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Comparative gene co-expression network analysis of epithelial to mesenchymal transition reveals lung cancer progression stages.

ABSTRACT: The epithelial to mesenchymal transition (EMT) plays a key role in lung cancer progression and drug resistance. The dynamics and stability of gene expression patterns as cancer cells transition from E to M at a systems level and relevance to patient outcomes are unknown.Using comparative network and clustering analysis, we systematically analyzed time-series gene expression data from lung cancer cell lines H358 and A549 that were induced to undergo EMT. We also predicted the putative regulatory networks controlling EMT expression dynamics, especially for the EMT-dynamic genes and related these patterns to patient outcomes using data from TCGA. Example EMT hub regulatory genes were validated using RNAi.We identified several novel genes distinct from the static states of E or M that exhibited temporal expression patterns or 'periods' during the EMT process that were shared in different lung cancer cell lines. For example, cell cycle and metabolic genes were found to be similarly down-regulated where immune-associated genes were up-regulated after middle EMT stages. The presence of EMT-dynamic gene expression patterns supports the presence of differential activation and repression timings at the transcriptional level for various pathways and functions during EMT that are not detected in pure E or M cells. Importantly, the cell line identified EMT-dynamic genes were found to be present in lung cancer patient tissues and associated with patient outcomes.Our study suggests that in vitro identified EMT-dynamic genes capture elements of gene EMT expression dynamics at the patient level. Measurement of EMT dynamic genes, as opposed to E or M only, is potentially useful in future efforts aimed at classifying patient's responses to treatments based on the EMT dynamics in the tissue.

SUBMITTER: Wang D

PROVIDER: S-EPMC5719936 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLung cancer is the most common and lethal malignancy worldwide. TCTP is highly expressed in various cancers including lung cancer. Epithelial-mesenchymal transition (EMT) could increase cancer cell invasion. Whether TCTP's expression is associated with EMT in lung adenocarcinoma is largely unknown.MethodsSeveral Gene Expression Omnibus datasets were used to analyze the correlation between TCTP expression and overall survival of lung adenocarcinoma patients by Kaplan-Meier survival analysis. Then, 24 surgically removed fresh lung adenocarcinoma tissue samples and paired paracancer tissue samples were used to analyze the correlation between TCTP expression and tumor stage by immunohistochemical analysis. Furthermore, stable cell lines were generated using lentiviral transduction systems to knock down or overexpress TCTP in A549 cells. Cell migration and invasion were measured by scratch and transwell assays, and EMT marker proteins such as α-SMA, ZEB1, and E-cadherin were quantitated by Western blot. The expression levels of miR-200a, miR-141, and miR-429 were determined by real-time quantitative PCR, and their target genes were predicted by an online database miRTarBase. The interaction between TCTP and these genes was analyzed by String database and visualized by Cytoscape.ResultsTCTP was highly expressed in tumor tissues compared to paracancer tissues. The expression of TCTP was associated with shorter overall survival. TCTP knockdown experiment in A549 cells suggested that TCTP knockdown could decrease the migration and invasion of lung cancer cells, and the expression level of ZEB1 and α-SMA, but increase the expression of E-cadherin and p53. Vice versa, overexpression of TCTP could increase the migration and invasion of cancer cells, and the expression level of ZEB1 and α-SMA, but decrease the expression of E-cadherin and p53. Furthermore, we found the expression of miR-200a, miR-141, and miR-429 was associated with TCTP expression.ConclusionTCTP promotes EMT in lung adenocarcinoma, and this effect may be associated with miR-200 family members like miR-200a, miR-141, and miR-429.

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Comparative gene co-expression network analysis of epithelial to mesenchymal transition reveals lung cancer progression stages.

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