MicroRNA-125a is over-expressed in insulin target tissues in a spontaneous rat model of Type 2 Diabetes

Background

The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. The benefit gained from the higher tissue specificity realized through LCM sampling is evaluated in this study through a comparison of microarray expression profiles obtained from same-samples using bulk and LCM processing.

Methods

Expression data from ten lung adenocarcinoma samples and six adjacent normal samples were acquired using LCM and bulk sampling methods. Expression values were evaluated for correlation between sample processing methods, as well as for bias introduced by the additional linear amplification required for LCM sample profiling.

Results

The direct comparison of expression values obtained from the bulk and LCM sampled datasets reveals a large number of probesets with significantly varied expression. Many of these variations were shown to be related to bias arising from the process of linear amplification, which is required for LCM sample preparation. A comparison of differentially expressed genes (cancer vs. normal) selected in the bulk and LCM datasets also showed substantial differences. There were more than twice as many down-regulated probesets identified in the LCM data than identified in the bulk data. Controlling for the previously identified amplification bias did not have a substantial impact on the differences identified in the differentially expressed probesets found in the bulk and LCM samples.

Conclusion

LCM-coupled microarray expression profiling was shown to uniquely identify a large number of differentially expressed probesets not otherwise found using bulk tissue sampling. The information gain realized from the LCM sampling was limited to differential analysis, as the absolute expression values obtained for some probesets using this study's protocol were biased during the second round of amplification. Consequently, LCM may enable investigators to obtain additional information in microarray studies not easily found using bulk tissue samples, but it is of critical importance that potential amplification biases are controlled for.     

Levels of adiponectin,a marker for PPAR-gamma activity,correlate with skin fibrosis in systemic sclerosis: potential utility as biomarker?

Introduction

Progressive fibrosis in systemic sclerosis (SSc) is linked to aberrant transforming growth factor beta (TGF-beta) signaling. Peroxisome proliferator-activated receptor gamma (PPAR-gamma) blocks fibrogenic TGF-beta responses in vitro and in vivo. Reduced expression and function of PPAR-gamma in patients with SSc may contribute to progression of fibrosis. Here we evaluated the levels of adiponectin, a sensitive and specific index of PPAR-gamma activity, as a potential fibrogenic biomarker in SSc.

Methods

Adiponectin levels were determined in the sera of 129 patients with SSc and 86 healthy controls, and serial determinations were performed in 27 patients. Levels of adiponectin mRNA in skin biopsies from SSc patients were assessed in an expression profiling microarray dataset. Regulation of adiponectin gene expression in explanted human subcutaneous preadipocytes and fibroblasts was examined by real-time quantitative PCR.

Results

Patients with diffuse cutaneous SSc had reduced serum adiponectin levels. A significant inverse correlation between adiponectin levels and the modified Rodnan skin score was observed. In longitudinal studies changes in serum adiponectin levels were inversely correlated with changes in skin fibrosis. Skin biopsies from a subset of SSc patients showed reduced adiponectin mRNA expression which was inversely correlated with the skin score. An agonist ligand of PPAR-gamma potently induced adiponectin expression in explanted mesenchymal cells in vitro.

Conclusions

Levels of adiponectin, reflecting PPAR-gamma activity, are correlated with skin fibrosis and might have potential utility as a biomarker in SSc.     

Exome localization of complex disease association signals

Background

Recent progress in high-throughput technologies has greatly contributed to the development of DNA methylation profiling. Although there are several reports that describe methylome detection of whole genome bisulfite sequencing, the high cost and heavy demand on bioinformatics analysis prevents its extensive application. Thus, current strategies for the study of mammalian DNA methylomes is still based primarily on genome-wide methylated DNA enrichment combined with DNA microarray detection or sequencing. Methylated DNA enrichment is a key step in a microarray based genome-wide methylation profiling study, and even for future high-throughput sequencing based methylome analysis.

Results

In order to evaluate the sensitivity and accuracy of methylated DNA enrichment, we investigated and optimized a number of important parameters to improve the performance of several enrichment assays, including differential methylation hybridization (DMH), microarray-based methylation assessment of single samples (MMASS), and methylated DNA immunoprecipitation (MeDIP). With advantages and disadvantages unique to each approach, we found that assays based on methylation-sensitive enzyme digestion and those based on immunoprecipitation detected different methylated DNA fragments, indicating that they are complementary in their relative ability to detect methylation differences.

Conclusions

Our study provides the first comprehensive evaluation for widely used methodologies for methylated DNA enrichment, and could be helpful for developing a cost effective approach for DNA methylation profiling.     

Perioperative immune responses in cancer patients undergoing digestive surgeries

Aims

We will examine the latest advances in genomic and proteomic laboratory technology. Through an extensive literature review we aim to critically appraise those studies which have utilized these latest technologies and ascertain their potential to identify clinically useful biomarkers.

Methods

An extensive review of the literature was carried out in both online medical journals and through the Royal College of Surgeons in Ireland library.

Results

Laboratory technology has advanced in the fields of genomics and oncoproteomics. Gene expression profiling with DNA microarray technology has allowed us to begin genetic profiling of colorectal cancer tissue. The response to chemotherapy can differ amongst individual tumors. For the first time researchers have begun to isolate and identify the genes responsible. New laboratory techniques allow us to isolate proteins preferentially expressed in colorectal cancer tissue. This could potentially lead to identification of a clinically useful protein biomarker in colorectal cancer screening and treatment.

Conclusion

If a set of discriminating genes could be used for characterization and prediction of chemotherapeutic response, an individualized tailored therapeutic regime could become the standard of care for those undergoing systemic treatment for colorectal cancer. New laboratory techniques of protein identification may eventually allow identification of a clinically useful biomarker that could be used for screening and treatment. At present however, both expression of different gene signatures and isolation of various protein peaks has been limited by study size. Independent multi-centre correlation of results with larger sample sizes is needed to allow translation into clinical practice.