ArticleBMC cancer2014
Large differences in global transcriptional regulatory programs of normal and tumor colon cells.
Article in BMC cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Pooled it
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- Gene regulation network inference using k-nearest neighbor-based mutual information estimation: revisiting an old DREAM.BMC bioinformatics · 2023Article
- Endoplasmic reticulum-resident protein Sec62 drives colorectal cancer metastasis via MAPK/ATF2/UCA1 axis.Cell proliferation · 2022Article
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- Tissue, age, sex, and disease patterns of matrisome expression in GTEx transcriptome data.Scientific reports · 2021Article
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- Mechanism-Centric Approaches for Biomarker Detection and Precision Therapeutics in Cancer.Frontiers in genetics · 2021Review
- METTL14-mediated N6-methyladenosine modification of SOX4 mRNA inhibits tumor metastasis in colorectal cancer.Molecular cancer · 2020Article
- Edgetic perturbation signatures represent known and novel cancer biomarkers.Scientific reports · 2020Article
- Enhancing reproducibility of gene expression analysis with known protein functional relationships: The concept of well-associated protein.PLoS computational biology · 2020Article
- Tumor suppressor genes and allele-specific expression: mechanisms and significance.Oncotarget · 2020Article
- Transcriptome and Network Dissection of Microsatellite Stable and Highly Instable Colorectal Cancer.Asian Pacific journal of cancer prevention : APJCP · 2019Article
- Identification of novel biomarkers and small molecule drugs in human colorectal cancer by microarray and bioinformatics analysis.Molecular genetics & genomic medicine · 2019Article
- Wnt-11 as a Potential Prognostic Biomarker and Therapeutic Target in Colorectal Cancer.Cancers · 2019Article
- Integrated Analysis of Oncogenic Networks in Colorectal Cancer Identifies GUCA2A as a Molecular Marker.Biochemistry research international · 2019Article
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDysregulation of transcriptional programs leads to cell malfunctioning and can have an impact in cancer development. Our study aims to characterize global differences between transcriptional regulatory programs of normal and tumor cells of the colon.
methodsAffymetrix Human Genome U219 expression arrays were used to assess gene expression in 100 samples of colon tumor and their paired adjacent normal mucosa. Transcriptional networks were reconstructed using ARACNe algorithm using 1,000 bootstrap replicates consolidated into a consensus network. Networks were compared regarding topology parameters and identified well-connected clusters. Functional enrichment was performed with SIGORA method. ENCODE ChIP-Seq data curated in the hmChIP database was used for in silico validation of the most prominent transcription factors.
resultsThe normal network contained 1,177 transcription factors, 5,466 target genes and 61,226 transcriptional interactions. A large loss of transcriptional interactions in the tumor network was observed (11,585; 81% reduction), which also contained fewer transcription factors (621; 47% reduction) and target genes (2,190; 60% reduction) than the normal network. Gene silencing was not a main determinant of this loss of regulatory activity, since the average gene expression was essentially conserved. Also, 91 transcription factors increased their connectivity in the tumor network. These genes revealed a tumor-specific emergent transcriptional regulatory program with significant functional enrichment related to colorectal cancer pathway. In addition, the analysis of clusters again identified subnetworks in the tumors enriched for cancer related pathways (immune response, Wnt signaling, DNA replication, cell adherence, apoptosis, DNA repair, among others). Also multiple metabolism pathways show differential clustering between the tumor and normal network.
conclusionsThese findings will allow a better understanding of the transcriptional regulatory programs altered in colon cancer and could be an invaluable methodology to identify potential hubs with a relevant role in the field of cancer diagnosis, prognosis and therapy.
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