASSO Cox regression algorithm. Furthermore, the ROC curve and KM curve showed that the TME signatures had a stable value in predicting the prognosis of HCC patients in the internal training cohort, internal validation, and external validation cohort. Differential genes analysis and qPCR experiment showed that the expression levels of AKR1B10, LAPTM4B, MMP9, and SPP1 were significantly increased in high-risk patients, while the expression of CD5L was lower. Further analysis found that AKR1B10 and MMP9 were associated with higher M0 macrophage infiltration, while CD5L was associated with higher plasma cell infiltration.ConclusionsTaken together, we performed a comprehensive evaluation of the immune landscape of HCC and constructed a novel and robust prognostic prediction model. AKR1B10, LAPTM4B, MMP9, SPP1, and CD5L were involved in important processes in the HCC tumor microenvironment and were expected to become HCC prediction markers and potential targets of treatment.

Project description:The tumor microenvironment (TME) plays a major role in the pathogenesis of multiple cancer types, including upper-gastrointestinal (GI) cancers that currently lack effective therapeutic options. Cancer-associated fibroblasts (CAF) are an essential component of the TME, contributing to tumorigenesis by secreting growth factors, modifying the extracellular matrix, supporting angiogenesis, and suppressing antitumor immune responses. Through an unbiased approach, we have established that IL-6 mediates cross-talk between tumor cells and CAF not only by supporting tumor cell growth, but also by promoting fibroblast activation. As a result, IL-6 receptor (IL6R?) and downstream effectors offer opportunities for targeted therapy in upper-GI cancers. IL-6 loss suppressed tumorigenesis in physiologically relevant three-dimensional (3D) organotypic and 3D tumoroid models and murine models of esophageal cancer. Tocilizumab, an anti-IL6R? antibody, suppressed tumor growth in vivo in part via inhibition of STAT3 and MEK/ERK signaling. Analysis of a pan-cancer TCGA dataset revealed an inverse correlation between IL-6 and IL6R? overexpression and patient survival. Therefore, we expanded evaluation of tocilizumab to head and neck squamous cell carcinoma patient-derived xenografts and gastric adenocarcinoma xenografts, demonstrating suppression of tumor growth and altered STAT3 and ERK1/2 gene signatures. We used small-molecule inhibitors of STAT3 and MEK1/2 signaling to suppress tumorigenesis in the 3D organotypic model of esophageal cancer. We demonstrate that IL6 is a major contributor to the dynamic cross-talk between tumor cells and CAF in the TME. Our findings provide a translational rationale for inhibition of IL6R? and downstream signaling pathways as a novel targeted therapy in oral-upper-GI cancers.Significance: These findings demonstrate the interaction of esophageal cancer and cancer-associated fibroblasts through IL-6 signaling, providing rationale for a novel therapeutic approach to target these cancers. Cancer Res; 78(17); 4957-70. ©2018 AACR.

Dataset Information

A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk.

Publications

A human lung tumor microenvironment interactome identifies clinically relevant cell-type cross-talk.

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