MicroRNAs Could Help Predict Response to TKIs for Metastatic RCC
A new study has found a series of potential microRNA biomarkers that could predict tyrosine kinase inhibitor response in RCC patients.
A new study has found a series of potential microRNA biomarkers that could predict tyrosine kinase inhibitor (TKI) response in patients with metastatic renal cell carcinoma (RCC).
Researchers led by Jesús GarcÃa-Donas, of the Oncology Unit at HM Hospitales–Centro Integral Oncológico HM Clara Campal in Madrid, identified 29 microRNAs expressed in the tumors of patients whose disease progressed while on a TKI; 6 of these microRNAs were validated in an independent data series.
“The results of this study argue for a prospective validation of microRNA expression in patients undergoing TKI therapy and suggest that metastatic clear cell RCC therapy could be further personalized,” the researchers wrote in JCI Insight.
According to the study, most patients with RCC are treated with TKIs as part of their initial treatment; however, some patients are refractory to these agents. Although there are dozens of biomarkers predicting drug response in cancer, there are none for metastatic RCC, nor for its standard therapy.
In this study, GarcÃa-Donas and colleagues conducted deep sequencing on 74 metastatic clear cell RCC cases uniformly treated with TKIs. Of these samples, 22% had disease progression at the first radiologic assessment and 78% had either a complete or partial response to treatment or stable disease.
Sequencing identified 65 microRNAs that were expressed in the tumors that progressed on TKI therapy compared with tumors that had stable disease or better (P < .01). Of these, 29 had a false discovery rate (FDR) of less than 0.05, and 21 were upregulated in the progressive disease group.
The researchers selected six of these microRNAs for validation in an independent series. Five of the microRNAs were found to be risk factors for progressive disease while on TKI treatment: miR–1307-3p, miR–155-5p, miR–221-3p, miR–425-5p, and miR–222-3p. The most significant P values were associated with miR–1307-3p, miR–155-5p, and miR–221-3p (4.6 × 10–3, 6.5 × 10–3, and 3.4 × 10–2, respectively).
Next, the researchers used the five microRNAs found to be markers of poor response to generate a predictive model for TKI response that included relevant clinical characteristics in 132 patients. After several analyses, they identified a model based on two microRNAs (miR–1307-3p and miR–425-5p) that showed “higher accuracy than any clinical factor tested,” regarding the prediction of how the tumor would respond to TKI-based treatments.
“Among these two microRNAs, miR-425 has been associated with tumor stage in gastric and lung cancer, and in RCC, it has been suggested as being a potential clear cell RCC biomarker associated with poor prognosis for chromophobe RCC and decreased progression-free survival during sunitinib treatment,” the researchers wrote.
Finally, the researchers identified microRNAs that were significantly associated with survival, including seven that were associated with progressive disease as best tumor response to a TKI, worse progression-free survival, and worse overall survival.
