Curtis Balch

MicroRNA and mRNA integrated analysis (MMIA): a web tool for examining biological functions of microRNA expression

MicroRNAs (miRNAs) are small (19–24 nt), nonprotein-coding nucleic acids that regulate specific ‘target’ gene products via hybridization to mRNA transcripts, resulting in translational blockade or transcript degradation. Although miRNAs have been implicated in numerous developmental and adult diseases, their specific impact on biological pathways and cellular phenotypes, in addition to miRNA gene promoter regulation, remain largely unknown. To improve and facilitate research of miRNA functions and regulation, we have developed MMIA (microRNA and mRNA integrated analysis), a versatile and user-friendly web server. By incorporating three commonly used and accurate miRNA prediction algorithms, TargetScan, PITA and PicTar, MMIA integrates miRNA and mRNA expression data with predicted miRNA target information for analyzing miRNA-associated phenotypes and biological functions by gene set analysis, in addition to analysis of miRNA primary transcript gene promoters. To assign biological relevance to the integrated miRNA/mRNA profiles, MMIA uses exhaustive human genome coverage, including classification into various disease-associated genes as well as conventional canonical pathways and Gene Ontology. In summary, this novel web server (cancer.informatics.indiana.edu/mmia) will provide life science researchers with a valuable tool for the study of the biological (and pathological) causes and effects of the expression of this class of interesting protein regulators.

Prognostic DNA Methylation Biomarkers in Ovarian Cancer

Purpose: Aberrant DNA methylation, now recognized as a contributing factor to neoplasia, often shows definitive gene/sequence preferences unique to specific cancer types. Correspondingly, distinct combinations of methylated loci can function as biomarkers for numerous clinical correlates of ovarian and other cancers. Experimental Design: We used a microarray approach to identify methylated loci prognostic for reduced progression-free survival (PFS) in advanced ovarian cancer patients. Two data set classification algorithms, Significance Analysis of Microarray and Prediction Analysis of Microarray, successfully identified 220 candidate PFS-discriminatory methylated loci. Of those, 112 were found capable of predicting PFS with 95% accuracy, by Prediction Analysis of Microarray, using an independent set of 40 advanced ovarian tumors (from 20 short-PFS and 20 long-PFS patients, respectively). Additionally, we showed the use of these predictive loci using two bioinformatics machine-learning algorithms, Support Vector Machine and Multilayer Perceptron. Conclusion: In this report, we show that highly prognostic DNA methylation biomarkers can be successfully identified and characterized, using previously unused, rigorous classifying algorithms. Such ovarian cancer biomarkers represent a promising approach for the assessment and management of this devastating disease.

Antimitogenic and chemosensitizing effects of the methylation inhibitor zebularine in ovarian cancer

Deoxycytosine methylation within CpG islands of tumor suppressor genes plays a prominent role in the development and progression of drug-resistant ovarian cancer. Consequently, epigenetic therapies directed toward tumor suppressor demethylation/reexpression could potentially reverse malignant phenotypes and chemosensitize recalcitrant tumors. In this report, we examined the demethylating agent zebularine [1-(β-d-ribofuranosyl)-1,2-dihydropyrimidin-2-one], in comparison with the well-known methylation inhibitor 5-aza-2′-deoxycytidine (5-aza-dC), for its ability to inhibit ovarian cancer cell proliferation and to demethylate and induce tumor suppressor genes. Zebularine exerted significant (>5-aza-dC) antiproliferative effects against the ovarian cancer cell lines Hey, A2780, and the cisplatin-resistant A2780/CP in a dose-dependent manner (65% versus 35% inhibition at 48 hours, zebularine versus 5-aza-dC). Moreover, 48-hour treatment with 0.2 mmol/L zebularine significantly induced demethylation of the tumor suppressors ras-associated domain family 1A and human MutL homologue-1. RASSF1A gene reexpression was also observed, as was reexpression of two other tumor suppressors, ARHI and BLU, although levels differed from those induced by 5-aza-dC. Global analyses of DNA methylation revealed similar overall demethylation (2.5- to 3-fold) by 5-aza-dC and zebularine as determined by methyl acceptance assay. However, differences in demethylation of individual loci were observed as determined by differential methylation hybridization. Finally, we found that zebularine could resensitize the drug-resistant cell line A2780/CP to cisplatin, with a 16-fold reduction in the IC50 of that conventional agent. In summary, zebularine seems to be a promising clinical candidate, singly or combined with conventional regimens, for the therapy of drug-resistant ovarian cancer.

Dominant-Negative Histone H3 Lysine 27 Mutant Derepresses Silenced Tumor Suppressor Genes and Reverses the Drug-Resistant Phenotype in Cancer Cells

Histone modifications and DNA methylation are epigenetic phenomena that play a critical role in many neoplastic processes, including silencing of tumor suppressor genes. One such histone modification, particularly at H3 and H4, is methylation at specific lysine (K) residues. Whereas histone methylation of H3-K9 has been linked to DNA methylation and aberrant gene silencing in cancer cells, no such studies of H3-K27 have been reported. Here, we generated a stable cell line overexpressing a dominant-negative point mutant, H3-K27R, to examine the role of that specific lysine in ovarian cancer. Expression of this construct resulted in loss of methylation at H3-K27, global reduction of DNA methylation, and increased expression of tumor suppressor genes. One of the affected genes, RASSF1, was shown to be a direct target of H3-K27 methylation-mediated silencing. By increasing DNA-platinum adduct formation, indicating increased access of the drug to target DNA sequences, removal of H3-K27 methylation resensitized drug-resistant ovarian cancer cells to the chemotherapeutic agent cisplatin. This increased platinum-DNA access was likely due to relaxation of condensed chromatin. Our results show that overexpression of mutant H3-K27 in mammalian cells represents a novel tool for studying epigenetic mechanisms and the Histone Code Hypothesis in human cancer. Such findings show the significance of H3-K27 methylation as a promising target for epigenetic-based cancer therapies.

An integrative ChIP-chip and gene expression profiling to model SMAD regulatory modules.

BackgroundThe TGF-β/SMAD pathway is part of a broader signaling network in which crosstalk between pathways occurs. While the molecular mechanisms of TGF-β/SMAD signaling pathway have been studied in detail, the global networks downstream of SMAD remain largely unknown. The regulatory effect of SMAD complex likely depends on transcriptional modules, in which the SMAD binding elements and partner transcription factor binding sites (SMAD modules) are present in specific context.ResultsTo address this question and develop a computational model for SMAD modules, we simultaneously performed chromatin immunoprecipitation followed by microarray analysis (ChIP-chip) and mRNA expression profiling to identify TGF-β/SMAD regulated and synchronously coexpressed gene sets in ovarian surface epithelium. Intersecting the ChIP-chip and gene expression data yielded 150 direct targets, of which 141 were grouped into 3 co-expressed gene sets (sustained up-regulated, transient up-regulated and down-regulated), based on their temporal changes in expression after TGF-β activation. We developed a data-mining method driven by the Random Forest algorithm to model SMAD transcriptional modules in the target sequences. The predicted SMAD modules contain SMAD binding element and up to 2 of 7 other transcription factor binding sites (E2F, P53, LEF1, ELK1, COUPTF, PAX4 and DR1).ConclusionTogether, the computational results further the understanding of the interactions between SMAD and other transcription factors at specific target promoters, and provide the basis for more targeted experimental verification of the co-regulatory modules.

Subcutaneous 5-Azacitidine Treatment of Naturally Occurring Canine Urothelial Carcinoma: A Novel Epigenetic Approach to Human Urothelial Carcinoma Drug Development

PURPOSE We determined the efficacy, biological activity, pharmacokinetics and safety of the hypomethylating agent 5-azacitidine (Celgene Corp., Summit, New Jersey) in dogs with naturally occurring invasive urothelial carcinoma. MATERIALS AND METHODS We performed a preclinical phase I trial in dogs with naturally occurring invasive urothelial carcinoma to examine once daily subcutaneous administration of 5-azacitidine in 28-day cycles at doses of 0.10 to 0.30 mg/kg per day according to 2 dose schedules, including days 1 to 5 (28-day cohort) or days 1 to 5 and 15 to 19 (14-day cohort). Clinical efficacy was assessed by serial cystosonography, radiography and cystoscopy. Urinary 5-azacitidine pharmacokinetic analysis was also done. Pretreatment and posttreatment peripheral blood mononuclear cell and invasive urothelial carcinoma DNA, respectively, was analyzed for global and gene specific [CDKN2A (p14ARF)] methylation changes. RESULTS Enrolled in the study were 19 dogs with naturally occurring invasive urothelial carcinoma. In the 28-day cohort the maximum tolerated dose was 0.20 mg/kg per day with higher doses resulting in grade 3 or 4 neutropenia in 4 of 6 dogs. In the 14-day cohort the maximum tolerated dose was 0.10 mg/kg per day with grade 3 or 4 neutropenia seen in 2 of 3 dogs treated at higher doses. No grade 3 or 4 nonhematological toxicity was observed during either dosing schedule. Of 18 dogs evaluable for tumor response partial remission, stable disease and progressive disease were observed in 4 (22.2%), 9 (50.0%) and 4 (22.2%), respectively. Consistent 5-azacitidine levels (205 to 857 ng/ml) were detected in urine. Pretreatment and posttreatment methylation analysis revealed no significant correlation with clinical response. CONCLUSIONS Subcutaneous 5-azacitidine showed promising clinical activity in a canine invasive urothelial carcinoma model, thus meriting further development in humans with urothelial carcinoma.

A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-α

MOTIVATION To detect and select patterns of transcription factor binding sites (TFBSs) which distinguish genes directly regulated by estrogen receptor-alpha (ERalpha), we developed an innovative mixture model-based discriminate analysis for identifying ordered TFBS pairs. RESULTS Biologically, our proposed new algorithm clearly suggests that TFBSs are not randomly distributed within ERalpha target promoters (P-value < 0.001). The up-regulated targets significantly (P-value < 0.01) possess TFBS pairs, (DBP, MYC), (DBP, MYC/MAX heterodimer), (DBP, USF2) and (DBP, MYOGENIN); and down-regulated ERalpha target genes significantly (P-value < 0.01) possess TFBS pairs, such as (DBP, c-ETS1-68), (DBP, USF2) and (DBP, MYOGENIN). Statistically, our proposed mixture model-based discriminate analysis can simultaneously perform TFBS pattern recognition, TFBS pattern selection, and target class prediction; such integrative power cannot be achieved by current methods. AVAILABILITY The software is available on request from the authors. CONTACT lali@iupui.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Empirical bayes model comparisons for differential methylation analysis

A number of empirical Bayes models were developed to investigate the differential methylation analysis. However, it is not clear which empirical Bayes model performs best in differential methylation analysis. In this paper, five empirical Bayes models were constructed and applied to the differential methylation analysis of A2780 cells between before and after 1, 3, and 5 round of cisplatin treatment. The log-normal model with the background variance showed the lowest minimized negative log-likelihood. It inferred increasing number of differentially methylated loci from 1 to 3 to 5 rounds of cisplatin treatment on the A2780 cells, which was consistent to cisplatin resistant IC50 data. Among differentially methylated loci selected from each empirical model, three time dependent methylation patterns were defined: stochastic hypomethylation, stochastic hypermethylation, and random methylation. If the empirical Bayes model of the DNA methylation assumed log-normal distribution, both stochastically hypomethylated loci and stochastically hypermethylated loci were enriched with a number of transcription factor binding sites. Almost no TFBS enrichment was observed if the gamma distribution was assumed in the empirical Bayes model. In summary, by comparing the performances of the differential methylation analysis and the TFBS enrichment analysis, log-normal distribution is a better statistical assumption than the gamma distribution in the empirical Bayes model.