Highly sensitive molecular diagnosis of prostate cancer using surplus material washed off from biopsy needles - Abstract

Institut d'Investigacions Biomèdiques August Pi i Sunyer, c. Villarroel 170, 08036, Barcelona, Spain.

Department of Cell Biology, Institute for Molecular Biology, Science Research Council, c. Baldiri Reixac 15-21, 08028, Barcelona, Spain.



Currently, final diagnosis of prostate cancer (PCa) is based on histopathological analysis of needle biopsies, but this process often bears uncertainties due to small sample size, tumour focality and pathologist's subjective assessment.

Prostate cancer diagnostic signatures were generated by applying linear discriminant analysis to microarray and real-time RT-PCR (qRT-PCR) data from normal and tumoural prostate tissue samples. Additionally, after removal of biopsy tissues, material washed off from transrectal biopsy needles was used for molecular profiling and discriminant analysis.

Linear discriminant analysis applied to microarray data for a set of 318 genes differentially expressed between non-tumoural and tumoural prostate samples produced 26 gene signatures, which classified the 84 samples used with 100% accuracy. To identify signatures potentially useful for the diagnosis of prostate biopsies, surplus material washed off from routine biopsy needles from 53 patients was used to generate qRT-PCR data for a subset of 11 genes. This analysis identified a six-gene signature that correctly assigned the biopsies as benign or tumoural in 92.6% of the cases, with 88.8% sensitivity and 96.1% specificity.

Surplus material from prostate needle biopsies can be used for minimal-size gene signature analysis for sensitive and accurate discrimination between non-tumoural and tumoural prostates, without interference with current diagnostic procedures. This approach could be a useful adjunct to current procedures in PCa diagnosis.

Written by:
Bermudo R, Abia D, Mozos A, García-Cruz E, Alcaraz A, Ortiz AR, Thomson TM, Fernández PL.   Are you the author?

Reference: Br J Cancer. 2011 Oct 18. Epub ahead of print.
doi: 10.1038/bjc.2011.435

PubMed Abstract
PMID: 22009027

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