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Micro-RNA expression profiles in upper tract urothelial carcinoma differentiate stage and tumor progression: a tool for clinical decision making
Brendan M. Browne, MD1, Chintan Patel, MD1, Travis Sullivan, MS1, Eric Burks, MD1, Jay Raman, MD2, Joshua Warrick, MD2, David Canes, MD1, Kimberly Rieger-Christ, PhD1.
1Lahey Hospital and Medical Center, Burlington, MA, USA, 2Penn State Milton S. Hershey Medical Center, Hershey, PA, USA.
Accurate clinical staging of upper tract urothelial carcinoma (UTUC) often proves challenging secondary to inadequate tissue sampling during endoscopic biopsy. Furthermore, accurate prediction of tumor biology would allow tailored treatment for patients who are not candidates for nephroureterectomy (NU) or who could benefit from less radical treatment. MicroRNAs (miRNAs) are promising cancer biomarkers measurable in tissue, serum and urine; however, miRNA profiling of UTUC tumors remains largely unexplored. We aimed to identify miRNA expression profiles with potential to differentiate invasive and non-invasive UTUC and that may identify tumors that will progress following NU.
Total RNA was extracted from formalin-fixed, paraffin-embedded NU samples from 2005 to 2013 under an IRB-approved study. Thirty-six unique tumors with diverse pathologies were profiled in the screening cohort using RT-qPCR array for 752 unique miRNA. Subsequently, evaluation of 27 differentially expressed miRNA was performed on a validation cohort of 123 additional NU tissue specimens, including 54 samples from a unique patient population at a collaborating institution.
The miRNA profile of the screening cohort identified 31 miRNA differentially expressed between invasive and non-invasive tumors (p<0.05). Twelve were up-regulated and 19 were down-regulated in the invasive specimens. Predicted probabilities from logistic regression analysis of the screening cohort revealed four miRNA with AUC ≥0.8 and an additional six with an AUC ≥0.7 (Table 1). Testing of selected miRNA on the validation cohort confirmed differential expression of 14 miRNA in invasive tumors. Clinical follow-up data for progression following surgery also showed miRNA that correlate with progression of disease. Complete logistical regression modeling is currently in process for the validation cohort.
UTUC miRNA profiles of NU specimens can discriminate invasive versus non-invasive disease as well as predict patients who will display tumor progression following surgery. Thus miRNA could instruct decision making for follow-up or adjuvant therapy pathways based on likelihood of progression. Furthermore, we are prospectively analyzing these miRNA in urine to develop a non-invasive assay for detection, surveillance, and risk stratification of UTUC. miRNA expression profiles may also aid in personalizing treatment decisions based on UTUC tumor biology.
Table 1. Results from logistic regression for detecting invasive UTUC: screening cohort
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