ArticleFrontiers in oncology2021
A Novel Prognostic Prediction Model for Colorectal Cancer Based on Nine Autophagy-Related Long Noncoding RNAs.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 15 citations in OpenAlex.
- Upregulation of CYP1B1-AS1 correlates with aggressive phenotypes and poor prognosis in thyroid cancer.World journal of surgical oncology · 2026Article
- Long non‑coding RNA NKILA regulates the JAK2/STAT3 pathway to exacerbate TGF‑β1‑mediated renal fibrosis.Molecular medicine reports · 2026Article
- lncRNA NKILA Promotes Warburg Effect and Immune Escape in Intrahepatic Cholangiocarcinoma by Regulating the MTX1/TOMM40 Axis.Mediators of inflammation · 2025Article
- Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer.World journal of gastrointestinal oncology · 2023Article
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- [mNan fang yi ke da xue xue bao = Journal of Southern Medical University · 2022Article
- N7-methylguanosine-related lncRNAs: Distinction between hot and cold tumors and construction of predictive models in colon adenocarcinoma.Frontiers in oncology · 2022Article
- N7-methylguanosine-related lncRNAs: Predicting the prognosis and diagnosis of colorectal cancer in the cold and hot tumors.Frontiers in genetics · 2022Article
- Identification of an m6A-Related Long Noncoding RNA Risk Model for Predicting Prognosis and Directing Treatments in Patients With Colon Adenocarcinoma.Frontiers in cell and developmental biology · 2022Article
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionColorectal cancer (CRC) is the most common gastrointestinal cancer and has a low overall survival rate. Tumor-node-metastasis staging alone is insufficient to predict patient prognosis. Autophagy and long noncoding RNAs play important roles in regulating the biological behavior of CRC. Therefore, establishing an autophagy-related lncRNA (ARlncRNA)-based bioinformatics model is important for predicting survival and facilitating clinical treatment.
methodsCRC data were retrieved from The Cancer Genome Atlas. The database was randomly divided into train set and validation set; then, univariate and multivariate Cox regression analyses were performed to screen prognosis-related ARlncRNAs for prediction model construction. Interactive network and Sankey diagrams of ARlncRNAs and messenger RNAs were plotted. We analyzed the survival rate of high- and low-risk patients and plotted survival curves and determined whether the risk score was an independent predictor of CRC. Receiver operating characteristic curves were used to evaluate model sensitivity and specificity. Then, the expression level of lncRNA was detected by quantitative real-time polymerase chain reaction, and the location of lncRNA was observed by fluorescence
resultsA prognostic prediction model of CRC was built based on nine ARlncRNAs (
conclusionThe new ARlncRNA-based model predicts CRC patient prognosis and provides new research ideas regarding potential mechanisms regulating the biological behavior of CRC. ARlncRNAs may play important roles in personalized cancer treatment.
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