DNA Ploidy as surrogate for biopsy gleason score for preoperative organ versus nonorgan-confined prostate cancer prediction

Quantification of large scale DNA organization for predicting prostate cancer recurrence

This study investigates whether Genomic Organization at Large Scales (which we propose to call GOALS) as quantified via nuclear phenotype characteristics and cell sociology features (describing cell organization within tissue) collected from prostate tissue microarrays (TMAs) can separate biochemical failure from biochemical nonevidence of disease (BNED) after radical prostatectomy (RP). Of the 78 prostate cancer tissue cores collected from patients treated with RP, 16 who developed biochemical relapse (failure group) and 16 who were BNED patients (nonfailure group) were included in the analyses (36 cores from 32 patients). A section from this TMA was stained stoichiometrically for DNA using the Feulgen-Thionin methodology, and scanned with a Pannoramic MIDI scanner. Approximately 110 nuclear phenotypic features, predominately quantifying large scale DNA organization (GOALS), were extracted from each segmented nuclei. In addition, the centers of these segmented nuclei defined a Voronoi tessellation and subsequent architectural analysis. Prostate TMA core classification as biochemical failure or BNED after RP using GOALS features was conducted (a) based on cell type and cell position within the epithelium (all cells, all epithelial cells, epithelial >2 cell layers away from basement membrane) from all cores, and (b) based on epithelial cells more than two cell layers from the basement membrane using a Classifier trained on Gleason 6, 8, 9 (16 cores) only and applied to a Test set consisting of the Gleason 7 cores (20 cores). Successful core classification as biochemical failure or BNED after RP by a linear classifier was 75% using all cells, 83% using all epithelial cells, and 86% using epithelial >2 layers. Overall success of predicted classification by the linear Classifier of (b) was 87.5% using the Training Set and 80% using the Test Set. Overall success of predicted progression using Gleason score alone was 75% for Gleason >7 as failures and 69% for Gleason >6 as failures. © 2017 International Society for Advancement of Cytometry.

Biomarkers in prostate cancer - Current clinical utility and future perspectives

Current tendencies in the treatment course of prostate cancer patients increase the need for reliable biomarkers that help in decision-making in a challenging clinical setting. Within the last decade, several novel biomarkers have been introduced. In the following comprehensive review article, we focus on diagnostic (PHI^®, 4K score, SelectMDx^®, ConfirmMDx^®, PCA3, MiPS, ExoDX^®, mpMRI) and prognostic (OncotypeDX GPS^®, Prolaris^®, ProMark^®, DNA-ploidy, Decipher^®) biomarkers that are in widespread clinical use and are supported by evidence. Hereby, we focus on multiple clinical situations in which innovative biomarkers may guide decision-making in prostate cancer therapy. In addition, we describe novel liquid biopsy approaches (circulating tumor cells, cell-free DNA) that have been described as predictive biomarkers in metastatic castration-resistant prostate cancer and might support an individual patient-centred oncological approach in the nearer future.

Revisiting tumour aneuploidy - the place of ploidy assessment in the molecular era

Chromosome instability (CIN) is gaining increasing interest as a central process in cancer. CIN, either past or present, is indicated whenever tumour cells harbour an abnormal quantity of DNA, termed 'aneuploidy'. At present, the most widely used approach to detecting aneuploidy is DNA cytometry - a well-known research assay that involves staining of DNA in the nuclei of cells from a tissue sample, followed by analysis using quantitative flow cytometry or microscopic imaging. Aneuploidy in cancer tissue has been implicated as a predictor of a poor prognosis. In this Review, we have explored this hypothesis by surveying the current landscape of peer-reviewed research in which DNA cytometry has been applied in studies with disease-appropriate clinical follow up. This area of research is broad, however, and we restricted our survey to results published since 2000 relating to seven common epithelial cancers (those of the breast; endometrium, ovary, and uterine cervix; oesophagus; colon and rectum; lung; prostate; and bladder). We placed particular emphasis on results from multivariate analyses to pinpoint situations in which the prognostic value of aneuploidy as a biomarker is strong compared with that of existing indicators, such as clinical stage, histological grade, and specific molecular markers. We summarize the implications of our findings for the prognostic use of ploidy analysis in the clinic and for the theoretical understanding of the role of CIN in carcinogenesis.

Prognostic prostate tissue biomarkers of potential clinical use

In prostate biopsies and in prostatectomy specimens, the Gleason score remains the strongest prognosticator of prostate cancer progression, in addition to serum PSA level and DRE findings, in spite of numerous potential biomarkers discovered during the last few decades. Inter- and intratumoural heterogeneity may have limited the employment of tissue biomarkers on prostate biopsies. Nevertheless, the monoclonality of morphologically heterogeneous (Gleason score 7) tumour foci would suggest that genetic biomarkers, arising early in prostate carcinogenesis, may overcome issues related to intratumoural heterogeneity. In spite of the above limitations, a few biomarkers including the proliferation marker Ki-67 and genetic markers such as c-MYC and PTEN have consistently shown their independent prognostic impact both for biochemical recurrence and for clinical outcome parameters such as metastatic disease or prostate-specific mortality. The routine application of biomarkers requiring immunostaining (e.g. Ki-67) has particularly been hindered by the lack of standardized protocols for processing and scoring, while the application of fluorescence in situ hybridization (FISH) technology is considered more labour intensive but better standardized. Future steps to enhance the uptake of prostate tissue biomarkers should be focused on prospective studies, particularly on prostate biopsy specimens, using protocols that are highly standardized for the processing and scoring of the biomarkers. A few recently developed RNA-based test signatures may provide an alternative to FISH or immunohistochemistry-based tests.

DNA ploidy measured on archived pretreatment biopsy material may correlate with prostate-specific antigen recurrence after prostate brachytherapy

PURPOSE

To explore whether DNA ploidy of prostate cancer cells determined from archived transrectal ultrasound-guided biopsy specimens correlates with disease-free survival.

METHODS AND MATERIALS

Forty-seven failures and 47 controls were selected from 1006 consecutive low- and intermediate-risk patients treated with prostate (125)I brachytherapy (July 1998-October 2003). Median follow-up was 7.5 years. Ten-year actuarial disease-free survival was 94.1%. Controls were matched using age, initial prostate-specific antigen level, clinical stage, Gleason score, use of hormone therapy, and follow-up (all P nonsignificant). Seventy-eight specimens were successfully processed; 27 control and 20 failure specimens contained more than 100 tumor cells were used for the final analysis. The Feulgen-Thionin stained cytology samples from archived paraffin blocks were used to determine the DNA ploidy of each tumor by measuring integrated optical densities.

RESULTS

The samples were divided into diploid and aneuploid tumors. Aneuploid tumors were found in 16 of 20 of the failures (80%) and 8 of 27 controls (30%). Diploid DNA patients had a significantly lower rate of disease recurrence (P=.0086) (hazard ratio [HR] 0.256). On multivariable analysis, patients with aneuploid tumors had a higher prostate-specific antigen failure rate (HR 5.13). Additionally, those with "excellent" dosimetry (V100 >90%; D90 >144 Gy) had a significantly lower recurrence rate (HR 0.25). All patients with aneuploid tumors and dosimetry classified as "nonexcellent" (V100 <90%; D90 <144 Gy) (5 of 5) had disease recurrence, compared with 40% of patients with aneuploid tumors and "excellent" dosimetry (8 of 15). In contrast, dosimetry did not affect the outcome for diploid patients.

CONCLUSIONS

Using core biopsy material from archived paraffin blocks, DNA ploidy correctly classified the majority of failures and nonfailures in this study. The results suggest that DNA ploidy can be used as a useful marker for aggressiveness of localized prostate cancer. A larger study will be necessary to further confirm our hypothesis.

Nuclear morphometry, nucleomics and prostate cancer progression

Prostate cancer (PCa) results from a multistep process. This process includes initiation, which occurs through various aging events and multiple insults (such as chronic infection, inflammation and genetic instability through reactive oxygen species causing DNA double-strand breaks), followed by a multistep process of progression. These steps include several genetic and epigenetic alterations, as well as alterations to the chromatin structure, which occur in response to the carcinogenic stress-related events that sustain proliferative signaling. Events such as evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis are readily observed. In addition, in conjunction with these critical drivers of carcinogenesis, other factors related to the etiopathogenesis of PCa, involving energy metabolism and evasion of the immune surveillance system, appear to be involved. In addition, when cancer spread and metastasis occur, the 'tumor microenvironment' in the bone of PCa patients may provide a way to sustain dormancy or senescence and eventually establish a 'seed and soil' site where PCa proliferation and growth may occur over time. When PCa is initiated and progression ensues, significant alterations in nuclear size, shape and heterochromatin (DNA transcription) organization are found, and key nuclear transcriptional and structural proteins, as well as multiple nuclear bodies can lead to precancerous and malignant changes. These series of cellular and tissue-related malignancy-associated events can be quantified to assess disease progression and management.

ProPSA and diagnostic biopsy tissue DNA content combination improves accuracy to predict need for prostate cancer treatment among men enrolled in an active surveillance program

OBJECTIVES

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.