Biological molecular layer classification of muscle-invasive bladder cancer opens new treatment opportunities.

ABSTRACT:

Background

Muscle-invasive bladder tumors are associated with a high risk of relapse and metastasis even after neoadjuvant chemotherapy and radical cystectomy. Therefore, further therapeutic options are needed and molecular characterization of the disease may help to identify new targets. The aim of this study was to characterize muscle-invasive bladder tumors at the molecular level using computational analyses.

Methods

The TCGA cohort of muscle-invasive bladder cancer patients was used to describe these tumors. Probabilistic graphical models, layer analyses based on sparse k-means coupled with Consensus Cluster, and Flux Balance Analysis were applied to characterize muscle-invasive bladder tumors at a functional level.

Results

Luminal and Basal groups were identified

SUBMITTER: Trilla-Fuertes L 

PROVIDER: S-EPMC6599340 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature