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Fisher Biomarker Research Laboratory
NEXT GENERATION FISHER BIOMARKER LAB IMAGE TECHNOLOGY

Today the Veltri-Partin Laboratory has developed newer tools to conduct nuclear morphometry and multiplexing of molecular biomarker research to predict prostate cancer outcomes. The availability of tumor tissue microarrays and the scanning microscope permits the collection a large data caches for analysis to better understand prostate cancer biology and pathogenesis.
TMA PREPARATIONS (Figure 1):There is a need for well documented and annotated biospecimens for research. Patient radical prostatectomy specimens are selected by an expert pathologist for studying a specific prostate cancer (CaP) outcome (i.e. recurrence, metastasis, or survival). All cases selected are reviewed and the tissue blocks 'mapped' by the pathologist for the normal-appearing and graded index tumor areas are identified and marked on the slide for each case.  The tissue microarrays (TMAs) are prepared using a Beecher MT1 manual arrayer (Beecher Instruments, Silver Spring, MD). http://tmaj.pathology.jhmi.edu . The H&E and Feulgen images are then imaged at 20X using the Aperio ScanScope-CS System.  These high resolution images are then captured for analysis.

Quantifying tissue architecture with ImagePro 9.1 software (Figure 2):  The H&E or Feulgen DNA tissue slides are scanned with Aperio Scanning microscope at 20X and the TIFF images of tumor area and normal glandular area were extracted using Aperio Image Scope Software in a none compression form.  An H&E or Feulgen histochemical stain specific macro is applied for capturing 1,000s of nuclei and these are designated regions of interest (ROIs). Each nucleus is automatically segmented. Data of 84 nuclear parameters (features) of each nucleus were generated for analysis. See Figure 2 below for how the individual nuclei are captured by using a CaP specific "profile" for cancer nuclei.  Next, we needed to reduce the number of nuclear features used in the ImagePro 9.1 software [Table 1] and we applied commercial computational software to do so.

 FIGURE 1

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 FIGURE 2

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Table1

prostate cancer research

Reduction of number of ImagePro 9.1 nuclear features applied "Principal Component Analysis" (PCA) which is a dimension-reduction tool to get 84 correlated nuclear features in ImagePro 9.1 down to 19 non-redundant uncorrelated features that can be used to predict outcomes. PCA is a mathematical method that transforms a number of possibly correlated variables into a (smaller) number of uncorrelated unique variables called "principal components".  http://www.mathworks.com/help/stats/manova1.html]. We obtained a AUC-ROC = 0.90 (Figure 3a) to separate less aggressive (3+3/3+4) and more aggressive (4+3 and above) CaP. The results also yielded the predictive probability (PP) plots on the right (Figure 3b) for each patient (n=80) of the AUC-ROC and is shown in Figure 3b. The p value for the PP plot is p > 0.0001. This same image technology can be used to quantify immunohistochemistry of molecular biomarkers.

Feulgen Stain Predicts Prostate Cancer Aggressive Phenotype
Less Aggressive = Gleason score (GS) = 3+3/3+4 vs. GS 4+3/> 7

Fig3a                                                Fig3b

prostate cancer research

Quantitative Immunohistochemistry (qIHC) Predicts CaP Outcomes

Now we can apply ImagePro 9.1 software to perform molecular biomarker quantitation in CaP tissue samples. Formalin fixed and paraffin embedded TMA samples were incubated with primary antibody at 1: xx dilution for 1hr at room temperature and followed by overnight at 4C. HRP conjugated anti mouse or anti-rabbit secondary antibody (KPL) was incubated with the samples at 1:200 dilutions for 1hr at room temperature. Below is an example of and IHC result for the RBM3 protein, known to be overexpressed in prostate cancer. The results (Figure 10) for the RBM3 biomarker to predict an aggressive phenotype of prostate cancer are illustrated below the IHC pictures (Figure 4). The RBM3 AUC-ROC was 0.86 and the patient-specific probability plot to predict aggressive CaP is show next to the AUC-ROC.  Hence, RBM3 is a strong predictor of indolent or less aggressive CaP.

 

qIHC FOR RBM3 PROTEIN IN PROSTATE CANCER
FIGURE 4
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FIGURE 5 Prediction of Indolent Prostate Cancer with RBM3 Biomarker IHC


prostate cancer research

MULTIPLEX TISSUE IMPRINTING (MTI) FOR PROSTATE CANCER BIOMARKERS

The Veltri-Partin laboratory is currently utilizing new and innovative technology to multiplex several protein and glycoprotein biomarkers on a single 5 micron tissue radical prostatectomy or biopsy tissue section.  Multiplex tissue immunoblotting (MTI) allows detection of multiple molecular targets in formalin fixed and paraffin embedded (FFPE) tissues. Starting with a standard FFPE slide (Figure 6), typically the procedure can obtain five replicate membranes from a 5µm thick tissue section. In general, MTI was able to survey 6 biomarkers on a single 5µm section: CACNA1D, Periostin, HER2/neu, EZH2, Ki67 and -7 ProPSA. All the images were quantified using the Typhoon Imager and the ImageQuant 7.2 software and the final data was normalized by total protein for each biomarker. 

FIGURE 6
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Below in Figure 7  we can see a demonstration of the MTI technology applied to a single 5 micron biopsy section of an active surveillance patient biopsy [control non-escapee vs. an escapee] stained for five different molecular tumor-associated biomarkers. Hence, this new MTI technology works effectively on radical (above in Figure 12) and biopsy tissue specimens.

FIGURE 7
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Hence, MTI technology permits assessment of up 6 biomarkers on a single 5-6 micron section of formalin fixed paraffin embedded tissue (FFPE) tissue (either radical prostatectomy or biopsy specimen). The results are quantified and normalized based on total protein in the tissue sample. The assay requires significant technical expertise and careful attention to detail but is reproducible and clinically relevant.





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