ArticleBMC gastroenterology2022
Construction of a novel necroptosis-related lncRNA signature for prognosis prediction in esophageal cancer.
Article in BMC gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 7 citations in OpenAlex.
- Development and validation of an m6A and autophagy related lncRNAs signature for predicting survival and modulating the immune microenvironment in esophageal squamous cell carcinoma.Frontiers in immunology · 2026Article
- Unveiling novel potential drug targets for lung cancer through Mendelian randomization analysis.Scientific reports · 2025Article
- PANoptosis: potential new targets and therapeutic prospects in digestive diseases.Apoptosis : an international journal on programmed cell death · 2025Review
- Prognostic analysis and risk assessment based on RNA editing in hepatocellular carcinoma.Journal of applied genetics · 2024Article
- A four-gene signature predicts overall survival of patients with esophageal adenocarcinoma.Translational cancer research · 2024Article
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8 authors at 2 institutions in 1 country.
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Abstract
backgroundEsophageal cancer (EC), one highly malignant gastrointestinal cancer, is the 6th leading cause of cancer-related deaths worldwide. Necroptosis and long non-coding RNA (lncRNA) play important roles in the occurrence and development of EC, but the research on the role of necroptosis-related lncRNA in EC is not conclusive. This study aims to use bioinformatics to investigate the prognostic value of necroptosis-related lncRNA in EC.
methodsTranscriptome data containing EC and normal samples, and clinical information were obtained from the Cancer Genome Atlas database. 102 necroptosis-related genes were obtained from Kanehisa Laboratories. Necroptosis-related lncRNAs were screened out via univariate, multivariate Cox and the least absolute shrinkage and selection operator regression analyses to construct the risk predictive model. The reliability of the risk model was evaluated mainly through quantitative real-time PCR (qRT-PCR), the receiver operating characteristic (ROC) curves and the constructed nomogram. KEGG pathways were explored in the high- and low-risk groups of EC patients via gene set enrichment analyses (GSEA) software. Immune microenvironment and potential therapeutic agents in risk groups were also analyzed.
resultsA 6 necroptosis-related lncRNAs risk model composed of AC022211.2, Z94721.1, AC007991.2, SAMD12-AS1, AL035461.2 and AC051619.4 was established to predict the prognosis level of EC patients. qRT-PCR analysis showed upregulated Z94721.1 and AL035461.2 mRNA levels and downregulated AC051619.4 mRNA level in EC tissues compared with normal tissues. According to clinical characteristics, the patients in the high-risk group had a shorter overall survival than the low-risk group. The ROC curve and nomogram confirmed this model as one independent and predominant predictor. GSEA analysis showed metabolic and immune-related pathways enriched in the risk model. Most of the immune cells and immune checkpoints were positively correlated with the risk model, mainly active in the high-risk group. For the prediction of potential therapeutic drugs, 16 compounds in the high-risk group and 2 compounds in the low-risk group exhibited higher sensitivity.
conclusionsOur results supported the necroptosis-related lncRNA signature could independently predict prognosis of EC patients, and provided theoretical basis for improving the clinical treatment of EC.
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