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A novel gene signature for molecular diagnosis of human prostate cancer by RT-qPCR.

Rizzi F, Belloni L, Crafa P, Lazzaretti M, Remondini D, Ferretti S, Cortellini P, Corti A, Bettuzzi S - PLoS ONE (2008)

Bottom Line: Validation of final results was obtained with 10-fold cross-validation procedure.CaP versus benign specimens were discriminated with (80+/-5)% accuracy, (81+/-6)% sensitivity and (78+/-7)% specificity.This result supports the notion of the "cancer field effect", in which transformed cells extend beyond morphologically evident tumour.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicina Sperimentale, University of Parma, Parma, Italy.

ABSTRACT

Background: Prostate cancer (CaP) is one of the most relevant causes of cancer death in Western Countries. Although detection of CaP at early curable stage is highly desirable, actual screening methods present limitations and new molecular approaches are needed. Gene expression analysis increases our knowledge about the biology of CaP and may render novel molecular tools, but the identification of accurate biomarkers for reliable molecular diagnosis is a real challenge. We describe here the diagnostic power of a novel 8-genes signature: ornithine decarboxylase (ODC), ornithine decarboxylase antizyme (OAZ), adenosylmethionine decarboxylase (AdoMetDC), spermidine/spermine N(1)-acetyltransferase (SSAT), histone H3 (H3), growth arrest specific gene (GAS1), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and Clusterin (CLU) in tumour detection/classification of human CaP.

Methodology/principal findings: The 8-gene signature was detected by retrotranscription real-time quantitative PCR (RT-qPCR) in frozen prostate surgical specimens obtained from 41 patients diagnosed with CaP and recommended to undergo radical prostatectomy (RP). No therapy was given to patients at any time before RP. The bio-bank used for the study consisted of 66 specimens: 44 were benign-CaP paired from the same patient. Thirty-five were classified as benign and 31 as CaP after final pathological examination. Only molecular data were used for classification of specimens. The Nearest Neighbour (NN) classifier was used in order to discriminate CaP from benign tissue. Validation of final results was obtained with 10-fold cross-validation procedure. CaP versus benign specimens were discriminated with (80+/-5)% accuracy, (81+/-6)% sensitivity and (78+/-7)% specificity. The method also correctly classified 71% of patients with Gleason score<7 versus > or =7, an important predictor of final outcome.

Conclusions/significance: The method showed high sensitivity in a collection of specimens in which a significant portion of the total (13/31, equal to 42%) was considered CaP on the basis of having less than 15% of cancer cells. This result supports the notion of the "cancer field effect", in which transformed cells extend beyond morphologically evident tumour. The molecular diagnosis method here described is objective and less subjected to human error. Although further confirmations are needed, this method poses the potential to enhance conventional diagnosis.

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Related in: MedlinePlus

Sandwich procedure developed for collection of specimens and direct comparison of morphological and molecular classification.
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Related In: Results  -  Collection


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pone-0003617-g001: Sandwich procedure developed for collection of specimens and direct comparison of morphological and molecular classification.

Mentions: To obtain a direct comparison between molecular data and pathological classification we developed a “sandwich” method (see Figure 1 and Methods: Prostate Tissue Specimens Collection and Handling). RNA extraction yielded an average of 50–60 µg of total RNA from 20 mg of human prostate tissue. The amount of total RNA obtained was high enough to directly check the quality of the preparation by spectrophotometry, followed by conventional electrophoresis. Only good quality RNA was used for RT-qPCR analysis. Eight informative genes plus 2 housekeepers were analysed starting from the same RNA sample.


A novel gene signature for molecular diagnosis of human prostate cancer by RT-qPCR.

Rizzi F, Belloni L, Crafa P, Lazzaretti M, Remondini D, Ferretti S, Cortellini P, Corti A, Bettuzzi S - PLoS ONE (2008)

Sandwich procedure developed for collection of specimens and direct comparison of morphological and molecular classification.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2570792&req=5

pone-0003617-g001: Sandwich procedure developed for collection of specimens and direct comparison of morphological and molecular classification.
Mentions: To obtain a direct comparison between molecular data and pathological classification we developed a “sandwich” method (see Figure 1 and Methods: Prostate Tissue Specimens Collection and Handling). RNA extraction yielded an average of 50–60 µg of total RNA from 20 mg of human prostate tissue. The amount of total RNA obtained was high enough to directly check the quality of the preparation by spectrophotometry, followed by conventional electrophoresis. Only good quality RNA was used for RT-qPCR analysis. Eight informative genes plus 2 housekeepers were analysed starting from the same RNA sample.

Bottom Line: Validation of final results was obtained with 10-fold cross-validation procedure.CaP versus benign specimens were discriminated with (80+/-5)% accuracy, (81+/-6)% sensitivity and (78+/-7)% specificity.This result supports the notion of the "cancer field effect", in which transformed cells extend beyond morphologically evident tumour.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicina Sperimentale, University of Parma, Parma, Italy.

ABSTRACT

Background: Prostate cancer (CaP) is one of the most relevant causes of cancer death in Western Countries. Although detection of CaP at early curable stage is highly desirable, actual screening methods present limitations and new molecular approaches are needed. Gene expression analysis increases our knowledge about the biology of CaP and may render novel molecular tools, but the identification of accurate biomarkers for reliable molecular diagnosis is a real challenge. We describe here the diagnostic power of a novel 8-genes signature: ornithine decarboxylase (ODC), ornithine decarboxylase antizyme (OAZ), adenosylmethionine decarboxylase (AdoMetDC), spermidine/spermine N(1)-acetyltransferase (SSAT), histone H3 (H3), growth arrest specific gene (GAS1), glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and Clusterin (CLU) in tumour detection/classification of human CaP.

Methodology/principal findings: The 8-gene signature was detected by retrotranscription real-time quantitative PCR (RT-qPCR) in frozen prostate surgical specimens obtained from 41 patients diagnosed with CaP and recommended to undergo radical prostatectomy (RP). No therapy was given to patients at any time before RP. The bio-bank used for the study consisted of 66 specimens: 44 were benign-CaP paired from the same patient. Thirty-five were classified as benign and 31 as CaP after final pathological examination. Only molecular data were used for classification of specimens. The Nearest Neighbour (NN) classifier was used in order to discriminate CaP from benign tissue. Validation of final results was obtained with 10-fold cross-validation procedure. CaP versus benign specimens were discriminated with (80+/-5)% accuracy, (81+/-6)% sensitivity and (78+/-7)% specificity. The method also correctly classified 71% of patients with Gleason score<7 versus > or =7, an important predictor of final outcome.

Conclusions/significance: The method showed high sensitivity in a collection of specimens in which a significant portion of the total (13/31, equal to 42%) was considered CaP on the basis of having less than 15% of cancer cells. This result supports the notion of the "cancer field effect", in which transformed cells extend beyond morphologically evident tumour. The molecular diagnosis method here described is objective and less subjected to human error. Although further confirmations are needed, this method poses the potential to enhance conventional diagnosis.

Show MeSH
Related in: MedlinePlus