Identification of a Three-Gene Signature Based on Epithelial-Mesenchymal Transition of Lung Adenocarcinoma Through Construction and Validation of a Risk-Prediction Model
Ontology highlight
ABSTRACT:
SUBMITTER: Shi J
PROVIDER: S-EPMC8567015 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Traditional pathological diagnoses and clinical methods are insufficient to accurately predict the prognosis of lung adenocarcinoma (LUAD). Epithelial-mesenchymal transition (EMT) process is closely related to tumor cell migration. However, the prognostic value of EMT-related genes in LUAD is still unclear. In this study, we collected bulk RNA-sequencing (RNA-seq) and microarray data of LUAD patients from public databases and identified different expressed EMT-related genes in tumor and normal tissues. Then, we used the least absolute shrinkage and selection operator Cox regression model to develop a multigene signature in the cancer genome atlas (TCGA) cohort and validated the model in the OncoSG (Singapore Oncology Data Portal) cohort as well as other datasets. Finally, we constructed a 12-gene signature to divide LUAD patients into high-risk and low-risk groups of overall survival (OS), which has a better stability and accuracy in predicating the OS of patients compared with some other published signatures of LUAD. In addition, evaluation of the risk model using the time-related receiver operating characteristic (ROC) curve confirmed the predictive ability of the model. Functional analysis showed that these genes are related to immunity. CD8 T cell and CD4 T cell types were significantly negatively correlated with the risk score in the analysis of immune infiltration. In general, our model provides useful information that may help clinicians better predict the prognosis of LUAD patients and provides potential targets for immunotherapy of LUAD.
| S-EPMC8753132 | biostudies-literature
Project description:Epithelial-mesenchymal transition (EMT) has been shown to be linked to a poor prognosis, particularly in patients with non-small-cell lung cancer. Nevertheless, little is known regarding the existence of EMT-related gene signatures and their prognostic values in lung adenocarcinoma (LUAD). In the current study, we systematically profiled the mRNA expression data of patients with LUAD in The Cancer Genome Atlas and Gene Expression Omnibus databases using a total of 1,184 EMT-related genes. The prognostic values of the EMT-related genes used to develop risk score models for overall survival were determined using LASSO and Cox regression analyses. A prognostic signature that consisted of nine unique EMT-related genes was generated using a training set. A nomogram, incorporating this EMT-related gene signature and clinical features of patients with LUAD, was constructed for potential clinical use. Calibration plots, decision-making curves, and receiver operating characteristic curve analysis showed that this model had a good ability to predict the survival of patients with LUAD. The EMT-associated gene signature and prognostic nomogram established in this study were reliable in predicting the survival of patients with LUAD. Thus, we first identified a novel EMT-related gene signature and developed a nomogram for predicting the prognosis of patients with LUAD.
| S-EPMC7835007 | biostudies-literature
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.
| S-EPMC6398409 | biostudies-literature
Project description:BackgroundFerroptosis is a novel form of programmed cell death characterized by the excessive accumulation of intracellular iron and an increase in reactive oxygen species. Emerging studies have shown that ferroptosis plays a vital role in the progression of lung adenocarcinoma, but the effect of ferroptosis-related genes on prognosis has been poorly studied. The purpose of this study was to explore the prognostic value of ferroptosis-related genes.MethodsLung adenocarcinoma samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was used to establish a predictive signature for risk stratification. Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the signature. We further explored the potential correlation between the risk score model and tumor immune status.ResultsA 15-gene ferroptosis signature was constructed to classify patients into different risk groups. The overall survival (OS) of patients in the high-risk group was significantly shorter than that of patients in the low-risk group. The signature could predict OS independent of other risk factors. Single-sample gene set enrichment analysis (ssGSEA) identified the difference in immune status between the two groups. Patients in the high-risk group had stronger immune suppression, especially in the antigen presentation process.ConclusionsThe 15-gene ferroptosis signature identified in this study could be a potential biomarker for prognosis prediction in lung adenocarcinoma. Targeting ferroptosis might be a promising therapeutic alternative for lung adenocarcinoma.
| S-EPMC8272465 | biostudies-literature
Project description:MicroRNA (miRNA, miR) has been reported to be highly implicated in a wide range of biological processes in lung cancer (LC), and identification of differentially expressed miRNAs between normal and LC samples has been widely used in the discovery of prognostic factors for overall survival (OS) and response to therapy. The present study was designed to develop and evaluate a miRNA-based signature with prognostic value for the OS of lung adenocarcinoma (LUAD), a common histologic subtype of LC. In brief, the miRNA expression profiles and clinicopathological factors of 499 LUAD patients were collected from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier (K-M) survival analysis showed significant correlations between differentially expressed miRNAs and LUAD survival outcomes. Afterward, 1,000 resample LUAD training matrices based on the training set was applied to identify the potential prognostic miRNAs. The least absolute shrinkage and selection operator (LASSO) cox regression analysis was used to constructed a six-miRNA based prognostic signature for LUAD patients. Samples with different risk scores displayed distinct OS in K-M analysis, indicating considerable predictive accuracy of this signature in both training and validation sets. Furthermore, time-dependent receiver operating characteristic (ROC) analysis demonstrated the nomogram achieved higher predictive accuracy than any other clinical variables after incorporating the clinical information (age, sex, stage, and recurrence). In the stratification analysis, the prognostic value of this classifier in LUAD patients was validated to be independent of other clinicopathological variables, such as age, gender, tumor recurrence, and early stage. Gene set annotation analyses were also conducted through the Hallmark gene set and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, indicating target genes of the six miRNAs were positively related to various molecular pathways of cancer, such as hallmark UV response, Wnt signaling pathway and mTOR signaling pathway. In addition, fresh cancer tissue samples and matched adjacent tissue samples from 12 LUAD patients were collected to verify the expression of miR-582's target genes in the model, further revealing the potential relationship between SOX9, RASA1, CEP55, MAP4K4 and LUAD tumorigenesis, and validating the predictive value of the model. Taken together, the present study identified a robust signature for the OS prediction of LUAD patients, which could potentially aid in the individualized selection of therapeutic approaches for LUAD patients.
| S-EPMC7798616 | biostudies-literature
Project description:The epithelial-to-mesenchymal transition (EMT) in cancer is associated with invasion, metastasis and chemoresistance. Recent studies have revealed the increased expression of programmed death-ligand 1 (PD-L1) in cells undergoing EMT. The underlying mechanism of EMT involves transforming growth factor-β (TGF-β) and fibroblast growth factor-2 (FGF-2). Pirfenidone and the known EMT-suppressor nintedanib suppress pulmonary fibrosis partially through suppression of TGF-β. The present study aimed to determine whether pirfenidone has the potential to induce EMT-reversion, using nintedanib as a reference. The human lung adenocarcinoma cell lines A-549, HCC-827, and PC-9 were treated with TGF-β and FGF-2 to induce EMT. The EMT-induced cells were further treated with pirfenidone or nintedanib. Phenotypic alterations associated with EMT were assessed by examining the following: i) The expression levels of E-cadherin, vimentin, fibronectin and slug, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and fluorescent immunohistochemistry; ii) cell motility via wound-healing assays; and iii) the expression of PD-L1 using RT-qPCR. The combination of TGF-β and FGF-2 successfully induced EMT in all three cell lines, characterized by a significant reduction in E-cadherin expression in the A-549 and HCC-827 cells, increased expression levels of vimentin, fibronectin, slug and PD-L1, and increased cell motility in all three cell lines. Pirfenidone and nintedanib reverted all of these phenotypes, with the exception of unaltered E-cadherin expression in all three cell lines, and inconsistent expression of vimentin in the HCC-827 and PC-9 cells. Thus, pirfenidone and nintedanib have the ability to induce EMT-reversion in human lung adenocarcinoma.
| S-EPMC5494670 | biostudies-other
Project description:Simple Summary Chemotherapeutic agents including cisplatin promote tumor metastasis while inhibiting tumor growth, which still represents a major obstacle for some patients in clinical practices. This study demonstrated that cisplatin induced epithelial-mesenchymal transition and tumor metastasis in lung adenocarcinoma. Further bioinformatic analysis showed that DCBLD2 may play a key role in metastasis after platinum chemotherapy. In terms of mechanism, DCBLD2 stabilized β-catenin through phosphorylation and inactivation of GSK3β, leading to the disintegration of the destruction complex of β-catenin. The accumulated β-catenin transported to the nucleus and promoted the expression of metastasis-related genes. In addition, cisplatin markedly enhanced DCBLD2 (Discoidin, CUB and LCCL domain containing 2) expression via ERK/AP-1 axis. Importantly, DCBLD2-specific siRNAs encapsulated by nanoparticles strikingly inhibited cisplatin-induced metastasis in tumor-bearing mice. Taken together, DCBLD2 mediates cisplatin-induced metastasis and DCBLD2 inhibition is a promising treatment option for preventing chemotherapy-induced metastasis. Abstract Growing evidence suggests that cisplatin and other chemotherapeutic agents promote tumor metastasis while inhibiting tumor growth, which is a critical issue for certain patients in clinical practices. However, the role of chemotherapeutics in promoting tumor metastasis and the molecular mechanism involved are unclear. Here, we investigated the roles of cisplatin in promoting tumor metastasis in lung adenocarcinoma (LUAD). We demonstrated that cisplatin promoted epithelial-mesenchymal transition (EMT), cell motility, and metastasis in vitro and in vivo. The bioinformatic analysis and molecular biology approaches also indicated that DCBLD2 (Discoidin, CUB and LCCL domain containing 2) is a key gene that mediates cisplatin-induced metastasis. DCBLD2 stabilizes β-catenin by phosphorylating GSK3β and transporting accumulated β-catenin to the nucleus to promote the expression of EMT-related transcriptional factors (TFs), ultimately resulting in tumor metastasis. We also identified that cisplatin enhanced DCBLD2 expression by phosphorylating ERK and hence the AP-1-driven transcription of DCBLD2. Furthermore, DCBLD2-specific siRNAs encapsulated by nanocarriers prominently inhibit cisplatin-induced metastasis in vivo. Therefore, DCBLD2 plays a key role in cisplatin-induced metastasis in LUAD and is a potential target for preventing chemotherapy-induced metastasis in vivo.
| S-EPMC8003509 | biostudies-literature
Project description:Epithelial-mesenchymal transition (EMT) plays an important role in the progression of lung carcinoma. Podocalyxin (PODXL), which belongs to the CD34 family and regulates cell morphology, has been linked to EMT in lung cancer, and PODXL overexpression is associated with poor prognosis in several different classes of cancers. The aim of this study was to clarify the role of PODXL overexpression in EMT in lung cancer, and to determine the prognostic value of PODXL overexpression in tumors from lung cancer patients. The morphology, EMT marker expression, and migration and invasion abilities of engineered A549 PODXL-knockdown (KD) or PODXL-overexpression (OE) lung adenocarcinoma cells were examined. PODXL expression levels were assessed by immunohistochemistry in 114 human clinical lung adenocarcinoma specimens and correlated with clinical outcomes. PODXL-KD cells were epithelial in shape, whereas PODXL-OE cells displayed mesenchymal morphology. Epithelial markers were upregulated in PODXL-KD cells and downregulated in PODXL-OE cells, whereas mesenchymal markers were downregulated in the former and upregulated in the latter. A highly selective inhibitor of phosphatidylinositol 3-kinase-Akt signaling attenuated EMT of PODXL-OE cells, while a transforming growth factor inhibitor did not, suggesting that PODXL induces EMT of lung adenocarcinoma cells via the phosphatidylinositol 3-kinase pathway. In lung adenocarcinoma clinical specimens, PODXL expression was detected in minimally invasive and invasive adenocarcinoma, but not in non-invasive adenocarcinoma. Disease free survival and cancer-specific survival were significantly worse for patients whose tumors overexpressed PODXL. PODXL overexpression induces EMT in lung adenocarcinoma and contributes to tumor progression.
| S-EPMC5378270 | biostudies-literature
Project description:Background: Glycolysis is closely related to the occurrence and progression of gastric cancer (GC). Currently, there is no systematic study on using the glycolysis-related long non-coding RNA (lncRNA) as a model for predicting the survival time in patients with GC. Therefore, it was essential to develop a signature for predicting the survival based on glycolysis-related lncRNA in patients with GC. Materials and methods: LncRNA expression profiles, containing 375 stomach adenocarcinoma (STAD) samples, were obtained from The Cancer Genome Atlas (TCGA) database. The co-expression network of lncRNA and glycolysis-related genes was used to identify the glycolysis-related lncRNAs. The Kaplan-Meier survival analysis and univariate Cox regression analysis were used to detect the glycolysis-related lncRNA with prognostic significance. Then, Bayesian Lasso-logistic and multivariate Cox regression analyses were performed to screen the glycolysis-related lncRNA with independent prognostic significance and to develop the risk model. Patients were assigned into the low- and high-risk cohorts according to their risk scores. A nomogram model was constructed based on clinical information and risk scores. Gene Set Enrichment Analysis (GSEA) was performed to visualize the functional and pathway enrichment analyses of the glycolysis-related lncRNA. Finally, the robustness of the results obtained was verified in an internal validation data set. Results: Seven glycolysis-related lncRNAs (AL353804.1, AC010719.1, TNFRSF10A-AS1, AC005586.1, AL355574.1, AC009948.1, and AL161785.1) were obtained to construct a risk model for prognosis prediction in the STAD patients using Lasso regression and multivariate Cox regression analyses. The risk score was identified as an independent prognostic factor for the patients with STAD [HR = 1.315, 95% CI (1.056-1.130), p < 0.001] via multivariate Cox regression analysis. Receiver operating characteristic (ROC) curves were drawn and the area under curve (AUC) values of 1-, 3-, and 5-year overall survival (OS) were calculated to be 0.691, 0.717, and 0.723 respectively. Similar results were obtained in the validation data set. In addition, seven glycolysis-related lncRNAs were significantly enriched in the classical tumor processes and pathways including cell adhesion, positive regulation of vascular endothelial growth factor, leukocyte transendothelial migration, and JAK_STAT signaling pathway. Conclusion: The prognostic prediction model constructed using seven glycolysis-related lncRNA could be used to predict the prognosis in patients with STAD, which might help clinicians in the clinical treatment for STAD.
| S-EPMC9614251 | biostudies-literature
Project description:Epithelial-mesenchymal transition (EMT) is associated with tumor invasion and progression, and is regulated by DNA methylation. A prognostic signature of lung squamous cell carcinoma (LUSC) with EMT-related gene data has not yet been established. In our study, we constructed a co-expression network using differentially expressed genes (DEGs) obtained from The Cancer Genome Atlas (TCGA) to identify hub genes. We conducted a correlation analysis between the differentially methylated hub genes and differentially expressed EMT-related genes to screen EMT-related differentially methylated genes (ERDMGs). Functional enrichment was performed to annotate the ERDMGs. The least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression analyses were performed to build a survival prognosis prediction model. Additionally, druggability analysis was performed to predict the potential drug targets of ERDMGs. We screened 11 ERDMGs that were enriched in cell adhesion molecules and other signaling pathways. Finally, we constructed a 4-ERDMG model, which showed good ability to predict survival prognosis in the training and validation sets. The model could serve as an independent predictive factor for patients with LUSC. Additionally, our druggability analysis predicted that CC chemokine ligand 23 (CCL23) and Hepatocyte nuclear factor 1b (HNF1B) may be the underlying drug targets of LUSC. We established a new risk score (RS) system as a prognostic indicator to predict the outcome of patients with LUSC, which will help in the improvement of treatment strategies.
| S-EPMC10344514 | biostudies-literature