Considering the recent increase in the number of colorectal cancer (CRC) cases in South Korea, we aimed to clarify the molecular characteristics of CRC unique to the Korean population. To gain insights into the complexities of CRC and promote the exchange of critical data, RNA-sequencing analysis was performed to reveal the molecular mechanisms that drive the development and progression of CRC; this analysis is critical for developing effective treatment strategies. We performed RNA-sequencing analysis of CRC and adjacent normal tissue samples from 214 Korean participants (comprising a total of 381 including 169 normal and 212 tumor samples) to investigate differential gene expression between the groups. We identified 19,575 genes expressed in CRC and normal tissues, with 3,830 differentially expressed genes (DEGs) between the groups. Functional annotation analysis revealed that the upregulated DEGs were significantly enriched in pathways related to the cell cycle, DNA replication, and IL-17, whereas the downregulated DEGs were enriched in metabolic pathways. We also analyzed the relationship between clinical information and subtypes using the Consensus Molecular Subtype (CMS) classification. Furthermore, we compared groups clustered within our dataset to CMS groups and performed additional analysis of the methylation data between DEGs and CMS groups to provide comprehensive biological insights from various perspectives. Our study provides valuable insights into the molecular mechanisms underlying CRC in Korean patients and serves as a platform for identifying potential target genes for this disease. The raw data and processed results have been deposited in a public repository for further analysis and exploration.

During the last decade, the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges, including access to human data, as well as transfer, storage, and sharing of enormous amounts of data. To promote data-driven biological research, the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station (K-BDS), which consists of multiple databases for individual data types. Here, we introduce the Korean Nucleotide Archive (KoNA), a repository of nucleotide sequence data. As of July 2022, the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects. To ensure data quality and prepare for international alignment, a standard operating procedure was adopted, which is similar to that of the International Nucleotide Sequence Database Collaboration. The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline, followed by manual examination. To ensure fast and stable data transfer, a high-speed transmission system called GBox is used in KoNA. Furthermore, the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express. This seamless coupling of KoNA, GBox, and Bio-Express enhances the data experience, including submission, access, and analysis of raw nucleotide sequences. KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics. The KoNA is available at https://www.kobic.re.kr/kona/.

NF-κB signaling through both canonical and non-canonical pathways plays a central role in immune responses and inflammation. NF-κB-inducing kinase (NIK) stabilization is a key step in activation of the non-canonical pathway and its dysregulation implicated in various hematologic malignancies. The tumor suppressor, p53, is an established cellular gatekeeper of proliferation. Abnormalities of the TP53 gene have been detected in more than half of all human cancers. While the non-canonical NF-κB and p53 pathways have been explored for several decades, no studies to date have documented potential cross-talk between these two cancer-related mechanisms. Here, we demonstrate that p53 negatively regulates NIK in an miRNA-dependent manner. Overexpression of p53 decreased the levels of NIK, leading to inhibition of the non-canonical NF-κB pathway. Conversely, its knockdown led to increased levels of NIK, IKKα phosphorylation, and p100 processing. Additionally, miR-34b induced by nutlin-3 directly targeted the coding sequences (CDS) of NIK. Treatment with anti-miR-34b-5p augmented NIK levels and subsequent non-canonical NF-κB signaling. Our collective findings support a novel cross-talk mechanism between non-canonical NF-κB and p53.

Genetically engineered animal tumor models have traditionally been generated by the gain of single or multiple oncogenes or the loss of tumor suppressor genes; however, the development of live animal models has been difficult given that cancer phenotypes are generally induced by somatic mutation rather than by germline genetic inactivation. In this study, we developed somatically mutated tumor models using TALEN-mediated somatic gene inactivation of cdkn2a/b or rb1 tumor suppressor genes in zebrafish. One-cell stage injection of cdkn2a/b-TALEN mRNA resulted in malignant peripheral nerve sheath tumors with high frequency (about 39%) and early onset (about 35 weeks of age) in F0 tp53e7/e7 mutant zebrafish. Injection of rb1-TALEN mRNA also led to the formation of brain tumors at high frequency (58%, 31 weeks of age) in F0 tp53e7/e7 mutant zebrafish. Analysis of each tumor induced by somatic inactivation showed that the targeted genes had bi-allelic mutations. Tumors induced by rb1 somatic inactivation were characterized as medulloblastoma-like primitive neuroectodermal tumors based on incidence location, histopathological features, and immunohistochemical tests. In addition, 3' mRNA Quanti-Seq analysis showed differential activation of genes involved in cell cycle, DNA replication, and protein synthesis; especially, genes involved in neuronal development were up-regulated.

In forensics, age prediction is useful to narrow down the number of potential suspects because it can provide some general characteristics for predicting appearance. Previous genome-wide studies based on DNA methylation have reported age prediction algorithms using a penalized multivariate regression method known as elastic net and a few dozen to hundreds of CpG sites. Although more CpG sites may provide better accuracy than fewer CpG sites, this approach is not applicable to forensics because the amounts of crime-scene DNA are usually limited. In this study, we selected three age-correlated CpG sites, namely cg16867657 (ELOVL2), which is known to be an excellent age predictor, cg04208403 (ZNF423), and cg19283806 (CCDC102B), from HumanMethylation450 BeadChip datasets of 1415 individuals. Furthermore, we evaluated these markers in a 535-sample training set and a 230-sample validation set from Korean individuals using a pyrosequencing platform. From the training set, an age prediction model using the multiple linear regression method explained 91.44% of age-correlated variation in DNA methylation patterns. The standard error of estimate and mean absolute deviation were 6.320 and 3.156 years, respectively. In the validation set, the standard error of estimate and mean absolute deviation were estimated as 6.853 and 3.346 years, respectively. For the validation set, the model explained 91.08% of the variation in methylation and predicted age (±6 years) with accuracy of 77.30% in the <60 years age group and 57.30% in the older group (≥60 years). These results suggest that our three DNA methylation markers may be useful for age prediction in samples from Asian populations.

Due to advances in omics technologies, numerous genome-wide studies on human samples have been published, and most of the omics data with the associated clinical information are available in public repositories, such as Gene Expression Omnibus and ArrayExpress. While analyzing several public datasets, we observed that errors in gender information occur quite often in public datasets. When we analyzed the gender description and the methylation patterns of gender-specific probes (glucose-6-phosphate dehydrogenase [G6PD], ephrin-B1 [EFNB1], and testis specific protein, Y-linked 2 [TSPY2]) in 5,611 samples produced using Infinium 450K HumanMethylation arrays, we found that 19 samples from 7 datasets were erroneously described. We also analyzed 1,819 samples produced using the Affymetrix U133Plus2 array using several gender-specific genes (X (inactive)-specific transcript [XIST], eukaryotic translation initiation factor 1A, Y-linked [EIF1AY], and DEAD [Asp-Glu-Ala-Asp] box polypeptide 3, Y-linked [DDDX3Y]) and found that 40 samples from 3 datasets were erroneously described. We suggest that the users of public datasets should not expect that the data are error-free and, whenever possible, that they should check the consistency of the data.

The mammalian cytoplasmic multi-tRNA synthetase complex (MSC) is a depot system that regulates non-translational cellular functions. Here we found that the MSC component glutamyl-prolyl-tRNA synthetase (EPRS) switched its function following viral infection and exhibited potent antiviral activity. Infection-specific phosphorylation of EPRS at Ser990 induced its dissociation from the MSC, after which it was guided to the antiviral signaling pathway, where it interacted with PCBP2, a negative regulator of mitochondrial antiviral signaling protein (MAVS) that is critical for antiviral immunity. This interaction blocked PCBP2-mediated ubiquitination of MAVS and ultimately suppressed viral replication. EPRS-haploid (Eprs+/-) mice showed enhanced viremia and inflammation and delayed viral clearance. This stimulus-inducible activation of MAVS by EPRS suggests an unexpected role for the MSC as a regulator of immune responses to viral infection.

Abstract Backgrounds There is a crucial need for practical molecular markers of bladder cancer recurrence, despite several molecular signatures for the bladder cancer outcomes have been numerously investigated. Here, we aim to identify a molecular signature consisting of small number of genes to predict disease recurrence in non-muscle invasive bladder cancer (NMIBC) and to assess its usefulness as a practical indicator. Methods Trascriptomic profiling was performed using gene expression data from 103 primary NMIBC specimens (Korean cohort) to identify a signature associated with disease recurrence. The prognostic value of the signature was validated in an independent cohort (European cohort, n = 302). Time-dependent receiver operating characteristic (ROC) curves of recurrence using the nearest neighbour estimation method with a cut-off value of 36 months were used to identify a small number of genes that strongly retain prognostic value. A prognostic index (PI) based on the expression data of 20 genes was developed in the Korean cohort and validated in the European cohort. The association between the 20-gene-based PI method and prognosis of NMIBC patients was assessed using Kaplan-Meier plot, the log-rank test, Cox proportional hazards model, and leave-one-out cross validation methods. Results The determination of gene expression patterns by transcriptome data analysis identified 822 genes associated with disease recurrence. Of the 822 genes, 20 genes which are highly associated with recurrence free survival were detected by time-dependent ROC curves. The PI was developed by using Cox coefficient values of 20 genes in the Korean cohort and its robustness was validated in the European cohort (log-rank test, P < 0.001). The PI was shown to be an independent risk factor by a multivariate analysis and subset stratification according to stage and (hazard ratio = 6.082, 95% confidence interval = 3.280 to 11.279, P < 0.001). The subset analysis also revealed that the PI could identify patients who would benefit from intravesical therapy. Finally, gene network analyses and experimental assays indicated that, among the 20 genes, CA9, ARTS-1 and FGF11 could be important mediators for NMIBC recurrence. Conclusions The PI system based on 20 genes illustrates a novel diagnostic tool to identify NMIBC patients that have a high risk of recurrence. Citation Format: Jong Hwan Kim, Seon-Kyu Kim, Seok-Joong Yun, Wun-Jae Kim, Seon-Young Kim. Prognostic index system based on 20 genes for predicting recurrence of non-muscle invasive bladder cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 592. doi:10.1158/1538-7445.AM2015-592

SUMMARY Because cancer has heterogeneous clinical behaviors due to the progressive accumulation of multiple genetic and epigenetic alterations, the identification of robust molecular signatures for predicting cancer outcome is profoundly important. Here, we introduce the APPEX Web-based analysis platform as a versatile tool for identifying prognostic molecular signatures that predict cancer diversity. We incorporated most of statistical methods for survival analysis and implemented seven survival analysis workflows, including CoxSingle, CoxMulti, IntransSingle, IntransMulti, SuperPC, TimeRoc and multivariate. A total of 236 publicly available datasets were collected, processed and stored to support easy independent validation of prognostic signatures. Two case studies including disease recurrence and bladder cancer progression were described using different combinations of the seven workflows. AVAILABILITY AND IMPLEMENTATION APPEX is freely available at http://www.appex.kr. CONTACT kimsy@kribb.re.kr SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

DNA methylation, which occurs at the 5′-position of the cytosine in CpG dinucleotides, has great potential for forensic identification of body fluids, because tissue-specific patterns of DNA methylation have been demonstrated, and DNA is less prone to degradation than proteins or RNA. Previous studies have reported several body fluid-specific DNA methylation markers, but DNA methylation differences are sometimes low in saliva and vaginal secretions. Moreover, specific DNA methylation markers in four types of body fluids (blood, saliva, semen, and vaginal secretions) have not been investigated with genome-wide profiling. Here, we investigated novel DNA methylation markers for identification of body fluids for use in forensic science using the Illumina HumanMethylation 450K bead array, which contains over 450,000 CpG sites. Using methylome data from 16 samples of blood, saliva, semen, and vaginal secretions, we first selected 2986 hypermethylated or hypomethylated regions that were specific for each type of body fluid. We then selected eight CpG sites as novel, forensically relevant DNA methylation markers: cg06379435 and cg08792630 for blood, cg26107890 and cg20691722 for saliva, cg23521140 and cg17610929 for semen, and cg01774894 and cg14991487 for vaginal secretions. These eight selected markers were evaluated in 80 body fluid samples using pyrosequencing, and all showed high sensitivity and specificity for identification of the target body fluid. We suggest that these eight DNA methylation markers may be good candidates for developing an effective molecular assay for identification of body fluids in forensic science.

Chemoresistance is one of the most serious problems in the treatment of cancer. In the present study, we show that Fn14 promotes resistance to 5-fluorouracil (5-FU) in gastric cancer (GC). We found that 5-FU treatment upregulated Fn14 expression in various cancer cell lines, including GC cell lines, and that knockdown of Fn14 using shRNA accelerated 5-FU sensitivity. In contrast, Fn14 overexpression or TWEAK treatment promoted resistance to 5-FU. Furthermore, we investigated the mechanisms underlying Fn14-mediated chemoresistance. We first revealed that 5-FU-mediated upregulation of Fn14 occurred as a result of NF-κB activation, indicating that 5-FU-mediated NF-κB activation was the principal event underlying Fn14 upregulation and 5-FU resistance in GC. Taken together, our results suggest that Fn14 is a novel therapeutic target and that inhibition of Fn14 combined with 5-FU treatment may be an effective molecular therapeutic strategy to treat 5-FU-resistant gastric cancers.