Cargando…

Predicting biomarkers for ovarian cancer using gene-expression microarrays

Ovarian cancer has the highest mortality rate of gynaecological cancers. This is partly due to the lack of effective screening markers. Here, we used oligonucleotide microarrays complementary to ∼12 000 genes to establish a gene-expression microarray (GEM) profile for normal ovarian tissue, as compa...

Descripción completa

Detalles Bibliográficos
Autores principales: Adib, T R, Henderson, S, Perrett, C, Hewitt, D, Bourmpoulia, D, Ledermann, J, Boshoff, C
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2409606/
https://www.ncbi.nlm.nih.gov/pubmed/14760385
http://dx.doi.org/10.1038/sj.bjc.6601603
Descripción
Sumario:Ovarian cancer has the highest mortality rate of gynaecological cancers. This is partly due to the lack of effective screening markers. Here, we used oligonucleotide microarrays complementary to ∼12 000 genes to establish a gene-expression microarray (GEM) profile for normal ovarian tissue, as compared to stage III ovarian serous adenocarcinoma and omental metastases from the same individuals. We found that the GEM profiles of the primary and secondary tumours from the same individuals were essentially alike, reflecting the fact that these tumours had already metastasised and acquired the metastatic phenotype. We have identified a novel biomarker, mammaglobin-2 (MGB2), which is highly expressed specific to ovarian cancer. MGB2, in combination with other putative markers identified here, could have the potential for screening.