Evidence map›Paper›PMID 29992322›Full record

ArticleDatabase : the journal of biological databases and curation2018

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.

Xin Chen, Zhengqiang Miao, Mayur Divate, Zuxianglan Zhao, Edwin Cheung

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
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  3. PMBC: a manually curated database for prognostic markers of breast cancer.Database : the journal of biological databases and curation · 2024
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  7. The lncRNAsMolecular therapy. Nucleic acids · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xin ChenGuangdong Key Laboratory of IoT Information Technology, School of Automation, Guangdong University of Technology, No. 100 Waihuan Xi Road, Guangzhou Higher Education Mega Center, Panyu District, Guangzhou 510006, PR China.
Zhengqiang MiaoFaculty of Health Sciences (E12), University of Macau, Avenida da Universidade, Room 4045, Taipa, Macau, China.
Mayur DivateFaculty of Health Sciences (E12), University of Macau, Avenida da Universidade, Room 4045, Taipa, Macau, China.
Zuxianglan ZhaoFaculty of Health Sciences (E12), University of Macau, Avenida da Universidade, Room 4045, Taipa, Macau, China.
Edwin CheungFaculty of Health Sciences (E12), University of Macau, Avenida da Universidade, Room 4045, Taipa, Macau, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Gene Expression Regulation, NeoplasticInternetSoftwareBiomarkers, TumorBreast NeoplasmsCell Line, TumorDatabases, GeneticFemaleHumansMaleProstatic NeoplasmsReproducibility of ResultsSurvival AnalysisBiomarkers, Tumor

Identifiers

PMID29992322
PMCPMC6041744

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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.