PrognoScan: a new database for meta-analysis of the prognostic value of genes

By Hideaki Mizuno, K. Kitada, Kenta Nakai, Akinori Sarai. BMC Medical Genomics, 2009

890 citations recorded by the source corpus.

BackgroundIn cancer research, the association between a gene and clinical outcome suggests the underlying etiology of the disease and consequently can motivate further studies. The recent availability of published cancer microarray datasets with clinical annotation provides the opportunity for linking gene expression to prognosis. However, the data are not easy to access and analyze without an effective analysis platform.DescriptionTo take advantage of public resources in full, a database named "PrognoScan" has been developed. This is 1) a large collection of publicly available cancer microarray datasets with clinical annotation, as well as 2) a tool for assessing the biological relationship between gene expression and prognosis. PrognoScan employs the minimum P-value approach for grouping patients for survival analysis that finds the optimal cutpoint in continuous gene expression measurement without prior biological knowledge or assumption and, as a result, enables systematic meta-analysis of multiple datasets.ConclusionPrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets and would accelerate cancer research. The database is publicly accessible at http://gibk21.bse.kyutech.ac.jp/PrognoScan/index.html.

Subfields: Molecular Biology, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/7ee0aeb80a2b540d17a6a99bcd75fd818a35fea6

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Citations in the corpus

PROGgeneV2: enhancements on the existing database (2014, methodology): “PROGgeneV2 offers several advantages over contemporary survival analysis tools, such as ITTACA [8], Prognoscan [9] and KMPlot [10].”
SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis (2013, methodology): “For the analysis of biomarkers, tools as ITTACA, KMPlot, RecurrenceOnline, bc-GeneExMiner, GOBO, and PrognoScan have been proposed [1,4–9].”
Comprehensive literature review and statistical considerations for microarray meta-analysis (2012, background): “Other secondary databases include Genevestigator (79), ArrayTrack (80), Gemma, NextBio (81), LOLA (82), L2L (83), A-MADMAN (84), PrognoScan (85), MiMiR (86), Microarray retriever (87), TranscriptomeBrowser (88), M 2 DB (89), MAMA (90) and GeneSigDB (91).”