Highly sensitive and specific microRNA expression profiling using BeadArray technology.

We have developed a highly sensitive, specific and reproducible method for microRNA (miRNA) expression profiling, using the BeadArray technology. This method incorporates an enzyme-assisted specificity step, a solid-phase primer extension to distinguish between members of miRNA families. In addition, a universal PCR is used to amplify all targets prior to array hybridization. Currently, assay probes are designed to simultaneously analyse 735 well-annotated human miRNAs. Using this method, highly reproducible miRNA expression profiles were generated with 100-200 ng total RNA input. Furthermore, very similar expression profiles were obtained with total RNA and enriched small RNA species (R(2) >or= 0.97). The method has a 3.5-4 log (10(5)-10(9) molecules) dynamic range and is able to detect 1.2- to 1.3-fold-differences between samples. Expression profiles generated by this method are highly comparable to those obtained with RT-PCR (R(2) = 0.85-0.90) and direct sequencing (R = 0.87-0.89). This method, in conjunction with the 96-sample array matrix should prove useful for high-throughput expression profiling of miRNAs in large numbers of tissue samples.

Allele-specific expression in the germline of patients with familial pancreatic cancer: an unbiased approach to cancer gene discovery.

Physiologic allele-specific expression (ASE) in germline tissues occurs during random X-chromosome inactivation and in genomic imprinting, wherein the two alleles of a gene in a heterozygous individual are not expressed equally. Recent studies have confirmed the existence of ASE in apparently non-imprinted autosomal genes; however, the extent of ASE in the human genome is unknown. We explored ASE in lymphoblastoid cell lines of 145 individuals using an oligonucleotide array based assay. ASE of autosomal genes was found to be a very common phenomenon in approximately 20% of heterozygotes at 78% of SNPs at 84% of the genes examined. Comparison of 100 affected individuals from familial pancreatic cancer kindreds and 45 controls revealed three types of changes in the germline: (a) loss of ASE, (b) gain of ASE, and, (c) rare instances of "extreme" (near monoallelic) ASE. The latter changes identified heterozygous deleterious mutations in a subset of these genes. Consequently, an ASE assay efficiently identifies candidate disease genes with altered germline expression properties as compared to controls, and provides insights into mechanisms that confer an inherited disease risk for pancreatic cancer.

DNA methylation markers of surfactant proteins in lung cancer.

Surfactant proteins play important roles in lung surfactant function and innate immunity. The DNA methylation state of 11 CpG sites of surfactant protein (SP)-A1, -B, -C, and -D was determined using universal bead arrays. A total of 90 cancerous and non-cancerous tissues from 23 patients with adenocarcinoma and 22 with squamous cell carcinoma were studied. These were divided into a training set and a testing set. The results indicate that DNA methylation profiling of these CpGs is associated with lung cancer. Four CpG sites, SP-A1_370, SP-A1_1080, SP-D_1170, and SP-D_1370, were hypomethylated in cancer and were significantly associated with both adenocarcinoma and squamous cell carcinoma, indicating that they have the potential to be used as biomarkers for lung cancer diagnosis and treatment. Normal lung tissues with a higher level of unmethylated SP-A1_1468 and SP-D_1170 CpG exhibited a higher level of SP-A1 and SP-D gene transcripts indicating that CpG methylation may play a role in gene expression. When the non-cancerous tissues were compared to cancerous tissues in patients with adenocarcinoma, the methylation profile results of these 46 samples (23 cancerous and 23 non-cancerous) could be clustered into 4 groups by agglomerative nesting. The percentage of tumor samples in each group was 0, 58, 91, and 100, respectively. A similar pattern was observed in squamous cell carcinoma patients. We speculate that SP-A1 and SP-D are subject to methylation/demethylation regulatory mechanisms and are involved in lung cancer pathogenesis by virtue of their function in innate host defense and/or regulation of inflammation.

Expression signatures that correlated with Gleason score and relapse in prostate cancer.

Predicting prognosis in prostate carcinoma remains a challenge when using clinical and pathologic criteria only. We used an array-based DASL assay to identify molecular signatures for predicting prostate cancer relapse in formalin-fixed, paraffin-embedded (FFPE) prostate cancers, through gene expression profiling of 512 prioritized genes. Of the 71 patients that we analyzed, all but 3 had no evidence of residual tumor (defined as negative surgical margins) following radical prostatectomy and no patient received adjuvant therapy following surgery. All of the 71 patients had an undetectable serum PSA following radical prostatectomy. Follow-up period was 44+/-15 months. Highly reproducible gene expression patterns were obtained with these samples (average R(2)=0.99). We identified a panel of 11 genes that correlated positively and 5 genes that correlated negatively with Gleason grade. A gene expression score (GEX) was derived from the expression levels of the 16 genes. We assessed the prognostic value of these genes and found the GEX significantly correlated with disease relapse (p=0.007). These results suggest that the approach we used is effective for expression profiling in heterogeneous FFPE tissues for cancer diagnosis/prognosis biomarker discovery and validation.

Human embryonic stem cells have a unique epigenetic signature.

Human embryonic stem (hES) cells originate during an embryonic period of active epigenetic remodeling. DNA methylation patterns are likely to be critical for their self-renewal and pluripotence. We compared the DNA methylation status of 1536 CpG sites (from 371 genes) in 14 independently isolated hES cell lines with five other cell types: 24 cancer cell lines, four adult stem cell populations, four lymphoblastoid cell lines, five normal human tissues, and an embryonal carcinoma cell line. We found that the DNA methylation profile clearly distinguished the hES cells from all of the other cell types. A subset of 49 CpG sites from 40 genes contributed most to the differences among cell types. Another set of 25 sites from 23 genes distinguished hES cells from normal differentiated cells and can be used as biomarkers to monitor differentiation. Our results indicate that hES cells have a unique epigenetic signature that may contribute to their developmental potential.

High-throughput DNA methylation profiling using universal bead arrays.

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.