Optimization of comparative expressed sequence hybridization for genome-wide expression profiling at chromosome level

Chromosome 16q genes CDH1, CDH13 and ADAMTS18 are correlated and frequently methylated in human lymphoma

The products of the E-cadherin (CDH1), H-cadherin (CDH13) and a disintegrin and metalloproteinase with thrombospondin motif 18 (ADAMTS18) genes are proteins displaying structural features and functions on the cell surface membrane, and have been reported to be involved in cancer progression. Using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and methylation-specific PCR (MSP) analysis, the promoter methylation status and messenger RNA (mRNA) expression levels of CDH1, CDH13 and ADAMTS18, which are putative tumor-suppressor genes located on chromosome 16q, were evaluated. In addition, the mRNA expression levels of DNA methyltransferases (DNMTs) 1, 3A and 3B were examined, and the correlations among the different parameters analyzed were studied in 36 lymphomas and 16 non-malignant lymphoid tissue samples. A significant positive correlation was identified between the expression levels of CDH1 and CDH13 (r=0.735, P<0.01). ADAMTS18 expression also exhibited a significant positive correlation with both CDH1 and CDH13 mRNA expression levels (r=0.625, P<0.01; and r=0.720, P<0.01, respectively). Our results indicated that CDH1, CDH13 and ADAMTS18, which are localized on chromosome 16q, are remarkably correlated and frequently methylated in human lymphomas, and their methylation could not be explained solely by the mRNA expression level of DNMTs.

Identification of high-risk human papillomavirus (hrHPV)-associated genes in early stage cervical squamous cell carcinomas

This retrospective study investigated gene expression in tumour samples from 38 patients with early stage human papillomavirus (HPV)-associated cervical squamous cell carcinoma (CSCC). The patients were divided into two groups based on the presence of viral markers of HPV16 or HPV18 infection. Gene expression profiles of tumour samples and the corresponding normal cervical epithelium were analysed using cDNA microarrays. Several genes showed differential expression between the two groups of HPV-infected CSCC patients, although seven genes showed similar changes in both groups. The four genes encoding cyclin-dependent kinase inhibitor 2A, matrix metallopeptidase 9, laminin γ-1, and epidermal growth factor receptor were up-regulated, and the three genes encoding transforming growth factor β receptor 1, interleukin-1α and insulin-like growth factor-binding protein 6 were down-regulated, in both HPV16(+) and HPV18(+) CSCC. These proteins are involved in cell proliferation, cell structure and cell attachment, so their expression might be involved in the mechanism of HPV-induced carcino genesis. A clearer understanding of HPV type-specific gene expression might aid diagnosis and treatment.

Hypermethylation-modulated downregulation of RASSF1A expression is associated with the progression of esophageal cancer

BACKGROUND AND AIMS

Chromosome 3p21 is an important locus harboring critical tumor suppressor genes (TSGs) implicated in the pathogenesis of multiple tumors including esophageal carcinoma (EC). Aberrant promoter methylation is a fundamental mechanism of inactivation of TSGs in cancer. RASSF1A, a candidate tumor suppressor gene, recently cloned from the lung tumor locus at 3p21.3, is frequently inactivated by hypermethylation of its promoter region in a number of malignancies. We undertook this study to investigate the methylation status of RASSF1A and its significance in esophageal squamous cell carcinoma (ESCC).

METHODS

Real-time RT-PCR and real-time methylation-specific PCR (real-time MSP) were used to detect RASSF1A expression and the methylation status of the RASSF1A promoter, respectively, in 124 primary ESCC tissues.

RESULTS

Hypermethylation, partial methylation and unmethylation of the promoter region of RASSF1A were detected in 56 (45.2%), 23 (18.6%) and 45 (36.2%) of 124 ESCC samples, respectively. Unmethylation of the promoter region of RASSF1A was detected in 119 (96%) of the 124 corresponding noncancerous tissues. Five (4.0%) of 124 noncancerous tissues showed partial methylation. The presence of hypermethylation was statistically associated with loss of RASSF1A mRNA expression in primary ESCC (p <0.05). There were statistically significant correlations between the presence of hypermethylation and regional lymph node involvement (p=0.000), histological differentiation (p=0.009) and tumor stage (p=0.000).

CONCLUSIONS

Our results suggest that RASSF1A may be one of the ESCC-related TSGs located at 3p21, and hypermethylation of the CpG island promoter of the RASSF1A is associated with the progression of ESCC.

Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences

MOTIVATION

Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance.

RESULT

In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field.

AVAILABILITY

Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.