Bladder cancer genomics

Salvatore Siracusano1, Riccardo Rizzetto1, Antonio Benito Porcaro1

  • 1Department of Urology, University of Verona, Verona, Italy.

Urologia
|January 17, 2020
PubMed

Insights

Molecular subtyping of bladder cancer, based on genetic alterations like FGFR3, TP53, and RB1, aids in personalized treatment. This classification helps identify patients who may not benefit from chemotherapy, improving bladder cancer management.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Traditional bladder cancer treatment relied on surgery, immunotherapy, or chemotherapy.
  • Recent advances in molecular analysis have revealed novel treatment strategies.
  • Understanding genetic alterations is crucial for classifying and treating bladder cancer.

Purpose of the Study:

  • To classify bladder cancers based on molecular alterations.
  • To differentiate between basal and luminal subtypes.
  • To correlate molecular subtypes with disease progression and treatment response.

Main Methods:

  • Utilizing polymerase chain reaction and genomic hybridization techniques.
  • Analyzing DNA alterations and gene expression patterns.
  • Leveraging data from projects like The Cancer Genome Atlas (TCGA).

Main Results:

  • Bladder cancers classified as papillary (FGFR3 mutations) or non-papillary (TP53, RB1 mutations).
  • Gene expression patterns identify basal (squamous, sarcomatoid) and luminal (papillary) subtypes.
  • Luminal cancers linked to muscle-invasive disease; basal cancers to advanced/metastatic disease.
  • Specific DNA mutations correlate with cisplatin chemotherapy sensitivity.

Conclusions:

  • Molecular subtyping of bladder cancer can guide personalized treatment strategies.
  • Classification may help identify chemoresistant tumors, allowing avoidance of neoadjuvant chemotherapy.
  • Targeting genomic alterations offers a promising therapeutic approach for invasive urothelial cancers.
  • Future research aims to combine treatment strategies based on genetic mutational load.