Quantitative Pathology: Historical Background, Clinical Research and Application of Nuclear Morphometry and DNA Image Cytometry

Quantitative analysis of histo- and cytochemical components such as DNA, RNA or chromatin pattern on one hand (cytometry) and the quantitative analysis of geometric non-chemical cell and tissue components (morphometry and sterology) on the other, have developed somewhat independently. Today, many different techniques, such as morphometry, sterology, and static image and flow cytometry are well established and routinely used in diagnostic quantitative pathology. The potential significance of these techniques in the individualization of care in cancer patients include the objective distinction between benign, borderline and malignant lesions, objective grading of invasive tumours, prediction of prognosis, and therapy response

Over-expression of β-catenin is associated with high grade of prostatic cancer in Libyan patients

Objectives: At present, sufficient prognostic markers for prostate cancer (PCa) progression are still lacking, in spite of thorough investigation. The aim of this study was to evaluate abnormalities of β-catenin protein expression, subcellular localization and determine its relation to different clinicopathological features anddisease free survival in prostate cancer patients.Patients and methods: Forty prostate cancer specimens, obtained from patients with different stages of prostate cancer (83% stage IV) who underwent a radical prostatectomy or TURP flanked by 2006 and 2011, β-catenin was determined by immuno-histochemistry (IHC). The membranous expression was semi- quantitatively evaluated in four scores (0, 1+, 2+, 3+). Clinical records of these patients were studied for follow up data.Results: β-Catenin immune staining results show over-expression of β-catenin in PCa Libyan patients. There was no statistically significant difference in β-catenin immune expression as regards histopathological type, perineural invasion, tumor stage, biological recurrence. However, β-catenin over-expression showed significant correlation with old age (p < 0.014).Conclusions: We concluded that changes in expression and cell distribution of β-catenin correlated with the progression degree of prostate adenocarcinoma, signifying a role of this molecule as a marker of progression and prognosis. Further investigations, on a larger and more heterogeneous population, should be carried out to validate and extend our results.Keywords: Prostate cancer; β-Catenin expression; Immuno-histochemistry; Gleason score; Prognosi

The Prognostic Role of RASSF1A Promoter Methylation in Breast Cancer: A Meta-Analysis of Published Data

promoter methylation status and both disease free survival (DFS) and overall survival (OS) in female breast cancer.Eligible studies were identified through searching the PubMed, Web of Science and Embase databases. Studies were pooled and summary hazard ratios (HR) with corresponding confidence intervals (CIs) were calculated. Funnel plots were also carried out to evaluate publication bias. promoter methylation status with OS in 1439 patients. The hazard estimates ranged from 1.21–6.90 with a combined random-effects estimates of 3.47 (95%CI 1.44–8.34). OS reported in multivariate analysis was evaluated in four series comprising 1346 cases and the summarized random-effects HR estimate was 3.35 (95%CI 1.14–9.85). Additionally, no publication bias was detected for both OS and DFS. promoter methylation

Prognostic factors in prostate cancer

Prognostic factors in organ confined prostate cancer will reflect survival after surgical radical prostatectomy. Gleason score, tumour volume, surgical margins and Ki-67 index have the most significant prognosticators. Also the origins from the transitional zone, p53 status in cancer tissue, stage, and aneuploidy have shown prognostic significance. Progression-associated features include Gleason score, stage, and capsular invasion, but PSA is also highly significant. Progression can also be predicted with biological markers (E-cadherin, microvessel density, and aneuploidy) with high level of significance. Other prognostic features of clinical or PSA-associated progression include age, IGF-1, p27, and Ki-67. In patients who were treated with radiotherapy the survival was potentially predictable with age, race and p53, but available research on other markers is limited. The most significant published survival-associated prognosticators of prostate cancer with extension outside prostate are microvessel density and total blood PSA. However, survival can potentially be predicted by other markers like androgen receptor, and Ki-67-positive cell fraction. In advanced prostate cancer nuclear morphometry and Gleason score are the most highly significant progression-associated prognosticators. In conclusion, Gleason score, capsular invasion, blood PSA, stage, and aneuploidy are the best markers of progression in organ confined disease. Other biological markers are less important. In advanced disease Gleason score and nuclear morphometry can be used as predictors of progression. Compound prognostic factors based on combinations of single prognosticators, or on gene expression profiles (tested by DNA arrays) are promising, but clinically relevant data is still lacking

Human Tumor Cell Proliferation Evaluated Using Manganese-Enhanced MRI

Tumor cell proliferation can depend on calcium entry across the cell membrane. As a first step toward the development of a non-invasive test of the extent of tumor cell proliferation in vivo, we tested the hypothesis that tumor cell uptake of a calcium surrogate, Mn(2+) [measured with manganese-enhanced MRI (MEMRI)], is linked to proliferation rate in vitro.Proliferation rates were determined in vitro in three different human tumor cell lines: C918 and OCM-1 human uveal melanomas and PC-3 prostate carcinoma. Cells growing at different average proliferation rates were exposed to 1 mM MnCl(2) for one hour and then thoroughly washed. MEMRI R(1) values (longitudinal relaxation rates), which have a positive linear relationship with Mn(2+) concentration, were then determined from cell pellets. Cell cycle distributions were determined using propidium iodide staining and flow cytometry. All three lines showed Mn(2+)-induced increases in R(1) compared to cells not exposed to Mn(2+). C918 and PC-3 cells each showed a significant, positive correlation between MEMRI R(1) values and proliferation rate (p≤0.005), while OCM-1 cells showed no significant correlation. Preliminary, general modeling of these positive relationships suggested that pellet R(1) for the PC-3 cells, but not for the C918 cells, could be adequately described by simply accounting for changes in the distribution of the cell cycle-dependent subpopulations in the pellet.These data clearly demonstrate the tumor-cell dependent nature of the relationship between proliferation and calcium influx, and underscore the usefulness of MEMRI as a non-invasive method for investigating this link. MEMRI is applicable to study tumors in vivo, and the present results raise the possibility of evaluating proliferation parameters of some tumor types in vivo using MEMRI

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases