The formation of new blood vessels in solid tumors is regulated by various endothelial trophic factors. We identified that CLEC11A, an extracellular C-type lectin, was over-expressed in lung cancer cell lines harboring mutated EGFR. CLEC11A expression was also frequently elevated in lung adenocarcinoma (LAC) tissues with EGFR mutation. CLEC11A-expressing H1299 cells formed larger tumors in nude mice than did the control cells. The CLEC11A-expressing tumors contained more CD31-positive cells, suggesting that they had a higher angiogenic activity. CLEC11A per se did not induce blood vessel formation, but enhanced angiogenesis triggered by VEGF-A or basic FGF in vivo. Additionally, the expression of small hairpin RNA against CLEC11A (shCLEC11A) in HCC827 LAC cells suppressed their tumorigenic ability. Purified CLEC11A exhibited a chemotactic ability, which is dependent on its integrin-binding RGD and LDT motifs, toward endothelial cells. This chemotactic activity was not affected by the presence of a VEGFR inhibitor. Conditioned medium produced by HCC827-shCLEC11A cells had diminished chemotactic ability toward endothelial cells. CLEC11A treatments increased the levels of active integrin β1 that were not associated with activation of focal adhesion kinases in endothelial cells. Our results indicated that CLEC11A was a factor of angiogenic potential and was involved in lung cancer tumorigenesis.

Anthracycline-induced cardiomyopathy has been noted as a non-neglectable issue in the field of clinical oncology. Remarkable progress has been achieved in searching for inherited susceptible genetic deficits underlying anthracycline cardiotoxicity in the past several years. In this case report, we present the preliminary results of a genetic study in a young male patient who was treated with standard dose anthracycline-based chemotherapy for his acute myeloid leukemia and attacked by acute congestive heart failure after just two courses of therapy. After a survey of 76 target genes, an in-frame deletion of the titin gene was recognized as the most possible genetic defect responsible for his cardiomyopathy caused by anthracycline. This defect proved to pass down from the patient′s mother and did not exist in seven unrelated chemotherapy-treated cancer patients without chemotherapy-induced cardiomyopathy and four other healthy volunteer DNA donors.

Primary Cutaneous Amyloidosis (PCA) is a skin-limited disorder more common in Southeast Asian. Previous studies have identified mutations located in a fibronectin type III-like repeat domain of OSMR gene, including p.G513D (c.1538G > A). To investigate the genetic background of PCA, we recruited a consecutive series of 91 unrelated PCA patients, and subjected to whole-exome sequencing (WES) for genomic analysis. We also analyzed population genomic data from Taiwan, Japan, Singapore, Vietnam, Brazil, and the USA to evaluate the distribution of OSMR variants across different countries and ethnicities. A genetic screening program was conducted on 37,770 individuals at a hospital using the Taiwan Precision Medicine Initiative array (TPMI). The OSMR variant, c.1538G > A p.G513D, was identified in 24.18% (22/91) of patients with PCA, compared to only 2.61% (39/1,495) in the control group from Taiwan Biobank (OR = 11.90; 95% CI: 6.69-21.17; p < 0.0001). Its proportion was higher among East Asians, particularly in Taiwanese, Vietnamese, and Chinese Singaporeans, and nearly absent in European or Japanese populations. A hospital-based genetic screening revealed that 2.5% (944/37,770) of individuals carried the OSMR p.G513D variant. Notably, 57.14% (4/7) of homozygous individuals were diagnosed with PCA, compared to 1.39% (13/937) of heterozygous individuals (OR = 94.77; 95% CI: 19.24-466.70; p < 0.0001). These findings establish OSMR p.G513D as a population-specific risk allele for PCA and highlight the need for ancestry-aware genetic screening in Southeast Asians.

Background: To enhance the efficiency of identifying rare variants within the Taiwanese population and to support genome-wide association studies (GWAS) and imputation studies for genetic risk prediction in the Han population, we have developed the National Health Research Institutes (NHRI) reference panel (NHRI-RP-1). Methods: NHRI-RP-1 is based on 2,561 whole genome sequences taken from the in-house NHRI datasets. Our objective was to optimize conditions of sample sizes (0.5K, 1K, 1.5K, 2K, 2.5K), minor allele frequency (MAF) thresholds (MAF ≥ 0.05, 0.01, 0.001, 2 × 10 ^–4 ), and imputation quality (r ² ≥ 0, 0.3, 0.5) to build an aggregated genome reference panel for genetic medicine by comparing with worldwide references. Clinical applications and GWAS were then evaluated to demonstrate the capability of the reference panel. Results: Among different combinations of relevant parameters, the NHRI-RP-1 (with a 2,500-sample size, MAF ≥ 2 × 10 ^–4 , r ² ≥ 0) demonstrated a superior F1 score on local match, genotype concordance and r-squared, as compared to those using worldwide reference genomes, particularly for rare MAFs. Furthermore, NHRI-RP-1 achieved over 95% accuracy for nine pathogenic variants present in the Taiwan Biobank and 93.49% and 92.9% accuracy for imputing two DRD1 variants. Conclusions: The use of different reference panels can influence the outcomes of GWAS. Our case studies demonstrate the utility of the NHRI-RP-1 for genetic medicine. Incorporating a population-specific panel such as NHRI-RP-1 can facilitate the development of prediction models using polygenic risk scores for diseases that are common in the Han population.

Background/Objectives: Cell-free DNA (cfDNA) fragmentomics from low-coverage whole-genome sequencing (lcWGS) is a promising approach for non-invasive cancer detection. However, most existing methods summarize millions of cfDNA fragments into handcrafted sample-level features before classification, potentially discarding informative patterns carried by individual molecules. We aimed to develop and benchmark a framework that learns directly from fragment-level signals. Methods: We developed FragMIL, a fragment-token multiple-instance learning framework that represents each cfDNA molecule as a learnable token integrating end-motif, genomic-position, and fragment-length information, and aggregates thousands of fragment tokens into a patient-level cancer score. FragMIL was evaluated on 934 samples from three public lcWGS cohorts (pan-cancer, lung cancer, and hepatocellular carcinoma) using five repeated subject-level splits, a 288-configuration design-space benchmark, and comparison with four established fragmentomic approaches (coverage, DELFI, end motif, and fragment size). Results: FragMIL achieved the highest mean areas under the receiver operating characteristic curve (AUROCs) in every cohort, with 0.963 ± 0.009, 0.802 ± 0.009, and 0.910 ± 0.015 in the DELFI/Cristiano 2019, LUCAS/Mathios 2021, and Jiang 2015 cohorts, respectively. End-motif encoding provided the strongest standalone discriminative signal, whereas the optimal fragment pool was cohort-dependent, with open chromatin region fragments performing best for pan-cancer detection and tumor-enriched fragments for disease-specific cohorts. Performance was retained across cancer stages and cancer types. Conclusions: Preserving molecule-level fragmentomic information improves cancer detection, supporting fragment-token learning as a promising framework for next-generation cfDNA fragmentomics.