Computational development of a molecular-based approach to improve risk stratification of endometrial cancer patients.

ABSTRACT: Histological classification and staging are the gold standard for the prognosis of endometrial cancer (EC). However, in morphologically intermediate and doubtful cases this approach results largely insufficient, defining the need for better classification criteria. In this work we developed an algorithm that based on EC genetic alterations and in combination with the current histological classification, improves EC patients prognostic stratification, in particular in doubtful cases. A panel of 26 cancer related genes was analyzed in 89 EC patients and somatic functional mutations were investigated in association with different histology and outcome. An unsupervised hierarchical clustering analysis revealed that two groups of patients with different tumor grade and different prognosis can b

SUBMITTER: Torricelli F 

PROVIDER: S-EPMC5986657 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature