ArticleFrontiers in pharmacology2020
Construction and Analysis of the Tumor-Specific mRNA-miRNA-lncRNA Network in Gastric Cancer.
Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 52 citations in OpenAlex.
- Use of machine learning-based integration to develop an immune-related signature for improving prognosis in patients with gastric cancer.Scientific reports · 2023Trial
- Lysine crotonylation-related long non-coding RNAs: a novel prognostic framework for gastric carcinoma.Translational cancer research · 2026Article
- TTF2 as a potential biomarker and immunotherapy target in glioma diagnosis and prognosis.Scientific reports · 2026Article
- Systems biology analysis of long non-coding RNAs and targets to identify key modules and biomarkers in breast cancer.Discover oncology · 2025Article
- Recent advances in understanding the relationship between lipid metabolism and immune escape in the tumor microenvironment of gastric cancer.Medical review (2021) · 2025Review
- Prognostic implication of six m6A-modulated genes signature in the ferroptosis for hepatocellular carcinoma patients.Clinical and experimental medicine · 2025Article
- Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods.Frontiers in bioinformatics · 2025Article
- Uncovering the ceRNA Network Related to the Prognosis of Stomach Adenocarcinoma Among 898 Patient Samples.Biochemical genetics · 2024Article
- Overexpression of ZFP69B promotes hepatocellular carcinoma growth by upregulating the expression of TLX1 and TRAPPC9.Cell division · 2024Article
- Role ofQuantitative biology (Beijing, China) · 2024Article
- ZNF643/ZFP69B Exerts Oncogenic Properties and Associates with Cell Adhesion and Immune Processes.International journal of molecular sciences · 2023Article
- MicroRNA-143 acts as a tumor suppressor through Musashi-2/DLL1/Notch1 and Musashi-2/Snail1/MMPs axes in acute myeloid leukemia.Journal of translational medicine · 2023Article
- Review
- MAB21L4 Deficiency Drives Squamous Cell Carcinoma via Activation of RET.Cancer research · 2022Article
- Exploration of hub genes, lipid metabolism, and the immune microenvironment in stomach carcinoma and cholangiocarcinoma.Annals of translational medicine · 2022Article
- Key Molecules of Fatty Acid Metabolism in Gastric Cancer.Biomolecules · 2022Review
- LINC00922 acts as a novel oncogene in gastric cancer.World journal of surgical oncology · 2022Article
- LncRNA OGFRP1 promotes cell proliferation and suppresses cell radiosensitivity in gastric cancer by targeting the miR-149-5p/MAP3K3 axis.Journal of molecular histology · 2022Article
- Identification of KIF21B as a Biomarker for Colorectal Cancer and Associated with Poor Prognosis.Journal of oncology · 2022Article
- Long non-coding RNA p53 upregulated regulator of p53 levels (PURPL) promotes the development of gastric cancer.Bioengineered · 2022Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Weighted correlation network analysis (WGCNA) is a statistical method that has been widely used in recent years to explore gene co-expression modules. Competing endogenous RNA (ceRNA) is commonly involved in the cancer gene expression regulation mechanism. Some ceRNA networks are recognized in gastric cancer; however, the prognosis-associated ceRNA network has not been fully identified using WGCNA. We performed WGCNA using datasets from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) to identify cancer-associated modules. The criteria of differentially expressed RNAs between normal stomach samples and gastric cancer samples were set at the false discovery rate (FDR) < 0.01 and |fold change (FC)| > 1.3. The ceRNA relationships obtained from the RNAinter database were examined by both the Pearson correlation test and hypergeometric test to confirm the mRNA-lncRNA regulation. Overlapped genes were recognized at the intersections of genes predicted by ceRNA relationships, differentially expressed genes, and genes in cancer-specific modules. These were then used for univariate and multivariate Cox analyses to construct a risk score model. The ceRNA network was constructed based on the genes in this model. WGCNA-uncovered genes in the green and turquoise modules are those most associated with gastric cancer. Eighty differentially expressed genes were observed to have potential prognostic value, which led to the identification of 12 prognosis-related mRNAs (
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