ArticleFrontiers in oncology2020
Differential Expression Analysis Revealing CLCA1 to Be a Prognostic and Diagnostic Biomarker for Colorectal Cancer.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 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
15 citing papers in PubMed, 26 citations in OpenAlex.
- Comprehensive bioinformatics analysis was used to identify and verify differentially expressed genes in targeted therapy of colon cancer.Scientific reports · 2025Article
- Establishment of two pathomic-based machine learning models to predict CLCA1 expression in colon adenocarcinoma.PloS one · 2025Article
- NMB promotes the progression of colorectal cancer by regulating the NF-κB/P65 signaling pathway.Frontiers in immunology · 2025Article
- Integrating machine learning and bioinformatics approaches for identifying novel diagnostic gene biomarkers in colorectal cancer.Scientific reports · 2024Article
- Weighted gene co-expression network analysis for hub genes in colorectal cancer.Pharmacological reports : PR · 2024Article
- Identification of GUCA2A and COL3A1 as prognostic biomarkers in colorectal cancer by integrating analysis of RNA-Seq data and qRT-PCR validation.Scientific reports · 2023Article
- Article
- An integrative transcriptome analysis reveals potential predictive, prognostic biomarkers and therapeutic targets in colorectal cancer.BMC cancer · 2022Article
- Article
- Article
- Article
- Identification of Hub Genes in Colorectal Adenocarcinoma by Integrated Bioinformatics.Frontiers in cell and developmental biology · 2022Article
- Integrated Analysis of ECT2 and COL17A1 as Potential Biomarkers for Pancreatic Cancer.Disease markers · 2022Article
- Identification of gene biomarkers and immune cell infiltration characteristics in rectal cancer.Journal of gastrointestinal oncology · 2021Article
- Expression of the CLCA4 Gene in Esophageal Carcinoma and Its Impact on the Biologic Function of Esophageal Carcinoma Cells.Journal of oncology · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is a common malignant tumor of the digestive tract and lacks specific diagnostic markers. In this study, we utilized 10 public datasets from the NCBI Gene Expression Omnibus (NCBI-GEO) database to identify a set of significantly differentially expressed genes (DEGs) between tumor and control samples and WGCNA (Weighted Gene Co-Expression Network Analysis) to construct gene co-expression networks incorporating the DEGs from The Cancer Genome Atlas (TCGA) and then identify genes shared between the GEO datasets and key modules. Then, these genes were screened
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.