ArticleFrontiers in cell and developmental biology2021
lncRNA Profiles Enable Prognosis Prediction and Subtyping for Esophageal Squamous Cell Carcinoma.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 51 citations in OpenAlex.
- Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer.World journal of gastrointestinal oncology · 2023Article
- Mechanisms of Chinese Medicine in Gastroesophageal Reflux Disease Treatment: Data Mining and Systematic Pharmacology Study.Chinese journal of integrative medicine · 2023Article
- Identification of m6A-related lncRNAs as prognostic signature within colon tumor immune microenvironment.Cancer reports (Hoboken, N.J.) · 2023Article
- Bioinformatics Analysis of the Inflammation-Associated lncRNA-mRNA Coexpression Network in Type 2 Diabetes.Journal of the renin-angiotensin-aldosterone system : JRAAS · 2023Article
- m7G-related lncRNAs are potential biomarkers for predicting prognosis and immune responses in patients with oral squamous cell carcinoma.Frontiers in genetics · 2022Article
- A Genomic Instability-Related Long Noncoding RNA Signature for Predicting Hepatocellular Carcinoma Prognosis.Journal of oncology · 2022Article
- Prognosis Risk Model Based on Pyroptosis-Related lncRNAs for Bladder Cancer.Disease markers · 2022Article
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8 authors at 2 institutions in 1 country.
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Abstract
Long non-coding RNAs (lncRNAs) have emerged as useful prognostic markers in many tumors. In this study, we investigated the potential application of lncRNA markers for the prognostic prediction of esophageal squamous cell carcinoma (ESCC). We identified ESCC-associated lncRNAs by comparing ESCC tissues with normal tissues. Subsequently, Kaplan-Meier (KM) method in combination with the univariate Cox proportional hazards regression (UniCox) method was used to screen prognostic lncRNAs. By combining the differential and prognostic lncRNAs, we developed a prognostic model using cox stepwise regression analysis. The obtained prognostic prediction model could effectively predict the 3- and 5-year prognosis and survival of ESCC patients by time-dependent receiver operating characteristic (ROC) curves (area under curve = 0.87 and 0.89, respectively). Besides, a lncRNA-based classification of ESCC was generated using k-mean clustering method and we obtained two clusters of ESCC patients with association with race and Barrett's esophagus (BE) (both
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