Figure 2 | British Journal of Cancer

Figure 2

From: Highly sensitive molecular diagnosis of prostate cancer using surplus material washed off from biopsy needles

Figure 2

A highly sensitive and specific minimal-size gene signature diagnostic of PCa generated by LDA applied to qRT–PCR data for transrectal prostate biopsy needle wash-off samples. (A) Material washed off from simulated prostate biopsy needles is suitable for real-time RT–PCR transcript quantification. The bar plots represent the ratios of tumoural vs non-tumoural wash-off samples, showing the overexpression in carcinomatous washed-off samples of AMACR, HPN and EPCAM, as well as the underexpression of KRT5 and LAMB3. Non-tumoural washed-off samples were obtained from tumour-free prostates from nodular hyperplasias or radical cystoprostatectomies. Tumoural washed-off samples were obtained from radical prostatectomies diagnosed of adenocarcinoma and whose simulated biopsy cores contained tumoural glands. *P-value <0.001. (B) Samples from colonic tissues display expression profiles for 11 selected genes that are distinct from normal and tumoural prostate samples. A hierarchical cluster was built with expression data obtained by qRT–PCR from non-tumoural colon (C–N) and tumoural (P–T) and non-tumoural (P–N) prostate samples. Pvclust analysis was used to assess the uncertainty of hierarchical clustering, obtaining AU values for each cluster, which show cluster stability when AU>95. Prostate data correspond to mean values from the available prostate samples. AU values are shown at the main branches of the hierarchical tree, illustrating that colonic samples display a gene expression profile that clearly differentiate them (AU>95) from all prostatic samples. (C) A highly sensitive and specific minimal-size gene signature diagnostic of PCa generated by LDA applied to qRT–PCR data for transrectal prostate biopsy needle wash-off samples. Results of the six-gene model generated by LDA, capable of discriminating wash-off samples from tumoural prostate biopsies (n=28) and non-tumoural ones (n=26). LDA scores obtained by each sample are represented in the y axis. Samples are classified as tumoural (filled circles) or non-tumoural (empty circles), when their corresponding LDA score is above or under the model's threshold (dashed line), respectively.

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