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Project

Regulatory networks in basal-like bladder cancer

Funder: Fondation ARC pour la Recherche sur le Cancer

Funding period
0
Funding amount
Abstract
Bladder cancer is frequent and of poor prognosis at the muscle-invasive stage. Multiple gene expression profiling studies have proposed a molecular classification of this cancer. They have all identified a particularly aggressive subtype: the basal-like subgroup. Cancer cells make use of many of the regulatory networks of normal cells for their migration, proliferation and the maintenance of differentiation states. The goal of this proposal is to identify and compare the networks found in normal and basal-like tumor states, and thereby assess key pathways in basal-like bladder cancer.
We will use available transcriptomic data of basal-like bladder tumors and normal urothelial cells to determine and then compare the regulatory networks found in the normal and cancer states. This work will build on previous studies carried out in collaboration with bioinformatics teams, which have successfully established tools to extract gene regulation networks from transcriptomic data. Identified key transcription factors and target genes from candidate networks in basal-like bladder cancers will be validated functionally, by studying the effects of activation and inhibition of the candidate genes in basal-like cell lines. Finally, we will determine the effect of chemotherapy treatment on the identified driver networks by comparing these networks to those found in treated tumors from available basal-like PDX models as well as basal-like cancer samples from patients treated with neoadjuvant chemotherapy.
We expect to identify driver regulatory networks in an aggressive variant type of bladder cancer: the basal-like subgroup. The delineation of deregulated networks will lead to a more comprehensive understanding of the underlying biology of basal-like bladder cancers. This proposal may also determine potential therapeutic targets, give insights into mechanisms of treatment resistance for this subtype, and therefore identify more efficient combination treatments.
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System

Categories
  • FOR (ANZSRC)

    1112 Oncology and Carcinogenesis

  • RCDC

    Cancer

  • RCDC

    Genetics

  • RCDC

    Urologic Diseases

  • HRCS HC

    Cancer

  • HRCS RAC

    2.1 Biological and endogenous factors

  • Health Research Areas

    Biomedical

  • Broad Research Areas

    Basic Science