Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis

Abstract : Tumour heterogeneity refers to the fact that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation, and metastatic potential. This phenomenon occurs both between tumours (inter-tumour heterogeneity) and within tumours (intra-tumour heterogeneity), and it is caused by genetic and non-genetic factors. The heterogeneity of cancer cells introduces significant challenges in using molecular prognostic markers as well as for classifying patients that might benefit from specific therapies. Thus, research efforts for characterizing heterogeneity would be useful for a better understanding of the causes and progression of disease. It has been suggested that the study of heterogeneity within Circulating Tumour Cells (CTCs) could also reflect the full spectrum of mutations of the disease more accurately than a single biopsy of a primary or metastatic tumour. In the last years many high throughput methodologies have raised for the study of heterogeneity at different levels (i.e.: RNA, DNA, protein, epigenetic events). The aim of the current review is to stress clinical implications of tumour heterogeneity, as well as current available methodologies for their study with a specific attention to those able to assess heterogeneity at the single cell level.
Liste complète des métadonnées

Littérature citée [80 références]  Voir  Masquer  Télécharger

http://www.hal.inserm.fr/inserm-01466086
Contributeur : Dominique Heymann <>
Soumis le : lundi 13 février 2017 - 12:58:39
Dernière modification le : jeudi 5 avril 2018 - 10:37:03
Document(s) archivé(s) le : dimanche 14 mai 2017 - 13:44:48

Fichiers

ijms-17-02142.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

Collections

Citation

Marta Tellez-Gabriel, Benjamin Ory, François Lamoureux, Marie-Françoise Heymann, Dominique Heymann. Tumour Heterogeneity: The Key Advantages of Single-Cell Analysis. International Journal of Molecular Sciences, MDPI, 2017, 17, pp.2142 - 2142. 〈10.3390/ijms17122142〉. 〈inserm-01466086〉

Partager

Métriques

Consultations de la notice

139

Téléchargements de fichiers

169