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Abstract Although alternative splicing (AS) is a major mechanism that adds diversity to gene expression patterns, its precise role in generating variability in ribosomal proteins, known as ribosomal heterogeneity, remains unclear. The ribosomal protein S24 (RPS24) gene, encoding a ribosomal component, undergoes AS; however, in-depth studies have been challenging because of three microexons between exons 4 and 6. We conducted a detailed analysis of RPS24 AS isoforms using a direct approach to investigate the splicing junctions related to these microexons, focusing on four AS isoforms. Each of these isoforms showed tissue specificity and relative differences in expression among cancer types. Significant differences in the proportions of these RPS24 AS isoforms between cancerous and normal tissues across diverse cancer types were also observed. Our study highlighted a significant correlation between the expression levels of a specific RPS24 AS isoform and the epithelial–mesenchymal transition process in lung and breast cancers. Our research contributes to a better understanding of the intricate regulatory mechanisms governing AS of ribosomal protein genes and highlights the biological implications of RPS24 AS isoforms in tissue development and tumorigenesis.

Primary myelofibrosis (PMF) is a myeloid proliferative neoplasm (MPN) characterized by bone marrow (BM) fibrosis. Pre-fibrotic PMF (pre-PMF) progresses to overt PMF. Megakaryocytes (MKs) play a primary role in PMF; however, the functions of MK subsets and those of other hematopoietic cells during PMF progression remain unclarified. Therefore, we analyzed BM aspirates in pre-PMFs, overt PMFs, and other MPNs using single-cell RNA sequencing (scRNA-seq). We identified 14 cell types with subsets, including hematopoietic stem and progenitor cells (HSPCs) and MKs. HSPCs in overt PMF were MK-biased and inflammation/fibrosis-enriched. Among MKs, the epithelial-mesenchymal transition (EMT)-enriched subset was abruptly increased in overt PMF. MKs in non-fibrotic/non-PMF MPN were MK differentiation-enriched, whereas those in fibrotic/non-PMF MPN were inflammation/fibrosis-enriched. Overall, the inflammation/fibrosis signatures of the HSPC, MK, and CD14+ monocyte subsets increased from pre-PMF to overt PMF. Cytotoxic and dysfunctional scores also increased in T and NK cells. Clinically, MK and HSPC subsets with high inflammation/fibrosis signatures were frequent in the patients with peripheral blood blasts ≥1%. scRNA-seq predicted higher cellular communications of MK differentiation, inflammation/fibrosis, immunologic effector/dysfunction, and tumor-associated signaling in overt PMF than pre-PMF. However, no decisive subset emerged during PMF progression. Our study demonstrated that HSPCs, monocytes, and lymphoid cells contribute to PMF progression, and subset specificity existed regarding inflammation/fibrosis and immunologic dysfunction. PMF progression may depend on multiple cell types’ alterations, and EMTenriched MKs may be potential targets for the diagnosis and therapy of the progression.

Abstract Background Drug-resistant tuberculosis (TB) is a major threat to global public health. Whole-genome sequencing (WGS) is a useful tool for species identification and drug resistance prediction, and many clinical laboratories are transitioning to WGS as a routine diagnostic tool. However, user-friendly and high-confidence automated bioinformatics tools are needed to rapidly identify M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), detect drug resistance, and further guide treatment options. Results We developed GenoMycAnalyzer, a web-based software that integrates functions for identifying MTBC and NTM species, lineage and spoligotype prediction, variant calling, annotation, drug-resistance determination, and data visualization. The accuracy of GenoMycAnalyzer for genotypic drug susceptibility testing (gDST) was evaluated using 5,473 MTBC isolates that underwent phenotypic DST (pDST). The GenoMycAnalyzer database was built to predict the gDST for 15 antituberculosis drugs using the World Health Organization mutational catalogue. Compared to pDST, the sensitivity of drug susceptibilities by the GenoMycAnalyzer for first-line drugs ranged from 95.9% for rifampicin (95% CI 94.8–96.7%) to 79.6% for pyrazinamide (95% CI 76.9–82.2%), whereas those for second-line drugs ranged from 98.2% for levofloxacin (95% CI 90.1–100.0%) to 74.9% for capreomycin (95% CI 69.3–80.0%). Notably, the integration of large deletions of the four resistance-conferring genes increased gDST sensitivity. The specificity of drug susceptibilities by the GenoMycAnalyzer ranged from 98.7% for amikacin (95% CI 97.8–99.3%) to 79.5% for ethionamide (95% CI 76.4–82.3%). The incorporated Kraken2 software identified 1,284 mycobacterial species with an accuracy of 98.8%. GenoMycAnalyzer also perfectly predicted lineages for 1,935 MTBC and spoligotypes for 54 MTBC. Conclusions GenoMycAnalyzer offers both web-based and graphical user interfaces, which can help biologists with limited access to high-performance computing systems or limited bioinformatics skills. By streamlining the interpretation of WGS data, the GenoMycAnalyzer has the potential to significantly impact TB management and contribute to global efforts to combat this infectious disease. GenoMycAnalyzer is available at http://www.mycochase.org .

Abstract This study aimed to identify somatic mutations in nontumor cells (NSMs) in normal prostate and benign prostatic hyperplasia (BPH) and to determine their relatedness to prostate cancer (PCA). From 22 PCA patients, two prostates were sampled for 3-dimensional mapping (50 normal, 46 BPH and 1 PCA samples), and 20 prostates were trio-sampled (two normal or BPH samples and one PCA sample) and analyzed by whole-genome sequencing. Normal and BPH tissues harbored several driver NSMs and copy number alterations (CNAs), including in FOXA1, but the variations exhibited low incidence, rare recurrence, and rare overlap with PCAs. CNAs, structural variants, and mutation signatures were similar between normal and BPH samples, while BPHs harbored a higher mutation burden, shorter telomere length, larger clone size, and more private NSMs than normal prostates. We identified peripheral-zonal dominance and right-side asymmetry in NSMs, but the asymmetry was heterogeneous between samples. In one normal prostate, private oncogenic RAS-signaling NSMs were detected, suggesting convergence in clonal maintenance. Early embryonic mutations exhibited two distinct distributions, characterized as layered and mixed patterns. Our study identified that the BPH genome differed from the normal prostate genome but was still closer to the normal genome than to the PCA genome, suggesting that BPH might be more related to aging or environmental stress than to tumorigenic processes.

Abstract Background Although meningioma is the most common primary brain tumor, treatments rely on surgery and radiotherapy, and recurrent meningiomas have no standard therapeutic options due to a lack of clinically relevant research models. Current meningioma cell lines or organoids cannot reflect biological features of patient tumors since they undergo transformation along culture and consist of only tumor cells without microenvironment. We aim to establish patient-derived meningioma organoids (MNOs) preserving diverse cell types representative of the tumor microenvironment. Methods The biological features of MNOs were evaluated using WST, LDH, and collagen-based 3D invasion assays. Cellular identities in MNOs were confirmed by immunohistochemistry (IHC). Genetic alteration profiles of MNOs and their corresponding parental tumors were obtained by whole-exome sequencing. Results MNOs were established from four patients with meningioma (two grade 1 and two grade 2) at a 100% succession rate. Exclusion of enzymatic dissociation-reaggregation steps endowed MNOs with original histology and tumor microenvironment. In addition, we used a liquid media culture system instead of embedding samples into Matrigel, resulting in an easy-to-handle, cost-efficient, and time-saving system. MNOs maintained their functionality and morphology after long-term culture (> 9 wk) and repeated cryopreserving-recovery cycles. The similarities between MNOs and their corresponding parental tumors were confirmed by both IHC and whole-exome sequencing. As a representative application, we utilized MNOs in drug screening, and mifepristone, an antagonist of progesterone receptor, showed prominent antitumor efficacy with respect to viability, invasiveness, and protein expression. Conclusion Taken together, our MNO model overcame limitations of previous meningioma models and showed superior resemblance to parental tumors. Thus, our model could facilitate translational research identifying and selecting drugs for meningioma in the era of precision medicine.

Background: Although PD-1 blockade is effective for treating several types of cancer, the efficacy of this agent in glioblastoma is largely limited. To overcome non-responders and the immunosuppressive tumor microenvironment, combinational immunotherapeutic strategies with anti-PD-1 need to be considered. Here, we developed IL-12-secreting mesenchymal stem cells (MSC_IL-12) with glioblastoma tropism and evaluated the therapeutic effects of anti-PD-1, MSC_IL-12, and their combination against glioblastoma. Methods: Therapeutic responses were evaluated using an immunocompetent mouse orthotopic model. Tumor-infiltrating lymphocytes (TILs) were analyzed using immunofluorescent imaging. Single-cell transcriptome was obtained from mouse brains after treatments. Results: Anti-PD-1 and MSC_IL-12 showed complete tumor remission in 25.0% (4/16) and 23.1% (3/13) of glioblastoma-implanted mice, respectively, and their combination yielded synergistic antitumor efficacy indicated by 50.0% (6/12) of complete tumor remission. Analyses of TILs revealed that anti-PD-1 increased CD8+ T cells, while MSC_IL-12 led to infiltration of CD4+ T cells and NK cells. Both therapies reduced frequencies of Tregs. All these aspects observed in each monotherapy group were superimposed in the combination group. Notably, no tumor growth was observed upon rechallenge in cured mice, indicating long-term immunity against glioblastoma provoked by the therapies. Single-cell RNA-seq data confirmed these results and revealed that the combined treatment led to immune-favorable tumor microenvironment–CD4+, CD8+ T cells, effector memory T cells, and activated microglia were increased, whereas exhausted T cells, Tregs, and M2 polarized microglia were reduced. Conclusion: Anti-PD-1 and MSC_IL-12 monotherapies show long-term therapeutic responses, and their combination further enhances antitumor efficacy against glioblastoma via inducing immune-favorable tumor microenvironment.

Abstract Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of AS in cancer research, the role of AS has not been systematically studied, especially in understanding cancer molecular classification. Herein, we analyzed the molecular subtype-specific regulation of AS using The Cancer Genome Atlas data and constructed a web-based database, named Alternative Splicing for Cancer Molecular Classification (AS-CMC). Our system harbors three analysis modules for exploring subtype-specific AS events, evaluating their phenotype association, and performing pan-cancer comparison. The number of subtype-specific AS events was found to be diverse across cancer types, and some differentially regulated AS events were recurrently found in multiple cancer types. We analyzed a subtype-specific AS in exon 11 of mitogen-activated protein kinase kinase 7 (MAP3K7) as an example of a pan-cancer AS biomarker. This AS marker showed significant association with the survival of patients with stomach adenocarcinoma. Our analysis revealed AS as an important determinant for cancer molecular classification. AS-CMC is the first web-based resource that provides a comprehensive tool to explore the biological implications of AS events, facilitating the discovery of novel AS biomarkers.

Many studies have demonstrated the mechanisms of progression to castration-resistant prostate cancer (CRPC) and novel strategies for its treatment. Despite these advances, the molecular mechanisms underlying the progression to CRPC remain unclear, and currently, no effective treatments for CRPC are available. Here, we characterized the key genes involved in CRPC progression to gain insight into potential therapeutic targets. Bicalutamide-resistant prostate cancer cells derived from LNCaP were generated and named Bical R. RNA sequencing was used to identify differentially expressed genes (DEGs) between LNCaP and Bical R. In total, 631 DEGs (302 upregulated genes and 329 downregulated genes) were identified. The Cytohubba plug-in in Cytoscape was used to identify seven hub genes (ASNS, AGT, ATF3, ATF4, DDIT3, EFNA5, and VEGFA) associated with CRPC progression. Among these hub genes, ASNS and DDIT3 were markedly upregulated in CRPC cell lines and CRPC patient samples. The patients with high expression of ASNS and DDIT3 showed worse disease-free survival in patients with The Cancer Genome Atlas (TCGA)-prostate adenocarcinoma (PRAD) datasets. Our study revealed a potential association between ASNS and DDIT3 and the progression to CRPC. These results may contribute to the development of potential therapeutic targets and mechanisms underlying CRPC progression, aiming to improve clinical efficacy in CRPC treatment.

Cellular composition and function are not clearly defined in heart failure after myocardial infarction. Here, using single cell and spatial transcriptomics in a MI-HF mouse model, the authors show that macrophages expressing Trem2 are found within the infarcts and this could be a useful biomarker.

Abstract Background Recent deep sequencing technologies have proven to be valuable resources to gain insights into the expression profiles of diverse tRNAs. However, despite these technologies, the association of tRNAs with diverse diseases has not been explored in depth because analytical tools are lacking. Results We developed a user-friendly tool, tRNA Expression Analysis Software Utilizing R for Easy use (tReasure), to analyze differentially expressed tRNAs (DEtRNAs) from deep sequencing data of small RNAs using R packages. tReasure can quantify individual mature tRNAs, isodecoders, and isoacceptors. By adopting stringent mapping strategies, tReasure supports the precise measurement of mature tRNA read counts. The whole analysis workflow for determining DEtRNAs (uploading FASTQ files, removing adapter sequences and poor-quality reads, mapping and quantifying tRNAs, filtering out low count tRNAs, determining DEtRNAs, and visualizing statistical analysis) can be performed with the tReasure package. Conclusions tReasure is an open-source software available for download at https://treasure.pmrc.re.kr and will be indispensable for users who have little experience with command-line software to explore the biological implication of tRNA expression.

Background: To decipher mutational signatures and their associations with biological implications in cutaneous melanomas (CMs), including those with a low ultraviolet (UV) signature.Materials and Methods: We applied non-negative matrix factorization (NMF) and unsupervised clustering to the 96-class mutational context of The Cancer Genome Atlas (TCGA) cohort (N = 466) as well as other publicly available datasets (N = 527). To explore the feasibility of mutational signature-based classification using panel sequencing data, independent panel sequencing data were analyzed.Results: NMF decomposition of the TCGA cohort and other publicly available datasets consistently found two mutational signatures: UV (SBS7a/7b dominant) and non-UV (SBS1/5 dominant) signatures. Based on mutational signatures, TCGA CMs were classified into two clusters: UV-high and UV-low. CMs belonging to the UV-low cluster showed significantly worse overall survival and landmark survival at 1-year than those in the UV-high cluster; low or high UV signature remained the most significant prognostic factor in multivariate analysis. The UV-low cluster showed distinct genomic and functional characteristic patterns: low mutation counts, increased proportion of triple wild-type and KIT mutations, high burden of copy number alteration, expression of genes related to keratinocyte differentiation, and low activation of tumor immunity. We verified that UV-high and UV-low clusters can be distinguished by panel sequencing.Conclusion: Our study revealed two mutational signatures of CMs that divide CMs into two clusters with distinct clinico-genomic characteristics. Our results will be helpful for the clinical application of mutational signature-based classification of CMs.

Although surgery followed by platinum-based therapy is effective as a standard treatment in the early stages of ovarian cancer, the majority of cases are diagnosed at advanced stages, leading to poor prognosis. Thus, the identification of novel therapeutic drugs is needed. In this study, we assessed the effectiveness of bepridil—a calcium channel blocker—in ovarian cancer cells using two cell lines: SKOV-3, and SKOV-3-13 (a highly metastatic clone of SKOV-3). Treatment of these cell lines with bepridil significantly reduced cell viability, migration, and invasion. Notably, SKOV-3-13 was more sensitive to bepridil than SKOV-3. The TGF-β1-induced epithelial–mesenchymal transition (EMT)-like phenotype was reversed by treatment with bepridil in both cell lines. Consistently, expression levels of EMT-related markers, including vimentin, β-catenin, and Snail, were also substantially decreased by the treatment with bepridil. An in vivo mouse xenograft model was used to confirm these findings. Tumor growth was significantly reduced by bepridil treatment in SKOV-3-13-inoculated mice, and immunohistochemistry showed consistently decreased expression of EMT-related markers. Our findings are the first to report anticancer effects of bepridil in ovarian cancer, and they suggest that bepridil holds significant promise as an effective therapeutic agent for targeting metastatic ovarian cancer.

Abstract Predicting the risk of metastasis before starting prostate cancer (PCa) treatment can minimize the overtreatment of indolent cases and help choosing appropriate treatment. The levels of circulating microRNAs (miRNAs) from body fluids can be used as noninvasive prognostic biomarkers. In this study, urinary exosomal miRNA expression profiles of 149 PCas were determined and the miRNAs associated with metastasis were identified: miR-21, miR-16, miR-142-3p, miR-451, and miR-636. When evaluating clinical factors together, miR-21, miR-451, miR-636, and preoperative prostate-specific antigen (PSA) level remained significant in the multivariate analysis. Based on them, we developed a “Prostate Cancer Metastasis Risk Scoring (PCa-MRS)” model. The PCa-MRS showed superior stratification power (AUC = 0.925) to preoperative PSA or clinical Gleason score. Patients with high scores showed significantly poorer biochemical recurrence-free survival than those with low scores (P = 6.53 × 10−10). Our results showed the potential of urinary exosomal miRNAs as noninvasive markers for predicting metastasis and prognosis in PCa patients.

Abstract Background Dedifferentiated liposarcoma (DDLPS), which accounts for an estimated 15–20% of liposarcomas, is a high-grade and aggressive malignant neoplasm, exhibiting a poor response to available therapeutic agents. However, genetic alteration profiles of DDLPS as well as the role of NF1 mutations have not been studied extensively. Case presentation The current study reports a patient presenting with rapidly growing DDLPS accompanied by multiple lung and pleural metastases, in whom whole-exome sequencing revealed a NF1 truncating mutation of the known pathogenic variant, c.C7486T, p.R2496X, as well as multiple copy number alterations (CNAs), including the well-known 12q13–15 amplification, and multiple chromothripsis events encompassing potential cancer-related genes. Conclusions Our results suggest that, in addition to the 12q13–15 amplification, NF1 inactivation mutation and other CNAs may contribute to DDLPS tumorigenesis accompanied by aggressive clinical features.

Abstract Background Bacterial isolates with multiple plasmids harbouring different carbapenemase genes have emerged and been identified repeatedly, despite a general notion that plasmids confer fitness cost in bacterial host. In this study, we investigated the effects of plasmids with carbapenemase genes on the fitness and virulence of bacteria. Methods Different plasmids harbouring the carbapenemase genes, bla NDM-1 and bla OXA-232, were isolated from a carbapenem-resistant K. pneumoniae strain. Each plasmid was conjugated into the Escherichia coli strain DH5α, and a transconjugant with both plasmids was also obtained by transformation. Their in vitro competitive ability, biofilm formation, serum resistance, survival ability within macrophage and fruit fly, and fly killing ability were evaluated. Results The transconjugants with a single plasmid showed identical phenotypes to the plasmid-free strain, except that they decreased fly survival after infection. However, significantly increased fitness, virulence and biofilm production were observed consistently for the transconjugant with both plasmids, harbouring bla NDM-1 and bla OXA-232. Conclusions Our data indicate that bacteria carrying multiple plasmids encoding different carbapenemases may have increased fitness and virulence, emphasizing the need for diverse strategies to combat antimicrobial resistance.

Trichophyton rubrum and Trichophyton mentagrophytes are the main causative pathogens of onychomycosis. However, the sensitivity and specificity of conventional microscopic tests are insufficient for reliable diagnoses of onychomycosis. In this study, we developed loop-mediated isothermal amplification (LAMP) assays for the rapid and specific identification of the two major Trichophytons spp. We designed LAMP primers targeting the internal transcribed spacer 1 region of the T. rubrum and T. mentagrophytes. Through rigorous optimization of the reaction conditions, we defined a universal reaction condition for both LAMP assays.

Highly pathogenic avian influenza (HPAI) viruses have caused severe respiratory disease and death in poultry and human beings. Although most of the avian influenza viruses (AIVs) are of low pathogenicity and cause mild infections in birds, some subtypes including hemagglutinin H5 and H7 subtype cause HPAI. Therefore, sensitive and accurate subtyping of AIV is important to prepare and prevent for the spread of HPAI. Next-generation sequencing (NGS) can analyze the full-length sequence information of entire AIV genome at once, so this technology is becoming a more common in detecting AIVs and predicting subtypes. However, an analysis pipeline of NGS-based AIV sequencing data, including AIV subtyping, has not yet been established. Here, in order to support the pre-processing of NGS data and its interpretation, we developed a user-friendly tool, named prediction of avian influenza virus subtype (PAIVS). PAIVS has multiple functions that support the pre-processing of NGS data, reference-guided AIV subtyping, de novo assembly, variant calling and identifying the closest full-length sequences by BLAST, and provide the graphical summary to the end users.

Prostate cancer: Promising protein biomarker A protein found in high levels in prostate cancer tissues could provide a biomarker and therapeutic target for the disease. Prostate cancer (PCa) is a common cause of cancer-related death, yet existing biomarkers cannot reliably predict PCa risk. The search for a novel biomarker led Yeun-Jun Chung at the Catholic University of Korea in Seoul, South Korea, and co-workers to examine the role of the trefoil factor family 3 (TFF3) protein. TFF3 overexpression is implicated in tumor invasion and in limiting tumor cell death in many cancers, including PCa. Chung’s team analyzed TFF3 levels in 108 cases of PCa and found they were significantly higher than in normal prostate tissues. Blocking the overexpression of TFF3 in two PCa cell lines limited tumor cell growth and migration, and increased cancer cell death.

Cancer immunotherapy: Improving animal models Improvements to mouse models for cancer immunotherapy could enhance the precision of new drugs. Immunotherapy trials require genetically modified animal models, including ‘humanized’ mice with a functioning human immune system, and patient-derived xenograft (PDX) mice, in which cells from patients’ tumors are implanted into immunodeficient mice. Charles Lee at the Jackson Laboratory for Genomic Medicine in Farmington, USA, Yeun-Jun Chung at the Catholic University of Korea in Seoul, and co-workers reviewed developments in both PDX and humanized-PDX mouse models for immunotherapy trials. PDX models improve the chances of finding novel biomarkers for drug development. However, humanized PDX mouse models will allow researchers to study diverse cancers in tumour and immune environments as close as possible to those of humans.

Patient-derived xenograft (PDX) models are useful tools for tumor biology research and testing the efficacy of candidate anticancer drugs targeting the druggable mutations identified in tumor tissue. However, it is still unknown how much of the genetic alterations identified in primary tumors are consistently detected in tumor tissues in the PDX model. In this study, we analyzed the genetic alterations of three primary colorectal cancers (CRCs) and matched xenograft tissues in PDX models using a next-generation sequencing cancer panel. Of the 17 somatic mutations identified from the three CRCs, 14 (82.4%) were consistently identified in both primary and xenograft tumors. The other three mutations identified in the primary tumor were not detected in the xenograft tumor tissue. There was no newly identified mutation in the xenograft tumor tissues. In addition to the somatic mutations, the copy number alteration profiles were also largely consistent between the primary tumor and xenograft tissue. All of these data suggest that the PDX tumor model preserves the majority of the key mutations detected in the primary tumor site. This study provides evidence that the PDX model is useful for testing targeted therapies in the clinical field and research on precision medicine.

Abstract Background Han Chinese, Japanese and Korean, the three major ethnic groups of East Asia, share many similarities in appearance, language and culture etc., but their genetic relationships, divergence times and subsequent genetic exchanges have not been well studied. Results We conducted a genome-wide study and evaluated the population structure of 182 Han Chinese, 90 Japanese and 100 Korean individuals, together with the data of 630 individuals representing 8 populations wordwide. Our analyses revealed that Han Chinese, Japanese and Korean populations have distinct genetic makeup and can be well distinguished based on either the genome wide data or a panel of ancestry informative markers (AIMs). Their genetic structure corresponds well to their geographical distributions, indicating geographical isolation played a critical role in driving population differentiation in East Asia. The most recent common ancestor of the three populations was dated back to 3000 ~ 3600 years ago. Our analyses also revealed substantial admixture within the three populations which occurred subsequent to initial splits, and distinct gene introgression from surrounding populations, of which northern ancestral component is dominant. Conclusions These estimations and findings facilitate to understanding population history and mechanism of human genetic diversity in East Asia, and have implications for both evolutionary and medical studies.

Accurate detection of genomic alterations, especially druggable hotspot mutations in tumors, has become an essential part of precision medicine. With targeted sequencing, we can obtain deeper coverage of reads and handle data more easily with a relatively lower cost and less time than whole-exome or whole-genome sequencing. Recently, we designed a customized gene panel for targeted sequencing of major solid cancers. In this study, we aimed to validate its performance. The cancer panel targets 95 cancer-related genes. In terms of the limit of detection, more than 86% of target mutations with a mutant allele frequency (MAF) 3% MAF can be detected. When we applied this system for the analysis of Acrometrix Oncology Hotspot Control DNA, which contains more than 500 COSMIC mutations across 53 genes, 99% of the expected mutations were robustly detected. We also confirmed the high reproducibility of the detection of mutations in multiple independent analyses. When we explored copy number alterations (CNAs), the expected CNAs were successfully detected, and this result was confirmed by target-specific genomic quantitative polymerase chain reaction. Taken together, these results support the reliability and accuracy of our cancer panel in detecting mutations. This panel could be useful for key mutation profiling research in solid tumors and clinical translation.

Ankylosing spondylitis (AS) is a chronic autoinflammatory disease that affects the spine and sacroiliac joints. Regarding its etiology, although HLA-B27 is known to be the strongest genetic factor of AS, much evidence suggests the potential contribution of non-MHC genes to the susceptibility to AS. Most of these non-MHC genes have been discovered in non-Asian populations; however, just some of them have been validated in Koreans. In this study, we aimed to identify additional AS-associated single-nucleotide polymorphism (SNP) candidates by replicating the candidate SNPs in Korean AS patients and healthy controls. For this, we selected three SNPs (rs11249215 in RUNX3, rs6556416 in IL12B, and rs8070463 in TBKBP1), which were previously reported as risk factors of AS but have not been studied in Koreans, and performed genotyping assays using a total of 1138 Korean samples (572 AS patients and 566 healthy controls). Of the three SNP candidates, one SNP in RUNX3 (rs11249215) was significantly associated with the risk of AS (odds ratio, 1.31; 95% confidence interval, 1.02 to 1.68, p = 0.03). These results will be helpful in elucidating the pathogenesis of AS and may be useful for developing AS risk prediction models in Koreans.

Robust identification of genetic alterations is important for the diagnosis and subsequent treatment of tumors. Screening for genetic alterations using tumor tissue samples may lead to biased interpretations because of the heterogeneous nature of the tumor mass. Liquid biopsy has been suggested as an attractive tool for the non-invasive follow-up of cancer treatment outcomes. In this study, we aimed to verify whether the mutations identified in primary tumor tissue samples could be consistently detected in plasma cell–free DNA (cfDNA) by digital polymerase chain reaction (dPCR). We first examined the genetic alteration profiles of three colorectal cancer (CRC) tissue samples by targeted next-generation sequencing (NGS) and identified 11 non-silent amino acid changes across six cancer-related genes (APC, KRAS, TP53, TERT, ARIDIA, and BRCA1). All three samples had KRAS mutations (G12V, G12C, and G13D), which were well-known driver events. Therefore, we examined the KRAS mutations by dPCR. When we examined the three KRAS mutations by dPCR using tumor tissue samples, all of them were consistently detected and the variant allele frequencies (VAFs) of the mutations were almost identical between targeted NGS and dPCR. When we examined the KRAS mutations using the plasma cfDNA of the three CRC patients by dPCR, all three mutations were consistently identified. However, the VAFs were lower (range, 0.166% to 2.638%) than those obtained using the CRC tissue samples. In conclusion, we confirmed that the KRAS mutations identified from CRC tumor tissue samples were consistently detected in the plasma cfDNA of the three CRC patients by dPCR.

The acquisition of somatic mutations is the most common event in cancer. Neoantigens expressed from genes with mutations acquired during carcinogenesis can be tumor-specific. Since the immune system recognizes tumor-specific peptides, they are potential targets for personalized neoantigen-based immunotherapy. However, the discovery of druggable neoantigens remains challenging, suggesting that a deeper understanding of the mechanism of neoantigen generation and better strategies to identify them will be required to realize the promise of neoantigen-based immunotherapy. Alternative splicing and RNA editing events are emerging mechanisms leading to neoantigen production. In this review, we outline recent work involving the large-scale screening of neoantigens produced by alternative splicing and RNA editing. We also describe strategies to predict and validate neoantigens from RNA sequencing data.

Due to the increasing interest in synonymous codons, several codon bias-related terms were introduced. As one measure of them, the tRNA adaptation index (tAI) was invented about a decade ago. The tAI is a measure of translational efficiency for a gene and is calculated based on the abundance of intracellular tRNA and the binding strength between a codon and a tRNA. The index has been widely used in various fields of molecular evolution, genetics, and pharmacology. Afterwards, an improved version of the index, named specific tRNA adaptation index (stAI), was developed by adapting tRNA copy numbers in species. Although a subsequently developed webserver (stAIcalc) provided tools that calculated stAI values, it was not available to access pre-calculated values. In addition to about 100 species in stAIcalc, we calculated stAI values for whole coding sequences in 148 species. To enable easy access to this index, we constructed a novel web database, named STADIUM (Species-specific tRNA adaptive index compendium). STADIUM provides not only the stAI value of each gene but also statistics based on pathway-based classification. The database is expected to help researchers who have interests in codon optimality and the role of synonymous codons. STADIUM is freely available at http://stadium.pmrc.re.kr.

Since the introduction of the pneumococcal conjugate vaccine, an increase in the incidence of Streptococcus pneumoniae serotype 19A and sequence type 320 (19A-ST320) isolates have been observed worldwide including in South Korea. We conducted a genome-wide analysis to investigate the temporal genetic changes in 26 penicillin-non-susceptible 19A-ST320 pneumococcal isolates from a hospital in South Korea over a period of 17 years (1999; 2004 to 2015). Although the strains were isolated from a single hospital and showed the same genotype and serotype, a whole-genome sequencing (WGS) analysis revealed that the S. pneumoniae isolates showed more extensive genetic variations compared with a reference isolate obtained in 1999. A phylogenetic analysis based on single nucleotide polymorphisms (SNPs) showed that the pneumococcal isolates from South Korea were not grouped together into limited clusters among the 19A-ST320 isolates from several continents. It was predicted that recombination events occurred in 11 isolates; larger numbers of SNPs were found within recombination blocks compared with point mutations identified in five isolates. WGS data indicated that S. pneumoniae 19A-ST320 isolates might have been introduced into South Korea from various other countries. In addition, it was revealed that recombination may play a great role in the evolution of pneumococci even in very limited places and periods.

The development of an in vitro three-dimensional (3D) culture system with cryopreserved biospecimens could accelerate experimental research screening anticancer drugs, potentially reducing costs and time bench-to-beside. However, minimal research has explored the application of 3D bioprinting-based in vitro cancer models to cryopreserved biospecimens derived from patients with advanced melanoma. We investigated whether 3D-printed collagen scaffolds enable the propagation and maintenance of patient-derived melanoma explants (PDMEs). 3D-printed collagen scaffolds were fabricated with a 3DX bioprinter. After thawing, fragments from cryopreserved PDMEs (approximately 1–2 mm) were seeded onto the 3D-printed collagen scaffolds, and incubated for 7 to 21 days. The survival rate was determined with MTT and live and dead assays. Western blot analysis and immunohistochemistry staining was used to express the function of cryopreserved PDMEs. The results show that 3D-printed collagen scaffolds could improve the maintenance and survival rate of cryopreserved PDME more than 2D culture. MITF, Mel A, and S100 are well-known melanoma biomarkers. In agreement with these observations, 3D-printed collagen scaffolds retained the expression of melanoma biomarkers in cryopreserved PDME for 21 days. Our findings provide insight into the application of 3D-printed collagen scaffolds for closely mimicking the 3D architecture of melanoma and its microenvironment using cryopreserved biospecimens.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects multiple organ systems. Although the etiology of SLE remains unclear, it is widely accepted that genetic factors could be involved in its pathogenesis. A number of genome-wide association studies (GWASs) have identified novel single-nucleotide polymorphisms (SNPs) associated with the risk of SLE in diverse populations. However, not all the SNP candidates identified from non-Asian populations have been validated in Koreans. In this study, we aimed to replicate the SNPs that were recently discovered in the GWAS; these SNPs have not been validated in Koreans or have only been replicated in Koreans with an insufficient sample size to conclude any association. For this, we selected five SNPs (rs1801274 in FCGR2A and rs2286672 in PLD2, rs887369 in CXorf21, rs9782955 in LYST, and rs3794060 in NADSYN1). Through the replication study with 656 cases and 622 controls, rs1801274 in FCGR2A was found to be significantly associated with SLE in Koreans (odds ratio, 1.26, 95% confidence interval, 1.06 to 1.50; p = 0.01 in allelic model). This association was also significant in two other models (dominant and recessive). The other four SNPs did not show a significant association. Our data support that FCGR polymorphisms play important roles in the susceptibility to SLE in diverse populations, including Koreans.

Tumor tissues from biopsies or surgery are major sources for the next generation sequencing (NGS) study, but these procedures are invasive and have limitation to overcome intratumor heterogeneity. Recent studies have shown that driver alterations in tumor tissues can be detected by liquid biopsy which is a less invasive technique capable of both capturing the tumor heterogeneity and overcoming the difficulty in tissue sampling. However, it is still unclear whether the driver alterations in liquid biopsy can be detected by targeted NGS and how those related to the tissue biopsy. In this study, we performed whole-exome sequencing for a breast cancer tissue and identified PTEN p.H259fs*7 frameshift mutation. In the plasma DNA (liquid biopsy) analysis by targeted NGS, the same variant initially identified in the tumor tissue was also detected with low variant allele frequency. This mutation was subsequently validated by digital polymerase chain reaction in liquid biopsy. Our result confirm that driver alterations identified in the tumor tissue were detected in liquid biopsy by targeted NGS as well, and suggest that a higher depth of sequencing coverage is needed for detection of genomic alterations in a liquid biopsy.

BackgroundAddictive use of the Internet and online games is a potential psychiatric disorder termed Internet gaming disorder (IGD). Altered microRNA (miRNA) expression profiles have been reported in blood and brain tissue of patients with certain psychiatric disorders and suggested as biomarkers. However, there have been no reports on blood miRNA profiles in IGD.MethodsTo discover IGD-associated miRNAs, we analyzed the miRNA expression profiles of 51 samples (25 IGD and 26 controls) using the TaqMan Low Density miRNA Array. For validation, we performed quantitative reverse transcription PCR with 36 independent samples (20 IGD and 16 controls).ResultsThrough discovery and independent validation, we identified three miRNAs (hsa-miR-200c-3p, hsa-miR-26b-5p, hsa-miR-652-3p) that were significantly downregulated in the IGD group. Individuals with all three miRNA alterations had a much higher risk of IGD than those with no alteration [odds ratio (OR) 22, 95% CI 2.29–211.11], and the ORs increased dose dependently with number of altered miRNAs. The predicted target genes of the three miRNAs were associated with neural pathways. We explored the protein expression of the three downstream target genes by western blot and confirmed that expression of GABRB2 and DPYSL2 was significantly higher in the IGD group.ConclusionWe observed that expressions of hsa-miR-200c-3p, hsa-miR-26b-5p, and hsa-miR-652-3p were downregulated in the IGD patients. Our results will be helpful to understand the pathophysiology of IGD.

Next-generation sequencing (NGS) is widely used to identify the causative mutations underlying diverse human diseases, including cancers, which can be useful for discovering the diagnostic and therapeutic targets. Currently, a number of single-nucleotide variant (SNV)-calling algorithms are available; however, there is no tool for visualizing the recurrent and phenotype-specific mutations for general researchers. In this study, in order to support defining the recurrent mutations or phenotype-specific mutations from NGS data of a group of cancers with diverse phenotypes, we aimed to develop a user-friendly tool, named mutation arranger for defining phenotype-related SNV (MAP). MAP is a user-friendly program with multiple functions that supports the determination of recurrent or phenotype-specific mutations and provides graphic illustration images to the users. Its operation environment, the Microsoft Windows environment, enables more researchers who cannot operate Linux to define clinically meaningful mutations with NGS data from cancer cohorts.

In November 2013, the US Food and Drug Administration (FDA) sent a warning letter to 23andMe, Inc. and ordered the company to discontinue marketing of the 23andMe Personal Genome Service (PGS) until it receives FDA marketing authorization for the device. The FDA considers the PGS as an unclassified medical device, which requires premarket approval or de novo classification. Opponents of the FDA's action expressed their concerns, saying that the FDA is overcautious and paternalistic, which violates consumers' rights and might stifle the consumer genomics field itself, and insisted that the agency should not restrict direct-to-consumer (DTC) genomic testing without empirical evidence of harm. Proponents support the agency's action as protection of consumers from potentially invalid and almost useless information. This action was also significant, since it reflected the FDA's attitude towards medical application of next-generation sequencing techniques. In this review, we followed up on the FDA-23andMe incident and evaluated the problems and prospects for DTC genetic testing.

The rapid advances in genetic knowledge and technology raise various, sometimes unprecedented, ethical dilemmas in the scientific community as well as the public realm. To deal with these dilemmas, the international community has prepared and issued ethical standards in various formats. In this review, seven international standards regarding genetics and genomics will be briefly introduced in chronological order. Critical reflections on them will not be provided in this review, and naturally, they have their own problems and shortcomings. However, a common set of the principles expressed in them will be highlighted here, because they are still relevant, and many of them will be more relevant in the future. Some of the interesting contents will be selected and described. After that, the morality of one recent event related to whole-genome sequencing and person-identifiable genetic data will be explored based on those international standards.

The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional FST measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the FST estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.

We have discovered copy number variations (CNVs) in 3,578 Korean individuals with the Affymetrix Genome-Wide SNP array 5.0, and 4,003 copy number variation regions (CNVRs) were defined in a previous study. To explore the details of the variants easily in related studies, we built a database, cataloging the CNVs and related information. This system helps researchers browsing these variants with gene and structure variant annotations. Users can easily find specific regions with search options and verify them from system-integrated genome browsers with annotations.

C-reactive protein (CRP) is a general marker of systemic inflammation and cardiovascular disease (CVD). The genetic contribution to differences in CRP levels remains to be explained, especially in non-European populations. Thus, the aim of this study was to identify genetic loci associated with CRP levels in Korean population. We performed genome-wide association studies (GWAS) using SNPs from 8,529 Korean individuals (7,626 for stage 1 and 903 for stage 2). We also performed pathway analysis. We identified a new genetic locus associated with CRP levels upstream of ARG1 gene (top significant SNP: rs9375813, Pmeta = 2.85×10(-8)), which encodes a key enzyme of the urea cycle counteract the effects of nitric oxide, in addition to known CRP (rs7553007, Pmeta = 1.72×10(-16)) and HNF1A loci (rs2259816, Pmeta = 2.90×10(-10)). When we evaluated the associations between the CRP-related SNPs with cardiovascular disease phenotypes, rs9375813 (ARG1) showed a marginal association with hypertension (P = 0.0440). To identify more variants and pathways, we performed pathway analysis and identified six candidate pathways comprised of genes related to inflammatory processes and CVDs (CRP, HNF1A, PCSK6, CD36, and ABCA1). In addition to the previously reported loci (CRP, HNF1A, and IL6) in diverse ethnic groups, we identified novel variants in the ARG1 locus associated with CRP levels in Korean population and a number of interesting genes related to inflammatory processes and CVD through pathway analysis.

BACKGROUND: Unlike Caucasian populations, genetic factors contributing to the risk of type 2 diabetes mellitus (T2DM) are not well studied in Asian populations. In light of this, and the fact that copy number variation (CNV) is emerging as a new way to understand human genomic variation, the objective of this study was to identify type 2 diabetes-associated CNV in a Korean cohort. METHODOLOGY/PRINCIPAL FINDINGS: Using the Illumina HumanHap300 BeadChip (317,503 markers), genome-wide genotyping was performed to obtain signal and allelic intensities from 275 patients with type 2 diabetes mellitus (T2DM) and 496 nondiabetic subjects (Total n = 771). To increase the sensitivity of CNV identification, we incorporated multiple factors using PennCNV, a program that is based on the hidden Markov model (HMM). To assess the genetic effect of CNV on T2DM, a multivariate logistic regression model controlling for age and gender was used. We identified a total of 7,478 CNVs (average of 9.7 CNVs per individual) and 2,554 CNV regions (CNVRs; 164 common CNVRs for frequency>1%) in this study. Although we failed to demonstrate robust associations between CNVs and the risk of T2DM, our results revealed a putative association between several CNVRs including chr15:45994758-45999227 (P = 8.6E-04, P(corr) = 0.01) and the risk of T2DM. The identified CNVs in this study were validated using overlapping analysis with the Database of Genomic Variants (DGV; 71.7% overlap), and quantitative PCR (qPCR). The identified variations, which encompassed functional genes, were significantly enriched in the cellular part, in the membrane-bound organelle, in the development process, in cell communication, in signal transduction, and in biological regulation. CONCLUSION/SIGNIFICANCE: We expect that the methods and findings in this study will contribute in particular to genome studies of Asian populations.