Combining volume-weighted mean nuclear volume with Gleason score and clinical stage to predict more reliably disease outcome of patients with prostate cancer

DMDtoolkit: a tool for visualizing the mutated dystrophin protein and predicting the clinical severity in DMD

BACKGROUND

Dystrophinopathy is one of the most common human monogenic diseases which results in Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD). Mutations in the dystrophin gene are responsible for both DMD and BMD. However, the clinical phenotypes and treatments are quite different in these two muscular dystrophies. Since early diagnosis and treatment results in better clinical outcome in DMD it is essential to establish accurate early diagnosis of DMD to allow efficient management. Previously, the reading-frame rule was used to predict DMD versus BMD. However, there are limitations using this traditional tool. Here, we report a novel molecular method to improve the accuracy of predicting clinical phenotypes in dystrophinopathy. We utilized several additional molecular genetic rules or patterns such as "ambush hypothesis", "hidden stop codons" and "exonic splicing enhancer (ESE)" to predict the expressed clinical phenotypes as DMD versus BMD.

RESULTS

A computer software "DMDtoolkit" was developed to visualize the structure and to predict the functional changes of mutated dystrophin protein. It also assists statistical prediction for clinical phenotypes. Using the DMDtoolkit we showed that the accuracy of predicting DMD versus BMD raised about 3% in all types of dystrophin mutations when compared with previous methods. We performed statistical analyses using correlation coefficients, regression coefficients, pedigree graphs, histograms, scatter plots with trend lines, and stem and leaf plots.

CONCLUSIONS

We present a novel DMDtoolkit, to improve the accuracy of clinical diagnosis for DMD/BMD. This computer program allows automatic and comprehensive identification of clinical risk and allowing them the benefit of early medication treatments. DMDtoolkit is implemented in Perl and R under the GNU license. This resource is freely available at http://github.com/zhoujp111/DMDtoolkit , and http://www.dmd-registry.com .

The role of volume-weighted mean nuclear volume in predicting tumour biology and clinical behaviour in patients with prostate cancer undergoing watchful waiting

OBJECTIVE

To investigate whether the volume-weighted mean nuclear volume (MNV, the only means by which unbiased estimates of three-dimensional variables can be obtained from a two-dimensional section by stereological methods) at diagnosis correlates with tumour biology and clinical behaviour in patients with prostate cancer treated by watchful waiting.

PATIENTS AND METHODS

In a prognostic study, 64 patients with clinically localized prostate cancer were followed prospectively with initial expectant management. The median (mean, range) follow-up was 22 (27, 6.0-68) months. The prostate specific antigen (PSA) doubling time (PSADT) was calculated by linear regression. The MNV was estimated using biopsy specimens, based on a stereological method, and compared with PSADT and traditional clinicopathological variables.

RESULTS

PSADT was significantly associated with MNV, but not with other clinicopathological variables. The PSA 'rapid-riser' subset (PSADT<median value) had significantly larger MNVs than did the PSA 'slow-riser' (PSADT>or=median value) and PSA-stable subsets (P = 0.0017 and 0.004, respectively). On multivariate analysis using a stepwise Cox proportional hazards regression, only MNV remained independently significant as a predictor of clinical progression among the clinicopathological variables (P < 0.001).

CONCLUSIONS

These findings suggest that cancer cell nuclear volume is significantly associated with tumour biology and behaviour in patients with prostate cancer. Although further study with a larger patient population is needed to confirm the findings, estimates of MNV may be an important prognostic indicator in men treated with watchful waiting.

Factors that influence the measurement of prostate cancer DNA ploidy and proliferation in paraffin embedded tissue evaluated by flow cytometry

DNA ploidy and proliferation have been shown in several studies to be prognostic markers for prostate cancer. Flow cytometry (FCM) is often used in the determination of ploidy and proliferation. However, FCM cannot readily distinguish among benign epithelium, stromal and inflammatory cells, high grade prostatic intraepithelial neoplasia (HGPIN), and cancer cells. In this study, we evaluated H&E histologic features of 322 radical prostatectomy formalin-fixed, paraffin-embedded tissue blocks used for determining DNA ploidy, percent S-phase (%S), and %S + %G2M by FCM. The microscopic findings included Gleason score, extent of cancer and HGPIN in the tissue block, and presence of a needle track. The amount of cancer in the block was expressed as a percentage of the total tissue surface area in quartiles: < or =25%, 26-50%, 51-75%, and > or =76%. The extent of HGPIN was recorded in rough 5% intervals. Needle track effect was defined as a combination of fibrohistiocytic reaction, fibrin clot, granuloma formation, and chronic inflammation. The associations between these histologic features and DNA ploidy and proliferation (%S and %S + %G2M) were assessed. In multivariate analyses, Gleason score, the amount of tumor in the tissue block, and the extent of HGPIN were significantly associated with ploidy. Gleason score was the only parameter significantly associated with the proliferation measure of %S. If we included %G2M as part of the proliferative fraction of the histogram, however, both Gleason score and the amount of tumor in the block were significantly associated with this measure of proliferation. The presence of a needle track was not significantly associated with DNA ploidy, %S, or %S + %G2M. In summary, prostate cancer DNA ploidy and proliferation results assessed by FCM in paraffin-embedded tissue blocks were associated with the Gleason score, amount of cancer in the tissue block, and extent of HGPIN. However, the presence of a needle track was not associated with the FCM results.

Volume-weighted mean nuclear volume predicts tumor biology of clinically organ-confined prostate cancer

BACKGROUND

Estimates of volume-weighted mean nuclear volume (MNV) are the only means by which unbiased estimates of three-dimensional parameters can be obtained from a single two-dimensional section, with stereological methods. The present study was conducted to elucidate the role of MNV in predicting tumor biology for patients treated with radical prostatectomy.

METHODS

A retrospective prognostic study of 71 patients with T1/T2 disease, treated with radical prostatectomy alone, was performed. MNV was estimated using biopsy specimens based on a stereological method, and was compared with other preoperative clinical variables. For patients with prostate-specific antigen (PSA) failure, we determined the correlation of MNV with PSA doubling time (PSA DT) which was calculated using PSA values obtained with an ultrasensitive assay.

RESULTS

Mean MNVs for pathologically organ-confined and non-organ-confined tumors were 198.9 and 236.3 microm3, respectively; this difference was significant (P = 0.0364). Univariate analysis showed that PSA, MNV, and Gleason score were significant predictors of prognosis (P = 0.0126, 0.0148, and 0.0375, respectively). Multivariate analysis revealed that MNV and preoperative PSA were powerful independent predictors of prognosis (P = 0.0160 and P = 0.0147, respectively), but the Gleason score was not correlated with prognosis (P = 0.4120). For patients with PSA failure, PSA DT was significantly correlated with MNV (r = -0.597, P = 0.0099). When these patients were classified using median PSA DT at 6 months into two groups, MNV was significantly greater in PSA rapid-riser group than in the slow-riser group (P = 0.0008), but no differences were observed between these groups in PSA, the Gleason score, or cancer volume.

CONCLUSIONS

The findings of the present study suggest that MNV is a powerful predictor of PSA failure for patients with clinically organ-confined disease treated with radical prostatectomy. More importantly, they suggest that MNV can be a useful new parameter for prediction of tumor biology for patients with PSA failure after radical prostatectomy.

Prognostic factors in prostate cancer. College of American Pathologists Consensus Statement 1999

BACKGROUND

Under the auspices of the College of American Pathologists, a multidisciplinary group of clinicians, pathologists, and statisticians considered prognostic and predictive factors in prostate cancer and stratified them into categories reflecting the strength of published evidence and taking into account the expert opinions of the Prostate Working Group members.

MATERIALS AND METHODS

Factors were ranked according to the previous College of American Pathologists categorical rankings: category I, factors proven to be of prognostic importance and useful in clinical patient management; category II, factors that have been extensively studied biologically and clinically but whose importance remains to be validated in statistically robust studies; and category III, all other factors not sufficiently studied to demonstrate their prognostic value. Factors in categories I and II were considered with respect to variations in methods of analysis, interpretation of findings, reporting of data, and statistical evaluation. For each factor, detailed recommendations for improvement were made. Recommendations were based on the following aims: (1) increasing uniformity and completeness of pathologic evaluation of tumor specimens, (2) enhancing the quality of data collected pertaining to existing prognostic factors, and (3) improving patient care.

RESULTS AND CONCLUSIONS

Factors ranked in category I included preoperative serum prostate-specific antigen level, TNM stage grouping, histologic grade as Gleason score, and surgical margin status. Category II factors included tumor volume, histologic type, and DNA ploidy. Factors in category III included perineural invasion, neuroendocrine differentiation, microvessel density, nuclear roundness, chromatin texture, other karyometric factors, proliferation markers, prostate-specific antigen derivatives, and other factors (oncogenes, tumor suppressor genes, apoptosis genes, etc).

The role of volume-weighted mean nuclear volume in predicting disease outcome in patients with stage M1 prostate cancer

BACKGROUND

Various factors have been reported to be of value in predicting the prognosis of prostate cancer. Gleason score (GS) and prostate-specific antigen (PSA) are the two most powerful prognosticators among them. We previously reported that estimation of volume-weighted mean nuclear volume (MNV) was a more useful prognosticator for prostate cancer than subjective histologic grading. In this study, we compared estimates of MNV with PSA and GS for predicting the prognosis of stage M1 prostate cancer.

EXPERIMENTAL DESIGN

A retrospective prognostic study of 66 patients with stage M1 prostate cancer diagnosed between January 1989 and December 1996 at Shizuoka City Hospital and Shizuoka Prefectural Hospital was performed. The prognostic value of unbiased estimates of MNV were compared with PSA and histologic grading according to GS.

RESULTS

Univariate analysis revealed that estimates of MNV (p=0.0136) and post-treatment nadir PSA level (p<0.0001) correlated significantly with the prognosis of stage M1 prostate cancer, whilst GS (p=0.9377), pre-treatment PSA level (p=0.7377) and rate of decrease in PSA level within 1 month after the beginning of therapy (p=0.8999) had no prognostic value. Multivariate analysis revealed that post-treatment PSA level and estimates of MNV were the two most powerful prognosticators.

CONCLUSIONS

This study indicates that estimation of MNV is an important prognosticator, in conjunction with post-treatment nadir PSA level, in stage M1 prostate cancer.