Dissecting the expression landscape of cytochromes P450 in hepatocellular carcinoma: towards novel molecular biomarkers.

biomarker cytochromes gene expression hepatocellular carcinoma

Journal

Genes & cancer
ISSN: 1947-6019
Titre abrégé: Genes Cancer
Pays: United States
ID NLM: 101516546

Informations de publication

Date de publication:
May 2019
Historique:
entrez: 2 7 2019
pubmed: 2 7 2019
medline: 2 7 2019
Statut: ppublish

Résumé

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths around the world. Recent advances in genomic technologies have allowed the identification of various molecular signatures in HCC tissues. For instance, differential gene expression levels of various cytochrome P450 genes (CYP450) have been reported in studies performed on limited numbers of HCC tissue samples, or focused on a small subset on CYP450s. In the present study, we monitored the expression landscape of all the members of the CYP450 family (57 genes) in more than 200 HCC tissues using RNA-Seq data from The Cancer Genome Atlas. Using stringent statistical filters and data from paired tissues, we identified significantly dysregulated CYP450 genes in HCC. Moreover, the expression level of selected CYP450s was validated by qPCR on cDNA samples from an independent cohort. Threshold values (sensitivity and specificity) based on dysregulated gene expression were also determined to allow for confident identification of HCC tissues. Finally, a global look at expression levels of the 57 members of the CYP450 family across ten different cancer types revealed specific expression signatures. Overall, this study provides useful information on the transcriptomic landscape of CYP450 genes in HCC and on new potential HCC biomarkers.

Identifiants

pubmed: 31258835
doi: 10.18632/genesandcancer.190
pii: 190
pmc: PMC6584210
doi:

Types de publication

Journal Article

Langues

eng

Pagination

97-108

Déclaration de conflit d'intérêts

CONFLICTS OF INTEREST The authors declare that they have no competing interests.

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Auteurs

Camille Martenon Brodeur (CM)

Département de biochimie, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, Québec, Canada.

Philippe Thibault (P)

Laboratoire de Génomique Fonctionnelle, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

Mathieu Durand (M)

Laboratoire de Génomique Fonctionnelle, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

Jean-Pierre Perreault (JP)

Département de biochimie, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, Québec, Canada.

Martin Bisaillon (M)

Département de biochimie, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, Québec, Canada.

Classifications MeSH