ArticleCancer communications (London, England)2018
Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma.
Article in Cancer communications (London, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- The functions of circular RNAs and long noncoding RNAs in cholangiocarcinoma.Discover oncology · 2025Review
- A circRNA promotes esophageal squamous cell carcinoma progression by inhibiting TRIM25-mediated degradation of IGF2BP family members.Molecular cancer · 2025Article
- Roles of long non-coding RNAs in oesophageal cancer pathogenesis.International journal of experimental pathology · 2025Review
- Bioinformatics Analysis Reveals a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma.International journal of medical sciences · 2024Article
- Development and validation of an individualized gene expression-based signature to predict overall survival of patients with high-grade serous ovarian carcinoma.European journal of medical research · 2023Article
- Novel chemokine related LncRNA signature correlates with the prognosis, immune landscape, and therapeutic sensitivity of esophageal squamous cell cancer.BMC gastroenterology · 2023Article
- Identification of seven-gene marker to predict the survival of patients with lung adenocarcinoma using integrated multi-omics data analysis.Journal of clinical laboratory analysis · 2022Article
- Construction of the Six-lncRNA Prognosis Signature as a Novel Biomarker in Esophageal Squamous Cell Carcinoma.Frontiers in genetics · 2022Article
- Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma.Frontiers in oncology · 2022Article
- Identification and Validation of a Hypoxia-Immune-Based Prognostic mRNA Signature for Oral Squamous Cell Carcinoma.Journal of oncology · 2022Article
- Evaluation of the Prognostic Value of Long Noncoding RNAs in Lung Squamous Cell Carcinoma.Journal of oncology · 2022Article
- Identification of 6 gene markers for survival prediction in osteosarcoma cases based on multi-omics analysis.Experimental biology and medicine (Maywood, N.J.) · 2021Article
- A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD).Cancer cell international · 2021Article
- The emerging role of long noncoding RNAs in esophageal carcinoma: from underlying mechanisms to clinical implications.Cellular and molecular life sciences : CMLS · 2021Review
- RNA sequencing reveals the expression profiles of circRNA and identifies a four-circRNA signature acts as a prognostic marker in esophageal squamous cell carcinoma.Cancer cell international · 2021Article
- Construction and Analysis of the Dysregulated ceRNA Network and Identification of Risk Long Noncoding RNAs in Breast Cancer.Frontiers in genetics · 2021Article
- Identification of a novel CpG methylation signature to predict prognosis in lung squamous cell carcinoma.Cancer biomarkers : section A of Disease markers · 2021Article
- Identification of a Novel Immune-Related CpG Methylation Signature to Predict Prognosis in Stage II/III Colorectal Cancer.Frontiers in genetics · 2021Article
- Emerging roles of long noncoding RNAs in cholangiocarcinoma: Advances and challenges.Cancer communications (London, England) · 2020Review
- An aberrant DNA methylation signature for predicting hepatocellular carcinoma.Annals of translational medicine · 2020Article
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12 authors.
Funding
Abstract
backgroundEsophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal carcinoma in China. This study was to develop a staging model to predict outcomes of patients with ESCC.
methodsUsing Cox regression analysis, principal component analysis (PCA), partitioning clustering, Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and classification and regression tree (CART) analysis, we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset.
resultsUnivariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes (PCGs) and 635 long non-coding RNAs (lncRNAs) were associated with the survival of patients with ESCC. PCA categorized these PCGs and lncRNAs into three principal components (PCs), which were used to cluster the patients into three groups. ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging (area under ROC curve [AUC]: 0.69 vs. 0.65, P < 0.05). Accordingly, we constructed a molecular disaggregated model comprising one lncRNA and two PCGs, which we designated as the LSB staging model using CART analysis in the GSE63624 dataset. This LSB staging model classified the GSE63622 dataset of patients into three different groups, and its effectiveness was validated by analysis of another cohort of 105 patients.
conclusionsThe LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.
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