Crosstalk between protein kinase C α and transforming growth factor ß signaling mediated by Runx2 in intestinal epithelial cells.

Tight coordination of growth regulatory signaling is required for intestinal epithelial homeostasis. Protein kinase C α (PKCα) and transforming growth factor ß (TGFß) are negative regulators of proliferation with tumor suppressor properties in the intestine. Here, we identify novel crosstalk between PKCα and TGFß signaling. RNA-Seq analysis of nontransformed intestinal crypt-like cells and colorectal cancer cells identified TGFß receptor 1 (TGFßR1) as a target of PKCα signaling. RT-PCR and immunoblot analysis confirmed that PKCα positively regulates TGFßR1 mRNA and protein expression in these cells. Effects on TGFßR1 were dependent on Ras-extracellular signal-regulated kinase 1/2 (ERK) signaling. Nascent RNA and promoter-reporter analysis indicated that PKCα induces TGFßR1 transcription, and Runx2 was identified as an essential mediator of the effect. PKCα promoted ERK-mediated activating phosphorylation of Runx2, which preceded transcriptional activation of the TGFßR1 gene and induction of Runx2 expression. Thus, we have identified a novel PKCα→ERK→Runx2→TGFßR1 signaling axis. In further support of a link between PKCα and TGFß signaling, PKCα knockdown reduced the ability of TGFß to induce SMAD2 phosphorylation and cell cycle arrest, and inhibition of TGFßR1 decreased PKCα-induced upregulation of p21Cip1 and p27Kip1 in intestinal cells. The physiological relevance of these findings is also supported by The Cancer Genome Atlas data showing correlation between PKCα, Runx2, and TGFßR1 mRNA expression in human colorectal cancer. PKCα also regulated TGFßR1 in endometrial cancer cells, and PKCα, Runx2, and TGFßR1 expression correlates in uterine tumors, indicating that crosstalk between PKCα and TGFß signaling may be a common mechanism in diverse epithelial tissues.

Co-regulation and function of FOXM1/RHNO1 bidirectional genes in cancer.

The FOXM1 transcription factor is an oncoprotein and a top biomarker of poor prognosis in human cancer. Overexpression and activation of FOXM1 is frequent in high-grade serous carcinoma (HGSC), the most common and lethal form of human ovarian cancer, and is linked to copy number gains at chromosome 12p13.33. We show that FOXM1 is co-amplified and co-expressed with RHNO1, a gene involved in the ATR-Chk1 signaling pathway that functions in the DNA replication stress response. We demonstrate that FOXM1 and RHNO1 are head-to-head (i.e., bidirectional) genes (BDG) regulated by a bidirectional promoter (BDP) (named F/R-BDP). FOXM1 and RHNO1 each promote oncogenic phenotypes in HGSC cells, including clonogenic growth, DNA homologous recombination repair, and poly-ADP ribosylase inhibitor resistance. FOXM1 and RHNO1 are one of the first examples of oncogenic BDG, and therapeutic targeting of FOXM1/RHNO1 BDG is a potential therapeutic approach for ovarian and other cancers.

KEGG2Net: Deducing gene interaction networks and acyclic graphs from KEGG pathways.

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database provides a manual curation of biological pathways that involve genes (or gene products), metabolites, chemical compounds, maps, and other entries. However, most applications and datasets involved in omics are gene or protein-centric requiring pathway representations that include direct and indirect interactions only between genes. Furthermore, special methodologies, such as Bayesian networks require acyclic representations of graphs. We developed KEGG2Net, a web resource that generates a network involving only the genes represented on a KEGG pathway with all of the direct and indirect gene-gene interactions deduced from the pathway. KEGG2Net offers four different methods to remove cycles from the resulting gene interaction network, converting them into directed acyclic graphs (DAGs). We generated synthetic gene expression data using the gene interaction networks deduced from the KEGG pathways and performed a comparative analysis of different cycle removal methods by testing the fitness of their DAGs to the data and by the number of edges they eliminate. Our results indicate that an ensemble method for cycle removal performs as the best approach to convert the gene interaction networks into DAGs. Resulting gene interaction networks and DAGs are represented in multiple user-friendly formats that can be used in other applications, and as images for quick and easy visualisation. The KEGG2Net web portal converts KEGG maps for any organism into gene-gene interaction networks and corresponding DAGS representing all of the direct and indirect interactions among the genes.

Importance of evaluating protein glycosylation in pluripotent stem cell-derived cardiomyocytes for research and clinical applications.

Proper protein glycosylation is critical to normal cardiomyocyte physiology. Aberrant glycosylation can alter protein localization, structure, drug interactions, and cellular function. The in vitro differentiation of human pluripotent stem cells into cardiomyocytes (hPSC-CM) has become increasingly important to the study of protein function and to the fields of cardiac disease modeling, drug testing, drug discovery, and regenerative medicine. Here, we offer our perspective on the importance of protein glycosylation in hPSC-CM. Protein glycosylation is dynamic in hPSC-CM, but the timing and extent of glycosylation are still poorly defined. We provide new data highlighting how observed changes in hPSC-CM glycosylation may be caused by underlying differences in the protein or transcript abundance of enzymes involved in building and trimming the glycan structures or glycoprotein gene products. We also provide evidence that alternative splicing results in altered sites of glycosylation within the protein sequence. Our findings suggest the need to precisely define protein glycosylation events that may have a critical impact on the function and maturation state of hPSC-CM. Finally, we provide an overview of analytical strategies available for studying protein glycosylation and identify opportunities for the development of new bioinformatic approaches to integrate diverse protein glycosylation data types. We predict that these tools will promote the accurate assessment of protein glycosylation in future studies of hPSC-CM that will ultimately be of significant experimental and clinical benefit.

FQStat: a parallel architecture for very high-speed assessment of sequencing quality metrics.

BACKGROUND: High throughput DNA/RNA sequencing has revolutionized biological and clinical research. Sequencing is widely used, and generates very large amounts of data, mainly due to reduced cost and advanced technologies. Quickly assessing the quality of giga-to-tera base levels of sequencing data has become a routine but important task. Identification and elimination of low-quality sequence data is crucial for reliability of downstream analysis results. There is a need for a high-speed tool that uses optimized parallel programming for batch processing and simply gauges the quality of sequencing data from multiple datasets independent of any other processing steps. RESULTS: FQStat is a stand-alone, platform-independent software tool that assesses the quality of FASTQ files using parallel programming. Based on the machine architecture and input data, FQStat automatically determines the number of cores and the amount of memory to be allocated per file for optimum performance. Our results indicate that in a core-limited case, core assignment overhead exceeds the benefit of additional cores. In a core-unlimited case, there is a saturation point reached in performance by increasingly assigning additional cores per file. We also show that memory allocation per file has a lower priority in performance when compared to the allocation of cores. FQStat's output is summarized in HTML web page, tab-delimited text file, and high-resolution image formats. FQStat calculates and plots read count, read length, quality score, and high-quality base statistics. FQStat identifies and marks low-quality sequencing data to suggest removal from downstream analysis. We applied FQStat on real sequencing data to optimize performance and to demonstrate its capabilities. We also compared FQStat's performance to similar quality control (QC) tools that utilize parallel programming and attained improvements in run time. CONCLUSIONS: FQStat is a user-friendly tool with a graphical interface that employs a parallel programming architecture and automatically optimizes its performance to generate quality control statistics for sequencing data. Unlike existing tools, these statistics are calculated for multiple datasets and separately at the "lane," "sample," and "experiment" level to identify subsets of the samples with low quality, thereby preventing the loss of complete samples when reliable data can still be obtained.

BORIS Expression in Ovarian Cancer Precursor Cells Alters the CTCF Cistrome and Enhances Invasiveness through GALNT14.

High-grade serous carcinoma (HGSC) is the most aggressive and predominant form of epithelial ovarian cancer and the leading cause of gynecologic cancer-related death. We have previously shown that CTCFL (also known as BORIS, Brother of the Regulator of Imprinted Sites) is expressed in most ovarian cancers, and is associated with global and promoter-specific DNA hypomethylation, advanced tumor stage, and poor prognosis. To explore its role in HGSC, we expressed BORIS in human fallopian tube secretory epithelial cells (FTSEC), the presumptive cells of origin for HGSC. BORIS-expressing cells exhibited increased motility and invasion, and BORIS expression was associated with alterations in several cancer-associated gene expression networks, including fatty acid metabolism, TNF signaling, cell migration, and ECM-receptor interactions. Importantly, GALNT14, a glycosyltransferase gene implicated in cancer cell migration and invasion, was highly induced by BORIS, and GALNT14 knockdown significantly abrogated BORIS-induced cell motility and invasion. In addition, in silico analyses provided evidence for BORIS and GALNT14 coexpression in several cancers. Finally, ChIP-seq demonstrated that expression of BORIS was associated with de novo and enhanced binding of CTCF at hundreds of loci, many of which correlated with activation of transcription at target genes, including GALNT14. Taken together, our data indicate that BORIS may promote cell motility and invasion in HGSC via upregulation of GALNT14, and suggests BORIS as a potential therapeutic target in this malignancy. IMPLICATIONS: These studies provide evidence that aberrant expression of BORIS may play a role in the progression to HGSC by enhancing the migratory and invasive properties of FTSEC.

Epigenetic activation of POTE genes in ovarian cancer.

The POTE gene family consists of 14 homologous genes localized to autosomal pericentromeres, and a sub-set of POTEs are cancer-testis antigen (CTA) genes. POTEs are over-expressed in epithelial ovarian cancer (EOC), including the high-grade serous subtype (HGSC), and expression of individual POTEs correlates with chemoresistance and reduced survival in HGSC. The mechanisms driving POTE overexpression in EOC and other cancers is unknown. Here, we investigated the role of epigenetics in regulating POTE expression, with a focus on DNA hypomethylation. Consistent with their pericentromeric localization, Pan-POTE expression in EOC correlated with expression of the pericentromeric repeat NBL2, which was not the case for non-pericentromeric CTAs. POTE genomic regions contain LINE-1 (L1) sequences, and Pan-POTE expression correlated with both global and POTE-specific L1 hypomethylation in EOC. Analysis of individual POTEs using RNA-seq and DNA methylome data from fallopian tube epithelia (FTE) and HGSC revealed that POTEs C, E, and F have increased expression in HGSC in conjunction with DNA hypomethylation at 5' promoter or enhancer regions. Moreover, POTEs C/E/F showed additional increased expression in recurrent HGSC in conjunction with 5' hypomethylation, using patient-matched samples. Experiments using decitabine treatment and DNMT knockout cell lines verified a functional contribution of DNA methylation to POTE repression, and epigenetic drug combinations targeting histone deacetylases (HDACs) and histone methyltransferases (HMTs) in combination with decitabine further increased POTE expression. In summary, several alterations of the cancer epigenome, including pericentromeric activation, global and locus-specific L1 hypomethylation, and locus-specific 5' CpG hypomethylation, converge to promote POTE expression in ovarian cancer.