Significant problems with non-diagnostic biopsies, and the inability to distinguish between benign oncocytomas and chromophobe renal cell carcinoma have also hampered the utility of biopsy in the management of patients. The group from Cornell has previously reported on a molecular diagnostic algorithm that may improve the diagnostic ability of renal mass biopsy, using quantitative real time PCR to examine the expression of selected genes that appear specific to selected histiotypes of renal tumors. Here, this group evaluates the efficacy of their molecular diagnostic algorithm, which examines the expression of carbonic anhydrase 9 (CA9), a-methylacyl coenzyme A racemase (AMACR), parvalbumin (PVALB), and kidney specific basolateral chloride channel (CLCNKB) in renal tumor samples, in comparison with and in addition to histologic examination of biopsy samples.

In this study, 72 patients underwent surgical resection of their renal tumor, followed by ex vivo biopsy of their tumor for this analysis. Two biopsy cores were submitted for histologic examination, and one was submitted for quantitative real time PCR for the genes listed above. The results were initially examined in a blinded fashion, and then corroborated to determine accuracy and possible synergy. There were 58 patients with renal cell carcinoma (RCC) (34 clear cell, 14 papillary, 6 chromophobe, 2 unclassified, and 2 mucinous tubular and spindle cell carcinoma). There were 7 oncocytomas, 6 non-RCC/non-oncocytoma tumors, and 6 non-neoplastic lesions. Of note, unlike their previously published study, expression of PVALB was unable to distinguish chromophobe RCC from oncocytoma and therefore was discarded from the analysis. Histology alone was accurate in 83.3% of cases in identifying the final diagnosis. Similarly, the molecular diagnostic algorithm was accurate in 83.3% of cases. Combined, histology and the algorithm correctly identified 95% of cases, with 7 cases being reclassified based on the algorithm result (i.e. it overruled histology). In determining clear cell from non-clear cell neoplasms, the addition of the molecular diagnostic algorithm to histologic examination improved sensitivity from 87.1% to 100% and negative predictive value from 87.5% to 100%.

The authors concluded that the combination of histologic examination and their molecular diagnostic algorithm improved the diagnostic accuracy of renal biopsy and was particularly useful in distinguishing clear cell from non-clear cell tumors. Unfortunately, it came up short in distinguishing the benign oncocytoma from other malignant tumors, which is usually the largest dilemma in interpreting renal tumor biopsies.

Barocas DA, Rohan SM, Kao J, Gurevich RD, Del Pizzo JJ, Vaughan Jr ED, Akhtar M, Chen YT, Scherr DS

J Urol 176(3): 1957-1962, 2006

UroToday.com Renal Cancer Section

Written by Christopher G. Wood, MD, a Contributing Editor with UroToday.

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