👤 Emiliano Bianchini

Conventional biomarkers such as low-density lipoprotein (LDL) and high-density lipoprotein may fail to identify patients' risk for significant coronary artery disease (CAD). This study evaluates the associations between multiple biomarkers and different CAD phenotypes, exploring a machine-learning biomarker-based patient clustering. We included 787 patients on primary prevention from the prospective ACTION registry (January 2024 to June 2025). All patients underwent coronary CTA and simultaneous biomarker testing, including LDL, high-density lipoprotein, triglyceride, apolipoprotein A-1, apolipoprotein B, lipoprotein(a) [Lp(a)], glycated hemoglobin (HbA1c), and high-sensitivity C-reactive protein. Of 382 patients (48.5%) with coronary artery calcium = 0, 42 (11%) had coronary plaque. These patients showed higher Lp(a) vs those without plaque (16.5 vs 11.5, P = .030), despite comparable SCORE2 risk (3.5% vs 3.0%, P = .284). Three biomarker-defined groups were identified after a machine learning unsupervised clustering: Cluster 1 had a favorable lipid profile with the lowest prevalence of CAD-Reporting and Data System (RADS) ≥ 3 (9.9%). Cluster 2 and 3, despite their significant intercluster differences in terms of Lp(a), LDL, and HbA1c levels, both showed a significantly higher prevalence of CAD-RADS ≥ 3 compared to cluster 1 (respectively 21.8% and 17.9%; vs cluster 1, P = .001). High-risk biomarker signatures were significantly associated to the prevalence of CAD-RADS ≥ 3, independently from the baseline SCORE2 (adjusted odds ratio 2.25; 95% confidence interval 1.32-3.82). Distinct biomarker signatures associate with distinct CAD prevalence and severity that conventional lipid markers fail to distinguish. Lp(a) appears relevant for early plaque detection in coronary artery calcium = 0 patients. A comprehensive biomarker evaluation may help identifying high-risk subgroups overlooked by a conventional assessment. Show less

While surgery is the usual treatment for localized well-differentiated and dedifferentiated liposarcomas (WDLPS/DDLPS), the therapeutic options for patients with advanced disease are limited. The classical antimitotic treatments are most often inefficient. The establishment of genetically characterized cell lines is therefore crucial for providing in vitro models for novel targeted therapies. We have used spectral karyotyping, fluorescence in situ hybridization with whole chromosome painting and locus-specific probes, and array-comparative genomic hybridization to identify the chromosomal and molecular alterations of a novel cell line established from a recurring sclerosing WDLPS. The karyotype was hypertriploid and showed multiple structural anomalies. All cells retained the presence of a giant marker chromosome that had been previously identified in the primary cell cultures. This giant chromosome contained high-level amplification of chromosomal regions 12q13-21 and lacked the alpha-satellite centromeric sequences associated with WDLPS/DDLPS. The 12q amplicon was large, containing 370 amplified genes. The DNA copy number ranged from 3 to 57. The highest levels of amplification were observed at 12q14.3 for GNS, WIF1, and HMGA2. We analyzed the mRNA expression status by real-time reverse transcription polymerase chain reaction for six genes from this amplicon: MDM2, HMGA2, CDK4, TSPAN31, WIF1, and YEATS4. mRNA overexpression was correlated with genomic amplification. A second amplicon originating from 10p11-14 was also present in the giant marker chromosome. The 10p amplicon contained 62 genes, including oncogenes such as MLLT10, previously described in chimeric fusion with MLL in leukemias, NEBL, and BMI1. Show less