Optimization of laser capture microdissection and RNA amplification for gene expression profiling of prostate cancer

BACKGROUND: To discover prostate cancer biomarkers, we profiled gene expression in benign and malignant cells laser capture microdissected (LCM) from prostate tissues and metastatic prostatic adenocarcinomas. Here we present methods developed, optimized, and validated to obtain high quality gene expression data. RESULTS: RNase inhibitor was included in solutions used to stain frozen tissue sections for LCM, which improved RNA quality significantly. Quantitative PCR assays, requiring minimal amounts of LCM RNA, were developed to determine RNA quality and concentration. SuperScript II™ reverse transcriptase was replaced with SuperScript III™, and SpeedVac concentration was eliminated to optimize linear amplification. The GeneChip(® )IVT labeling kit was used rather than the Enzo BioArray™ HighYield™ RNA transcript labeling kit since side-by-side comparisons indicated high-end signal saturation with the latter. We obtained 72 μg of labeled complementary RNA on average after linear amplification of about 2 ng of total RNA. CONCLUSION: Unsupervised clustering placed 5/5 normal and 2/2 benign prostatic hyperplasia cases in one group, 5/7 Gleason pattern 3 cases in another group, and the remaining 2/7 pattern 3 cases in a third group with 8/8 Gleason pattern 5 cases and 3/3 metastatic prostatic adenocarcinomas. Differential expression of alpha-methylacyl coenzyme A racemase (AMACR) and hepsin was confirmed using quantitative PCR

Effects of Swallowing Training and Follow-up on the Problems Associated with Dysphagia in Patients with Stroke

AIM: This study aimed to determine the effect of poststroke swallowing training and follow-up on swallowing function, nutritional status, and the development of problems associated with dysphagia

Evaluation of health related quality of life in patients with Parkinson's disease

Objectives: To evaluate the socio-demographic and clinical feature of patients with Parkinson's disease, their health-related quality of life (HRQoL), and the relationship between these

Association between gene expression profile of the primary tumor and chemotherapy response of metastatic breast cancer

Abstract Background To better predict the likelihood of response to chemotherapy, we have conducted a study comparing the gene expression patterns of primary tumours with their corresponding response to systemic chemotherapy in the metastatic setting. Methods mRNA expression profiles of breast carcinomas of patients that later developed distant metastases were analyzed using supervised and non-supervised classification techniques to identify predictors of response to chemotherapy. The top differentially expressed genes between the responders and non-responders were identified and further explored. An independent dataset which was generated to predict response to neo-adjuvant CT was utilized for the purpose of validation. Response to chemotherapy was also correlated to the clinicopathologic characteristics, molecular subtypes, metastatic behavior and survival outcomes. Results Anthracycline containing regimens were the most common first line treatment (58.4%), followed by non-anthracycline/non-taxane containing (25.8%) and taxane containing (15.7%) regimens. Response was achieved in 41.6% of the patients to the first line CT and in 21.8% to second line CT. Response was not found to be significantly correlated to tumour type, grade, lymph node status, ER and PR status. Patients with HER2+ tumours showed better response to anthracycline containing therapy (p: 0.002). Response to first and second line chemotherapy did not differ among gene expression based molecular subtypes (p: 0.236 and p: 0.20). Using supervised classification, a 14 gene response classifier was identified. This 14-gene predictor could successfully predict the likelihood of better response to first and second line CT (p: <.0001 and p: 0.761, respectively) in the training set. However, the predictive value of this gene set in data of response to neoadjuvant chemotherapy could not be validated. Conclusions To our knowledge, this is the first study revealing the relation between gene expression profiles of the primary tumours and their chemotherapy responsiveness in the metastatic setting. In contrast to the findings for neoadjuvant chemotherapy treatment, there was no association of molecular subtype with response to chemotherapy in the metastatic setting. Using supervised classification, we identified a classifier of chemotherapy response; however, we could not validate this classifier using neoadjuvant response data. Trial registration Non applicable. Subjects were retrospectively registered