Literature DB >> 33599248

bc-GenExMiner 4.5: new mining module computes breast cancer differential gene expression analyses.

Pascal Jézéquel1,2,3, Wilfried Gouraud1,3, Fadoua Ben Azzouz1,3, Catherine Guérin-Charbonnel1,3, Philippe P Juin2,3, Hamza Lasla1,3, Mario Campone2,3,4.   

Abstract

'Breast cancer gene-expression miner' (bc-GenExMiner) is a breast cancer-associated web portal (http://bcgenex.ico.unicancer.fr). Here, we describe the development of a new statistical mining module, which permits several differential gene expression analyses, i.e. 'Expression' module. Sixty-two breast cancer cohorts and one healthy breast cohort with their corresponding clinicopathological information are included in bc-GenExMiner v4.5 version. Analyses are based on microarray or RNAseq transcriptomic data. Thirty-nine differential gene expression analyses, grouped into 13 categories, according to clinicopathological and molecular characteristics ('Targeted' and 'Exhaustive') and gene expression ('Customized'), have been developed. Output results are visualized in four forms of plots. This new statistical mining module offers, among other things, the possibility to compare gene expression in healthy (cancer-free), tumour-adjacent and tumour tissues at once and in three triple-negative breast cancer subtypes (i.e. C1: molecular apocrine tumours; C2: basal-like tumours infiltrated by immune suppressive cells and C3: basal-like tumours triggering an ineffective immune response). Several validation tests showed that bioinformatics process did not alter the pathobiological information contained in the source data. In this work, we developed and demonstrated that bc-GenExMiner 'Expression' module can be used for exploratory and validation purposes. Database URL: http://bcgenex.ico.unicancer.fr.
© The Author(s) 2021. Published by Oxford University Press.

Entities:  

Year:  2021        PMID: 33599248     DOI: 10.1093/database/baab007

Source DB:  PubMed          Journal:  Database (Oxford)        ISSN: 1758-0463            Impact factor:   3.451


  25 in total

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7.  Expression Characteristics and Significant Prognostic Values of PGK1 in Breast Cancer.

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Journal:  Front Mol Biosci       Date:  2021-07-05

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