Abstract

One of the major problems in genomics and medicine is the identification of gene networks and pathwaysderegulated in complex and polygenic diseases, like cancer. In this paper, we address the problem ofassessing the variability of results of pathways analysis identified in different and independent genomewide expression studies, in which the same phenotypic conditions are assayed. To this end, we assessedthe deregulation of 1891 curated gene sets in four independent gene expression data sets of subjectsaffected by colorectal cancer (CRC). In this comparison we used two well-founded statistical modelsfor evaluating deregulation of gene networks. We found that the results of pathway analysis in expressionstudies are highly reproducible. Our study revealed 53 pathways identified by the two methods inall the four data sets analyzed with high statistical significance and strong biological relevance withthe pathology examined. This set of pathways associated to single markers as well as to whole biologicalprocesses altered constitutes a signature of the disease which sheds light on the genetics bases of CRC.

Autore Pugliese

• Ancona Nicola , Maglietta Rosalia , D'addabbo Annarita

Tutti gli autori

• R. Maglietta; A. Distaso; A. Piepoli; O. Palumbo; M. Carella; A. D’Addabbo; S. Mukherjee; N. Ancona

Titolo volume/Rivista

Journal of biomedical informatics

Anno di pubblicazione

2010

ISSN

1532-0464

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

Non Disponibile

Ultimo Aggiornamento Citazioni

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Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile