TcellInflamedDetector: an R package to distinguish T cell inflamed tumor types from non–T cell inflamed tumor types

A major issue in the use of immune checkpoint inhibitors is their lack of efficacy in many patients. Previous studies have reported that the T cell inflamed signature can help predict the response to immunotherapy. Thus, many studies have investigated mechanisms of immunotherapy resistance by defining the tumor microenvironment based on T cell inflamed and non–T cell inflamed subsets. Although methods of calculating T cell inflamed subsets have been developed, valid screening tools for distinguishing T cell inflamed from non–T cell inflamed subsets using gene expression data are still needed, since general researchers who are unfamiliar with the details of the equations can experience difficulties using extant scoring formulas to conduct analyses. Thus, we introduce TcellInflamedDetector, an R package for distinguishing T cell inflamed from non–T cell inflamed samples using cancer gene expression data via bulk RNA sequencing.

Epigenetic modification of α-N-acetylgalactosaminidase enhances cisplatin resistance in ovarian cancer

Although cisplatin is one of the most effective antitumor drugs for ovarian cancer, the emergence of chemoresistance to cisplatin in over 80% of initially responsive patients is a major barrier to successful therapy. The precise mechanisms underlying the development of cisplatin resistance are not fully understood, but alteration of DNA methylation associated with aberrant gene silencing may play a role. To identify epigenetically regulated genes directly associated with ovarian cancer cisplatin resistance, we compared the expression and methylation profiles of cisplatin-sensitive and -resistant human ovarian cancer cell lines. We identified α-Nacetylgalactosaminidase (NAGA) as one of the key candidate genes for cisplatin drug response. Interestingly, in cisplatin-resistant cell lines, NAGA was significantly downregulated and hypermethylated at a promoter CpG site at position +251 relative to the transcriptional start site. Low NAGA expression in cisplatin-resistant cell lines was restored by treatment with a DNA demethylation agent, indicating transcriptional silencing by hyper-DNA methylation. Furthermore, overexpression of NAGA in cisplatin-resistant lines induced cytotoxicity in response to cisplatin, whereas depletion of NAGA expression increased cisplatin chemoresistance, suggesting an essential role of NAGA in sensitizing ovarian cells to cisplatin. These findings indicate that NAGA acts as a cisplatin sensitizer and its gene silencing by hypermethylation confers resistance to cisplatin in ovarian cancer. Therefore, we suggest NAGA may be a promising potential therapeutic target for improvement of sensitivity to cisplatin in ovarian cancer.

Aberrant epigenetic regulation of GABRP associates with aggressive phenotype of ovarian cancer

Metastasis is a major cause of therapeutic failure in ovarian cancer. To elucidate molecular mechanisms of ovarian cancer metastasis, we previously established a metastatic xenograft mouse model using human ovarian carcinoma SK-OV-3 cells. Using gene expression profiling, we found that γ-aminobutyric acid (GABA)A receptor π subunit (GABRP) expression was upregulated (>4-fold) in metastatic tissues from our xenograft mice compared with SK-OV-3 cells. Importantly, GABRP knockdown diminished the migration and invasion of SK-OV-3 cells, and reduced extracellular signal-regulated kinase (ERK) activation while overexpression of GABRP exhibited significantly increased cell migration, invasion and ERK activation. Moreover, treatment with the mitogen-activated protein kinase (MAPK)/ERK kinase (MEK) inhibitor U0126 similarly suppressed the migration and invasion of SK-OV-3 cells, implying that GABRP promotes these cellular behaviors by activating the MAPK/ERK pathway. Using genome-wide DNA methylation profiling, we identified hypomethylated CpG sites in the GABRP promoter in metastatic tissues from the xenograft mice compared with SK-OV-3 cells. Treatment with a DNA methyltransferase inhibitor demonstrated that methylation at −963 bp from the GABRP transcription start site (−963 CpG site) was critical for the epigenetic regulation of GABRP. Finally, we analyzed human ovarian cancer patient samples and showed DNA hypomethylation at the GABRP −963 CpG site in advanced stage, but not early-stage, primary tumors compared with their paired normal tissues. These findings suggest that GABRP enhances the aggressive phenotype of ovarian cancer cells, and that the DNA methylation status of the GABRP −963 CpG site may be useful for predicting the metastatic potential in ovarian cancer patients.

Aberrant Hypomethylation of Solute Carrier Family 6 Member 12 Promoter Induces Metastasis of Ovarian Cancer

PURPOSE: Ovarian cancer (OC) is the most fatal of gynecological malignancies with a high rate of recurrence. We aimed to evaluate the expression of solute carrier family 6, member 12 (SLC6A12) and methylation of its promoter CpG sites in a xenograft mouse model of metastatic OC, and to investigate the regulatory mechanisms that promote aggressive properties during OC progression. MATERIALS AND METHODS: Expression of SLC6A12 mRNA was determined by reverse-transcription quantitative polymerase chain reaction (RT-qPCR), and DNA methylation status of its promoter CpGs was detected by quantitative methylation-specific PCR. The metastatic potential of SLC6A12 was evaluated by in vitro migration/invasion transwell assays. Gene expression and DNA methylation of SLC6A12 and clinical outcomes were further investigated from publicly available databases from curatedOvarianData and The Cancer Genome Atlas. RESULTS: SLC6A12 expression was 8.1–14.0-fold upregulated and its DNA methylation of promoter CpG sites was 41–62% decreased in tumor metastases. After treatment with DNA methyltransferase inhibitor and/or histone deacetylase inhibitor, the expression of SLC6A12 was profoundly enhanced (~8.0-fold), strongly supporting DNA methylation-dependent epigenetic regulation of SLC6A12. Overexpression of SLC6A12 led to increased migration and invasion of ovarian carcinoma cells in vitro, approximately 2.0-fold and 3.3-fold, respectively. The meta-analysis showed that high expression of SLC6A12 was significantly associated with poor overall survival [hazard ratio (HR)=1.07, p value=0.016] and that low DNA methylation levels of SLC6A12 at specific promoter CpG site negatively affected patient survival. CONCLUSION: Our findings provide novel evidence for the biological and clinical significance of SLC6A12 as a metastasis-promoting gene.

Estimation of Prognostic Marker Genes by Public Microarray Data in Patients with Ovarian Serous Cystadenocarcinoma

PURPOSE: Lymphatic invasion (LI) is regarded as a predictor of the aggressiveness of ovarian cancer (OC). However, LI is not always the major determinant of long-term patient survival. To establish proper diagnosis and treatment for OC, we analyzed differentially expressed genes (DEGs) for patients with serous epithelial OC, with or without LI, who did or did not survive for 5 years. MATERIALS AND METHODS: Gene expression data from 63 patients with OC and LI, and 35 patients with OC but without LI, were investigated using an Affymetrix Human Genome U133 Array and analyzed using The Cancer Genome Atlas (TCGA) database. Among these 98 patients, 16 survived for 5 years or more. DEGs were identified using the Bioconductor R package, and their functions were analyzed using the DAVID web tool. RESULTS: We found 55 significant DEGs (p<0.01) from the patients with LI and 20 highly significant DEGs (p<0.001) from those without it. Pathway analysis showed that DEGs associated with carbohydrate metabolism or with renal cell carcinoma pathways were enriched in the patients with and without LI, respectively. Using the top five prognostic marker genes, we generated survival scores that could be used to predict the 5-year survival of patients with OC without LI. CONCLUSION: The DEGs identified in this study could be used to elucidate the mechanism of tumor progression and to guide the prognosis and treatment of patients with serous OC but without LI.

A Computer-aided Design Tool with Semiautomatic Image-Processing Features for Visualizing Biological Pathways

The explosion in biological data resulting from highthroughput experiments requires new software tools to manipulate and display pathways in a way that can integrate disparate sources of information. A visual Java-based CAD tool for drawing and annotating biological pathways with semiautomatic image-processing features is described in this paper. The result of the image-editing process is an XML file for the appropriate links. This tool integrates the pathway images and XML file sources. The system has facilities for linking graphical objects to external databases and is capable of reproducing existing visual representations of pathway maps.

J2.5dPathway: A 2.5D Visualization Tool to Display Selected Nodes in Biological Pathways, in Parallel Planes

The characteristics of metabolic pathways make them particularly amenable to layered graph drawing methods. This paper presents a visual Java-based tool for drawing and annotating biological pathways in twoand- a-half dimensions (2.5D) as an alternative to three dimensional (3D) visualizations. Such visualization allows user to display different groups of clustered nodes, in different parallel planes, and to see a detailed view of a group of objects in focus and its place in the context of the whole system. This tool is an extended version of J2dPathway.

J2dpathway: A Global Metabolic Pathway Viewer with Node-Abstracting Features

The static approach of representing metabolic pathway diagrams offers no flexibility. Thus, many systems adopt automatic graph layout techniques to visualize the topological architecture of pathways. There are weaknesses, however, because automatically drawn figures are generally difficult to understand. The problem becomes even more serious when we attempt to visualize all of the information in a single, big picture, which usually results in a confusing diagram. To provide a partial solution to this thorny issue, we propose J2dpathway, a metabolic pathway atlas viewer that has node-abstracting features.

Refactoring the Code for Visualizing Protein Database Information in a 3D Viewer for Software Reusability

We have released five Java Application Programming Interface (API) packages for viewing three-dimensional structures of proteins from the Protein Data Bank. To this end, the user interface of an earlier version has been refactored in an object-oriented fashion, in which refactoring is the process of changing a software system to improve its internal structure, without altering the external behavior. Various GUI design and features have been provided conveniently thanks to the Model-View-Control (MVC)model, which is an architectural pattern used in software engineering. Availability: The source code and API specification can be downloaded from https://sourceforge.net/projects/j3dpsv/.

Refactoring the Code for Visualizing Protein Database Information in a 3D Viewer for Software Reusability

We have released five Java Application Programming Interface (API) packages for viewing three-dimensional structures of proteins from the Protein Data Bank. To this end, the user interface of an earlier version has been refactored in an object-oriented fashion, in which refactoring is the process of changing a software system to improve its internal structure, without altering the external behavior. Various GUI design and features have been provided conveniently thanks to the Model-View-Control (MVC)model, which is an architectural pattern used in software engineering. Availability: The source code and API specification can be downloaded from https://sourceforge.net/projects/j3dpsv/.