SynthesisBMC cancer2008
Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer.
Synthesis in BMC cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.
What it found
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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.
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
45 citing papers in PubMed, 2 syntheses or guidelines pooled it, 81 citations in OpenAlex.
- Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE).PLoS computational biology · 2019Pooled it
- Transcriptome meta-analysis reveals dysregulated pathways in nasopharyngeal carcinoma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2015Pooled it
- Deep-learning-enabled multi-omics analyses for prediction of future metastasis in cancer.Nature communications · 2026Article
- Article
- Clinical Significance of Nuclear Yin-Yang Overexpression Evaluated by Immunohistochemistry in Tissue Microarrays and Digital Pathology Analysis: A Useful Prognostic Tool for Breast Cancer.International journal of molecular sciences · 2025Article
- Identification of hub modules and therapeutic targets associated with CD8Scientific reports · 2024Article
- Regulation of PD-L1 Expression by YY1 in Cancer: Therapeutic Efficacy of Targeting YY1.Cancers · 2024Review
- Yin Yang 1 expression predicts a favourable survival in diffuse large B-cell lymphoma.Heliyon · 2024Article
- Construction of ovarian metastasis-related immune signature predicting prognosis of gastric cancer patients.Cancer medicine · 2023Article
- Identification of Hub Genes for Colorectal Cancer with Liver Metastasis Using miRNA-mRNA Network.Disease markers · 2023Article
- RNF144A exerts tumor suppressor function in breast cancer through targeting YY1 for proteasomal degradation to downregulate GMFG expression.Medical oncology (Northwood, London, England) · 2022Article
- Solving the Puzzle: What Is the Role of Progestogens in Neovascularization?Biomolecules · 2021Review
- Roles Played by YY1 in Embryonic, Adult and Cancer Stem Cells.Stem cell reviews and reports · 2021Review
- YBX1 Enhances Metastasis and Stemness by Transcriptionally Regulating MUC1 in Lung Adenocarcinoma.Frontiers in oncology · 2021Article
- Considerations for feature selection using gene pairs and applications in large-scale dataset integration, novel oncogene discovery, and interpretable cancer screening.BMC medical genomics · 2020Article
- Article
- HybridCancers · 2019Article
- The Two Sides of YY1 in Cancer: A Friend and a Foe.Frontiers in oncology · 2019Review
- E2F6 is essential for cell viability in breast cancer cells during replication stress.Turkish journal of biology = Turk biyoloji dergisi · 2019Article
- Deciphering the roles of lncRNAs in breast development and disease.Oncotarget · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMetastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets.
methodsWe have analyzed 8 publicly available gene expression data sets. A global approach, "gene set enrichment analysis" as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets.
resultsThe major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis.
conclusionBy pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may constitute new targets are identified.
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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.