ArticleOncology reports2014
Gene profiling and bioinformatics analyses reveal time course differential gene expression in surgically resected colorectal tissues.
Article in Oncology reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Regulatory role of phosphatidylcholine metabolic reprogramming in colorectal cancer progression and neutrophil interactions.iScience · 2025Article
- Identification and Validation of SLC9A2 as A Potential Tumor Suppressor in Colorectal Cancer: Integrating Bioinformatics Analysis with Experimental Confirmation.Current medical science · 2024Article
- Collection and Processing of Lymph Nodes from Large Animals for RNA Analysis: Preparing for Lymph Node Transcriptomic Studies of Large Animal Species.Journal of visualized experiments : JoVE · 2018Article
- The focus on sample quality: Influence of colon tissue collection on reliability of qPCR data.Scientific reports · 2016Article
- Identification and Validation of a Potential Marker of Tissue Quality Using Gene Expression Analysis of Human Colorectal Tissue.PloS one · 2015Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has previously been reported that gene profiles in surgically-resected colorectal cancer tissues are altered over time possibly due to the different tissue-acquisition methods and sample extraction timing that were used. However, the changes that occur are still not clearly understood. In the present study, time-dependent changes in gene expression profiling in colorectal surgical specimens were analyzed. Normal and tumor tissues at several time-points (0, 30, 60 and 120 min) were extracted, and RNA quality, microarray experiments, quantitative PCR and bioinformatics clustering were performed. Although RNA integrity was preserved 2 h after resection, inherent increased/decreased gene expression was observed from 30-120 min in approximately 10% of genes. Bioinformatics clustering could not distinguish case-by-case, probably due to gene profiling changes. Irregular changes in gene expression after surgical resection were found, which could be a crucial confounding factor for quantitative analyses.
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