Validation of quantitative fluorescence imaging analysis (QFIA) of β-catenin in archived prostate tissues for cancer biomarker discovery

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Background: The objective of this study was to develop a sensitive tissue proteomic assay for quantifying proteins (e.g. β- catenin) in tissues and prostate core biopsies by QFIA. A second objective was to apply the validated methodology to quantify other biomarkers for prostate cancer risk assessment, and to study oxidative stress in BPH, prostate cancer, the cancer field, and in inflammatory prostatitis in animals and human prostatitis. Methods: Biopsies from controls and cancer patients were depariffinized, the antigen retrieved, and labeled with a robotic BioGenex Stainer with a primary mouse monoclonal antibody (1/100) to β-catenin. A secondary goat anti-mouse IgG antibody (2° Ab 1/100) coupled with Alexa Fluor 568 was used as the indicator system. The Leica Fluorescence Microscope was calibrated and standardized with fluorescence beads, LNCAP cells, and BPH tissue sections. QFIA of β-catenin was validated by RPPA methacarn fixed tissues. Adjacent 4-micron tissue sections were analyzed by QFIA for total β-catenin content by RPPA. Results: Reproducibility was 10% or less for the LNCAP cells and BPH tissue controls. Adjacent tissue sections assayed by QFIA and RPPA exhibited a strong linear correlation (r=.97) as did tissues fixed in methacarn vs.10% buffered-formalin and assayed by QFIA (r=0.84). For the core biopsy specimens the average MPI (AMPI) from 40 to 200 acini was quantified. The AMPI of cancerous acini (CA) compared to nomal acini (NA) was reduced in 37 of 42 cases p<.02. ROC plots revealed that β-catenin expression in NAA identified 42% (95%CI 25 - 52%) of cancer cases, with 88% (95% CI 80%-96%) specificity. The tissue QFIA method was used to quantify oxidative stress biomarkers (MnSOD, HNE, 8-OHdG) and other field disease biomarkers (Connexin42, and UDP-glucose dehydrogenase (UGDH) in BPH, prostate cancer, and in prostatitis. Conclusions: A tissue based QFIA method has been developed for the quantification of β-catenin in prostate core biopsy specimens, and the method has been validated by RPPA. Assay of β-catenin in prostate core biopsy specimens shows promise as a potential biomarker for a profile defining individuals at risk for prostate cancer and studying oxidative stress in relation to the pathogenesis of disease.

No significant financial relationships to disclose.

Identifying the biologically relevant gene categories based on gene expression and biological data: an example on prostate cancer

MOTIVATION

Most gene-expression based studies aim to identify genes with the capability of distinguishing different phenotypes. Although analysis at the genomic level is important, results of the molecular/cellular level are essential for understanding biological mechanisms. To deliver molecular/cellular-level results, a two-stage scheme is widely employed. This scheme just evaluates biological processes/molecular activities individually, totally overlooking the relationship between processes/activities. This treatment conflicts with the fact that most biological processes/molecular activities do not work alone. In order to deliver improved results, this shortcoming should be addressed.

RESULTS

We design a selection model from a novel perspective to directly detect important gene functional categories (each category represents a cellular process or a molecular activity). More importantly, the correlations between gene categories are considered. Contributed by this capability, the proposed method shows its advantages over others.

AVAILABILITY

the source code in Matlab is accessible via http://www.ee.cityu.edu.hk/~twschow/category_selection/category_selection.htm

Association of variants in theIL12Bgene with leprosy and tuberculosis

There is a great range in outcomes after mycobacterial infections, and this is probably due to individual variation in immune responses. One of the key cytokine regulators of the immune response is interleukin (IL-) 12. The IL12B gene encodes the p40 chain of both IL-12 and IL-23 and it has two major variant sites at which different alleles are associated with increased levels of gene expression and with susceptibility to a range of immune-related diseases. We hypothesized that IL12B variants associated with increased expression would be as associated with susceptibility to persistent mycobacterial infection. We tested this hypothesis by genotyping Indian subjects, having either leprosy or tuberculosis (TB), as well as ethnically matched controls. Subjects with leprosy were less likely to have the 3'UTR genotype associated with lower IL12B expression (P= 0.001). Subjects with TB were not only more likely to have the high-expressing IL12B promoter genotype (P= 0.01) but also more likely to have this in the same haplotype with the high expressing 3'UTR allele (P= 0.0009). These results suggest these infectious diseases may be improved by modulating IL-l2p40 production.

Feature extraction using recursive cluster-based linear discriminant with application to face recognition

A novel recursive procedure for extracting discriminant features, termed recursive cluster-based linear discriminant (RCLD), is proposed in this paper. Compared to the traditional Fisher linear discriminant (FLD) and its variations, RCLD has a number of advantages. First of all, it relaxes the constraint on the total number of features that can be extracted. Second, it fully exploits all information available for discrimination. In addition, RCLD is able to cope with multimodal distributions, which overcomes an inherent problem of conventional FLDs, which assumes uni-modal class distributions. Extensive experiments have been carried out on various types of face recognition problems for Yale, Olivetti Research Laboratory, and JAFFE databases to evaluate and compare the performance of the proposed algorithm with other feature extraction methods. The resulting improvement of performances by the new feature extraction scheme is significant.

Altered expression of β-catenin and UDP-glucose dehydrogenase in normal appearing acini of cancer-bearing prostate glands, detected by quantitative fluorescence imaging analysis

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Background: Expression of β-catenin and UDP-glucose dehydrogenase (UGDH) is markedly altered in prostate adenocarcinomas. The objective of this work was to evaluate expression of these proteins in normal appearing acini (NAA) of cancer-bearing prostate glands, as potential biomarkers of PC field disease. Methods: Archived core biopsies of 42 pairs of PC cases and controls were labeled for β-Catenin, and a tissue microarray of 10 prostatectomy specimens of cancer cases and controls were labeled for UGDH. A fluorophore-conjugated secondary antibody was incorporated into the staining protocol. Fluorescence in prostatic acini was measured with an automated Leica microscope and Image Pro Plus software and expressed as mean pixel intensity (MPI) per acinus and average MPI (AMPI) per case or control. Results: Mean AMPI of β-catenin in NAA of 33 cases (545 ± 93) was lower (p < 0.01) than that of normal acini (NA) in age-matched controls (684 ± 90), whereas mean AMPI of NAA in the remaining 9 cases (712 ± 111) was higher (p = 0.003) than that of the matched controls (634 ± 95). Twelve cases under-expressing β-catenin in NAA had AMPIs below the lowest AMPI (506 ± 83) of all controls. Mean AMPI of UGDH in NAA of 7 cases (372 ± 169) was lower (p < 0.05) in comparison to both NA (558 ± 119) and cancerous acini (CA) (645 ± 88). The difference between CA and NA did not achieve statistical significance. Conclusions: Reduced expression of β-catenin is a cancer-associated event in NAA. A cut-off AMPI (506) for β-catenin detected 29% of PC cases with 100% specificity. Altered expression of UGDH in NAA is a potential biomarker of PC. Funded by DoD grant DAMD17–02–1-0121.

No significant financial relationships to disclose.

Enhancing density-based data reduction using entropy

Data reduction algorithms determine a small data subset from a given large data set. In this article, new types of data reduction criteria, based on the concept of entropy, are first presented. These criteria can evaluate the data reduction performance in a sophisticated and comprehensive way. As a result, new data reduction procedures are developed. Using the newly introduced criteria, the proposed data reduction scheme is shown to be efficient and effective. In addition, an outlier-filtering strategy, which is computationally insignificant, is developed. In some instances, this strategy can substantially improve the performance of supervised data analysis. The proposed procedures are compared with related techniques in two types of application: density estimation and classification. Extensive comparative results are included to corroborate the contributions of the proposed algorithms.