Analysis of nuclear DNA and morphometry, and proliferating cell nuclear antigen in primary and metastatic malignant melanoma

Nuclear roundness variance predicts prostate cancer progression, metastasis, and death: A prospective evaluation with up to 25 years of follow-up after radical prostatectomy

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.

Tissue biomarkers for prognosis in cutaneous melanoma: a systematic review and meta-analysis

In the clinical management of early-stage cutaneous melanoma, it is critical to determine which patients are cured by surgery alone and which should be treated with adjuvant therapy. To assist in this decision, many groups have made an effort to use molecular information. However, although there are hundreds of studies that have sought to assess the potential prognostic value of molecular markers in predicting the course of cutaneous melanoma, at this time, no molecular method to improve risk stratification is part of recommended clinical practice. To help understand this disconnect, we conducted a systematic review and meta-analysis of the published literature that reported immunohistochemistry-based protein biomarkers of melanoma outcome. Three parallel search strategies were applied to the PubMed database through January 15, 2008, to identify cohort studies that reported associations between immunohistochemical expression and survival outcomes in melanoma that conformed to the REMARK criteria. Of the 102 cohort studies, we identified only 37 manuscripts, collectively describing 87 assays on 62 distinct proteins, which met all inclusion criteria. Promising markers that emerged included melanoma cell adhesion molecule (MCAM)/MUC18 (all-cause mortality [ACM] hazard ratio [HR] = 16.34; 95% confidence interval [CI] = 3.80 to 70.28), matrix metalloproteinase-2 (melanoma-specific mortality [MSM] HR = 2.6; 95% CI = 1.32 to 5.07), Ki-67 (combined ACM HR = 2.66; 95% CI = 1.41 to 5.01), proliferating cell nuclear antigen (ACM HR = 2.27; 95% CI = 1.56 to 3.31), and p16/INK4A (ACM HR = 0.29; 95% CI = 0.10 to 0.83, MSM HR = 0.4; 95% CI = 0.24 to 0.67). We further noted incomplete adherence to the REMARK guidelines: 14 of 27 cohort studies that failed to adequately report their methods and nine studies that failed to either perform multivariable analyses or report their risk estimates were published since 2005.

Histomorphometry of brain tumours

In this review, the results of previous histomorphometric studies of brain tumours are summarized and discussed with respect to their potential value for diagnostic purposes and for tumour research. In the majority of these studies, human gliomas were investigated. In a few studies, human meningiomas and other human or experimental tumour types were investigated. A computerized image analysis system was used for the morphometric analyses in most studies. The three main histologic structures examined were tumour cell nuclei, nucleolar organizer regions and tumour vessels. The current state of knowledge provides evidence that a diagnostic benefit could be provided by histomorphometric investigations of brain tumours, especially for grading of gliomas and with respect to independent prognostic information. Additional studies are necessary to delineate the spectrum of histomorphometric parameters and the investigation of their prognostic significance for cases with the same tumour type and tumour grade. Together with many recently published observations in this field, this review shows that histomorphometry is an important approach towards the investigation of brain tumour biology.