A Novel Multiplex Cell Viability Assay for High-Throughput RNAi Screening

Cell-based high-throughput RNAi screening has become a powerful research tool in addressing a variety of biological questions. In RNAi screening, one of the most commonly applied assay system is measuring the fitness of cells that is usually quantified using fluorescence, luminescence and absorption-based readouts. These methods, typically implemented and scaled to large-scale screening format, however often only yield limited information on the cell fitness phenotype due to evaluation of a single and indirect physiological indicator. To address this problem, we have established a cell fitness multiplexing assay which combines a biochemical approach and two fluorescence-based assaying methods. We applied this assay in a large-scale RNAi screening experiment with siRNA pools targeting the human kinome in different modified HEK293 cell lines. Subsequent analysis of ranked fitness phenotypes assessed by the different assaying methods revealed average phenotype intersections of 50.7±2.3%–58.7±14.4% when two indicators were combined and 40–48% when a third indicator was taken into account. From these observations we conclude that combination of multiple fitness measures may decrease false-positive rates and increases confidence for hit selection. Our robust experimental and analytical method improves the classical approach in terms of time, data comprehensiveness and cost

DNA methylation status of REIC/Dkk-3 gene in human malignancies

The REIC (reduced expression in immortalized cells)/Dkk-3 is down-regulated in various cancers and considered to be a tumor suppressor gene. REIC/Dkk-3 mRNA has two isoforms (type-a,b). REIC type-a mRNA has shown to be a major transcript in various cancer cells, and its promoter activity was much stronger than that of type-b. In this study, we examined the methylation status of REIC/Dkk-3 type-a in a broad range of human malignancies. We examined REIC/Dkk-3 type-a methylation in breast cancers, non-small-cell lung cancers, gastric cancers, colorectal cancers, and malignant pleural mesotheliomas using a quantitative combined bisulfite restriction analysis assay and bisulfate sequencing. REIC/Dkk-3 type-a and type-b expression was examined using reverse transcriptional PCR. The relationships between the methylation and clinicopathological factors were analyzed. The rate of REIC/Dkk-3 type-a methylation ranged from 26.2 to 50.0% in the various primary tumors that were examined. REIC/Dkk-3 type-a methylation in breast cancer cells was significantly heavier than that in the other cell lines that we tested. REIC/Dkk-3 type-a methylation was inversely correlated with REIC/Dkk-3 type-a expression. There was a correlation between REIC/Dkk-3 type-a and type-b mRNA expression. REIC/Dkk-3 type-a expression was restored in MDA-MB-231 cells using 5-aza-2'-deoxycytidine treatment. We found that estrogen receptor-positive breast cancers were significantly more common among the methylated group than among the non-methylated group. REIC/Dkk-3 type-a methylation was frequently detected in a broad range of cancers and appeared to play a key role in silencing REIC/Dkk-3 type-a expression in these malignancies

Wnt signalling in human breast cancer: expression of the putative Wnt inhibitor Dickkopf-3 (DKK3) is frequently suppressed by promoter hypermethylation in mammary tumours

INTRODUCTION: Expression of the putative Wnt signalling inhibitor Dickkopf-3 (DKK3) is frequently lost in human cancer tissues because of aberrant 5'-cytosine methylation within the DKK3 gene promoter. Since other Wnt signalling inhibitors have been reported to be targets of epigenetic inactivation in human breast cancer, we questioned if DKK3 expression is also epigenetically silenced during breast carcinogenesis and therefore might contribute to oncogenic Wnt signalling commonly found in this disease. METHODS: DKK3 mRNA expression and DKK3 promoter methylation were determined by RT-PCR, realtime PCR and methylation-specific PCR in breast cell lines (n = 9), normal breast tissues (n = 19) and primary breast carcinomas (n = 150), respectively. In vitro DNA demethylation was performed by incubating breast cell lines with 5-aza-2'-deoxycytidine and trichostatin A. DKK3 protein expression was analysed by immunohistochemistry in breast carcinomas (n = 16) and normal breast tissues (n = 8). Methylation data were statistically correlated with clinical patient characteristics. All statistical evaluations were performed with SPSS 14.0 software. RESULTS: DKK3 mRNA was downregulated in 71% (five of seven) of breast cancer cell lines and in 68% of primary breast carcinomas (27 of 40) compared with benign cell lines and normal breast tissues, respectively. A DNA demethylating treatment of breast cell lines resulted in strong induction of DKK3 mRNA expression. In tumourous breast tissues, DKK3 mRNA downregulation was significantly associated with DKK3 promoter methylation (p < 0.001). Of the breast carcinomas, 61% (92 of 150) revealed a methylated DKK3 promoter, whereas 39% (58 of 150) retained an unmethylated promoter. Loss of DKK3 expression in association with DKK3 promoter methylation (p = 0.001) was also confirmed at the protein level (p < 0.001). In bivariate analysis, DKK3 promoter methylation was not associated with investigated clinicopathological parameters except patient age (p = 0.007). CONCLUSIONS: DKK3 mRNA expression and consequently DKK3 protein expression become frequently downregulated during human breast cancer development due to aberrant methylation of the DKK3 promoter. Since DKK3 is thought to negatively regulate oncogenic Wnt signalling, DKK3 may be a potential tumour suppressor gene in normal breast tissue

DNA Methylation Changes in Atypical Adenomatous Hyperplasia, Adenocarcinoma In Situ, and Lung Adenocarcinoma

BACKGROUND:Aberrant DNA methylation is common in lung adenocarcinoma, but its timing in the phases of tumor development is largely unknown. Delineating when abnormal DNA methylation arises may provide insight into the natural history of lung adenocarcinoma and the role that DNA methylation alterations play in tumor formation. METHODOLOGY/PRINCIPAL FINDINGS:We used MethyLight, a sensitive real-time PCR-based quantitative method, to analyze DNA methylation levels at 15 CpG islands that are frequently methylated in lung adenocarcinoma and that we had flagged as potential markers for non-invasive detection. We also used two repeat probes as indicators of global DNA hypomethylation. We examined DNA methylation in 249 tissue samples from 93 subjects, spanning the putative spectrum of peripheral lung adenocarcinoma development: histologically normal adjacent non-tumor lung, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS, formerly known as bronchioloalveolar carcinoma), and invasive lung adenocarcinoma. Comparison of DNA methylation levels between the lesion types suggests that DNA hypermethylation of distinct loci occurs at different time points during the development of lung adenocarcinoma. DNA methylation at CDKN2A ex2 and PTPRN2 is already significantly elevated in AAH, while CpG islands at 2C35, EYA4, HOXA1, HOXA11, NEUROD1, NEUROD2 and TMEFF2 are significantly hypermethylated in AIS. In contrast, hypermethylation at CDH13, CDX2, OPCML, RASSF1, SFRP1 and TWIST1 and global DNA hypomethylation appear to be present predominantly in invasive cancer. CONCLUSIONS/SIGNIFICANCE:The gradual increase in DNA methylation seen for numerous loci in progressively more transformed lesions supports the model in which AAH and AIS are sequential stages in the development of lung adenocarcinoma. The demarcation of DNA methylation changes characteristic for AAH, AIS and adenocarcinoma begins to lay out a possible roadmap for aberrant DNA methylation events in tumor development. In addition, it identifies which DNA methylation changes might be used as molecular markers for the detection of preinvasive lesions

hTERT promoter activity and CpG methylation in HPV-induced carcinogenesis

<p>Abstract</p> <p>Background</p> <p>Activation of telomerase resulting from deregulated hTERT expression is a key event during high-risk human papillomavirus (hrHPV)-induced cervical carcinogenesis. In the present study we examined hTERT promoter activity and its relation to DNA methylation as one of the potential mechanisms underlying deregulated hTERT transcription in hrHPV-transformed cells.</p> <p>Methods</p> <p>Using luciferase reporter assays we analyzed hTERT promoter activity in primary keratinocytes, HPV16- and HPV18-immortalized keratinocyte cell lines and cervical cancer cell lines. In the same cells as well as cervical specimens we determined hTERT methylation by bisulfite sequencing analysis of the region spanning -442 to +566 (relative to the ATG) and quantitative methylation specific PCR (qMSP) analysis of two regions flanking the hTERT core promoter.</p> <p>Results</p> <p>We found that in most telomerase positive cells increased hTERT core promoter activity coincided with increased hTERT mRNA expression. On the other hand basal hTERT promoter activity was also detected in telomerase negative cells with no or strongly reduced hTERT mRNA expression levels. In both telomerase positive and negative cells regulatory sequences flanking both ends of the core promoter markedly repressed exogenous promoter activity.</p> <p>By extensive bisulfite sequencing a strong increase in CpG methylation was detected in hTERT positive cells compared to cells with no or strongly reduced hTERT expression. Subsequent qMSP analysis of a larger set of cervical tissue specimens revealed methylation of both regions analyzed in 100% of cervical carcinomas and 38% of the high-grade precursor lesions, compared to 9% of low grade precursor lesions and 5% of normal controls.</p> <p>Conclusions</p> <p>Methylation of transcriptionally repressive sequences in the hTERT promoter and proximal exonic sequences is correlated to deregulated hTERT transcription in HPV-immortalized cells and cervical cancer cells. The detection of DNA methylation at these repressive regions may provide an attractive biomarker for early detection of cervical cancer.</p

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases