Cargando…

Metabonomic analysis of ovarian tumour cyst fluid by proton nuclear magnetic resonance spectroscopy

The majority of ovarian tumours are of the epithelial type, which can be sub classified as benign, borderline or malignant. Epithelial tumours usually have cystic spaces filled with cyst fluid, the metabolic profile of which reflects the metabolic activity of the tumour cells, due to their close pro...

Descripción completa

Detalles Bibliográficos
Autores principales: Kyriakides, Michael, Rama, Nona, Sidhu, Jasmin, Gabra, Hani, Keun, Hector C., El-Bahrawy, Mona
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4872780/
https://www.ncbi.nlm.nih.gov/pubmed/26769844
http://dx.doi.org/10.18632/oncotarget.6891
Descripción
Sumario:The majority of ovarian tumours are of the epithelial type, which can be sub classified as benign, borderline or malignant. Epithelial tumours usually have cystic spaces filled with cyst fluid, the metabolic profile of which reflects the metabolic activity of the tumour cells, due to their close proximity. The approach of metabonomics using (1)H-NMR spectroscopy was employed to characterize the metabolic profiles of ovarian cyst fluid samples (n = 23) from benign, borderline and malignant ovarian tumours in order to shed more light into ovarian tumour and cancer development. The analysis revealed that citrate was elevated in benign versus malignant tumours, while the amino acid lysine was elevated in malignant versus non-malignant tumours, both at a 5% significance level. Choline and lactate also had progressively increasing levels from benign to borderline to malignant samples. Finally, hypoxanthine was detected exclusively in a sub-cohort of the malignant tumours. This metabonomic study demonstrates that ovarian cyst fluid samples have potential to be used to distinguish between the different types of ovarian epithelial tumours. Furthermore, the respective metabolic profiles contain mechanistic information which could help identify biomarkers and therapeutic targets for ovarian tumours.