Prediction of pathological stage in patients with prostate cancer: a neuro-fuzzy model

The prediction of cancer staging in prostate cancer is a process for estimating the likelihood that the cancer has spread before treatment is given to the patient. Although important for determining the most suitable treatment and optimal management strategy for patients, staging continues to present significant challenges to clinicians. Clinical test results such as the pre-treatment Prostate-Specific Antigen (PSA) level, the biopsy most common tumor pattern (Primary Gleason pattern) and the second most common tumor pattern (Secondary Gleason pattern) in tissue biopsies, and the clinical T stage can be used by clinicians to predict the pathological stage of cancer. However, not every patient will return abnormal results in all tests. This significantly influences the capacity to effectively predict the stage of prostate cancer. Herein we have developed a neuro-fuzzy computational intelligence model for classifying and predicting the likelihood of a patient having Organ-Confined Disease (OCD) or Extra-Prostatic Disease (ED) using a prostate cancer patient dataset obtained from The Cancer Genome Atlas (TCGA) Research Network. The system input consisted of the following variables: Primary and Secondary Gleason biopsy patterns, PSA levels, age at diagnosis, and clinical T stage. The performance of the neuro-fuzzy system was compared to other computational intelligence based approaches, namely the Artificial Neural Network, Fuzzy C-Means, Support Vector Machine, the Naive Bayes classifiers, and also the AJCC pTNM Staging Nomogram which is commonly used by clinicians. A comparison of the optimal Receiver Operating Characteristic (ROC) points that were identified using these approaches, revealed that the neuro-fuzzy system, at its optimal point, returns the largest Area Under the ROC Curve (AUC), with a low number of false positives (FPR = 0.274, TPR = 0.789, AUC = 0.812). The proposed approach is also an improvement over the AJCC pTNM Staging Nomogram (FPR = 0.032, TPR = 0.197, AUC = 0.582)

GOLPH2 protein expression as a novel tissue biomarker for prostate cancer: implications for tissue-based diagnostics

GOLPH2 is coding the 73-kDa type II Golgi membrane antigen GOLPH2/GP73. Upregulation of GOLPH2 mRNA has been recently reported in expression array analyses of prostate cancer. As GOLPH2 protein expression in prostate tissues is currently unknown, this study aimed at a comprehensive analysis of GOLPH2 protein in benign and malignant prostate lesions. Immunohistochemically detected GOLPH2 protein expression was compared with the basal cell marker p63 and the prostate cancer marker α-methylacyl-CoA racemase (AMACR) in 614 radical prostatectomy specimens. GOLPH2 exhibited a perinuclear Golgi-type staining pattern and was preferentially seen in prostatic gland epithelia. Using a semiquantitative staining intensity score, GOLPH2 expression was significantly higher in prostate cancer glands compared with normal glands (P<0.001). GOLPH2 protein was upregulated in 567 of 614 tumours (92.3%) and AMACR in 583 of 614 tumours (95%) (correlation coefficient 0.113, P=0.005). Importantly, GOLPH2 immunohistochemistry exhibited a lower level of intratumoral heterogeneity (25 vs 45%). Further, GOLPH2 upregulation was detected in 26 of 31 (84%) AMACR-negative prostate cancer cases. These data clearly suggest GOLPH2 as an additional ancillary positive marker for tissue-based diagnosis of prostate cancer

HDAC inhibitor confers radiosensitivity to prostate stem-like cells

Background: Radiotherapy can be an effective treatment for prostate cancer, but radiorecurrent tumours do develop. Considering prostate cancer heterogeneity, we hypothesised that primitive stem-like cells may constitute the radiation-resistant fraction. Methods: Primary cultures were derived from patients undergoing resection for prostate cancer or benign prostatic hyperplasia. After short-term culture, three populations of cells were sorted, reflecting the prostate epithelial hierarchy, namely stem-like cells (SCs, α2β1integrinhi/CD133+), transit-amplifying (TA, α2β1integrinhi/CD133−) and committed basal (CB, α2β1integrinlo) cells. Radiosensitivity was measured by colony-forming efficiency (CFE) and DNA damage by comet assay and DNA damage foci quantification. Immunofluorescence and flow cytometry were used to measure heterochromatin. The HDAC (histone deacetylase) inhibitor Trichostatin A was used as a radiosensitiser. Results: Stem-like cells had increased CFE post irradiation compared with the more differentiated cells (TA and CB). The SC population sustained fewer lethal double-strand breaks than either TA or CB cells, which correlated with SCs being less proliferative and having increased levels of heterochromatin. Finally, treatment with an HDAC inhibitor sensitised the SCs to radiation. Interpretation: Prostate SCs are more radioresistant than more differentiated cell populations. We suggest that the primitive cells survive radiation therapy and that pre-treatment with HDAC inhibitors may sensitise this resistant fraction

Coherent electron–nuclear coupling in oligothiophene molecular wires

In molecular electronics individual molecules serve as electronic devices. In these systems, electron–vibron (e–ν) coupling can be expected to lead to new physical phenomena and potential device functions1, 2, 3. In previous studies of molecular wires, the e–ν coupling occurred as a result of the well-known Franck–Condon principle, for which the Born–Oppenheimer approximation holds. This means that after a vibronic excitation, the electrons and the vibrations evolve independently from each other. Here we show that this simple picture changes markedly when two electronic levels in a molecule are coupled by a molecular vibration4, 5. In molecular wires we observe a non-Born–Oppenheimer regime, for which a coherent coupling of electronic and nuclear motion emerges6. This phenomenon should occur in all systems with strong electron–vibration coupling and an electronic level spacing of the order of vibrational energies. The coherent coupling of electronic and nuclear motion could be used to implement mechanical control of electron transport in molecular electronics