CaPSSA: visual evaluation of cancer biomarker genes for patient stratification and survival analysis using mutation and expression data.

Summary: Predictive biomarkers for patient stratification play critical roles in realizing the paradigm of precision medicine. Molecular characteristics such as somatic mutations and expression signatures represent the primary source of putative biomarker genes for patient stratification. However, evaluation of such candidate biomarkers is still cumbersome and requires multistep procedures especially when using massive public omics data.

Identification of tumor suppressor miRNAs by integrative miRNA and mRNA sequencing of matched tumor-normal samples in lung adenocarcinoma.

The roles of miRNAs in lung cancer have not yet been explored systematically at the genome scale despite their important regulatory functions. Here, we report an integrative analysis of miRNA and mRNA sequencing data for matched tumor-normal samples from 109 Korean female patients with non-small-cell lung adenocarcinoma (LUAD). We produced miRNA sequencing (miRNA-Seq) and RNA-Seq data for 48 patients and RNA-Seq data for 61 additional patients.

Mito-TEMPO improves development competence by reducing superoxide in preimplantation porcine embryos.

Mito-TEMPO is a well-known mitochondria-specific superoxide scavenger. However, the effect of Mito-TEMPO on porcine embryo development, to our knowledge, has not been studied yet. In the present study, porcine embryos were classified into two groups (G1 and G2) based on the cytoplasm lipid contents at the zygote stage.

An integrated clinical and genomic information system for cancer precision medicine.

Background: Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient's genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly.

Korean Variant Archive (KOVA): a reference database of genetic variations in the Korean population.

Despite efforts to interrogate human genome variation through large-scale databases, systematic preference toward populations of Caucasian descendants has resulted in unintended reduction of power in studying non-Caucasians. Here we report a compilation of coding variants from 1,055 healthy Korean individuals (KOVA; Korean Variant Archive). The samples were sequenced to a mean depth of 75x, yielding 101 singleton variants per individual.

MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

Background: Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed.

Positive feedback loop between Sox2 and Sox6 inhibits neuronal differentiation in the developing central nervous system.

How a pool of undifferentiated neural progenitor cells is maintained in the developing nervous system is an issue that remains unresolved. One of the key transcription factors for self-renewal of these cells is Sox2, the forced expression of which has been shown to inhibit neuronal differentiation in vivo. To dissect the molecular mechanisms of Sox2 activity, a ChIP-on-chip assay has been carried out for Sox2, and multiple candidate direct target genes have been isolated.

A high-dimensional, deep-sequencing study of lung adenocarcinoma in female never-smokers.

Background: Deep sequencing techniques provide a remarkable opportunity for comprehensive understanding of tumorigenesis at the molecular level. As omics studies become popular, integrative approaches need to be developed to move from a simple cataloguing of mutations and changes in gene expression to dissecting the molecular nature of carcinogenesis at the systemic level and understanding the complex networks that lead to cancer development.

Results: Here, we describe a high-throughput, multi-dimensional sequencing study of primary lung adenocarcinoma tumors and adjacent normal tissues of six Korean female never-smoker patients.

hiPathDB: a human-integrated pathway database with facile visualization.

One of the biggest challenges in the study of biological regulatory networks is the systematic organization and integration of complex interactions taking place within various biological pathways. Currently, the information of the biological pathways is dispersed in multiple databases in various formats. hiPathDB is an integrated pathway database that combines the curated human pathway data of NCI-Nature PID, Reactome, BioCarta and KEGG.

GARNET--gene set analysis with exploration of annotation relations.

Background: Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information.

Clinical validation of colorectal cancer biomarkers identified from bioinformatics analysis of public expression data.

Purpose: Identification of novel biomarkers of cancer is important for improved diagnosis, prognosis, and therapeutic intervention. This study aimed to identify marker genes of colorectal cancer (CRC) by combining bioinformatics analysis of gene expression data and validation experiments using patient samples and to examine the potential connection between validated markers and the established oncogenes such as c-Myc and K-ras.

Experimental Design: Publicly available data from GenBank and Oncomine were meta-analyzed leading to 34 candidate marker genes of CRC.