DNA IMAGE CYTOMETRY ON BIOPSIES CAN HELP THE DETECTION OF LOCALIZED GLEASON 3+3 PROSTATE CANCERS

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 value of Her-2/neu and DNA index for progression, metastasis and prostate cancer-specific death in men with long-term follow-up after radical prostatectomy

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; <0.0001). Further, the proportions of Her-2/neu positive and high %DNA index tumors significantly increased from patients who died from another cause without progression to those who died from another cause with progression to those died with PCa-specific death (p = 0.027; <0.0001). Her-2/neu expression and %DNA index were significant prognosticators for progression (p <or= 0.001), metastasis (p <or= 0.01) PCa-specific death (p <or= 0.04) in univariate analyses. Multivariately, Her-2/neu expression and %DNA index were also significant for progression (p = 0.001), metastasis (p = 0.001) and PCa-specific death (p = 0.02). When all other clinicopathologic information is available, the increment in concordance index by addition of either Her-2/neu or DNA index was approximately 2% and of both biomarkers was approximately 3% for progression, metastasis and PCa-specific death free survival models. Therefore, patients with Her-2/neu positive and high %DNA index are at a higher risk for disease progression, metastasis and PCa-specific death. Further, Her-2/neu expression and %DNA index may be used with clinicopathologic parameters for prediction of long-term prognosis in PCa.

Identification of patients with low-risk for aneuploidy: comparative discriminatory models using linear and machine-learning classifiers in prostate cancer

BACKGROUND

Prostate needle biopsy (PNB) ploidy status has proven utility to predict adverse outcomes after prostatectomy. We sought to develop models to predict ploidy status using clinicopathologic variables.

METHODS

We identified a cohort of 169 patients with a diagnosis of prostatic adenocarcinoma on PNB, and estimated ploidy status (determined using Feulgen stained biopsy tissue) using four predictors, including age, prebiopsy PSA, highest Gleason score (GS), and the percentage of involvement by carcinoma at the biopsy site with the highest GS (PCARBX). Logistic regression (LR), Neural Network (NN), and CART classifiers were constructed.

RESULTS

Univariate analyses revealed all four predictors to be significantly associated with ploidy status. On multivariable analyses, LR identified a 2-parameter model, including GS and PCARBX that had a significant ability to predict ploidy status with a 74% and 75% correct classification rate (CCR), respectively. Using the same variables, CART and NN yielded similar CCRs of 70.4%. Within GS = 6 cohort, the CART model classified over 90% of biopsies as diploid when patients had a PCARBX < 55% and a log(PSA) < 1.7.

CONCLUSIONS

Our study demonstrates that models using GS and PCARBX are able to predict PNB ploidy status with acceptable accuracy. While machine learning classifier-derived models yield similar accuracy as LR-derived models, the latter methodology has the distinct advantage of being applicable in future datasets to estimate case-specific predictions. This information may be useful in identifying potentially aneuploid patients, who can then be targeted for more aggressive therapy.

[Cell ploidy: predictive factor of locally advanced prostate cancer]

OBJECTIVE

This study was designed to demonstrate that the study of cell ploidy on biopsies of clinically localized prostate cancers can contribute to the diagnosis of a tumour extending beyond the prostatic capsule and can complete imaging for local staging.

METHODS

Analysis of the histological results of 140 patients operated for clinically localized prostate cancer distinguished two groups of patients in whom the initial tumour was Gleason score 6 or 7. The first group was composed of 33 patients whose tumour was classified as pT3 and the second group was composed of 24 patients whose tumour was classified as pT2. The cell ploidy study was performed on biopsies and operative specimens in the two groups.

RESULTS

In the pT3N0M0 group, 72% of tumours presented an aneuploid contingent versus 16% of tumours of the pT2N0M0 group. A strong correlation was demonstrated between cell ploidy and tumour stage (p = 0.0002) and a highly significant correlation was observed between tumour stage and the presence of a tumour contingent with ploidy greater than 5C (p = 0.0009).

CONCLUSION

The presence of an aneuploid contingent on biopsies of clinically localized prostate cancer significantly increases the risk of a more advanced tumour. This technique could therefore constitute a simple complementary tool in the staging of prostate cancer in combination with transrectal MRI, but this needs to be confirmed by other studies.

The significance of tumor heterogeneity for prediction of DNA ploidy of prostate cancer

OBJECTIVE

In a previous study, we mapped the ploidy heterogeneity of prostate cancer using flow cytometry in 676 tumor samples from 50 radical prostatectomy specimens. Ploidy heterogeneity was common (42% of tumors) and was found in all non-diploid tumors. The volume of non-diploid tumor was estimated and found to predict extra-prostatic extension and seminal vesicle invasion. The aim of this study was to evaluate the impact of tumor heterogeneity on preoperative ploidy assessment.

MATERIAL AND METHODS

In 50 men at least six core biopsies were taken before prostatectomy. Sections from biopsies with cancer were Feulgen-stained for image cytometry. After exclusion of biopsies with insufficient material, 123 histograms from 48 men (mean 2.6; range 1-7) remained for analysis.

RESULTS

In 32 men, biopsies were diploid. In 16 men, at least one biopsy was non-diploid (14 tetraploid, two aneuploid) and 10 of them also had diploid biopsies. In 34 men (71%), the prostatectomy specimens were correctly predicted as being either diploid (48%) or non-diploid (23%). The sensitivity and specificity of biopsies for predicting non-diploid cancer were 55% and 82%, respectively, and the positive and negative predictive values were 69% and 72%, respectively. The ploidy status of tumors with and without ploidy heterogeneity was correctly predicted in 55% and 82% of cases, respectively (p=0.04). Biopsies underestimated ploidy in 9/20 tumors (45%) with heterogeneous ploidy status. Underestimation mainly occurred when one or two cores were analyzed.

CONCLUSIONS

Preoperative prediction of the ploidy status of prostate cancer is hampered by tumor heterogeneity. Analysis of multiple biopsies is important for correct preoperative ploidy estimation.