Genome and Company (South Korea)

Checkpoint kinase 2 (CHEK2) encodes a serine/threonine kinase involved in the DNA damage response through ATM-Chk2-p53 signaling. Its function in maintaining genomic stability classifies it as a tumor suppressor. Heterozygous germline pathogenic variants in CHEK2 are associated with a moderate increase in lifetime risk of breast and prostate cancer. This study assessed the prevalence of CHEK2 variants globally, with a focus on East Asian and Korean populations, for which data have remained limited. We analyzed 125,748 exomes from the Genome Aggregation Database (gnomAD), including 9,197 East Asians, along with additional data from 5,305 individuals in the Korean Variant Archive, 3,617 in Korea4K, and 1,722 in the Korean Reference Genome Database. All CHEK2 variants were classified according to guidelines established by the American College of Medical Genetics, Genomics, and Clinical Genome Resources. The global prevalence of CHEK2 variants was 0.76%, with the highest observed in the Finnish population (2.04%) and the lowest in East Asians (0.11%). By integrating data from Korean genomic databases and gnomAD, representing a total of 12,553 Korean individuals, the overall prevalence in the Korean population was estimated at 0.13%. These findings represent the first integrated estimate of CHEK2 variant frequency in Koreans using multiple population-specific genomic datasets. The results provide a useful reference for future studies and highlight the need for region-specific genetic research to inform counseling and hereditary cancer risk management.

Abstract The small nucleoside molecule LJ‐4827 exhibited potent kinase inhibition and in vitro anticancer activity. Driven by bio‐isosteric principles, we synthesized LJ‐5157, which also demonstrated high kinase selectivity and anticancer efficacy. To further expand the structural diversity of bioactive nucleoside analogs, we developed a metal‐free, late‐stage strategy for converting terminal alkynes to nitriles using tert ‐butyl nitrite ( t BuONO). By substituting 2‐picoline N ‐oxide with N ‐methylmorpholine N ‐oxide (NMO) as the oxidant, we accomplished efficient nitrile formation in nucleoside scaffolds. This approach broadens the scope of alkyne cleavage chemistry and offers a practical route for analog diversification.

Contamination in low-biomass samples, such as urine, presents a major challenge for 16S rRNA gene sequencing, as extraneous DNA from reagents and the environment often obscures microbial signals. Existing in silico decontamination algorithms face limitations in accurately identifying and removing these contaminants. To address this issue, we developed CleanSeqU, a novel decontamination algorithm designed to enhance the accuracy of 16S rRNA gene sequencing data for catheterized urine samples. This approach is grounded in the principle that the compositional pattern of potential contaminant taxa remains similar between biological samples and blank controls. Also, the algorithm identifies potential contaminants based on ecological plausibility and custom blacklist. We evaluated CleanSeqU’s performance using vaginal microbiome dilution experiments as a proxy for low-biomass urine samples and compared it to the Decontam, Microdecon, and SCRuB algorithm. CleanSeqU consistently outperformed Decontam, Microdecon, and SCRuB across various contamination levels, with superior accuracy, F1-scores, and reduced beta-dissimilarity. CleanSeqU improved specificity and positive predictive value by correctly identifying and removing a higher number of contaminant amplicon sequence variants (ASVs). Furthermore, the reduced alpha diversity in the decontaminated datasets suggests more precise contaminant elimination. With its practical use of a single blank extraction control per batch and adjustable decontamination rules, CleanSeqU provides an efficient and scalable solution that delivers accurate microbial profiles. Our findings highlight its potential to significantly advance urine microbiome research by delivering more accurate microbial profiles.

The mechanistic link between the complex mutational landscape of de novo methyltransferase DNMT3A and the pathology of acute myeloid leukemia (AML) has not been clearly elucidated so far. Motivated by a recent discovery of the significance of DNMT3A-destabilizing mutations (DNMT3AINS) in AML, we here investigate the common characteristics of DNMT3AINS AML methylomes through computational analyses. We present that methylomes of DNMT3AINS AMLs are considerably different from those of DNMT3AR882 AMLs in that they exhibit increased intratumor DNA methylation heterogeneity in bivalent chromatin domains. This epigenetic heterogeneity was associated with the transcriptional variability of developmental and membrane-associated factors shaping stem cell niche, and also was a predictor of the response of AML cells to hypomethylating agents, implying that the survival of AML cells depends on stochastic DNA methylations at bivalent domains. Altogether, our work provides a novel mechanistic model suggesting the genomic origin of the aberrant epigenomic heterogeneity in disease conditions.

This study investigated the anti-inflammatory effects of OJlipo1, a lipocalin-like protein derived from Oenanthe javanica. Through cloning and expressing OJlipo1 in E. coli, and subsequent rigorous characterization including amino acid analysis and mass spectrometry, its potential against inflammation was evaluated. Studies on lipopolysaccharide-stimulated RAW 264.7 cells highlighted its capability to suppress nitric oxide synthase and cyclooxygenase-2 expression, as well as its interference with nuclear factor kappa B and mitogen-activated protein kinase pathways, which are essential for toll-like receptor 4 (TLR4) signaling. Utilizing TAK242, a TLR4 pathway inhibitor, reinforced OJlipo1's specific targeting mechanism. These findings underscore OJlipo1's significant anti-inflammatory potential, aligning with the traditional uses of O. javanica, and suggest new therapeutic avenues, especially for diseases associated with TLR4 dysregulation. This validates the traditional application of O. javanica in inflammation and positions OJlipo1 as a promising therapeutic candidate, enriching our understanding of its molecular underpinnings and therapeutic prospects.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan-Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10-5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10-4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with PCE did not significantly outperform the PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.

Abstract Background: With the emergence of new immune checkpoint inhibitors and tyrosine kinase inhibitors for advanced HCC, determining the optimal first-line therapy is challenging due to the lack of precise biomarkers. This underscores the urgent need for biomarker-based strategies for treatment decisions. Methods: This prospective biomarker study analyzed plasma cfDNA from 267 advanced HCC patients treated with first-line sorafenib (S) (n=212), lenvatinib (L) (n=32), or atezolizumab plus bevacizumab (AteBev) (n=23). Low-depth whole-genome sequencing was performed on cfDNA to identify genome-wide copy number alterations (CNAs). The 'I-score' was established to quantify genomic instability, calculated as the sum of absolute Z-scores of sequenced reads for each chromosome. The treatment outcomes of the three different therapies were compared based on the I-score. The I-score cutoff to differentiate high from low genomic instability was set the level separating progressive disease (PD) from non-PD at the first response evaluation .Results: Patient demographics and disease characteristics were predominantly male (90.6%) with a median age of 59 years. The majority had an ECOG performance status of 1 (55.4%), HBV etiology (81.3%), and were classified as Child-Pugh class A (88.8%), with most presenting at BCLC stage C (95.1%). The high I-score group (n=164) exhibited a higher prevalence of macrovascular invasion (56.8% vs. 24.6%; p&amp;lt;0.001), lymph node metastasis (39.6% vs. 27.2%; p=0.038), and bone metastasis (14.6% vs. 4.9%; p=0.012) but lower peritoneal metastasis (5.5% vs. 12.6%; p=0.039) compared to the low I-score group (n=103). The high I-score group showed a worse disease control rate (50.6% vs. 74.8%; p&amp;lt;0.001), shorter time to progression (TTP) (median, 2.1 vs. 4.3 months; p&amp;lt;0.001), and poorer overall survival (OS) (6.0 vs. 18.5 months; p&amp;lt;0.001) compared to the low I-score group. Treatment efficacy varied within the high I-score group, with AteBev showing the most favorable outcomes: the median TTP was 6.0 months for AteBev vs. 4.1 months for L vs. 1.8 months for S (p=0.005), and the median OS was not reached for AteBev vs. 7.6 months for L vs. 5.4 months for S (p=0.036). However, in the low I-score group, there were no significant differences in TTP and OS among the treatment types: the median TTP was 9.4 months for AteBev vs. 3.9 months for L vs. 4.2 months for S (p=0.665), and the median OS was not reached for AteBev vs. 9.9 months for L vs. 18.8 months for S (p=0.412). Conclusions: The I-score, reflecting genome-wide CNA in cfDNA, has potential as a prognostic biomarker for outcomes in advanced HCC patients receiving first-line treatments. It may be instrumental in guiding the selection of the most appropriate therapy. Citation Format: Sook Ryun Park, Bo Hyun Kim, Ye-eun Lee, Ju Hyun Shim, Danbi Lee, Jonggi Choi, Eun-Hae Cho. Optimizing first-line systemic therapy selection in advanced hepatocellular carcinoma (HCC): A biomarker approach using circulating cell-free DNA (cfDNA) (atezolizumab plus bevacizumab vs. lenvatinib vs. sorafenib) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 984.

BackgroundThere is limited data regarding the clinical outcomes of clonal hematopoiesis of indeterminate potential (CHIP) in patients with chronic obstructive pulmonary disease (COPD). This study aimed to evaluate the clinical significance of CHIP as a COPD biomarker.MethodsThis retrospective study was conducted on patients with COPD who were enrolled prospectively in the Seoul National University Hospital Airway Registry from January 2013 to December 2019 and underwent pulmonary function and blood tests. We evaluated the CHIP score according to smoking status and severity of airflow obstruction.ResultsWe analyzed next-generation sequencing data to detect CHIP in 125 patients with COPD. Current smokers had a higher prevalence of CHIP in combination of DNMT3A, TET2, and PPM1D (DTP), DNA methyltransferase 3 alpha (DNMT3A), and protein phosphatase, Mg2+/Mn2+ dependent 1D (PPM1D) genes than in never- or ex-smokers. CHIP of DTP and DNMT3A genes was significantly associated with current smokers (adjusted odds ratio [aOR], 2.80; 95% confidence interval [CI], 1.01 to 7.79) (aOR, 4.03; 95% CI, 1.09 to 14.0). Patients with moderate-to-severe airflow obstruction had a higher prevalence of CHIP in most of the explored genes than those with mild obstruction, although the difference was not statistically significant. CHIP in ASXL transcriptional regulator 1 (ASXL1) genes was significantly associated with history of mild, severe, and total acute exacerbation.ConclusionGiven that CHIP in specific genes was significantly associated with current smoking status and acute exacerbation, CHIP can be considered as a candidate biomarker for COPD patients.

In general, fetal cfDNA is shorter than maternal cfDNA, and accuracy of noninvasive prenatal testing (NIPT) results can be improved by selecting shorter cfDNA fragments to enrich fetal-derived cfDNA. This study investigated potential improvements in the accuracy of NIPT by performing classification and analysis based on differences in cfDNA size. We performed paired-end sequencing to identify size ranges of fetal and maternal cfDNA from 62,374 pregnant women. We then developed a size-selection method to isolate and analyze both fetal and maternal cfDNA, defining fetal-derived cfDNA as less than 150 bp and maternal-derived cfDNA as greater than 180 bp. By implementing size-selection method, the accuracy of NIPT was improved, resulting in an increase in the overall positive predictive value for all aneuploidies from 89.57% to 97.1%. This was achieved by enriching both fetal and maternal-derived cfDNA, which increased fetal DNA fraction while the number of false positives for all aneuploidies was reduced by more than 70%. We identified the differences in read length between fetal and maternal-derived cfDNA, and selectively enriched both shorter and longer cfDNA fragments for subsequent analysis. Our approach can increase the detection accuracy of NIPT for detecting fetal aneuploidies and reduce the number of false positives caused by maternal chromosomal abnormalities.