Deep sequencing reveals microRNAs predictive of antiangiogenic drug response

Jesús García-Donas1,2, Benoit Beuselinck3,4, Lucía Inglada-Pérez5,6

  • 1Oncology Unit, HM Hospitales - Centro Integral Oncológico HM Clara Campal, Madrid, Spain.

JCI Insight
|October 5, 2016
PubMed

Insights

MicroRNAs (miRNAs) can predict treatment response in metastatic renal cell carcinoma (RCC) patients receiving tyrosine kinase inhibitors (TKI). This study identified specific miRNAs that indicate progressive disease, offering potential biomarkers for personalized RCC therapy.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Metastatic renal cell carcinoma (RCC) treatment often involves tyrosine kinase inhibitors (TKI), but some patients are refractory.
  • MicroRNAs (miRNAs) are key regulatory molecules and have shown promise as cancer biomarkers.

Purpose of the Study:

  • To identify microRNAs (miRNAs) that predict disease progression in metastatic clear cell RCC patients treated with TKIs.
  • To evaluate the predictive value of identified miRNAs for TKI response and patient survival.

Main Methods:

  • Deep sequencing of 74 metastatic clear cell RCC tumors from patients uniformly treated with TKIs.
  • Differential expression analysis to identify miRNAs associated with progressive disease.
  • Validation of selected miRNAs and development of a miRNA-based classifier.

Main Results:

  • Twenty-nine miRNAs were differentially expressed in patients progressing on TKI therapy.
  • miR-1307-3p, miR-155-5p, and miR-221-3p showed significant associations with TKI treatment outcomes.
  • A 2-miRNA classifier accurately predicted progressive disease (AUC = 0.75) and outperformed clinicopathological factors.
  • Several miRNAs were significantly associated with progression-free and overall survival.

Conclusions:

  • This study demonstrates the predictive value of miRNAs for TKI response in metastatic RCC.
  • Identified miRNAs serve as potential biomarkers to guide treatment decisions for RCC patients.
  • This research offers novel insights into the miRNome landscape of TKI-refractory RCC.