Anti-Inflammatory Effect of Korean Soybean Sauce (Ganjang) in Mice with Induced Colitis.

Inflammatory bowel disease (IBD), characterized by chronic inflammation of the gut, is caused by several factors. Among these factors, microbial factors are correlated with the gut microbiota, which produces short-chain fatty acids (SCFAs) via anaerobic fermentation. Fermented foods are known to regulate the gut microbiota composition. Ganjang (GJ), a traditional fermented Korean soy sauce consumed worldwide, has been shown to exhibit antioxidant, anticancer, anti-colitis, and antihypertensive activities. However, its effects on the gut microbiota remain unknown. In the present study, we aimed to compare the anti-inflammatory effects of GJ manufactured using different methods and investigate its effect on SCFA production in the gut. To evaluate the antiinflammatory effects of GJ in the gut, we performed animal experiments using a mouse model of dextran sulfate sodium (DSS)-induced colitis. All GJ samples attenuated DSS-induced colitis symptoms, including reduced colonic length, by suppressing the expression of inflammatory cytokines. In addition, GJ administration modulated SCFA production in the DSS-induced colitis model. Overall, GJ exerted anti-inflammatory effects by reducing DSS-induced symptoms via regulation of inflammation and modulation of SCFA levels in a DSS-induced colitis model. Thus, GJ is a promising fermented food with the potential to prevent IBD.

N-terminal acetylation of Set1-COMPASS fine-tunes H3K4 methylation patterns.

H3K4 methylation by Set1-COMPASS (complex of proteins associated with Set1) is a conserved histone modification. Although it is critical for gene regulation, the posttranslational modifications of this complex that affect its function are largely unexplored. This study showed that N-terminal acetylation of Set1-COMPASS proteins by N-terminal acetyltransferases (NATs) can modulate H3K4 methylation patterns. Specifically, deleting NatA substantially decreased global H3K4me3 levels and caused the H3K4me2 peak in the 5' transcribed regions to shift to the promoters. NatA was required for N-terminal acetylation of three subunits of Set1-COMPASS: Shg1, Spp1, and Swd2. Moreover, deleting Shg1 or blocking its N-terminal acetylation via proline mutation of the target residue drastically reduced H3K4 methylation. Thus, NatA-mediated N-terminal acetylation of Shg1 shapes H3K4 methylation patterns. NatB also regulates H3K4 methylation, likely via N-terminal acetylation of the Set1-COMPASS protein Swd1. Thus, N-terminal acetylation of Set1-COMPASS proteins can directly fine-tune the functions of this complex, thereby substantially shaping H3K4 methylation patterns.

The Relationship Between Fast Food Consumption and Daily Lifestyle Changes During School Closures Following the COVID-19 Pandemic: A Cross-Sectional Study Among Adolescents in Korea.

OBJECTIVE: Increased fast food consumption can have adverse effects on health and well-being among adolescents, posing a significant public health concern. The school closures due to the coronavirus disease-2019 (COVID-19) pandemic have led to changes in eating patterns and disrupted a balance diet among adolescents. This study explored the factors associated with fast food consumption among adolescents during school closures due to the COVID-19 pandemic. METHODS: A total of 1,710 middle and high school students in Gwangju, South Korea participated in a cross-sectional survey. The self-administered questionnaire included items assessing dietary intake, physical activity, sleep, media use, and sociodemographic information. The Patient Health Questonnaire-9, Generalized Anxiety Disorder-7, and three item version of the UCLA Loneliness Scale were also administered. Multivariable logistic regression was used to examine the factors associated with increased fast food consumption. RESULTS: Approximately 34.6% of the surveyed adolescents reported increased fast food consumption during school closures, as well as increased sleep duration, increased sedentary behaviors including watching TV and using the internet, and reduced physical activity. Multivariable logistic regression analysis revealed that fast food consumption during school closures was associated with irregular patterns of main meals and sleep, decreased physical activity, increased internet use, and a lack of daytime adult supervision. CONCLUSION: Our results highlight the need for dietary and lifestyle monitoring and guidelines to promote health among adolescents, especially during school closures. In conclusion, nutrition intervention programs aiming to limit fast food consumption and enhance healthy dietary habits among adolescents during long-term school closures are warranted.

AI-MARRVEL - A Knowledge-Driven AI System for Diagnosing Mendelian Disorders.

BACKGROUND: Diagnosing genetic disorders requires extensive manual curation and interpretation of candidate variants, a labor-intensive task even for trained geneticists. Although artificial intelligence (AI) shows promise in aiding these diagnoses, existing AI tools have only achieved moderate success for primary diagnosis. METHODS: AI-MARRVEL (AIM) uses a random-forest machine-learning classifier trained on over 3.5 million variants from thousands of diagnosed cases. AIM additionally incorporates expert-engineered features into training to recapitulate the intricate decision-making processes in molecular diagnosis. The online version of AIM is available at https://ai.marrvel.org. To evaluate AIM, we benchmarked it with diagnosed patients from three independent cohorts. RESULTS: AIM improved the rate of accurate genetic diagnosis, doubling the number of solved cases as compared with benchmarked methods, across three distinct real-world cohorts. To better identify diagnosable cases from the unsolved pools accumulated over time, we designed a confidence metric on which AIM achieved a precision rate of 98% and identified 57% of diagnosable cases out of a collection of 871 cases. Furthermore, AIM's performance improved after being fine-tuned for targeted settings including recessive disorders and trio analysis. Finally, AIM demonstrated potential for novel disease gene discovery by correctly predicting two newly reported disease genes from the Undiagnosed Diseases Network. CONCLUSIONS: AIM achieved superior accuracy compared with existing methods for genetic diagnosis. We anticipate that this tool may aid in primary diagnosis, reanalysis of unsolved cases, and the discovery of novel disease genes. (Funded by the NIH Common Fund and others.).

Estrogen-related receptor alpha promotes thyroid tumor cell survival via a tumor subtype-specific regulation of target gene networks.

Mortalin (encoded by HSPA9) is a mitochondrial chaperone often overexpressed in cancer through as-yet-unknown mechanisms. By searching different RNA-sequencing datasets, we found that ESRRA is a transcription factor highly correlated with HSPA9 in thyroid cancer, especially in follicular, but not C cell-originated, tumors. Consistent with this correlation, ESRRA depletion decreased mortalin expression only in follicular thyroid tumor cells. Further, ESRRA expression and activity were relatively high in thyroid tumors with oncocytic characteristics, wherein ESRRA and mortalin exhibited relatively high functional overlap. Mechanistically, ESRRA directly regulated HSPA9 transcription through a novel ESRRA-responsive element located upstream of the HSPA9 promoter. Physiologically, ESRRA depletion suppressed thyroid tumor cell survival via caspase-dependent apoptosis, which ectopic mortalin expression substantially abrogated. ESRRA depletion also effectively suppressed tumor growth and mortalin expression in the xenografts of oncocytic or ESRRA-overexpressing human thyroid tumor cells in mice. Notably, our Bioinformatics analyses of patient data revealed two ESRRA target gene clusters that contrast oncocytic-like and anaplastic features of follicular thyroid tumors. These findings suggest that ESRRA is a tumor-specific regulator of mortalin expression, the ESRRA-mortalin axis has higher significance in tumors with oncocytic characteristics, and ESRRA target gene networks can refine molecular classification of thyroid cancer.

Multi-omics analysis sandbox toolkit for swift derivations of clinically relevant genesets and biomarkers.

The utilization of multi-omics research has gained popularity in clinical investigations. However, effectively managing and merging extensive and diverse datasets presents a challenge due to its intricacy. This research introduces a Multi-Omics Analysis Sandbox Toolkit, an online platform designed to facilitate the exploration, integration, and visualization of datasets ranging from single-omics to multi-omics. This platform establishes connections between clinical data and omics information, allowing for versatile analysis and storage of both single and multi-omics data. Additionally, users can repeatedly utilize and exchange their findings within the platform. This toolkit offers diverse alternatives for data selection and gene set analysis. It also presents visualization outputs, potential candidates, and annotations. Furthermore, this platform empowers users to collaborate by sharing their datasets, analyses, and conclusions with others, thus enhancing its utility as a collaborative research tool. This Multi-Omics Analysis Sandbox Toolkit stands as a valuable asset in comprehensively grasping the influence of diverse factors in diseases and pinpointing potential biomarkers.

KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data.

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/.

Anti-Obesity Properties of Blackberries Fermented with L. plantarum JBMI F5 via Suppression of Adipogenesis Signaling Mechanisms.

Blackberries (Rubus fruticosus), which are known to include a variety of bioactive substances, have been extensively studied for their antioxidant properties. Blackberries possess multiple health beneficial effects, including anti-inflammation, anti-atherosclerosis, anti-tumor and immunomodulatory activity. However, the potential biological effects and precise molecular mechanisms of the fermented extracts remain largely unexplored. In this research, we demonstrate the effect of blackberries fermented with Lactobacillus for addressing obesity. We investigated the effect of blackberries fermented by Lactobacillus on mice fed a high-fat (60% kcal) diet for 12 weeks. Fermented blackberry administration reduced the body weight and epididymal fat caused by a high-fat diet compared to the obese group. The triglyceride and total cholesterol, which are blood lipid indicators, and the levels of leptin, which is an insulin resistance indicator, were significantly increased in the obese group but were significantly decreased in the fermented blackberries-treated group. Additionally, the expression of adipogenesis marker proteins, such as CEBPα, PPAR-γ and SREBP-1, was significantly increased in the obese group, whereas it was decreased in the fermented blackberries-treated group. These results suggest that fermented blackberries have a protective effect against high-fat-diet-induced obesity by inhibiting adipogenesis and are a potential candidate for the treatment of obesity.

Overexpression of heat shock protein 47 is associated with increased proliferation and metastasis in gastric cancer.

Here, we investigated that the heat shock protein 47 (HSP47) plays a crucial role in the progression of gastric cancer (GC). We analyzed HSP47 gene expression in GC cell lines and patient tissues. The HSP47 mRNA and protein expression levels were significantly higher in GC cell lines and tumor tissues compared to normal gastric mucosa. Using siRNA to silence the expression of HSP47 in GC cells resulted in a significant reduction in their proliferation, wound healing, migration, and invasion capacities. Additionally, we also showed that the mRNA expression of matrix metallopeptidase-7 (MMP-7), a metastasis-promoting gene, was significantly reduced in HSP47 siRNA-transfected GC cells. We confirmed that the HSP47 promoter region was methylated in the SNU-216 GC cell line expressing low levels of HSP47 and in most non-cancerous gastric tissues. It means that the expression of HSP47 is regulated by epigenetic regulatory mechanisms. These findings suggest that targeting HSP47, potentially through its promoter methylation, could be a useful new therapeutic strategy for treating GC.

Whole Genome Sequencing Analysis of Soybean Diversity Across Different Countries and Selection Signature of Korean Soybean Accession.

Soybean is an important agricultural crop known for its high protein and oil content, contributing to essential nutritional and health benefits for humans. Domesticated in China over 5000 years ago, soybean has since adapted to diverse environments and spread worldwide. This study aimed to investigate the genomic characteristics and population structures of 2,317 publicly available soybean whole-genome sequences from diverse geographical regions, including China, Korea, Japan, Europe, North America and South America. We used large-scale whole-genome sequencing data to perform high-resolution analyses to reveal the genetic characteristics of soybean accessions. Soybean accessions from China and Korea exhibited landrace characteristics, indicating higher genetic diversity and adaptation to local environments. On the other hand, soybean accessions from Japan, the European Union, and South America were found to have low genetic diversity due to artificial selection and breeding for agronomic traits. We also identified key variants and genes associated with the ability to adapt to different environments. In Korean soybean accessions, we observed strong selection signals for isoflavone synthesis, an adaptive trait critical for improving soybean adaptability, survival, and reproductive success by mitigating environmental stress. Identifying specific genomic regions showing unique patterns of selective sweeps for genes such as HIDH, CYP73A11, IFS1, and CYP81E11 associated with isoflavone synthesis provided valuable insights into potential adaptation mechanisms. Our research has significantly improved our understanding of soybean diversity at the genetic level. We have identified key genetic variants and genes influencing adaptability, laying the foundation for future advances in genomics-based breeding programs and crop improvement efforts.

Transcriptomic characteristics according to tumor size and SUVmax in papillary thyroid cancer patients.

The SUVmax is a measure of FDG uptake and is related with tumor aggressiveness in thyroid cancer, however, its association with molecular pathways is unclear. Here, we investigated the relationship between SUVmax and gene expression profiles in 80 papillary thyroid cancer (PTC) patients. We conducted an analysis of DEGs and enriched pathways in relation to SUVmax and tumor size. SUVmax showed a positive correlation with tumor size and correlated with glucose metabolic process. The genes that indicate thyroid differentiation, such as SLC5A5 and TPO, were negatively correlated with SUVmax. Unsupervised analysis revealed that SUVmax positively correlated with DNA replication(r = 0.29, p = 0.009), pyrimidine metabolism(r = 0.50, p < 0.0001) and purine metabolism (r = 0.42, p = 0.0001). Based on subgroups analysis, we identified that PSG5, TFF3, SOX2, SL5A5, SLC5A7, HOXD10, FER1L6, and IFNA1 genes were found to be significantly associated with tumor aggressiveness. Both high SUVmax PTMC and macro-PTC are enriched in pathways of DNA replication and cell cycle, however, gene sets for purine metabolic pathways are enriched only in high SUVmax macro-PTC but not in high SUVmax PTMC. Our findings demonstrate the molecular characteristics of high SUVmax tumor and metabolism involved in tumor growth in differentiated thyroid cancer.

CILP2 is a potential biomarker for the prediction and therapeutic target of peritoneal metastases in colorectal cancer.

Peritoneal metastases (PM) in colorectal cancer (CRC) is associated with a dismal prognosis. Identifying and exploiting new biomarkers, signatures, and molecular targets for personalised interventions in the treatment of PM in CRC is imperative. We conducted transcriptomic profiling using RNA-seq data generated from the primary tissues of 19 CRC patients with PM. Using our dataset established in a previous study, we identified 1422 differentially expressed genes compared to non-metastatic CRC. The profiling demonstrated no differential expression in liver and lung metastatic CRC. We selected 12 genes based on stringent criteria and evaluated their expression patterns in a validation cohort of 32 PM patients and 84 without PM using real-time reverse transcription-polymerase chain reaction. We selected cartilage intermediate layer protein 2 (CILP2) because of high mRNA expression in PM patients in our validation cohort and its association with a poor prognosis in The Cancer Genome Atlas. Kaplan-Meier survival analysis in our validation cohort demonstrated that CRC patients with high CILP2 expression had significantly poor survival outcomes. Knockdown of CILP2 significantly reduced the proliferation, colony-forming ability, invasiveness, and migratory capacity and downregulated the expression of molecules related to epithelial-mesenchymal transition in HCT116 cells. In an in vivo peritoneal dissemination mouse knockdown of CILP2 also inhibited CRC growth. Therefore, CILP2 is a promising biomarker for the prediction and treatment of PM in CRC.

Neutrophil diversity is associated with T-cell immunity and clinical relevance in patients with thyroid cancer.

Neutrophil heterogeneity is involved in autoimmune diseases, sepsis, and several cancers. However, the link between neutrophil heterogeneity and T-cell immunity in thyroid cancer is incompletely understood. We investigated the circulating neutrophil heterogeneity in 3 undifferentiated thyroid cancer (UTC), 14 differentiated thyroid cancer (DTC) (4 Stage IV, 10 Stage I-II), and healthy controls (n = 10) by transcriptomic data and cytometry. Participants with UTC had a significantly higher proportion of immature high-density neutrophils (HDN) and lower proportion of mature HDN in peripheral blood compared to DTC. The proportion of circulating PD-L1+ immature neutrophils were significantly increased in advanced cancer patients. Unsupervised analysis of transcriptomics data from circulating HDN revealed downregulation of innate immune response and T-cell receptor signaling pathway in cancer patients. Moreover, UTC patients revealed the upregulation of glycolytic process and glutamate receptor signaling pathway. Comparative analysis across tumor types and stages revealed the downregulation of various T-cell-related pathways, such as T-cell receptor signaling pathway and T-cell proliferation in advanced cancer patients. Moreover, the proportions of CD8+ and CD4+ T effector memory CD45RA+ (TEMRA) cells from peripheral blood were significantly decreased in UTC patients compared to DTC patients. Finally, we demonstrated that proportions of tumor-infiltrated neutrophils were increased and related with poor prognosis in advanced thyroid cancer using data from our RNA-seq and TCGA (The Cancer Genome Atlas) data. In conclusion, observed prevalence of circulating immature high-density neutrophils and their immunosuppressive features in undifferentiated thyroid cancers underscore the importance of understanding neutrophil dynamics in the context of tumor progression in thyroid cancer.

Proteogenomic Characterization Reveals Estrogen Signaling as a Target for Never-Smoker Lung Adenocarcinoma Patients without EGFR or ALK Alterations.

Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major genetic alterations observed in NSLA, and NSLA with these alterations have been well studied and can be treated with targeted therapies. To provide insights into the molecular profile of NSLA without EGFR and ALK alterations (NENA), we selected 141 NSLA tissues and performed proteogenomic characterization, including whole genome sequencing (WGS), transcriptomic, methylation EPIC array, total proteomic, and phosphoproteomic analyses. Forty patients with NSLA harboring EGFR and ALK alterations and seven patients with NENA with microsatellite instability were excluded. Genome analysis revealed that TP53 (25%), KRAS (22%), and SETD2 (11%) mutations and ROS1 fusions (14%) were the most frequent genetic alterations in NENA patients. Proteogenomic impact analysis revealed that STK11 and ERBB2 somatic mutations had broad effects on cancer-associated genes in NENA. DNA copy number alteration analysis identified 22 prognostic proteins that influenced transcriptomic and proteomic changes. Gene set enrichment analysis revealed estrogen signaling as the key pathway activated in NENA. Increased estrogen signaling was associated with proteogenomic alterations, such as copy number deletions in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14. Finally, saracatinib, an Src inhibitor, was identified as a potential drug for targeting activated estrogen signaling in NENA and was experimentally validated in vitro. Collectively, this study enhanced our understanding of NENA NSLA by elucidating the proteogenomic landscape and proposed saracatinib as a potential treatment for this patient population that lacks effective targeted therapies. SIGNIFICANCE: The proteogenomic landscape in never-smoker lung cancer without known driver mutations reveals prognostic proteins and enhanced estrogen signaling that can be targeted as a potential therapeutic strategy to improve patient outcomes.

Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups.

BACKGROUND: Phenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome-wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics. RESULTS: Here, we present 4,157 whole genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest genomic resource of the Korean Genome Project. It encompasses most of the variants with allele frequency >0.001 in Koreans, indicating that it sufficiently covered most of the common and rare genetic variants with commonly measured phenotypes for Koreans. Korea4K provides 45,537,252 variants, and half of them were not present in Korea1K (1,094 samples). We also identified 1,356 new genotype-phenotype associations that were not found by the Korea1K dataset. Phenomics analyses further revealed 24 significant genetic correlations, 14 pleiotropic associations, and 127 causal relationships based on Mendelian randomization among 37 traits. In addition, the Korea4K imputation reference panel, the largest Korean variants reference to date, showed a superior imputation performance to Korea1K across all allele frequency categories. CONCLUSIONS: Collectively, Korea4K provides not only the largest Korean genome data but also corresponding health check-up parameters and novel genome-phenome associations. The large-scale pathological whole genome-wide omics data will become a powerful set for genome-phenome level association studies to discover causal markers for the prediction and diagnosis of health conditions in future studies.

Analysis of CSF3R mutations in atypical chronic myeloid leukemia and other myeloid malignancies.

We report a series of patients with CSF3R-mutant (CSF3Rmut) atypical chronic myeloid leukemia (aCML), chronic neutrophilic leukemia (CNL) or other hematologic malignancies. We included 25 patients: 5 aCML and 4 CNL CSF3Rmut patients; 1 aCML, 2 CNL, and 2 myelodysplastic/myeloproliferative neoplasm, not otherwise specified patients without CSF3R mutation; and 11 CSF3Rmut patients with other diseases [8 acute myeloid leukemia (AML), 1 chronic myelomonocytic leukemia (CMML), 1 myelodysplastic syndrome (MDS), and 1 acute lymphoblastic leukemia (ALL)]. Patients with aCML or CNL were tested by Sanger sequencing and pyrosequencing to identify CSF3R T618I. Twenty-two patients underwent gene panel analysis. CSF3R mutations, mostly T618I (8/9), were found at high frequencies in both aCML and CNL patients [5/6 aCML and 4/6 CNL]. Two aCML patients in early adulthood with CSF3R T618I and biallelic or homozygous CEBPA mutations without other mutations presented with increased blasts and exhibited remission for >6 years after transplantation. The other 7 CSF3Rmut aCML or CNL patients were elderly adults who all had ASXL1 mutations and frequently presented with SEBP1 and SRSF2 mutations. Five AML patients had CSF3R exon 14 or 15 point mutations, and 6 other patients (3 AML, 1 CMML, 1 MDS, and 1 ALL) had truncating mutations, demonstrating differences in leukocyte counts and mutation status. In conclusion, CSF3R mutations were found at a higher frequency in aCML patients than in previous studies, which might reflect ethnic differences. Additional studies are needed to confirm these findings and the relationship between CSF3R and CEBPA mutations.

Anti-Obesity Effect and Signaling Mechanism of Potassium Poly-γ-Glutamate Produced by Bacillus subtilis Chungkookjang in High-Fat Diet-Induced Obese Mice.

The purpose of this work was to examine the effects of potassium poly-γ-glutamate (PGA-K) on mice fed a high-fat diet consisting of 60% of total calories for 12 weeks. PGA-K administration reduced the increase in body weight, epididymal fat, and liver weight caused by a high-fat diet compared to the obese group. The triglyceride, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol levels, which are blood lipid indicators, were significantly increased in the obese group but were significantly decreased in the PGA-K-treated group. The administration of PGA-K resulted in a significant inhibition of pro-inflammatory cytokines, including tumor necrosis factor α and interleukin 6. Moreover, the levels of leptin and insulin, which are insulin resistance indicators, significantly increased in the obese group but were significantly decreased in the PGA-K-treated group. These results suggest that PGA-K exhibits a protective effect against obesity induced by a high-fat diet, underscoring its potential as a candidate for obesity treatment.

Strategies for Overcoming Immune Evasion in Bladder Cancer.

Tumors intricately shape a highly immunosuppressive microenvironment, hampering effective antitumor immune responses through diverse mechanisms. Consequently, achieving optimal efficacy in cancer immunotherapy necessitates the reorganization of the tumor microenvironment and restoration of immune responses. Bladder cancer, ranking as the second most prevalent malignant tumor of the urinary tract, presents a formidable challenge. Immunotherapeutic interventions including intravesical BCG and immune checkpoint inhibitors such as atezolizumab, avelumab, and pembrolizumab have been implemented. However, a substantial unmet need persists as a majority of bladder cancer patients across all stages do not respond adequately to immunotherapy. Bladder cancer establishes a microenvironment that can actively hinder an efficient anti-tumor immune response. A deeper understanding of immune evasion mechanisms in bladder cancer will aid in suppressing recurrence and identifying viable therapeutic targets. This review seeks to elucidate mechanisms of immune evasion specific to bladder cancer and explore novel pathways and molecular targets that might circumvent resistance to immunotherapy.

Comparison of structural variant callers for massive whole-genome sequence data.

BACKGROUND: Detecting structural variations (SVs) at the population level using next-generation sequencing (NGS) requires substantial computational resources and processing time. Here, we compared the performances of 11 SV callers: Delly, Manta, GridSS, Wham, Sniffles, Lumpy, SvABA, Canvas, CNVnator, MELT, and INSurVeyor. These SV callers have been recently published and have been widely employed for processing massive whole-genome sequencing datasets. We evaluated the accuracy, sequence depth, running time, and memory usage of the SV callers. RESULTS: Notably, several callers exhibited better calling performance for deletions than for duplications, inversions, and insertions. Among the SV callers, Manta identified deletion SVs with better performance and efficient computing resources, and both Manta and MELT demonstrated relatively good precision regarding calling insertions. We confirmed that the copy number variation callers, Canvas and CNVnator, exhibited better performance in identifying long duplications as they employ the read-depth approach. Finally, we also verified the genotypes inferred from each SV caller using a phased long-read assembly dataset, and Manta showed the highest concordance in terms of the deletions and insertions. CONCLUSIONS: Our findings provide a comprehensive understanding of the accuracy and computational efficiency of SV callers, thereby facilitating integrative analysis of SV profiles in diverse large-scale genomic datasets.

Assessing the performance and utility of targeted next-generation sequencing for screening and genotyping of human papillomaviruses.

A next-generation sequencing (NGS)-based Ezplex HPV NGS kit (SML Genetree, Seoul, Korea) was used for human papillomavirus (HPV) screening. Of 885 cervical swab samples, HPV was detected in 162 samples. High-risk HPVs were detected in 82 samples, and other types of HPV were detected in 13 samples (HPV86, 71, 102, 91, and 114). At the read depth ≥ 500, NGS results exhibited 100 % agreement among repeated tests. HPV NGS results were compared with those of real-time PCR assays, Anyplex HPV28 (Seegene, Seoul, Korea) (n = 383) and Cobas HPV (Roche, Mannheim, Germany) (n = 64); concordances were 92.4 % and 95.0 %, respectively. Sanger sequencing of discordant results (n = 13) produced compatible results with those of HPV NGS. Pap smear abnormalities were detected in 31 patients (3.5 %), and 19 patients had high-risk HPV. Using HPV NGS for screening, rare HPV subtypes were detected, and quantitative values were obtained as read depth.