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• To develop a '2010 Partin Nomogram' with total prostate-specific antigen (tPSA) as a continuous biomarker, in light of the fact that the current 2007 Partin Tables restrict the application of tPSA as a non-continuous biomarker by creating 'groups' for risk stratification with tPSA levels (ng/mL) of 0-2.5, 2.6-4.0, 4.1-6.0, 6.1-10.0 and10.0. • To use a 'predictiveness curve' to calculate the percentile risk of a patient among the cohort.• In all, 5730 and 1646 patients were treated with radical prostatectomy (without neoadjuvant therapy) between 2000 and 2005 at the Johns Hopkins Hospital (JHH) and University Clinic Hamburg-Eppendorf (UCHE), respectively. • Multinomial logistic regression analysis was performed to create a model for predicting the risk of the four non-ordered pathological stages, i.e. organ-confined disease (OC), extraprostatic extension (EPE), and seminal vesicle (SV+) and lymph node (LN+) involvement. • Patient-specific risk was modelled as a function of the B-spline basis of tPSA (with knots at the first, second and third quartiles), clinical stage (T1c, T2a, and T2b/T2c) and biopsy Gleason score (5-6, 3 + 4 = 7, 4 + 3 = 7, 8-10).• The '2010 Partin Nomogram' calculates patient-specific absolute risk for all four pathological outcomes (OC, EPE, SV+, LN+) given a patient's preoperative clinical stage, tPSA and biopsy Gleason score. • While having similar performance in terms of calibration and discriminatory power, this new model provides a more accurate prediction of patients' pathological stage than the 2007 Partin Tables model. • The use of 'predictiveness curves' has also made it possible to obtain the percentile risk of a patient among the cohort and to gauge the impact of risk thresholds for making decisions regarding radical prostatectomy.• The '2010 Partin Nomogram' using tPSA as a continuous biomarker together with the corresponding 'predictiveness curve' will help clinicians and patients to make improved treatment decisions.

To assess a novel application of the Prostate Health Index (phi) and biopsy tissue DNA content in benign-adjacent and cancer areas to predict which patients would eventually require treatment of prostate cancer in the Proactive Surveillance cohort.We identified 71 men who had had serum and biopsy tissue from their diagnosis banked and available for the present study. Of the 71 patients, 39 had developed unfavorable biopsy findings and 32 had maintained favorable biopsy status during surveillance. The serum total prostate-specific antigen (tPSA), free PSA (fPSA) and [-2]proPSA were measured using the Beckman Coulter immunoassay. The DNA content measurements of Feulgen-stained biopsy sections were performed using the AutoCyte imaging system.The ratio of phi was significantly greater (37.23 ± 15.76 vs 30.60 ± 12.28; P = .03) in men who ultimately had unfavorable biopsy findings. The serum phi ratio (P = .003), [-2]proPSA/%fPSA (P = .004), biopsy tissue DNA content (ie, benign-adjacent excess of optical density, P = .019; and cancer area standard deviation of optical density, P = .002) were significant predictors of unfavorable biopsy conversion on Cox regression analysis. However, phi and [-2]proPSA/%fPSA showed a highly significant correlation (rho = 0.927, P.0001) and no difference in accuracy (c-index, 0.6247 vs 0.6158; P = .704) for unfavorable biopsy conversion prediction. Furthermore, phi and [-2]proPSA/%fPSA remained significant (P = .047 and P = .036, respectively) in the multivariate models and, combined with the biopsy tissue DNA content, showed improvement in the predictive accuracy (c-index, 0.6908 and 0.6884, respectively) for unfavorable biopsy conversion.The Prostate Health Index to proPSA/%fPSA, combined with biopsy tissue DNA content, improved the accuracy to about 70% to predict unfavorable biopsy conversion at the annual surveillance biopsy examination among men enrolled in an Active Surveillance program.

BACKGROUND Nuclear structure is often altered in cancer due to spatial rearrangements of chromatin organization via activation of oncogenes and other chromatin remodeling genes. Therefore, we evaluated the prognostic value of nuclear roundness variance (NRV) for prostate cancer (PCa) progression, metastasis and PCa-specific death free survivals in a cohort of 116 men after radical prostatectomy (RP). METHOD NRV was calculated for each case using the variance of the nuclear roundness from approximately 150 nuclei captured at a magnification of 2,440x for each case in 1992-1993. $${\rm Nuclear}\,{\rm roundness} = {{{\rm Radius}({\rm circumference})} \over {{\rm radius}({\rm area})}} = {R \over r} = {{P/2\pi } \over {\sqrt {A/\pi } }}$$ NRV data were merged with clinical, pathologic, and follow-up data for all patients in 2009. Cox proportional hazards regression and Kaplan-Meier plots were employed to analyze the data. RESULTS Median follow-up time after RP for all patients was 19 years (range: 1-25 years, mean: 17 years), with approximately 92% (107/116), 71% (82/116), and 47% (55/116) patients having >or=10, 15, and 20 years of follow-up, respectively. NRV was the most significant parameter for prediction of all three outcomes and its concordance-index (C-Index) increased from progression (0.7080) to metastasis (0.7332) to PCa-specific death (0.8090) free survival predictions. Of note, NRV C-Index was significantly higher compared to Gleason Score C-Index for metastasis (0.7332 vs. 0.6046; P = 0.027) and PCa-specific death (0.8090 vs. 0.6336; P = 0.004) free survival predictions. However, the difference between NRV and Gleason Score C-Indexes was not statistically significant for progression free survival prediction (0.7080 vs. 0.6463; P = 0.106). CONCLUSION NRV is valuable nuclear structural feature that exceeds Gleason score to predict an aggressive phenotype of PCa.

To evaluate the clinical utility of quantitative nuclear morphometry--i.e., alteration in nuclear size/shape, DNA content and chromatin structure-of intact cells obtained from the sediment of urine specimens collected from people living in an area highly endemic for Schistosoma haematobium in Ghana.Digital images of Feulgen-DNA-stained squamous cell (SC) and transitional cell (TC) urothelial nuclei were captured using the AutoCyte imaging system, and nuclear morphometric descriptors (NMDs) were calculated. A total of 3,495 and 4,523 SC and TC nuclei from normal bladder ultrasound subjects (n =21) and 3,465 and 3,064 SC and TC nuclei from severely abnormal bladder ultrasound subjects (n = 20) were captured.Univariate logistic regression analyses of pooled SC and TC nuclei training sets showed that 27/40 NMDs and 24/40 NMDs were univariately significant for differentiating between SCs and TCs of subjects with normal and severely abnormal bladder ultrasound. Multivariate models constructed using NMDs withor = 50% inclusion frequency yielded AUC-ROCs of 75.23% and 74.42% in the SC training and validation, and 69.90% and 66.70% for TC training and validation. Further, a squamous cell patient-specific model predicted severe bladder damage with an AUC-ROC of 86.90%, yielding the sensitivity, specificity and accuracy of 85.00%, 76.19% and 80.49%, respectively.Quantitative nuclear structure alterations can be used to make a noninvasive assessment of cytologic changes observed in both SC and TC bladder epithelia due to S haematobium infection.

The association between chronic infection with Schistosoma haematobium and squamous cell carcinoma of the bladder is well known but there are few epidemiological data available to assess the extent of this cancer in schistosome-endemic areas. Invasive surgical procedures are not practical for epidemiological appraisal, therefore this important health matter is unresolved. This review examines recent work done to identify and detect biomarkers that can be found in voided urine and therefore obtained without invasive procedures. A variety of products of cell cycle kinetics, nuclear activity enzymes and even nuclear morphometry have been studied in urine specimens and these in concert may be sufficient to indicate the likelihood of the presence of bladder cancer or some predictive pre-cancerous state. Although these techniques require a sophisticated central laboratory for analysis, specimens can easily be collected in the field and brought to the centre, which could serve regional programmes. We suggest that early diagnosis of pre-cancerous conditions associated with urinary schistosomiasis, if appropriately treated, could save countless lives.

Abnormal DNA content in tumor cells represents large scale chromosomal alterations and reflects later changes of genetic instability. Her-2/neu oncogene is amplified in 20-30% of breast and ovarian cancer patients and is associated with poor prognosis. Therefore, we evaluated prognostic value of Her-2/neu expression and DNA content measurements in 252 clinically localized PCa patients with long-term follow-up after radical prostatectomy for progression, metastasis and PCa-specific death. Her-2/neu expression was determined by immunohistochemistry and DNA content measurements employed Feulgen-stained cancer nuclei captured using static image cytometry system. Cox proportional hazard regression and Kaplan-Meir plots were used to identify significant prognostic factors for progression, metastasis and PCa-specific death. The proportions of Her-2/neu positive and high %DNA index tumors significantly increased from nonprogressor to progressors without metastasis to progressors with metastasis (p < 0.0001

Changes in nuclear structure occur in response to normal physiological processes such as cell division, apoptosis, cell differentiation, and senescence, as well as in disease-related processes such as cancer, where they are manifested in response to numerous alterations in gene expression (1). Therefore, the accurate and reproducible measurement of nuclear structure changes can provide important objective information when assessing and managing the pathologic disease process (2, 3, 4). Several studies have demonstrated that transformation of a normal cell into a malignant cell requires a series of genetic changes (or hits) (5, 6, 7) such as mutations, DNA methylation events in promoters or exons, chromosome deletions, insertions, amplifications, and translocations (7, 8, 9, 10, 11, 12, 13). Additionally, several classes of well-characterized nuclear organelles (spliceosomes, centrosomes, telomeres, and nucleosomes), gene families (HMGA, SWI/SNF modifiers, RARs, MARs, etc.), and key structural and regulatory proteins (e.g., nuclear matrix proteins, HMG proteins, nuclear histones H1, H2A, H2B, H3, and H4, and SWI/SNF complex) have been identified as being important to maintenance of nuclear chromatin structure and function (13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27). One example in this area involves work on the combinatorial chemistry of the histone tails of the nucleosome’s protein core. There is evidence that acetylation, methylation, phosphorylation, glycosylation, and ubiquination of the histone tail can produce changes in chromatin structure directly related to differential patterns of gene expression (27).

Background: Nuclear morphometric signatures can be calculated using nuclear size, shape, DNA content, and chromatin texture descriptors [nuclear morphometric descriptor (NMD)]. We evaluated the use of a patient-specific quantitative nuclear grade (QNG) alone and in combination with routine pathologic features to predict biochemical [prostate-specific antigen (PSA)] recurrence-free survival in patients with prostate cancer. Methods: The National Cancer Institute Cooperative Prostate Cancer Tissue Resource (NCI-CPCTR) tissue microarray was prepared from radical prostatectomy cases treated in 1991 to 1992. We assessed 112 cases (72 nonrecurrences and 40 PSA recurrences) with long-term follow-up. Images of Feulgen DNA–stained nuclei were captured and the NMDs were calculated using the AutoCyte system. Multivariate logistic regression was used to calculate QNG and pathology-based solutions for prediction of PSA recurrence. Kaplan-Meier survival curves and predictive probability graphs were generated. Results: A QNG signature using the variance of 14 NMDs yielded an area under the receiver operator characteristic curve (AUC-ROC) of 80% with a sensitivity, specificity, and accuracy of 75% at a predictive probability threshold of ≥0.39. A pathology model using the pathologic stage and Gleason score yielded an AUC-ROC of 67% with a sensitivity, specificity, and accuracy of 70%, 50%, and 57%, respectively, at a predictive probability threshold of ≥0.35. Combining QNG, pathologic stage, and Gleason score yielded a model with an AUC-ROC of 81% with a sensitivity, specificity, and accuracy of 75%, 78%, and 77%, respectively, at a predictive probability threshold of ≥0.34. Conclusions: PSA recurrence is more accurately predicted using the QNG signature compared with routine pathology information alone. Inclusion of a morphometry signature, routine pathology, and new biomarkers should improve the prognostic value of information collected at surgery. (Cancer Epidemiol Biomarkers Prev 2008;17(1):102–10)

We assessed the use of quantitative clinical and pathologic information to predict which patients would eventually require treatment for prostate cancer (CaP) in an expectant management (EM) cohort.We identified 75 men having prostate cancer with favorable initial biopsy characteristics; 30 developed an unfavorable biopsy (Gleason grade6,2 cores with cancer,50% of a core with cancer, or a palpable nodule) requiring treatment and 45 maintained favorable biopsies throughout a median follow-up of 2.7 years. Demographic, clinical data and quantitative tissue histomorphometry determined by digital image analysis were analyzed.Logistic regression (LR) modeling generated a quantitative nuclear grade (QNG) signature based on the enrollment biopsy for differentiation of Favorable and Unfavorable groups using a variable LR selection criteria of P(z)0.05. The QNG signature utilized 12 nuclear morphometric descriptors (NMDs) and had an area under the receiver operator characteristic curve (ROC-AUC) of 87% with a sensitivity of 82%, specificity of 70% and accuracy of 75%. A multivariable LR model combining QNG signature with clinical and pathological variables yielded an AUC-ROC of 88% and a sensitivity of 81%, specificity of 78% and accuracy of 79%. A LR model using prostate volume, PSA density, and number of pre-diagnosis biopsies resulted in an AUC-ROC of 68% and a sensitivity of 85%, specificity of 37% and accuracy of 56%.QNG using EM prostate biopsies improves the predictive accuracy of LR models based on traditional clinicopathologic variables in determining which patients will ultimately develop an unfavorable biopsy. Our QNG-based model must be rigorously, prospectively validated prior to use in the clinical arena.

BACKGROUND We recently demonstrated the protein expression profiling of Dunning rat tumor cell lines of varying metastatic potential (G (0%), AT-1 (∼20%), and MLL (100%)) using SELDI-TOF-MS. As a parallel effort, we have been pursuing the identification of the protein(s) comprising the individual discriminatory “peaks” and evaluating their utility as potential biomarkers for prostate cancer progression. METHODS To identify the observed SELDI-TOF-MS m/z (mass/charge) values with discriminatory expression between different sublines, we employed a combination of chemical pre-fractionation, liquid chromatography, gel electrophoresis and tandem mass spectroscopy. Identified proteins were then verified by immuno-assay and Western analysis. RESULTS A 17.5 K m/z SELDI-TOF-MS peak was found to retain discriminatory value in each of two separate study-sets with an increased expression in the metastatic MLL line. Sequence identification and subsequent immunoassays verified that Histone H2B is the observed 17.5 K m/z SELDI peak. SELDI-based immuno-assay and Western Blotting revealed that Histone H2B is specifically over-expressed in metastatic MLL lines. CONCLUSIONS SELDI-TOF MS analysis of the Dunning prostate cancer cell lines confirmed the consistent overexpression of a 17.5 K m/z peak in metastatic MLL subline. The 17.5 kDa protein from MLL has been isolated and identified as Histone H2B. Prostate 67: 1565–1575, 2007. © 2007 Wiley-Liss, Inc.

There will be an anticipated 29,480 prostate cancer (PCa) deaths in 2014 in the US. Nearly 40% of PCa patients will undergo radical prostatectomy (RP), which reduces the risk of death from PCa. Roughly ∼15% of these PCa patients tend to recur and of these a portion will metastasize (∼40%). Hence, a more accurate and objective computer-assisted image analysis (CAIA) automated PCa grading system should be considered. The current standard for Gleason grading involves an expert pathologist visually scoring Gleason grade patterns based upon H&E histologic glandular architecture (size, shape and organization). Using the same tissue microarray (TMA) containing 80 radical prostatectomy (RP) cases stratified by Gleason scores, the authors selected a subset of up to fifty 20X Aperio whole slide scanned H&E images representing GG 3 and GG4 cases. Three separate approaches to measure tissue texture and nuclear structure were used: 1) adaptive active contour scheme (AdACM) segmentation which focuses on nuclear shape and texture features 2) Curvelet transform based histologic tissue texture method and 3) MediaCybernetics ImagePro 9.1 software that includes ∼22 nuclear structure features. Data analysis utilized area under the curve (AUC) for the receiver operating characteristics (ROC) with assessment of accuracy, sensitivity and specificity. Ali and Madabhushi at Case Western Reserve University utilized AdACM segmentation approach and three nuclear features to obtain an AUC = 0.88 yielding an accuracy of 86.1% with sensitivity = 85.2% and specificity = 87.1% applying a quadratic discriminant analysis (QDA) classifier to separate GG 3 from GG4. Next, the University of Pittsburgh's EEE group (Wen-Chyi Lin and C. C. Li) applied a curvelet based tissue feature extraction method and a tree-structured classifier consisting of three Gaussian-kernel support vector machines each with an embedded voting mechanism and discriminated Gleason grade (GG) 3 vs GG 4 generating a AUC = 0.98 yielding an accuracy = 95.7% with sensitivity = 94.5% and specificity = 96.9%. Finally, the Veltri laboratory differentiated GG3 and GG4 and obtained an AUC = 0.96 and yielding an accuracy = 85%, sensitivity = 82%, specificity = 90% to separate GG pattern 3 from 4. Therefore using CAIA with three different laboratories we were able to use PCa glandular histologic and cell nuclear quantitative measurements to accurately discriminate GG patterns 3 and 4. More work is required to apply these automated tools to confirm the optimal method and also to predict PCa outcomes of recurrence, metastasis and survival. Citation Format: Robert W. Veltri, Sahirzeeshan Ali, Wen-Chyi Lin, Guangjing Zhu, Jonathan I. Epstein, Ching-Chung Li, Anant Madabhushi. Cancer histologic and cell nucleus architecture differentiate prostate cancer Gleason patterns 3 from 4. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4349. doi:10.1158/1538-7445.AM2015-4349

Introduction: The prostate-specific antigen (PSA) test has improved the early detection of PCa and also recurrence after radical prostatectomy (RP). However, it is estimated that 35% of patients submitted to RP that progress with detectable PSA levels will never present metastatic disease. Thus, there is a need to distinguish localized curable disease from a subset of patients at risk for progression. Currently, the D’Amico Stratification System defines high risk PCa as any combination of the following factors: PSA >20ng/ml, a Gleason score (GS) of 8-10, or clinical stage T2c or greater. As some aggressive PCa did not fit these criteria, a more accurate test to classify high risk patients is crucial. Objective: The objective of this study is to identify a cancer/testis antigen (CTA)-based biomarker to discern PCa patients with potentially aggressive disease. The CTAs are a unique group of genes whose expression is normally confined to germ cells in normal testis and placenta, but aberrantly expressed in several types of cancers. Methods and results: Using Nanostring multiplex approach, we screened the expression of 22 CTA genes in 20 localized (LPCa) and 20 metastatic prostate cancer (MPCa) samples, obtained from University of Washington. Using ROC curve analysis we ranked the CTAs capable of discriminating LPCa and MPCa. We found one under-expressed CTA (PAGE4) and seven over-expressed (CEP55, NUF2, PBK, RQCD1, SPAG4, SSX2 and TTK) in MPCa, considering AUC>0.70. qRT-PCR was used to validate Nanostring results in the same set of samples and to identify the candidate CTA biomarkers. The eight CTAs selected showed significant expression changes and were also capable of separating LPCa and MPCa cases (AUC>0.70). A multivariate logistic regression model (MLR) showed that combined expression patterns of CEP55, NUF2, PBK and TTK was capable of discriminating MPCa from LPCa with AUC = 0.95 (pr = 0.15), sensitivity = 80%, specificity = 90%. Using this model 85% of the PCa cases were correctly classified. We then evaluated, by q-RT-PCR, if CTA expression profile is associated with GS using the same 20 LPCa samples and a new set of 25 PCa samples. The PCa cases were separated in two groups according to GS: (1) 3+3/3+4 and (2) other GS. The expression pattern of the CTA panel CEP55, NUF2 and RQCD1 correctly separated 83% of the samples according to the GS with AUC = 0.89 (pr = 0.05), sensitivity = 88%, specificity 75%. Conclusion: The results of the study are clinically and biologically relevant, since little is known about the role of CTAs in PCa. The CTA expression pattern was shown to be different between two extreme pathologic phenotypes and also among samples of different GS. The CTA profile may be useful to identify high risk LPCa patients and to stratify patients according to GS, which may guide treatment strategies for the different groups of patients. Citation Format: Luciane T. Kagohara, Prakash Kulkarni, Takumi Shiraishi, Guangjing Zhu, Robert Vessella, Robert Veltri. Cancer/testis antigen expression pattern is a potential biomarker for prostate cancer aggressiveness. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4826. doi:10.1158/1538-7445.AM2015-4826

Introduction: The progression of prostate cancer (PCa) involves both tissue morphometric changes and critical molecular alterations (such as cancer-associated markers). We have studied 80 men that underwent radical prostatectomy (RP) to evaluate this dual approach to discriminate Gleason score and progression. Next, we applied our approach at the diagnostic biopsy of men that chose active surveillance (AS) as an option for the management of their PCa, to predict the likelihood for re-classification of their disease to immediate treatment. Materials & Methods: Two tissue microarrays (TMAs) with 80 RP PCa cases, stratified by Gleason scores were used first. Next, a total of 27 favorable and 24 unfavorable AS biopsy PCa cases were evaluated. In both series we applied multiplex tissue immunoblotting (MTI) & quantitative nuclear morphometry studies. Data were first analyzed alone and then in combination using multivariate logistic regression (MLR) to predict the aggressive RP cases or AS biopsy reclassification status of the cancer. MTI was used to simultaneously detect 5∼6 biomarkers ((-5,-7)ProPSA, PCNA, RBM3, Her2/neu, & CACNA1D, etc) on a single 5 micron section. Proteins on the slide were transferred onto a series of 5∼6 P-film membranes and each membrane was probed with different primary antibody. The quantified FITC fluorescence signal of the biomarker were normalized to CY5 labelled total protein. For the nuclear morphometry analysis, quantification of the nuclear features were achieved either using ImagePro Premier 9.1 Software for the TMAs or the adaptive active contour scheme (AdACM) that uses nuclear shape, architectural and textural features extracted from AS biopsies. RESULTS: Using MLR, to differentiate aggressive PCa (Gleason score 4+3 & > = 8) from less aggressive PCa (Gleason score 3+3 & 3+4) on the TMAs of RP cases, our biomarkers model generated an ROC-AUC of 0.8 with accuracy of 71.43%, while morphometry model generate an ROC-AUC of 0.92 with accuracy of 82.50 %. When combined, it improved to an ROC-AUC of 0.96 and accuracy of 87.01%. Additionally, MLR was used for differentiation unfavorable biopsy cases that requires reclassification due to upgraded Gleason score, increased tumor volume, and/or PSA/PSAD during monitoring and need definitive treatment. On the contrary, favorable cases are very low risk (VLR) PCa biopsies that are not reclassified and can continue monitoring. The biomarkers model produced an ROC-AUC of 0.71 with an accuracy of 73.91% while morphometry model produces an ROC-AUC of 0.84 and accuracy of 74.51%. When combined, the new model produces an ROC-AUC of 0.88 and accuracy of 80.43%. CONCLUSIONS: Our method combining tissue morphometry with biomarkers demonstrated its translational clinical relevance since it can predict PCa aggressiveness in men that have undergone RP. Also, this approach predicts AS PCa cases requiring reclassification and immediate treatment at biopsy. Citation Format: Guangjing Zhu, George Lee, Christine Davis, Luciane Tsukamoto Kagohara, Jonathan I. Epstein, Patricia Landis, H. Ballantine Carter, Anant Madabhushi, Robert W. Veltri. Prediction of prostate cancer progression with biomarkers and tissue morphometry changes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4352. doi:10.1158/1538-7445.AM2015-4352

ContextProstate safety is a primary concern when aging men receive testosterone replacement therapy (TRT), but little information is available regarding the effects of TRT on prostate tissue in men.ObjectiveTo determine the effects of TRT on prostate tissue of aging men with low serum testosterone levels.Design, Setting, and ParticipantsRandomized, double-blind, placebo-controlled trial of 44 men, aged 44 to 78 years, with screening serum testosterone levels lower than 300 ng/dL (

Precursors of prostate-specific antigen (proPSA) have been previously shown to be more concentrated in prostate cancer tissue. This study characterizes the immunohistochemical staining (IHS) of proPSA forms in metastatic prostate cancer compared with prostate specific antigen (PSA) and prostatic acid phosphatase (PAP). A tissue microarray, consisting of 74 cases of metastatic prostate carcinoma and control tissues, was used. IHS, using monoclonal antibodies against proPSA with a truncated proleader peptide containing 2 amino acids ([-2]pPSA), native ([-5/-7]pPSA), PSA, and PAP, was analyzed. The monoclonal antibodies were specific for both benign and malignant prostatic glandular tissue. IHS with [-5/-7]pPSA showed the least number of cases with negative staining (3%), and the most number of cases with moderate or strong staining (76%). In the 60 cases where all 4 stains could be evaluated, none of them were negative for proPSA and positive for PSA or PAP, and all 7 cases that were negative for both PSA and PAP showed IHS to proPSA. [-5/-7]pPSA (native proPSA) may be a better marker than PSA and PAP in characterizing metastatic prostate adenocarcinoma, with most of the cases showing positivity for the marker. Even cases that were negative for PSA and PAP, were reactive for proPSA. Such enhanced detection is particularly important in poorly differentiated carcinomas involving metastatic sites where prostate carcinoma is a consideration. A panel of markers, including proPSA, should be performed when metastatic prostate carcinoma is in the differential diagnosis.

PURPOSE OF REVIEW Bladder cancer is one of the most common genitourinary malignancies and is a potentially life-threatening diagnosis. For many patients, however, the diagnosis of bladder cancer entails a lifetime of vigilant, costly, and invasive surveillance for recurrent and/or progressive disease. In the context of relative limitations of the current standard of cystoscopy and cytology, there has been burgeoning activity in the development of novel molecular urine-based markers for bladder cancer detection. RECENT FINDINGS A large number of candidate bladder cancer biomarkers have emerged as our understanding of the molecular pathogenesis of the disease has evolved. Many of these are in the relatively earlier phases of development but several have received the approval of the United States Food and Drug Administration for clinical use and are already being applied to patients in clinical practice. SUMMARY Urine-based markers for bladder cancer detection represent an area of substantial innovation and discovery with potentially profound scientific, clinical, and economic implications. As more of these tests become standardized and undergo evaluation in large multicenter trials, it is conceivable that a novel marker or panel of markers will emerge as a major enhancement to the current standard of care.

Long-term infection with urinary schistosomiasis has been associated with development of bladder cancer. However, bladder cancer is difficult to diagnose without invasive measures such as cystoscopy, thus there is little information on the epidemiological extent of the problem. Studies have been either case-control studies or case examinations in different geographical areas, estimating a schistosome-associated bladder cancer incidence of 3-4 cases per 100,000. We have used three indicators to examine the potential bladder cancer problem in an adult rural population in Ghana endemic for urinary schistosomiasis: (i) parasitological positivity; (ii) age prevalence of bladder damage from ultrasound scans; and (iii) detection of biomarkers associated with the presence of bladder cancer. Biomarkers were BLCA-4 test (urine) and nuclear morphometry or quantitative nuclear grading (QNG) of epithelial cells (urine sediment), which quantifies DNA ploidy status and nuclear morphometric descriptors, both of which can detect the presence of bladder cancer. Our data show an increasing association between age, severe bladder abnormalities and the occurrence of these biomarkers. Sixty-two of 73 cytopathology Papanicolaou-stained smears were seen to have squamous metaplasia. Although further investigations are needed, we suggest that schistosome-associated bladder cancer is an important public health concern in areas where Schistosoma haematobium is prevalent.

We measured the histologic stromal and epithelial tissue components of the benign (normal) and malignant tissue compartments of Japanese-Americans (J-A) and native Japanese (NJ) men living in Japan. The patient cohort included 25 NJ men undergoing radical prostatectomy (RP) in Nagoya, Japan and 25 J-A (second or third generation US born). We conducted tissue image quantitation (in-house image software) of the stromal and epithelial compartments in malignant and adjacent normal tissue areas from a tissue microarray (TMA) selected from radical prostatectomy (RP) blocks. Stromal–epithelial (S–E) areas were determined using immunohistochemical stains for CAM-5.2 epithelial cytokeratin marker and the Masson trichrome stain to measure the stroma component. We observed differences in the volumes of normal and cancer epithelium and stroma within both the J-A and NJ study populations (P

Surface enhanced laser desorption and ionization-time-of-flight (SELDI-TOF) is an evolving proteomic technology for improving biomarker discovery that allows for rapid and sensitive analysis of complex protein mixtures generated from body fluids, cells, and/or tissues. SELDI--based profiling identifies unique, differentially expressed proteins relating to specific cancer-related disease states. We utilized SELDI-TOF following pre-processing with molecular separation and chemical fractionation of cell membrane extracts from three Dunning rat prostate cancer cell lines of varying metastatic potential to search novel proteins that are differentially expressed.Dunning rat cell sublines of variable (%) metastatic potential; G (0%), AT-1 (20%), and Mat-Ly-Lu (100%) were cultured in two different laboratories. Cell lysis was performed in a homogenation buffer (320 mM sucrose/50 mM Tris/0.5 mM PSMF) using Dounce homogenation. After centrifugation, the membrane pellet was washed 2x and then solublized in 2% CHAPS/8 M urea. This sample was further processed using positive pressure molecular ultrafiltration at 30 kDa or precipitation with 50% ammonium sulfate. Next, each sample was applied to an IMAC3-Ni ProteinChip (Ciphergen Biosystems, Freemont, CA) and analyzed using Ciphergen's Protein Biology System with protein peak analysis software.SELDI-TOF analysis differentiated the three Dunning rat cell sublines based upon protein concentration normalized profiles between 5,000 and 20,000 Da. The preparations from the three cells lines showed clear differences when the extracts from the metastatic sublines (AT-1 and MLL) were compared to the benign subline (G) for proteins with molecular weights of 9 kDa (decrease), 12 kDa (significant decrease), 14 kDa (decrease), and 17 kDa (significant gain). After pre-processing extracts with ammonium sulfate and molecular ultrafiltration, the molecular profile changes from one subline to the next became more apparent. Our results were reproducible using multiple runs including from Dunning cells cultured in a separate laboratory, and using different lots of SELDI ProteinChips.The application of SELDI-TOF to a series of Dunning rat prostate cancer cell lines illustrated apparent changes in protein profiles among the three cell lines with known differences in metastatic biologic activity. SELDI-TOF identified four reproducible changes in protein expression in the AT1 and MLL metastatic cell sublines. Three of the expression changes were manifested as decreases, but one protein (17 kDa) was over-expressed in the AT1 and MLL cell lines. Emphasis will be placed on the isolation, purification, and characterization of the 17 kDa over-expressed protein and its potential role in PCa metastasis.

Purpose: Malignant transformation in the prostate produces significant alterations in glandular architecture (Gleason grade) and nuclear structure that provide valuable prognostic information. Normal-appearing nuclei (NN) adjacent to cancer may also have altered functions in response to malignancy. We studied NN adjacent to peripheral zone (PZ) prostate cancer (PCa), as well as the PZ cancer nuclei (CaN) using quantitative image cytometry. The nuclear structure information was combined with routine pathological findings to predict metastatic PCa progression and/or death. Experimental Design: Tissue microarrays of normal-appearing and cancer areas were prepared from 182 pathologist-selected paraffin blocks. Feulgen-stained CaN and NN were captured from the tissue microarrays using the AutoCyte Pathology Workstation. Multivariate logistic regression was used to calculate quantitative nuclear grade (QNG) solutions based on nuclear morphometric descriptors determined from NN and CaN. Multivariate logistic regression and Kaplan-Meier plots were also used to predict risk for distant metastasis and/or PCa-specific death using QNG solutions and routine pathology. Results: The pathology model yielded an area under the receiver operator characteristic curve of 72.5%. The QNG-NN and QNG-CaN solutions yielded an area under the receiver operator characteristic curve of 81.6 and 79.9%, respectively, but used different sets of nuclear morphometric descriptors. Kaplan-Meier plots for the pathology variables, the QNG-NN and QNG-CaN solutions, were combined with pathology to defined three statistically significantly distinct risk groups for distant metastasis and/or death (P < 0.0001). Conclusions: Alterations in cancer or normal-appearing nuclei adjacent to peripheral zone cancer areas can predict PCa progression and/or death. The QNG-NN and QNG-CA solutions could be combined with pathology variables to improve the prediction of distant metastasis.

Numerous studies have assessed serum total PSA (tPSA) levels among different races. We extended the serum biomarker profiling using prostate-specific antigen (PSA) derivatives in age-matched screening populations that included white, black, and Korean-American patients. The median ages were 61 years for white and black patients and 63 years for Korean-American patients. Serum samples from 70 men in each ethnic group were analyzed using 3 different tPSA assays (Tosoh AIA 600II, Bayer Immuno-1, Roche Elecsys 2010). The percentage of free PSA (fPSA) was measured directly by Roche Elecsys 2010 immunoassay and then calculated from complexed PSA (cPSA) and tPSA results determined with the Bayer Immuno-1. The percentage of cPSA was determined using cPSA and tPSA assayed by the Immuno-1 method. Statistical analyses included nonparametric Kruskal-Wallis and analysis of variance (ANOVA) evaluations. There were no differences noted in the tPSA values based on ANOVA among the 3 races irrespective of the assay platform methodology employed. Also, the PSA derivatives, percentages of fPSA and cPSA, evaluated using the Kruskal-Wallis test, showed no significant differences for either derivative assayed on 2 different assay platforms among the 3 groups. In a contemporary screening population comparing tPSA, percentage of fPSA, and percentage of cPSA levels in 3 races, there were no significant differences identified among the groups.

BACKGROUND Microscopic histologic grade has been the best predictor of prostate carcinoma (PCa) progression in men after surgical therapy. The ability to predict accurately, at the time of surgery, which patients are likely to develop metastatic PCa would enable optimization of disease management with adjuvant therapy. The authors assessed the ability of pathologic, nuclear morphometric, and chromatin parameters to predict metastatic PCa progression and/or death in 227 men with biochemical recurrence and long-term follow-up after undergoing radical prostatectomy. METHODS Multivariate logistic regression (LR) was used to calculate quantitative nuclear grade (QNG) solutions using the variances of 60 nuclear morphometric descriptors (NMDs) of nuclear size, shape, DNA content, and chromatin organization that predicted distant metastasis and/or PCa-specific death. An LR model also was generated to predict this outcome using a combination of pathologic variables and the best QNG solution. Cox proportional hazards models were generated, and Kaplan–Meier plots were used to display three risk groups based on pathology, QNG, and a combination of these variables. RESULTS A multivariate LR model using pathology retained lymph node (LN) status, seminal vesicle status, and prostatectomy Gleason score, yielding an area under the curve–receiver operator characteristic (AUC-ROC) of 75% with an accuracy of 59% at 90% sensitivity. The best QNG solution used the variance of 25 NMDs, yielding an AUC-ROC of 84% and an accuracy of 70% at 90% sensitivity. The combined pathology-QNG model retained LN status, prostatectomy Gleason score, and QNG, yielding an AUC-ROC of 86% with an accuracy of 76% at 90% sensitivity. The Cox proportional hazards models produced the following significant univariate and multivariate hazard ratios: QNG, 3.5 and 2.9, respectively; LN, 2.7 and 1.8, respectively; and prostatectomy Gleason score, 2.8 and 2.1, respectively. CONCLUSIONS Alterations in the structure of tumor nuclei measured by computer-assisted image analysis were strong predictors of PCa progression and death in men with long-term follow-up who had biochemical recurrence after undergoing radical prostatectomy. QNG solutions can serve as a new supplemental biomarker for accurate prediction of PCa progression at the time of surgery. Cancer 2003;98:2583–91. © 2003 American Cancer Society.

A prospective clinical study was conducted to assess the ability of the DD23 murine monoclonal antibody to enhance detection of bladder cancer in routine alcohol fixed urine cytology samples.Prospectively, 308 bladder cytology specimens were obtained from patients with a history of bladder cancer with a mean age of 71.4+/-11.9 (27% female, 73% male). Data included 121 biopsy-confirmed results and 187 cystoscopy results to assess presence or absence of cancer. Thirty-five normal cytology specimens were obtained from asymptomatic men and women between 55-85 years of age. Separate slides from the alcohol fixed cytology specimens were stained using the Papanicolaou (Pap) and Feulgen staining procedures. The DD23 assay was performed using an avidin-biotin alkaline phosphatase immunocytochemical procedure, with a single urothelial cell exhibiting intense immunostaining sufficient to make a positive call.Pap-Feulgen cytopathology for the 308 cases yielded an overall sensitivity of 65.5% and a specificity of 85.1%, and the DD23 biomarker alone yielded a sensitivity of 80.5% and a specificity of 59.7%. Analysis of the voided urines only (n=164) yielded sensitivities of 61.0% and 73.2% and specificities of 86.2% and 67.5% for cytopathology and DD23 alone, respectively. Results in 49 bladder wash urine cytology cases produced a sensitivity of 70.2% and 100% and specificities of 92.3% and 61.5% for cytopathology and DD23 alone, respectively. In 133 patients that underwent biopsy or had positive cystoscopy results, cytopathology yielded a sensitivity of 65.5% and a specificity of 69.6% while DD23 yielded a sensitivity of 80.5% and a specificity of 58.7%. In 25 biopsy-confirmed low-grade cancers, DD23 improved cancer detection from 32% to 72% when compared to cytopathology. The DD23 biomarker had a specificity of 85.7% in 35 age-matched normal asymptomatic control specimens.The DD23 biomarker is an adjuvant test that provides improved detection of bladder cancer in cytology specimens and enhances the sensitivity of the cytopathology diagnosis, especially in low-grade cancers.

Objectives To determine whether DD23 increases the sensitivity of urinary-based detection of transitional cell carcinoma (TCC) recurrence. The murine monoclonal antibody DD23 recognizes a 185-kDa tumor-associated antigen that is expressed in human bladder cancer cells in vitro and in vivo but is not detected in normal urothelium. Methods Using alcohol-fixed urinary cytology, matched voided urine and bladder wash specimens were evaluated for the contribution of DD23 antigen expression in the detection of recurrent TCC. The selected patient population had a history of bladder cancer, and urine cytology analysis was performed in a single commercial reference laboratory. DD23 antigen expression in a cohort of 81 patients was compared with urine cytology findings, and the sensitivity and specificity for each urine-based test was determined. The presence of recurrent disease was determined by positive pathologic biopsy. Results The 81-patient cohort produced 151 urine specimens for which both biopsy and cytology information were obtained. Of these specimens, 64 were confirmed by a tissue diagnosis for TCC recurrence. These biopsy-proven recurrences were used as the dependent variable to assess the accuracy of cytology testing. For the detection of TCC, the DD23 antigen had a sensitivity of 70.3% and a specificity of 59.8%. Combined with cytopathologic findings, DD23 enhanced the sensitivity for the detection of TCC from 43.8% (cytology alone) to 78.1%. For low-grade TCC (n = 20) DD23 enhanced the sensitivity from 20.0% (cytology alone) to 55.0%. For high-grade TCC (n = 25), DD23 enhanced the sensitivity from 64.0% (cytology alone) to 76.0%. In patients with a prior history of intravesical treatment, DD23 had a sensitivity of 94.7% and a specificity of 33.3% compared with a sensitivity of 52.6% and a specificity of 83.3% for cytology. Conclusions DD23 antigen expression can be used as an adjunct to cytopathologic evaluation to enhance the sensitivity of urinary cytology detection of TCC. In addition, DD23 does not appear to lose sensitivity in patients with a prior history of bladder cancer treated with intravesical agents.

We assessed the impact of age and prostate specific antigen (PSA) on extended systematic biopsy schemes for detecting prostate carcinoma and better characterized these tumors as a function of patient age and PSA.We retrospectively reviewed the records of 2,299 consecutive patients who underwent initial systematic biopsy performed by 167 community based urologists. A total of 12 systematic biopsies of the peripheral zone were obtained in all patients. Various biopsy schemes were then created and cancer detection rates were calculated. Data analyses were stratified by patient age and PSA.On biopsy 1,020 patients (44.4%) had cancer. Detection rates increased with increasing patient age. Increasing age and PSA were associated with larger, higher grade tumors. Overall and unique site specific cancer detection rates were highest for laterally directed biopsies and the apical biopsy of the standard sextant scheme. The 12 site biopsy scheme outperformed all other schemes in patients with PSA 7 ng./ml. or less and in those 60 years or younger. The variation in age related and PSA related detection rates was greatest for the standard sextant scheme and this variability decreased for extended biopsy schemes.This multi-practice community based study confirms the inadequacy of sextant biopsies and emphasizes the need for extended peripheral zone sampling of the lateral aspect of the prostate. Generally increasing patient age and PSA were associated with larger, higher grade tumors. Extended biopsy schemes minimize PSA and age related detection rates.

To examine the nuclear chromatin characteristics of epithelial cells, looking for an SPHB-mediated effect on nuclear DNA structure and organization. Saw palmetto herbal blend (SPHB) causes contraction of prostate epithelial cells and suppression of tissue dihydrotestosterone levels in men with symptomatic benign prostatic hyperplasia, but a fundamental mechanism remains unknown.A 6-month randomized trial, comparing prostatic tissue of men treated with SPHB (n = 20) or placebo (n = 20), was performed. At baseline, the two groups were similar in age (65 versus 64 years), symptoms (International Prostate Symptom Score 18 versus 17), uroflow (maximal urinary flow rate 10 versus 11 mL/s), prostate volume (59 versus 58 cm(3)), prostate-specific antigen (4.2 versus 2.7 ng/mL), and percentage of epithelium (17% versus 16%). Prostatic tissue was obtained by sextant biopsy before and after treatment. Five-micron sections were Feulgen stained and quantitatively analyzed using the AutoCyte QUIC-DNA imaging system. Images were captured from 200 randomly selected epithelial cell nuclei, and 60 nuclear morphometric descriptors (NMDs) (eg, size, shape, DNA content, and textural features) were determined for each nucleus. Logistic regression analysis was used to assess the differences in the variances of the NMDs between the treated and untreated prostate epithelial cells.At baseline, the SPHB and placebo groups had similar NMD values. After 6 months of placebo, no significant change from baseline was found in the NMDs. However, after 6 months of SPHB, 25 of the 60 NMDs were significantly different compared with baseline, and a multivariate model for predicting treatment effect using 4 of the 25 was created (P0.001). The multivariate model had an area under the receiver operating characteristic curve of 94% and an accuracy of 85%.Six months of SPHB treatment appears to alter the DNA chromatin structure and organization in prostate epithelial cells. Thus, a possible molecular basis for tissue changes and therapeutic effect of the compound is suggested.

Refinements in prostate-specific antigen (PSA) through the use of its derivatives have augmented early detection rates of prostate cancer. However, these improvements are coupled with relatively large increases in unit cost per detected cancer. We used decision-analytic modeling to determine the most appropriate PSA derivative for population-based screening. We constructed a decision-analytic model to determine the PSA derivative with the highest cost-benefit ratio for prostate cancer screening. We defined 5 screening strategies: total PSA (tPSA) 4.0 ng/mL; free PSA/tPSA (f/tPSA) in conjunction with tPSA; and complexed PSA (cPSA) 3.8, 3.4, and 3.0 ng/mL. Prostate cancer prevalence, false-positive rates, and false-negative rates for each test strategy were calculated from a database of 2138 men. The direct costs were obtained from literature review and our department of clinical chemistry. The derivative cPSA with a positive threshold of 3.8 ng/mL was the dominant strategy. The average cost of screening was $138.93. The strategy of tPSA became dominant when the cost of cPSA was $35.00 or the cost of a prostate biopsy was $67.30. To match the false-negative rate of tPSA 4.0 ng/mL, a cPSA threshold of 3.0 ng/mL is necessary (sensitivity 92.5%). At this level, the marginal cost increase over tPSA is $9.40. The dominant strategy for populationbased prostate cancer screening is use of cPSA with a positive threshold of 3.8 ng/mL. The use of cPSA with a threshold of 3.0 ng/mL identifies a similar number of cancers with fewer biopsies than tPSA at 4.0 ng/mL. UROLOGY 60 (Suppl 4A): 42‐46, 2002. © 2002, Elsevier Science Inc.

Age-specific prostate-specific antigen (PSA) cutoffs were previously suggested and were found to miss significant cancers in older men. We assessed the influence of an age-adjusted PSA cutoff to optimize the diagnostic performance (sensitivity and specificity) of complexed PSA (cPSA) and total PSA (tPSA) in the differentiation of benign disease from prostate cancer using a contemporary referral patient cohort. The cPSA and tPSA values were determined using the Bayer Immuno 1 system. The diagnostic utility of tPSA and cPSA was assessed using a diverse contemporary test population consisting of sera prospectively collected between June 1999 and October 2000 from 3597 men who recently underwent a systematic biopsy by urologists in clinical practices throughout the United States. This contemporary patient sample had biopsy diagnoses of either no evidence of malignancy (NEM; N = 2189) or prostate cancer (n = 1408). All serum samples had tPSA values between 2.0 and 20.0 ng/mL. The mean tPSAs (ng/mL) for the NEM and prostate cancer groups were 7.1 +/- 3.2 and 7.3 +/- 3.3, respectively (P = 0.026). The mean cPSAs (ng/mL) for the NEM and prostate cancer groups were 5.6 +/- 2.7 and 6.0 +/- 2.9, respectively (P0.001). As the tPSA increased from 2.0 to 10.0 ng/mL, the cancer detection rate remained relatively constant at approximately 39% when evaluated using increments of 2.0 ng/mL for tPSA. For fixed sensitivities of 80%, 85%, 90%, and 95%, as the age range increased (45 to 59, 60 to 69, 70 to 79,or=80), the tPSA and cPSA assay cutoffs required to sustain the specified sensitivity level markedly increased, with the exception of the 95% sensitivity level, where the cutoffs only slightly increased between the age ranges of 45 to 69 andor=70. Overall, cPSA showed a marginal improvement in specificity versus tPSA across all age groups at all sensitivity levels. In this community referral population, the cancer detection rate remained fairly constant over the tPSA range of 2.0 to 20.0 ng/mL. This study demonstrated that to maintain a given sensitivity level for cPSA and tPSA in the age ranges studied, continuous upward adjustment of the cutoffs was required as age increased.

Prostate cancer (PCa) pathologic staging remains a challenge for the physician using individual pretreatment variables. We have previously reported that UroScore, a logistic regression (LR)-derived algorithm, can correctly predict organ-confined (OC) disease state with90% accuracy. This study compares statistical and neural network (NN) approaches to predict PCa stage.A subset (756 of 817) of radical prostatectomy patients was assessed: 434 with OC disease, 173 with capsular penetration (NOC-CP), and 149 with metastases (NOC-AD) in the training sample. Additionally, an OC + NOC-CP (n = 607) vs NOC-AD (n = 149) two-outcome model was prepared. Validation sets included 120 or 397 cases not used for modeling. Input variables included clinical and several quantitative biopsy pathology variables. The classification accuracies achieved with a NN with an error back-propagation architecture were compared with those of LR statistical modeling.We demonstrated95% detection of OC PCa in three-outcome models, using both computational approaches. For training patient samples that were equally distributed for the three-outcome models, NNs gave a significantly higher overall classification accuracy than the LR approach (40% vs 96%, respectively). In the two-outcome models using either unequal or equal case distribution, the NNs had only a marginal advantage in classification accuracy over LR.The strength of a mathematics-based disease-outcome model depends on the quality of the input variables, quantity of cases, case sample input distribution, and computational methods of data processing of inputs and outputs. We identified specific advantages for NNs, especially in the prediction of multiple-outcome models, related to the ability to pre- and postprocess inputs and outputs.

We developed an algorithm for predicting the likelihood of organ confined disease in patients with clinical stage T1c prostate cancer using biopsy pathology, computer assisted image analysis and serum prostate specific antigen (PSA).Of the 557 consecutive men enrolled in this study between October 1998 and January 2000 scheduled for radical prostatectomy at a single institution 386 (69%) presented with clinical stage T1c disease. Study exclusion criteria included neoadjuvant hormonal treatment with luteinizing hormone-releasing hormone, antiandrogen or 5alpha-reductase inhibitors. Preoperative serum, biopsy histology slides, clinical demographic information, prostatectomy pathology and prostate weight data were obtained. Biomarkers assessed included total PSA, complexed PSA, free PSA, the free-to-total PSA ratio, quantitative nuclear grade determined by image analysis, complexed PSA density, and biopsy Gleason grade and score. To determine patient specific quantitative nuclear grade values, images from approximately 125 cancer nuclei were captured per patient from the area of the biopsy section with the highest Gleason score. The variance in 60 nuclear size, shape and chromatin texture descriptors was calculated for each gallery of nuclei. Logistic regression was done to determine the most accurate combination of variables for predicting organ confined prostate cancer.Complete results and data were available on 255 of the 386 men (66%) with an average age plus or minus standard deviation of 58.8 +/- 6 years who had stage T1c disease, including 49 (19%) with pathologically nonorgan confined disease. Logistic regression analysis revealed that quantitative nuclear grade, biopsy Gleason score, total PSA, the calculated free-to-total PSA ratio, complexed PSA and complexed PSA density were univariately significant for predicting organ confined disease (p0.05). On backward stepwise logistic regression only quantitative nuclear grade, complexed PSA density and Gleason score remained in a model yielding an area under the receiver operating characteristics curve of 82.4%.The quantitative nuclear grade biomarker was the strongest independent predictor of pathological stage in men with clinical stage T1c prostate cancer when combined with biopsy Gleason score and complexed PSA density data.

Background: Epithelial-mesenchymal transition (EMT) is associated with metastasis in human prostate cancer (PCa). As metastatic tumors are the major cause of death in most cancer patients, identifying instances of EMT in patients may serve as a good prognostic indicator of progressive disease. Abnormal morphologic deformation of the cell nucleus is strongly associated with an aggressive cancer phenotype and computer-aided quantitative nuclear morphometry (QNM) has been used to quantify this deformation. In the present study, we go further to investigate the association of nuclear morphologic features between an epithelial PCa phenotype and an EMT-induced mesenchymal PCa phenotype across a panel of extracellular matrix (ECM) substrates on which cells are grown in vitro. Methods: PC3 epithelial cells (PC3-Epi) are established human PCa cultures from bone metastatic lesions. M2 macrophages induced PC3-Epi cells to undergo EMT and become mesenchymal PC3 cells (PC3- EMT). PC3-Epi and PC3-EMT cells were cultured independently on glass tissue-culture slides and also on a panel of ECM component substrates, including collagen 1, poly-D-Lysine, and various molecular weight hyaluronic acid polymers. Slides were stained with Feulgen or hematoxylin and eosin (H&E). The images were digitized with a slide-scanning microscope. Computer aided image processing software measured a total of 41 non-redundant features. This included nuclear size, shape, and texture features. Features were statistically analyzed using both supervised and unsupervised machine learning algorithms. Results: Statistical classification between PC3-Epi and PC3-EMT was performed on a panel of ECM substrates. The PC3-Epi and PC3-EMT morphological features were characterized by the type of ECM substrate on which cells were cultured. Chromatin texture and shape features, such as Feret diameter, were among the most significant in contributing to separation of the PC3-Epi and PC3-EMT. In contrast, the morphological features could not be separated when cells were grown on glass surfaces. Conclusions: The PC3-Epi and PC3-EMT cells were statistically separated more effectively with extracellular matrix substrates than with glass. Furthermore, our findings suggest that ECM components affect chromatin texture, a function of chromatin organization, and nuclear morphology. Our results also indicate quantitative nuclear morphometric analysis may be a viable tool for demonstrating instances of EMT in clinical samples, potentially adding quantitative prognostic value to this technique. Nuclear morphometric factors, such as those used here, have also found applications to distinguish aggressive human prostate cancers in fixed biopsy samples (See review: Veltri, R.W., et al. “Nuclear morphometry, nucleomics and prostate cancer progression”. Asian Journal of Andrology (2012) 14, 375-384.) Citation Format: James E. Verdone, Robert W. Veltri, Steven M. Mooney, James R. Hernandez, Calvin A. Harberg, Donald S. Coffey, Kenneth J. Pienta. Extracellular matrix components direct chromatin texture and nuclear morphological changes in epithelial-mesenchymal transition. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1139. doi:10.1158/1538-7445.AM2014-1139

Introduction and Objective: This study was designed to develop an integrated, quantitative histomorphometric and molecular biomarker-based predictor for prostate cancer (PCa) progression based on a tissue microarray (TMA) useful for small volume active surveillance biopsies. Methods: Two TMAs with 80 PCa cases of different Gleason scores were used and each PCa case includes quadruplicates of cancer and cancer-adjacent benign areas. Also, 25% of the 80 cases had recurrence. Multiplex Tissue Immunoblotting (MTI) was used to detect and pre-qualify the expression of five biomarkers on a single 5 micron section: CACNA1D, Periostin, Her2/neu, EZH2 and (-7)ProPSA. Immunofluorescence was determined using excitation at 633 nm which produced the Cy5 fluorescence, while excitation at 488 nm produced FITC fluorescence for the biomarkers. The scanned images were analyzed using ImageQuant 5.2 software and the final data was normalized by total protein for each biomarker. The results were graphically and statistically analyzed to study the relationship with PCa grades and recurrence risk. The same approach was applied to active surveillance biopsies. RESULTS: The biomarkers showed that for CACNA1D, an epithelial expressed Ca++ transporter glycoprotein biomarker, demonstrated a decrease with increasing Gleason score in both cancer and benign areas. The ROC (Receiver Operating Characteristic) curve showed a continuous increase in the AUC (Area Under the Curve) and statistical analysis also showed clear difference by comparing group of Gleason score 3+3 with 8 and above. The expression of Periostin, a stromal glycoprotein biomarker indicated a decrease with increasing Gleason score from 3+3 to 3+4 and 4+3, but the expression rebounded in Gleason score 8 and above. A field effect was shown in benign cancer-adjacent area of prostate tissues for most biomarkers. (-7)ProPSA, an epithelial biomarker shown to be significantly elevated with increasing Gleason score in PCa, which was supported by the AUC-ROC in both cancer and benign area. Applying Logistic Regression analysis, CACNA1D and Her2/neu biomarkers predicted recurrence yielding a 0.87 AUC-ROC. Additionally, (-7)ProPSA, Her2/neu, CACNA1D and Periostin separated Gleason score up to 7.0 vs. above 7.0 with a AUC 0.97. CONCLUSIONS: Our results suggest that several molecular biomarkers may be useful to predict a PCa aggressive phenotype (i.e. CACNA1D, Periostin, Her2/neu, and (-7)ProPSA). Further, this MTI tool is currently being used to characterize aggressive PCa of active surveillance patients. Citation Format: Zhi Liu, Christhunesa Christudass, Hui Zhang, Joon-Yong Chung, Stephen Hewitt, Jonathan Epstein, Robert W. Veltri. A novel quantitative histomorphological tool to assess multiple biomarkers to predict prostate cancer aggression. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4013. doi:10.1158/1538-7445.AM2014-4013

Standardized processes should be used in the identification and development of intermediate endpoint biomarkers (IEB) for the prediction of patient-specific disease outcomes. Using our own experiences, we outline some of our standardized processes. Using computer-assisted image analysis, we developed a new biomarker of genetic instability, termed quantitative nuclear grade (QNG). The QNG biomarker is derived using nuclear images analyzed from the tumor areas of Feulgen-stained 5-μm biopsy or radical prostatectomy tissue sections. From the variances of 41 to 60 different nuclear size, shape, and chromatin organization features, a QNG solution is computed using either logistic regression or artificial neural networks. QNG can then be used as an input for models that solve for a patient-specific probability to accurately predict disease outcomes. Preoperatively, QNG predicted both the pathologic stage and progression of prostate cancer using biopsies (P

Objectives. To use pathologic, morphometric, DNA ploidy, and clinical data to develop and test a genetically engineered neural network (GENN) for the prediction of biochemical (prostate-specific antigen [PSA]) progression after radical prostatectomy in a select group of men with clinically localized prostate cancer. Methods. Two hundred fourteen men who underwent anatomic radical retropubic prostatectomy for clinically localized prostate cancer were selected on the basis of adequate follow-up, pathologic criteria indicating an intermediate risk of progression, and availability of archival tissue. The median age was 58.9 years (range 40 to 87). Men with Gleason score 5 to 7 and clinical Stage T1b-T2c tumors were included. Follow-up was a median of 9.5 years. Three GENNs were developed using pathologic findings (Gleason score, extraprostatic extension, surgical margin status), age, quantitative nuclear grade (QNG), and DNA ploidy. These networks were developed using three randomly selected training (n 5 136) and testing (n 5 35) sets. Different variable subsets were compared for the ability to maximize prediction of progression. Both standard logistic regression and Cox regression analyses were used concurrently to calculate progression risk. Results. Biochemical (PSA) progression occurred in 84 men (40%), with a median time to progression of 48 months (range 1 to 168). GENN models were trained using inputs consisting of (a) pathologic features and patient age; (b) QNG and DNA ploidy; and (c) all variables combined. These GENN models achieved an average accuracy of 74.4%, 63.1%, and 73.5%, respectively, for the prediction of progression in the training sets. In the testing sets, the three GENN models had an accuracy of 74.3%, 80.0%, and 78.1%, respectively. Conclusions. The GENN models developed show promise in predicting progression in select groups of men after radical prostatectomy. Neural networks using QNG and DNA ploidy as input variables performed as well as networks using Gleason score and staging information. All GENN models were superior to logistic regression modeling and to Cox regression analysis in prediction of PSA progression. The development of models using improved input variables and imaging systems in larger, well-characterized patient groups with long-term follow-up is ongoing. UROLOGY 54: 791‐795, 1999. © 1999, Elsevier Science Inc.

Objectives. To evaluate pathology trends of 62,537 first-time prostate needle-core biopsies submitted by office-based urologists, processed at a single pathology laboratory. Methods. Prostate biopsy cases obtained over a 2-year period were assessed. Patient information included age, digital rectal examination (DRE) status, and prostate-specific antigen (PSA) serum levels. Biopsy pathology results included the number of tissue samples per case, Gleason score, presence of Gleason grades 4 or 5, percent of biopsy length with evidence of cancer, number of samples with cancer per biopsy, and determination of DNA ploidy status using microspectrophotometry. Results. Adenocarcinoma, suspicious lesions, and isolated high-grade prostatic intraepithelial neoplasia (PIN) were diagnosed in 38.3%, 2.9%, and 4.1% of the biopsies, respectively. For each serum PSA and age range assessed, the positive biopsy rate and incidence of critical pathologic features increased consistently. The average percentage of biopsy length with evidence of tumor, the percentage of cases with Gleason grades 4 or 5, and the percentage of cases with an abnormal DNA ploidy all decreased significantly over the 2-year period ( P Conclusions. The number of tissue cores and anatomic sites (locations) being sampled per biopsy are increasing. The tumor size detected and percentage of cases with Gleason grades 4 and 5 are decreasing. There has been a slight increase in the number of biopsies performed on men younger than 60 years of age and a slight decrease in biopsies performed on men older than 70 years of age. The decline in meaningful pathologic features observed in biopsies over time may be clinically relevant to improved disease management.

Prostate cancer clinical staging methods and decision support tools were reviewed to assess their accuracy to predict pathological staging results and determine what comprises an appropriate clinical staging evaluation.The MEDLINE data base was searched and 238 abstracts were obtained. Data were extracted from 142 articles that evaluated the preoperative accuracy of digital rectal examination, prostate specific antigen, prostatic acid phosphatase, systematic biopsy parameters (including Gleason scoring), seminal vesicle biopsy, various imaging studies and pelvic lymphadenectomy versus pathological staging results. The sensitivity, specificity and accuracy rates were calculated and tabulated from the reported data on each method or decision support tools for organ confined, nonorgan confined and lymph node metastatic tumor.Decision support tools based on logistic regression analysis, which combine several statistically independent staging parameters, had greater accuracy than any single clinical staging method alone. The most accurate decision support tools for clinical staging combined digital rectal examination (T stage), systematic biopsy parameters (including Gleason scoring) and prostate specific antigen.The components that comprise the most accurate decision support tools for clinical staging represent an appropriate staging evaluation for the newly diagnosed prostate cancer patient in 1997. Limited use of radiographic imaging and seminal vesicle biopsy may be indicated in select patients to detect bone metastases, and plan pelvic lymphadenectomy and surgical therapy.

Introduction and Objective: Although Paclitaxel has demonstrated antitumor activity against several cancers, the acquisition of resistance during treatment remains a significant problem. Several potential mechanisms were proposed and the recent studies determined that drug resistance may involve histone H3 acetylation. Histone deacetylases (HDACs) are overexpressed in prostate cancer (PCa) and HDAC inhibitors have greater anti-proliferative activity against prostate and breast cancer models. We have investigated the interaction of the HDAC inhibitors Valproic Acid (VPA) and SAHA (Vorinostat) with Paclitaxel in both susceptible and resistance PCa cell lines. We evaluated anti-proliferative activity, nuclear morphometry, expression of apoptotic genes: Caspases 3 and 9 and Annexin A5, and three keratins (8, 18 and 19) which are involved in cell differentiation. Methods: Four PCa cell lines PC3, PC3-TxR (Paclitaxel resistant), DU145 and DU145-TxR (Paclitaxel resistant) were grown in 96 well & 24 well tissue culture plates. After a day, the cells were exposed to 1.2mM of VPA and 5μM of SAHA for 24 hours followed by treatment with 4.5nM Paclitaxel for 48 hours. WST-1 cytotoxicity assay was performed in the 96 well plates. From the 24 well plates, RNA was isolated and the real-time PCR for expression of specific genes was done using gene specific primers and β-actin (to calculate relative expression). Nuclear morphometry was done in Feulgen stained nuclei using AutoCyteTM Pathology Workstation and QUIC-DNA software. Results: We found after 24hrs treatment: (i) VPA (1.2mM) reversed Paclitaxel resistance only in PC3 cell lines (50%) while (ii) SAHA made all the PCa cell lines more susceptible to Paclitaxel (50-60%). We observed specific changes in DNA ploidy and in nuclear structure in Paclitaxel resistant DU145-TxR cell lines when compared to DU145 cells. Our results showed different patterns of apoptotic and keratin gene expression occurred in DU145 and DU145-TxR cell lines following treatment with SAHA but no significant changes in PC3 and PC3-TxR cell lines. Expressions of Caspase 3, Caspase 9 and Annexin A5 were increased significantly in SAHA treated DU145-TxR cells, and KRT-8 and KRT-19 (keratins) were significantly downregulated in DU145-TxR cell lines irrespective of treatment. Conclusions: Hence, resistance to Paclitaxel can be rescued by HDAC inhibitors VPA and SAHA, but likely by different mechanisms that are yet to be established. Also, altered expression of apoptotic biomarkers, but not keratins shows that the rescue by SAHA involves apoptosis but not epithelial mesenchymal transition. Source of funding: National Cancer Institute of the National Institutes of Health through awards funded under Grant number 1U54CA143868-03 Citation Format: Christhunesa S. Christudass, Karan Sood, David Yeater, Robert W. Veltri. Paclitaxel resistance in prostate cancer: rescue of resistance using HDAC inhibitor SAHA involves apoptosis. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 979. doi:10.1158/1538-7445.AM2013-979

Introduction and Objective: Historically an impressive response to chemotherapy for metastatic testicular cancer is in stark contrast to the dismal results with metastatic pancreatic cancers. Based on our hypothesis that nuclear chromatin structure plays a key role in determining the aggressiveness and the curability of cancer, and the chromatin regulatory proteins alter nuclear structure and hence may be differentially expressed between curable and incurable cancers, we have studied several of these proteins in Tera-1 & Tera-2 (from metastatic testicular carcinoma) and in PANC-1 & CAPAN-1 (from metastatic pancreatic cancer) cell lines.- The nuclear protein targets are SATB1 (special AT-rich sequence-binding protein-1), HP1 (Heterochromatin Protein 1), NUMA (nuclear mitotic apparatus protein), Transcriptional repressor CTCF (11-zinc finger protein), Lamin A/C, Lamin B, and High-mobility group AT-hook 1 (HMGA1). Methods: The cell lines were grown in 4-well chamber slides coated with poly- L-lysine (BD, USA) using specific media. After fixing the cells with acetone: methanol (1:1), immunocytochemistry was done using specific commercial antibodies, biotinylated secondary antibody, Avidin/Biotinylated Complex system and Vector red dye. Some proteins were not done in Tera-1 cell lines since we had some problems in culturing them. Nuclear morphometry was quantified using Feulgen stained nuclei captured by the AutoCyte Pathology Workstation which calculated - features of shape, size, DNA content and texture. Results: The nuclear chromatin protein expressions of CTCF, HP1, HMGA1 and NuMA were determined as moderate (2+) to strong (3-4+) in pancreatic cell lines, but were weak (≤1+) to no expression in testicular cancer cell lines. For Lamin A/C, though no significant difference between the cell lines occurred, in the testicular cells the expression was confined to nucleus whereas in pancreatic cells staining was both nuclear and cytoplasmic. The expression of Lamin B did not differ between cell lines and no expression of SAT B1 was found in the cell lines. The nuclear morphometry features showed significant difference in DNA content and size & shape factors between pancreatic and testicular cell lines. Conclusions: Our preliminary results indicate that the differential expression of nuclear chromatin regulatory proteins may play an important role in responsiveness to treatment and might offer new targets for study. Further, measurement of nuclear structure support alterations in nuclear shape and DNA content commensurate with these nuclear protein studies. Funding: National Cancer Institute of the National Institutes of Health through awards funded under Grant number 1U54CA143803-03. Citation Format: Robert W. Veltri, Christhunesa S. Christudass, Sneha Vivekanandhan, David Yeater, Donald S. Coffey. Chromatin regulatory nuclear proteins and nuclear architecture in cell lines derived from curable and incurable metastatic human cancers. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 411. doi:10.1158/1538-7445.AM2013-411

Purpose Schistosoma haematobium is associated with chronic bladder damage and may subsequently induce bladder cancer in humans, thus posing a serious threat where the parasite is endemic. Here we evaluated aberrant promoter DNA methylation as a potential biomarker to detect severe bladder damage that is associated with schistosomiasis by analyzing urine specimens. Materials and Methods A quantitative methylation-specific PCR (QMSP) assay was used to examine the methylation status of seven genes (RASSF1A, RARβ2, RUNX3, TIMP3, MGMT, P16, ARF) in 57 urine samples obtained from volunteers that include infected and uninfected by S. haematobium from an endemic region. The Fishers Exact Test and Logistic Regression analysis were used to evaluate the methylation status with bladder damage (as assessed by ultrasound examination) in subjects with S. haematobium infection. Results RASSF1A and TIMP3 were significant to predict severe bladder damage both in univariate (p = 0.015 and 0.023 respectively) and in multivariate (p = 0.022 and 0.032 respectively) logistic regression analysis. Area under the receiver operator characteristic curves (AUC-ROC) for RASSF1A and TIMP3 to predict severe bladder damage were 67.84% and 63.73% respectively. The combined model, which used both RASSF1A and TIMP3 promoter methylation, resulted in significant increase in AUC-ROC compared to that of TIMP3 (77.55% vs. 63.73%.29; p = 0.023). Conclusions In this pilot study, we showed that aberrant promoter methylation of RASSF1A and TIMP3 are present in urine sediments of patients with severe bladder damage associated with S. haematobium infection and that may be used to develop non-invasive biomarker of S. haematobium exposure and early molecular risk assessmentof neoplastic transformation.

Objectives Ratios of free to total prostate-specific antigen (f/t PSA ratio) improved differentiation of benign prostatic hyperplasia (BPH) from prostate cancer (CaP). Using sera obtained at least 1 month prior to biopsyconfirmed diagnosis and logistic regression adjusted for disease prevalence, probability curves are constructed to predict the presence of CaP. Methods The patient population included 122 (44%) BPH sera and 155 (56%) prostate carcinoma sera collected prior to any therapy. The total PSA range = 2.0–20.0 ng/mL; median age = 69 years. External reference standards for both free and total PSA assays were used to standardize the assays and correct the ratio. Probability curves and tables for cancer incidence were formulated for a subset of the total test population (total PSA range = 2.0–10.0 ng/mL; 98 BPH, 118 CaP patients) by using logistic regression and prior cancer prevalence statistics derived from a published patient screening study. Results Median f/t PSA ratios were 0.18 and 0.12 in the overall sample and 0.19 and 0.12 in the subset for BPH and CaP, respectively (P = 0.0001). The median total PSA concentrations for BPH and CaP were 5.8 and 6.7 ng/mL when total PSA range = 2.0–20.0 ng/mL and were 4.9 and 5.9 ng/mL when total PSA range = 2.0–10.0, respectively. Conclusions Cancer probability curves were constructed to help guide decisions concerning biopsy and other aspects of prostate cancer disease management. Further validation of this approach in another series of patients is necessary and is planned.

Objectives To investigate the abundance of chondroitin sulfate proteoglycans at the bladder lumenal and subepithelial surfaces in bladder biopsies derived from patients with interstitial cystitis (IC) and controls. Methods Tissue sections derived from biopsies from 31 IC patients and 24 pathologically normal control sections were labeled for proteoglycans using the 2B6 anti-“stub” antibody and detected by immunohis tochemistry. Results On the lumenal surface, 5 of 31 (19%) IC sections were positive for proteoglycans versus 14 of 24 (58%) control sections ( P = 0.00011). At the basal surface, 5 of 19 IC patients were positive versus 7 of 12 controls ( P = 0.032). Conclusions A deficit of bladder lumenal and basal proteoglycans is associated with IC. The deficit in basal layer proteoglycans suggests an altered urothelial differentiation program. The lumenal deficit suggests that the charge-dependent exclusion of ions from the bladder surface is compromised in IC.

It is controversial whether neuroendocrine (NE) differentiation in adenocarcinoma of the prostate is associated with more aggressive behavior. Most studies included patients with tumors of a wide range of grades and stages and an end point of disease-specific survival, a relatively insensitive marker of progression. The authors studied completely embedded radical prostatectomy specimens from 104 patients with clinically organ-confined carcinoma and no history of adjuvant or neoadjuvant therapy. Progression was marked by a serum prostate-specific antigen (PSA) concentration greater than or equal to 0.2 ng/mL. Seventy-six men did not progress, with a mean follow-up period of 8.0 years (range = 7 to 10 years). Forty-eight men progressed at a mean time after surgery of 3.6 years (range = 1 to 8 years). Twenty-one percent of the tumors were organ confined: 79% had capsular penetration. Seminal vesicles and lymph nodes were negative in all cases. A representative section through the main tumor mass was stained for chromogranin A. Reactive neoplastic cells were counted subjectively as well as individually enumerated. Gleason grade, pathological stage, and degree of NE differentiation all correlated with progression. Only grade and extent of NE differentiation predicted progression in a multivariate analysis. NE differentiation did not correlate with stage or grade. Extent of NE differentiation separated patients (59 cases) with tumors of Gleason sum less than or equal to 6 into groups with high and low risks for progression (P.008) independent of Gleason sum. Extent of NE differentiation provides prognostic information in addition to that provided by grade in cases of early prostate cancer treated by radical prostatectomy.

Long-term primary cultures of epithelial cells from rainbow trout (Oncorhynchus mykiss) liver have been established. Nearly homogenous (>97%) populations of hepatocytes were placed into primary culture and remained viable and proliferative for at least 70 d. In addition to hepatocytes, proliferative biliary cells persisted in the cultures for at least 30 d. Finally, a third type of epithelial cell, which we have termed a “spindle cell,” consistently appeared and proliferated to confluence in these cultures. The confluent cultures of spindle cells were successfully subcultured and passaged. The initial behavior, growth, and optimization of serum and media requirements for these cells is described. All three cell types proliferated as measured by thymidine incorporation, autoradiography, proliferating cellular nuclear antigen analysis, and propidium iodine staining. Further efforts to characterize the cells included western blotting and immunohistochemical staining with antibodies to cytokeratins previously reported in fish liver. From these data, it appears that all three cell populations are epithelial in nature. Furthermore, significant changes in actin organization, often indicative of transformation or pluripotent cells, were observed with increased time in primary culture.

Introduction and Objective: Our laboratory has identified several expressed sequence tags (ESTs) from primary prostate cancer (PCa) Stage T2b tissue and five were identified as Prostate and breast cancer overexpressed 1 (PBOV1), Calcium channel, voltage-dependent, l type, alpha 1d subunit (CACNA1D), Tomoregulin-1 (TMEFF1), and Copine-1 & 4 (CPNE1 & CPNE 4). PBOV1 gene is overexpressed in prostate, breast and bladder cancers and CACNA1D exists in several isoforms but little is known about their role in cancer biology. TMEFF1 is predominantly expressed in the brain and is also a cancer testes antigen. The Copines are a novel family of ubiquitous Ca2+-dependent, phospholipid-binding proteins and there is very little known about their role in cancer etiopathogenesis. We have studied their expression in cancerous and benign cancer adjacent areas of radical prostatectomy specimens as well as their protein levels in PCa, BPH and normal prostate cell lines. Methods: Nineteen sets of RNA samples, extracted from PCa tissues and respective benign adjacent areas were received from Dr. DeMarzo. From 50ng of RNA, cDNA was generated and the real-time PCR for expression was done using SsoFast EvaGreen supermix kit in an iCycler instrument (BioRad Laboratories) utilizing the gene specific primers. For calculating relative expression, a portion of β-actin was also amplified using a validated primer set (OriGene). Alongside cell lines of PCa (PC3, DU145 & LNCaP); of Benign prostatic hyperplasia (BPH) and of normal prostate (PrEC) were grown in cultures and total protein was extracted from each. Using specific antibodies, the presence of these proteins were identified by Western blotting. Results: When compared to the corresponding benign adjacent areas, the expression increased significantly in cancer tissues of: 12 samples for PBOV1, 14 samples for CACNA1D, 7 samples for TMEFF1, 9 samples for CPNE1 and 13 samples for CPNE4. Also, preliminary proteomic data by Western blotting in cell line extracts also demonstrates differential expression in PCa and control cell lines: PBOV1 was expressed in PC3, DU145 & BPH; TMEFF1 in PC3 & DU145 (not tested in BPH & PrEC); CACNA1D in PC3, DU145 & LNCaP; CPNE1 in BPH & PrEC and CPNE4 in none of the cell lines. Conclusions: The increased expression of these novel biomarkers in cancer areas vs. the benign cancer-adjacent may be very useful in establishing significant ratios and cut-off values to determine their potential clinical applications. Currently we continue correlating these altered expressions with Gleason grades, stages and other outcomes using a larger sample size. We also continue to study the role of these biomarkers in the pathogenesis of more aggressive prostate cancer phenotypes. Source of Funding: NIH U54CA143803 grant, Prostate Cancer Foundation and the Patana Fund Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3640. doi:1538-7445.AM2012-3640

Introduction: We used two novel computer-assisted imaging applications that incorporate nuclear shape and texture analysis to differentiate Gleason grade patterns 3 and 4 of H&Ein a tissue microarray (TMA). The two approaches utilized a variational adaptive segmentation scheme (AdACM) (Rutgers) and the cardinal multiridgelet transform (CMRT) based texture analysis (University of Pittsburgh). Methods: The TMA include 0.6 mm cores from blocks that included Gleason patterns of CaP radical prostatectomy cases from 40 patients. The TMA comprised 13 Gleason patterns 6 (3+3), 8 pattern 7 (3+4), 7 pattern 8 (4+4) and 5 pattern 9 (4+5) Gleason grade (GG) patterns. The AdACM uses 200 × 200 pixel images extracted for nuclear & architectural textural features. All features were based on mathematical energy terms with a shape prior in a multi-level set formulation. The CMRT is an image transform that is translation- and rotation-invariant, and provides a means of displaying texture contents for selection of discriminative features. With a 3-scale decomposition, it gives 8 ridgelet packets and 16 statistical texture features in a 256 x 256 pixel image patch that are averaged over 9 non-overlapping patches in a given image for separation of GG patterns 3 and 4. Results: The CMRT study utilized 3 of 16 texture features extracted from images and trained a Gaussian kernel support vector machine (SVM), a leave-one-out cross-validation showed an accuracy of 94% and AUC of 0.97. For AdACM, nuclear features and architectural features were extracted. Linear Discriminant Analysis (LDA) was employed for feature selection and best features from all three classes could discriminate Gleason grade 3 vs. 4 with an accuracy of 86% via a SVM classifier. Conclusions: Unique quantitative imaging of tissue nuclear shape and texture features can accurately differentiate Gleason patterns 3 and 4. Our research will next evaluate CaP outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4061. doi:1538-7445.AM2012-4061

We report the performances of cancer cell classification by using supervised and unsupervised learning techniques. A single hidden layer feedforward NN with error back-propagation training is adopted for supervised learning, and c-means clustering methods, fuzzy and nonfuzzy, are used for unsupervised learning. Network configurations with various activation functions, namely sigmoid, sinusoid and gaussian, are studied. A set of features, including cell size, average intensity, texture, shape factor and pgDNA are selected as the input for the network. These features, in particular the texture information, are shown to be very effective in capturing the discriminate information in cancer cells. It is found, based on the data from 467 cell images from six cases, the neural network approach achieves a classification rate of 96.9% while fuzzy c-means scores 76.5%. >