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KM-express: an integrated online patient survival and gene expression analysis tool for the identification and functional characterization of prognostic markers in breast and prostate cancers
Author(s) -
Xin Chen,
Zhengqiang Miao,
Mayur Divate,
Zuxianglan Zhao,
Edwin Cheung
Publication year - 2018
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/bay069
Subject(s) - prostate cancer , breast cancer , computational biology , identification (biology) , cancer , transcriptome , microrna , gene , gene expression , bioinformatics , biology , computer science , genetics , botany
The identification and functional characterization of novel biomarkers in cancer requires survival analysis and gene expression analysis of both patient samples and cell line models. To help facilitate this process, we have developed KM-Express. KM-Express holds an extensive manually curated transcriptomic profile of 45 different datasets for prostate and breast cancer with phenotype and pathoclinical information, spanning from clinical samples to cell lines. KM-Express also contains The Cancer Genome Atlas datasets for 30 other cancer types with matching cell line expression data for 23 of them. We present KM-Express as a hypothesis generation tool for researchers to identify potential new prognostic RNA biomarkers as well as targets for further downstream functional cell-based studies. Specifically, KM-Express allows users to compare the expression level of genes in different groups of patients based on molecular, genetic, clinical and pathological status. Moreover, KM-Express aids the design of biological experiments based on the expression profile of the genes in different cell lines. Thus, KM-Express provides a one-stop analysis from bench work to clinical prospects. We have used this tool to successfully evaluate the prognostic potential of previously published biomarkers for prostate cancer and breast cancer. We believe KM-Express will accelerate the translation of biomedical research from bench to bed.Database URL: http://ec2-52-201-246-161.compute-1.amazonaws.com/kmexpress/index.php.

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