ArticleInternational journal of molecular sciences2016
Identification of 42 Genes Linked to Stage II Colorectal Cancer Metastatic Relapse.
Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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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.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Diagnosis of early-stage non-small cell lung cancer using DNA methylation in tissue and plasma.Genes & diseases · 2025Article
- Polygonum barbatum extract reduces colorectal cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition via YAP and β-catenin pathway regulation.Scientific reports · 2023Article
- Prognostic value of the ratio of carcinoembryonic antigen concentration to maximum tumor diameter in patients with stage II colorectal cancer.Journal of gastrointestinal oncology · 2021Article
- Exosomal Components and Modulators in Colorectal Cancer: Novel Diagnosis and Prognosis Biomarkers.Biomedicines · 2021Review
- Identification and Validation of a Six Immune-Related Genes Signature for Predicting Prognosis in Patients With Stage II Colorectal Cancer.Frontiers in genetics · 2021Article
- Systematic analysis of alternative splicing signature unveils prognostic predictor for kidney renal clear cell carcinoma.Journal of cellular physiology · 2019Article
- Emerging Roles of GLI-Similar Krüppel-like Zinc Finger Transcription Factors in Leukemia and Other Cancers.Trends in cancer · 2019Review
- A signature of hypoxia-related factors reveals functional dysregulation and robustly predicts clinical outcomes in stage I/II colorectal cancer patients.Cancer cell international · 2019Article
- Aberrantly Expressed Genes and miRNAs in Slow Transit Constipation Based on RNA-Seq Analysis.BioMed research international · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is one of the leading causes of cancer mortality. Metastasis remains the primary cause of CRC death. Predicting the possibility of metastatic relapse in early-stage CRC is of paramount importance to target therapy for patients who really need it and spare those with low-potential of metastasis. Ninety-six stage II CRC cases were stratified using high-resolution array comparative genomic hybridization (aCGH) data based on a predictive survival algorithm and supervised clustering. All genes included within the resultant copy number aberrations were each interrogated independently at mRNA level using CRC expression datasets available from public repositories, which included 1820 colon cancers, and 167 normal colon tissues. Reduced mRNA expression driven by copy number losses and increased expression driven by copy number gains revealed 42 altered transcripts (29 reduced and 13 increased transcripts) associated with metastatic relapse, short disease-free or overall survival, and/or epithelial to mesenchymal transition (EMT). Resultant genes were classified based on gene ontology (GO), which identified four functional enrichment groups involved in growth regulation, genomic integrity, metabolism, and signal transduction pathways. The identified 42 genes may be useful for predicting metastatic relapse in stage II CRC. Further studies are necessary to validate these findings.
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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.