Gene profiles between non-invasive and invasive colon cancer using laser microdissection and polypeptide analysis

Prognostic value of opioid binding protein/cell adhesion molecule-like promoter methylation in bladder carcinoma

The OPCML gene (opioid binding protein/cell adhesion molecule-like), a putative tumour suppressor gene, is frequently inactivated in carcinomas, namely through aberrant promoter methylation. Herein, we aimed to determine whether OPCML altered expression mediated by epigenetic mechanisms was implicated in bladder carcinogenesis and to assess its potential as a bladder cancer epi-marker. OPCML promoter methylation levels from 91 samples of bladder urothelial carcinoma, 25 normal bladder tissues and bladder cancer cell lines were assessed by quantitative methylation-specific polymerase chain reaction, and correlated with OPCML mRNA expression, determined by quantitative reverse-transcription polymerase chain reaction. To prove the epigenetic regulation of OPCML, five bladder cancer cell lines were exposed to 5-aza-2'deoxycytidine (5-aza-dC), a specific DNA methyltransferase inhibitor and trichostatin A (TSA), a histone deacetylase inhibitor. In bladder tumours, the overall frequency of methylation was 60% and methylation levels were significantly higher when compared with normal mucosa (P=0.0001). No correlation was found between methylation levels and clinicopathological parameters. Interestingly, OPCML promoter methylation was associated with worse disease-specific survival (P=0.022) in univariate analysis. Furthermore, a significant inverse correlation between OPCML promoter methylation and mRNA expression levels was found, although a significant re-expression was only achieved when 5-aza-dC and TSA were used simultaneously. The high frequency of OPCML promoter methylation in urothelial carcinomas suggests an important role for this epigenetic alteration in bladder carcinogenesis, highlighting its potential as an epigenetic biomarker for bladder urothelial carcinoma with prognostic significance.

Modeling oncogenic signaling in colon tumors by multidirectional analyses of microarray data directed for maximization of analytical reliability

Background

Clinical progression of colorectal cancers (CRC) may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence.

Methodology/Principal Findings

Studies were performed on normal mucosa, adenoma, and carcinoma samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data was generated using two normalization algorithms: MAS5.0 and GCRMA with least-variant set (LVS). The data was evaluated using pair-wise comparisons and data decomposition into singular value decomposition (SVD) modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Expressional profiles obtained in 105 samples of whole tissue sections were used to establish oncogenic signaling alterations in progression of CRC, while those representing 40 microdissected specimens were used to select differences in KEGG pathways between epithelium and mucosa. Based on a consensus of the results obtained by two normalization algorithms, and two probe set sorting criteria, we identified 14 and 17 KEGG signaling and metabolic pathways that are significantly altered between normal and tumor samples and between benign and malignant tumors, respectively. Several of them were also selected from the raw microarray data of 2 recently published studies (GSE4183 and GSE8671).

Conclusion/Significance

Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results.