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Overexpression of adhesion molecules and barrier molecules is associated with differential infiltration of immune cells in non-small cell lung cancer.

ABSTRACT: Immunotherapy is emerging as a promising option for lung cancer treatment. Various endothelial adhesion molecules, such as integrin and selectin, as well as various cellular barrier molecules such as desmosome and tight junctions, regulate T-cell infiltration in the tumor microenvironment. However, little is known regarding how these molecules affect immune cells in patients with lung cancer. We demonstrated for the first time that overexpression of endothelial adhesion molecules and cellular barrier molecule genes was linked to differential infiltration of particular immune cells in non-small cell lung cancer. Overexpression of endothelial adhesion molecule genes is associated with significantly lower infiltration of activated CD4 and CD8 T-cells, but higher infiltration of activated B-cells and regulatory T-cells. In contrast, overexpression of desmosome genes was correlated with significantly higher infiltration of activated CD4 and CD8 T-cells, but lower infiltration of activated B-cells and regulatory T-cells in lung adenocarcinoma. This inverse relation of immune cells aligns with previous studies of tumor-infiltrating B-cells inhibiting T-cell activation. Although overexpression of endothelial adhesion molecule or cellular barrier molecule genes alone was not predictive of overall survival in our sample, these genetic signatures may serve as biomarkers of immune exclusion, or resistance to T-cell mediated immunotherapy.

SUBMITTER: Chae YK

PROVIDER: S-EPMC5773521 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Overexpression of adhesion molecules and barrier molecules is associated with differential infiltration of immune cells in non-small cell lung cancer.

Chae Young Kwang YK Choi Wooyoung M WM Bae William H WH Anker Jonathan J Davis Andrew A AA Agte Sarita S Iams Wade T WT Cruz Marcelo M Matsangou Maria M Giles Francis J FJ

Scientific reports 20180118 1

Immunotherapy is emerging as a promising option for lung cancer treatment. Various endothelial adhesion molecules, such as integrin and selectin, as well as various cellular barrier molecules such as desmosome and tight junctions, regulate T-cell infiltration in the tumor microenvironment. However, little is known regarding how these molecules affect immune cells in patients with lung cancer. We demonstrated for the first time that overexpression of endothelial adhesion molecules and cellular ba ...[more]

PMID: 29348685

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Project description:ObjectiveTo perform gene set enrichment analysis (GSEA) and analysis of immune cell infiltration on non-small-cell lung cancer (NSCLC) expression profiling microarray data based on bioinformatics, construct TICS scoring model to distinguish prognosis time, screen key genes and cancer-related pathways for NSCLC treatment, explore differential genes in NSCLC patients, predict potential therapeutic targets for NSCLC, and provide new directions for the treatment of NSCLC.MethodsTranscriptome data of 81 NSCLC patients and the GEO database were used to download matching clinical data (access number: GSE120622). Form the expression of non-small cell lung cancer (NSCLC). TICS values were calculated and grouped according to TICS values, and we used mRNA expression profile data to perform GSEA in non-small-cell lung cancer patients. Biological process (GO) analysis and DAVID and KOBAS were used to undertake pathway enrichment (KEGG) analysis of differential genes. Use protein interaction (PPI) to analyze the database STRING, and construct a PPI network model of target interaction.ResultsWe obtained 6 significantly related immune cells including activated B cells through the above analysis (Figure 1(b), p < 0.001). Based on the TICS values of significantly correlated immune cells, 41 high-risk and 40 low-risk samples were obtained. TICS values and immune score values were subjected to Pearson correlation coefficient calculation, and TICS and IMS values were found to be significantly correlated (Cor = 0.7952). Based on non-small-cell lung cancer mRNA expression profile data, a substantial change in mRNA was found between both the high TICS group as well as the low TICS group (FDR 0.01, FC > 2). The researchers discovered 730 mRNAs that were considerably upregulated in the high TICS group and 121 mRNAs that were considerably downregulated in the low TICS group. High confidence edges (combined score >0.7) were selected using STRING data; then, 191 mRNAs were matched to the reciprocal edges; finally, an undirected network including 164 points and 777 edges was constructed. Important members of cellular chemokine-mediated signaling pathways, such as CCL19, affect patient survival time.Conclusion(1) The longevity of patients with non-small-cell lung cancer was substantially connected with the presence of immature B cells, activated B cells, MDSC, effector memory CD4 T cells, eosinophils, and regulatory T cells. (2) Immune-related genes such as CX3CR1, CXCR4, CXCR5, and CCR7, which are associated with the survival of NSCLC, affect the prognosis of NSCLC patients by regulating the immune process.

Project description:BACKGROUND:Increasing evidence has demonstrated the functional relevance of long non-coding RNAs (lncRNAs) to immunity regulation and the tumor microenvironment in non-small cell lung cancer (NSCLC). However, tumor immune infiltration-associated lncRNAs and their value in improving clinical outcomes and immunotherapy remain largely unexplored. METHODS:We developed a computational approach to identify an lncRNA signature (TILSig) as an indicator of immune cell infiltration in patients with NSCLC through integrative analysis for lncRNA, immune and clinical profiles of 115 immune cell lines, 187 NSCLC cell lines and 1533 patients with NSCLC. Then the influence of the TILSig on the prognosis and immunotherapy in NSCLC was comprehensively investigated. RESULTS:Computational immune and lncRNA profiling analysis identified an lncRNA signature (TILSig) consisting of seven lncRNAs associated with tumor immune infiltration. The TILSig significantly stratified patients into the immune-cold group and immune-hot group in both training and validation cohorts. These immune-hot patients exhibit significantly improved survival outcome and greater immune cell infiltration compared with immune-cold patients. Multivariate analysis revealed that the TILSig is an independent predictive factor after adjusting for other clinical factors. Further analysis accounting for TILSig and immune checkpoint gene revealed that the TILSig has a discriminatory power in patients with similar expression levels of immune checkpoint genes and significantly prolonged survival was observed for patients with low TILSig and low immune checkpoint gene expression implying a better response to immune checkpoint inhibitor (ICI) immunotherapy. CONCLUSIONS:Our finding demonstrated the importance and value of lncRNAs in evaluating the immune infiltrate of the tumor and highlighted the potential of lncRNA coupled with specific immune checkpoint factors as predictive biomarkers of ICI response to enable a more precise selection of patients.

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Overexpression of adhesion molecules and barrier molecules is associated with differential infiltration of immune cells in non-small cell lung cancer.

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Overexpression of adhesion molecules and barrier molecules is associated with differential infiltration of immune cells in non-small cell lung cancer.

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