ArticlePloS one2016
Identification of Cancer Related Genes Using a Comprehensive Map of Human Gene Expression.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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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
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- An algorithm-based meta-analysis of genome- and proteome-wide data identifies a combination of potential plasma biomarkers for colorectal cancer.Scientific reports · 2019Pooled it
- Bone marrow microenvironments that contribute to patient outcomes in newly diagnosed multiple myeloma: A cohort study of patients in the Total Therapy clinical trials.PLoS medicine · 2020Trial
- Characterization of Cancer/Testis Antigens as Prognostic Markers of Ovarian Cancer.Diagnostics (Basel, Switzerland) · 2023Article
- Assessment of deep learning and transfer learning for cancer prediction based on gene expression data.BMC bioinformatics · 2022Article
- Characterization ofBiomolecules · 2021Article
- Band-based similarity indices for gene expression classification and clustering.Scientific reports · 2021Article
- Deep GONet: self-explainable deep neural network based on Gene Ontology for phenotype prediction from gene expression data.BMC bioinformatics · 2021Article
- Elevated Expression of Cathepsin K in Periodontal Ligament Fibroblast by Inflammatory Cytokines Accelerates Osteoclastogenesis via Paracrine Mechanism in Periodontal Disease.International journal of molecular sciences · 2021Article
- Use of signals of positive and negative selection to distinguish cancer genes and passenger genes.eLife · 2021Article
- Biological interpretation of deep neural network for phenotype prediction based on gene expression.BMC bioinformatics · 2020Article
- Extreme Downregulation of Chromosome Y and Cancer Risk in Men.Journal of the National Cancer Institute · 2020Article
- Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder.Nature communications · 2020Article
- Secreted modular calcium-binding proteins in pathophysiological processes and embryonic development.Chinese medical journal · 2019Review
- A rectified factor network based biclustering method for detecting cancer-related coding genes and miRNAs, and their interactions.Methods (San Diego, Calif.) · 2019Article
- Article
- Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma.Scientific reports · 2018Article
- Cancer transcriptome profiling at the juncture of clinical translation.Nature reviews. Genetics · 2018Review
- Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics.Nucleic acids research · 2018Article
- Overexpression of SMOC2 Attenuates the Tumorigenicity of Hepatocellular Carcinoma Cells and Is Associated With a Positive Postoperative Prognosis in Human Hepatocellular Carcinoma.Journal of Cancer · 2017Article
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 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rapid accumulation and availability of gene expression datasets in public repositories have enabled large-scale meta-analyses of combined data. The richness of cross-experiment data has provided new biological insights, including identification of new cancer genes. In this study, we compiled a human gene expression dataset from ∼40,000 publicly available Affymetrix HG-U133Plus2 arrays. After strict quality control and data normalisation the data was quantified in an expression matrix of ∼20,000 genes and ∼28,000 samples. To enable different ways of sample grouping, existing annotations where subjected to systematic ontology assisted categorisation and manual curation. Groups like normal tissues, neoplasmic tissues, cell lines, homoeotic cells and incompletely differentiated cells were created. Unsupervised analysis of the data confirmed global structure of expression consistent with earlier analysis but with more details revealed due to increased resolution. A suitable mixed-effects linear model was used to further investigate gene expression in solid tissue tumours, and to compare these with the respective healthy solid tissues. The analysis identified 1,285 genes with systematic expression change in cancer. The list is significantly enriched with known cancer genes from large, public, peer-reviewed databases, whereas the remaining ones are proposed as new cancer gene candidates. The compiled dataset is publicly available in the ArrayExpress Archive. It contains the most diverse collection of biological samples, making it the largest systematically annotated gene expression dataset of its kind in the public domain.
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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.