Diagnosis of renal tumors on needle biopsy specimens by histological and molecular analysis.
Academic Article
Overview
abstract
PURPOSE: We diagnosed the subtypes of renal cell carcinoma on needle core biopsies using a combination of histopathology and a molecular diagnostic algorithm. MATERIALS AND METHODS: Core biopsies were taken of renal tumors following nephrectomy. RNA was extracted and quantitative real-time polymerase chain reaction was performed for 4 gene products to differentiate among renal cell carcinoma subtypes. Histopathological diagnosis was achieved on a second core before and after obtaining the molecular diagnostic algorithm results. RESULTS: Based on the nephrectomy diagnosis 6 of 77 renal masses were nonneoplastic and 71 were tumors, including 65 renal cell carcinoma/oncocytomas. The overall diagnostic accuracy using histology and our molecular diagnostic algorithm combined was 90.0% (70 of 77). Side by side comparison of histology vs molecular diagnostic algorithm was feasible for 60 classifiable renal cell carcinoma/oncocytomas (31 clear cell, 14 papillary renal cell carcinoma, 6 chromophobe renal cell carcinoma, 2 mucinous tubular and spindle cell carcinoma, and 7 oncocytoma). In this group histology correctly predicted the final histological subtype in 83.3% (50 of 60) of cores. Addition of the molecular diagnostic algorithm to histology improved the subtyping accuracy to 95% (57 of 60), whereas the molecular diagnostic algorithm alone was accurate in 50 of 60 cases (83.3%). Dividing these 60 specimens into clear cell and nonclear cell neoplasms, the addition of the molecular diagnostic algorithm improved the sensitivity for the diagnosis of clear cell carcinoma from 87.1% (27 of 31) to 100% and the negative predictive value from 87.5% to 100%. CONCLUSIONS: Core biopsies of renal tumors provide adequate material for diagnosing and subtyping renal cell carcinoma. The addition of our molecular diagnostic algorithm to histology improved the diagnostic accuracy of core biopsies of renal masses.
