Epithelial-mesenchymal transition markers screened in a cell-based model and validated in lung adenocarcinoma.
ABSTRACT: BACKGROUND:Re-capture of the differences between tumor and normal tissues observed at the patient level in cell cultures and animal models is critical for applications of these cancer-related differences. The epithelial-mesenchymal transition (EMT) process is essential for tumor migratory and invasive capabilities. Although plenty of EMT markers are revealed, molecular features during the early stages of EMT are poorly understood. METHODS:A cell-based model to induce lung cell (A549) EMT using conditioned medium of in vitro cancer activated fibroblast (WI38) was established. High-throughput sequencing methods, including RNA-seq and miRNA-seq, and advanced bioinformatics methods were used to explore the transcriptome profile transitions accompanying the progression of EMT. We validated our findings with experimental techniques including transwell and immunofluorescence assay, as well as the TCGA data. RESULTS:We have constructed an in vitro cell model to mimic the EMT in patients. We discovered that several new transcription factors were among the early genes (3 h) to respond to cancer micro-environmental cues which could play critical roles in triggering further EMT signals. The early EMT markers also included genes encoding membrane transporters and blood coagulation function. Three of the nine-examined early EMT hallmark genes, GALNT6, SPARC and HES7, were up-regulated specifically in the early stages of lung adenocarcinoma (LUAD) and confirmed by TCGA patient transcriptome data. In addition, we showed that miR-3613, a regulator of EGFR pathway genes, was constantly repressed during EMT progress and indicative of an epithelial miRNA marker. CONCLUSIONS:The CAF-stimulated EMT cell model may recapture some of the molecular changes during EMT progression in clinical patients. The identified early EMT hallmark genes GALNT6, SPARC and HES7and miR-3613 provide new markers and therapeutic targets for LUAD for the further clinical diagnosis and drug screening.
Project description:Aberrant activation of nuclear factor ?B (NF-?B)/RELA is often found in lung adenocarcinoma (LUAD). In this study, we determined that microRNA-3613-5p (miR-3613-5p) plays a crucial role in RELA-mediated post-transcriptional regulation of LUAD cell proliferation. Expression of miR-3613-5p in clinical LUAD specimens is associated with poor prognosis in LUAD. Upregulation of miR-3613-5p promotes LUAD cell proliferation in vitro and in vivo. Our results suggested a mechanism whereby miR-3613-5p expression is induced by RELA through its direct interaction with JUN, thereby stimulating the AKT/mitogen-activated protein kinase (MAPK) pathway by directly targeting NR5A2. In addition, we also found that phosphorylation of AKT1 and MAPK3/1 co-transactivates RELA, thus constituting a RELA/JUN/miR-3613-5p/NR5A2/AKT1/MAPK3/1 positive feedback loop, leading to persistent NF-?B activation. Our findings also revealed that miR-3613-5p plays an oncogenic role in LUAD by promoting cell proliferation and acting as a key regulator of the positive feedback loop underlying the link between the NF-?B/RELA and AKT/MAPK pathways. Graphical Abstract Aberrant activation of nuclear factor ?B (NF-?B)/RELA is often found in lung adenocarcinoma (LUAD). However, RELA as a direct therapeutic target for lung cancer remains a challenge. This study investigated that microRNA-3613-5p (miR-3613-5p) plays a crucial role in RELA-mediated post-transcriptional regulation of LUAD cell proliferation.
Project description:Lung adenocarcinoma remains a threat to human health due to its high rate of recurrence and distant metastasis. However, the molecular mechanism underlying lung adenocarcinoma metastasis remains yet incompletely understood. Here, we show that upregulated expression of polypeptide N-acetylgalactosaminyltransferase6 (GALNT6) in lung adenocarcinoma is associated with lymph node metastasis and poor prognosis. In lung adenocarcinoma cells, GALNT6 over-expression promoted epithelial-mesenchymal transition (EMT), wound healing, and invasion which could be significantly reversed by GALNT6 silencing. GALNT6 silencing also mitigated the metastasis of lung adenocarcinoma and prolonged the survival of xenograft tumor-bearing mice. Furthermore, GALNT6 directly interacted with, and O-glycosylated chaperone protein GRP78, which promoted EMT by enhancing the MEK1/2/ERK1/2 signaling in lung cancer cells. Therefore, GALNT6 is emerging as novel positive regulator for the malignancy of human lung adenocarcinoma. Targeting GALNT6-GRP78-MEK1/2/ERK1/2 may thus represent a new avenue to develop therapeutics against lung cancer metastasis.
Project description:Background:Novel diagnostic predictors and drug targets are needed for LUAD (lung adenocarcinoma). We aimed to build a specific SVM (support vector machine) classifier for diagnosis of LUAD and identify molecular markers with prognostic value for LUAD. Methods:The expression differences of miRNAs, lncRNAs and mRNAs between LUAD and normal samples were compared using data from TCGA (The Cancer Genome Atlas) database. A LUAD related miRNA-lncRNA-mRNA network was constructed, based on which feature genes were selected for the construction of LUAD specific SVM classifier. The robustness and transferability of SVM classifier were validated using gene expression profile datasets GSE43458 and GSE10072. Prognostic markers were identified from the network. A set of LUAD-related differentially expressed miRNAs, lncRNAs and miRNAs were identified and a LUAD related miRNA-lncRNA-mRNA network was obtained. The LUAD specific SVM classifier constructed on the basis of the network was robust and efficient for classification of samples from TCGA dataset and two independent validation datasets. Results:Eight RNAs with prognostic value were identified, including hsa-miR-96, hsa-miR-204, PGM5P2 (phosphoglucomutase 5 pseudogene 2), SFTA1P (surfactant associated 1), RGS20 (regulator of G protein signaling 20), RGS9BP (RGS9-binding protein), FGB (fibrinogen beta chain) and INA (alpha-internexin). Among them, RGS20 and INA were regulated by hsa-miR-96. RGS20 was also regulated by hsa-miR-204, which was a potential target of SFTA1P. Conclusion:The LUAD specific SVM classifier may serve as a novel diagnostic predictor. hsa-miR-96, hsa-miR-204, PGM5P2, SFTA1P, RGS20, RGS9BP, FGB and INA may serve as prognostic markers in clinical practice.
Project description:BACKGROUND:The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD. METHODS:The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan-Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts. RESULTS:A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR?=?4.31, 95% CI 2.29-8.11; P?=?6.16E-06), GSE31210 (HR?=?11.91, 95% CI 4.15-34.19; P?=?4.10E-06), GSE50081 (HR?=?3.63, 95% CI 1.90-6.95; P?=?9.95E-05), the combined data set (HR?=?3.15, 95% CI 1.98-5.02; P?=?1.26E-06) and the validation data set, including TCGA-LUAD (HR?=?2.16, 95% CI 1.49-3.13; P?=?4.54E-05) and GSE72094 (HR?=?2.95, 95% CI 1.86-4.70; P?=?4.79E-06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design. CONCLUSIONS:Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.
Project description:BACKGROUND: Immunohistochemical staining has been widely used in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC), which is of vital importance for the diagnosis and treatment of lung cancer. Due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher diagnostic accuracy. METHODS: Herein first, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we attempted to identify the genes which might be suitable as immunohistochemical markers in distinguishing LUAD from LUSC. Then we detected the expression of six of these genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in lung cancer sections using immunohistochemical staining. RESULTS: A number of genes were identified as candidate immunohistochemical markers with high sensitivity and specificity in distinguishing LUAD from LUSC. Then the staining results confirmed the potentials of the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in distinguishing LUAD from LUSC, and their sensitivity and specificity were not less than many commonly used markers. CONCLUSIONS: The results revealed that the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) might be suitable markers in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data.
Project description:Background:As one of the most common malignant tumors in humans, lung cancer has experienced a gradual increase in morbidity and mortality. This study examined prognosis-related methylation-driven genes specific to lung adenocarcinoma (LUAD) to provide a basis for prognosis prediction and personalized targeted therapy for LUAD patients. Methods:The methylation and survival time data from LUAD patients in the TCGA database were downloaded. The MethylMix algorithm was used to identify the differential methylation status of LUAD and adjacent tissues based on the ?-mixture model to obtain disease-related methylation-driven genes. A COX regression model was then used to screen for LUAD prognosis-related methylation-driven genes, and a linear risk model based on five methylation-driven gene expression profiles was constructed. A methylation and gene expression combined survival analysis was performed to further explore the prognostic value of 5 genes independently. Results:There were 118 differentially expressed methylation-driven genes in the LUAD tissues and adjacent tissues. Five of the genes, CCDC181, PLAU, S1PR1, ELF3, and KLHDC9, were used to construct a prognostic risk model. Overall, the survival time was significantly lower in the high-risk group compared with that in the low-risk group (P?<?0.05). In addition, the methylation and gene expression combined survival analysis found that the combined expression levels of the genes CCDC181, PLAU, and S1PR1 as well as KLHDC9 alone can be used as independent prognostic markers or drug targets. Conclusion:Our findings provide an important bioinformatic basis and relevant theoretical basis for guiding subsequent LUAD early diagnosis and prognosis assessments.
Project description:Loss of connexin-mediated cell-cell communication is a hallmark of breast cancer progression. Pannexin1 (PANX1), a glycoprotein that shares structural and functional features with connexins and engages in cell communication with its environment, is highly expressed in breast cancer metastatic foci; however, PANX1 contribution to metastatic progression is still obscure. Here we report elevated expression of PANX1 in different breast cancer (BRCA) subtypes using RNA-seq data from The Cancer Genome Atlas (TCGA). The elevated PANX1 expression correlated with poorer outcomes in TCGA BRCA patients. In addition, gene set enrichment analysis (GSEA) revealed that epithelial-to-mesenchymal transition (EMT) pathway genes correlated positively with PANX1 expression. Pharmacological inhibition of PANX1, in MDA-MB-231 and MCF-7 breast cancer cells, or genetic ablation of PANX1, in MDA-MB-231 cells, reverted the EMT phenotype, as evidenced by decreased expression of EMT markers. In addition, PANX1 inhibition or genetic ablation decreased the invasiveness of MDA-MB-231 cells. Our results suggest PANX1 overexpression in breast cancer is associated with a shift towards an EMT phenotype, in silico and in vitro, attributing to it a tumor-promoting effect, with poorer clinical outcomes in breast cancer patients. This association offers a novel target for breast cancer therapy.
Project description:Lung adenocarcinoma (LUAD) is one of the most common types of lung cancer and its poor prognosis largely depends on the tumor pathological stage. Critical roles of microRNAs (miRNAs) have been reported in the tumorigenesis and progression of lung cancer. However, whether the differential expression pattern of miRNAs could be used to distinguish early?stage (stage I) from mid?late?stage (stages II?IV) LUAD tumors is still unclear. In this study, clinical information and miRNA expression profiles of patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. TCGA?LUAD (n=470) dataset was used for model training and validation, and the GSE62182 (n=94) and GSE83527 (n=36) datasets were used as external independent test datasets. The diagnostic model was created through miRNA feature selection followed by SVM classifier and was confirmed by 5?fold cross?validation. A receiver operating characteristic curve was calculated to evaluate the accuracy and robustness of the model. Using the DX score and LIBSVM tool, a 16?miRNA signature that could distinguish LUAD pathological stages was identified. The area under the curve rates were 0.62 [95% confidence interval (CI): 0.56?0.67], 0.66 (95% CI: 0.54?0.76) and 0.63 (95% CI: 0.43?0.82) in TCGA?LUAD internal validation dataset, the GSE62182 external validation dataset, and the GSE83527 external validation dataset, respectively. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses suggested that the target genes of the 16?miRNA signature were mainly involved in metabolic pathways. The present findings demonstrate that a 16?miRNA signature could serve as a promising diagnostic biomarker for pathological staging in LUAD.
Project description:BACKGROUND:We have previously developed a unique metastasis-associated signature consisting of six long non-coding RNAs (lncRNAs), including a novel lncRNA, namely LINC02323. In the present study, we aimed to investigate the underlying roles of LINC02323 in the migration, invasion and TGF-?-induced epithelial-mesenchymal transition (EMT) of lung adenocarcinoma (LUAD) cells. METHODS:The distribution of LINC02323 was detected by the nuclear-plasma separation experiment. Cell proliferation was assessd by MTT assay, and cell migration and invation were detected by transwell assays. EMT was detected by RT-qPCR and western blotting. Interaction between miRNA and LINC02323 was predicted by starBase v2.0 and confirmed by the double luciferase reporting system. RESULTS:LINC02323 was distributed in the cytoplasm and nucleus. The overexpression or deletion of LINC02323 did not affect the proliferation of LUAD cells, while significantly affected the migration and invasion of LUAD cells. TGF-?-induced EMT process was significantly affected by both RNA interference (RNAi) and overexpression of LINC02323. The predicted results showed that there were binding sites between LINC02323 and miR-1343-3p. The expression of LINC02323 was found to be negatively correlated with miR-1343-3p in LUAD by analyzing The Cancer Genome Atlas (TCGA) database. The double luciferase reporting system, RT-qPCR and western blotting experiments confirmed that LINC02323 could bind to miR-1343-3p, which bound to TGF-? receptor 1 (TGFBR1). Inhibition of miR-1343-3p reversed LINC02323 silencing-mediated suppression of migration, invasion and EMT. CONCLUSIONS:LINC02323 acts as a competing endogenous RNA (ceRNA), which sponged miR-1343-3p to upregulate the TGFBR1 expression and promote the EMT and metastasis in LUAD. KEY POINTS:SIGNIFICANT FINDINGS OF THE STUDY: LINC02323 promotes epithelial-mesenchymal transition and metastasis via sponging miR-1343-3p in lung adenocarcinoma. WHAT THIS STUDY ADDS:LINC02323 is a key molecule in the process of invasion and metastasis of LUAD and might be used as a potential target in metastatic cancer.
Project description:The lack of effective markers leads to missed optimal treatment times, resulting in poorer prognosis in most cancers. Drosophila mothers against decapentaplegic protein (SMAD) family members are important cytokines in the transforming growth factor-beta family. They jointly regulate the processes of cell growth, differentiation, and apoptosis. However, the expression of SMAD family genes in pan-cancers and their impact on prognosis have not been elucidated. Perl software and R software were used to perform expression analysis and survival curve analysis on the data collected by TCGA, GTEx, and GEO, and the potential regulatory pathways were determined through gene ontology enrichment and kyoto encyclopedia of genes and genomes enrichment analysis. It was found that SMAD7 and SMAD9 expression decreased in lung adenocarcinoma (LUAD), and their expression was positively correlated with survival time. Additionally, SMAD7 could be used as an independent prognostic factor for LUAD. In general, SMAD7 and SMAD9 can be used as prognostic markers of LUAD. Further, SMAD7 is expected to become a therapeutic target for LUAD.