ArticleBMC cancer2022
Construction of CeRNA regulatory network based on WGCNA reveals diagnosis biomarkers for colorectal cancer.
Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Identifying Essential Hub Genes and circRNA-Regulated ceRNA Networks in Hepatocellular Carcinoma.International journal of molecular sciences · 2025Article
- SCIN: A Key Driver in Chronic Atrophic Gastritis-Gastric Cancer Cascade with Implications for Immunity and Prognosis.Journal of inflammation research · 2025Article
- Sparassis latifolia and exercise training as complementary medicine mitigated the 5-fluorouracil potent side effects in mice with colorectal cancer: bioinformatics approaches, novel monitoring pathological metrics, screening signatures, and innovative management tactic.Cancer cell international · 2024Article
- Identification of a prognosis-related gene signature and ceRNA regulatory networks in lung adenocarcinoma.Heliyon · 2024Article
- Research progress on the biological basis of Traditional Chinese Medicine syndromes of gastrointestinal cancers.Heliyon · 2023Review
- Identification and verification of a prognostic signature based on a miRNA-mRNA interaction pattern in colon adenocarcinoma.Frontiers in cell and developmental biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundColorectal cancer is the third most common cause of death among cancers in the world. Although improvements in various treatments have greatly improved the survival time of colorectal cancer patients, since colorectal cancer is often at an advanced stage when diagnosed, the prognosis of patients is still very poor. Since the ceRNA regulatory network was proposed in 2011, it has greatly promoted the study of the molecular mechanism of colorectal cancer occurrence and development.
objectiveExploring the new molecular mechanism of colorectal cancer occurrence and development and providing new targets for the diagnosis and treatment of colorectal cancer.
methodWe analyzed the RNA-seq data of CRC from TCGA, such as differential expression analysis, weighted gene co-expression network analysis (WGCNA) and construction of ceRNA regulatory network.
resultsWe constructed a ceRNA network using RNA-seq data of CRC from TCGA. In the ceRNA regulatory network, 19 hub molecules with significant prognostic effects were ultimately identified, including 8 lncRNAs, 2 mRNAs and 9 miRNAs. These hub molecules constitute the lncRNA-miRNA, miRNA-mRNA or lncRNA-miRNA-mRNA axis.
conclusionIn this article, some new ceRNA regulatory axes have been discovered, which may potentially disclose new molecular mechanisms for the occurrence and development of colorectal cancer, thereby providing an important blueprint for the treatment and prognosis assessment of CRC patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.