Machine Learning-Driven discovery of immunogenic cell Death-Related biomarkers and molecular classification for diabetic ulcers.

In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers linked to immunogenic cell death (ICD) in DUs by utilizing RNA-sequencing data of Gene Expression Omnibus (GEO) analysis combined with a comprehensive database interrogation. Employing a random forest algorithm, we have developed a diagnostic model that demonstrates improved accuracy in distinguishing DUs from normal tissue, with satisfactory results from ROC analysis. Beyond mere diagnosis, our model categorizes DUs into novel molecular classifications, which may enhance our comprehension of their underlying pathophysiology. This study bridges the gap between molecular insights and clinical practice. It sets the stage for transformative strategies in DUs management, marking a significant step forward in personalized medicine for diabetic patients.

Low-Coverage Sequencing of Urine Sediment DNA for Detection of Copy Number Aberrations in Bladder Cancer.

PURPOSE: Chromosomal copy number aberrations (CNAs) are a hallmark of bladder cancer and a useful target for diagnostic explorations. Here we constructed a low-coverage whole-genome sequencing method for the detection of CNAs in urine sediment DNA from patients with bladder cancer. PATIENTS AND METHODS: We conducted a prospective study using urine sediment samples from 65 patients with bladder tumors, including 54 patients with bladder cancer and 11 patients with benign bladder tumors. Forty-three healthy individuals were included as normal controls. DNA was extracted from urine sediments and analyzed by low-coverage whole-genome sequencing to compare differences in CNAs among these three groups. CNAs are defined by arbitrary R values (normal range ± 2). When these values exceed ± 0.2 of normal range, gain/duplication or loss/deletion are suspected. RESULTS: With this method, CNAs were detected in 39 of 51 patients with bladder cancer, 2 of 10 patients with benign bladder tumors, and 8 of 39 normal controls. The lengths of DNA deletion and duplication were significantly larger in patients with bladder cancer than in patients with benign tumors or normal controls (P < 0.05). Bladder cancer duplicate CNAs mainly occurred on chromosomes 1q, 5p, 6p, 7p, 8q, and 13q, while deletions mainly occurred on 2q, 8p, 9q, 9p, and 11p. Those regions contained bladder cancer tumor-related genes, such as STK3, COX6C, SPAG1, CDKAL1, C9orf53, CDKN2A, CDKN2B, MIR31, and IFNA1. The number of CNAs detected in urine sediment DNA during the follow-up period was significantly reduced. CONCLUSION: Our sequencing method is highly sensitive and can detect a minimal chromosome repeat/microdeletion change of 0.15 Mb. The use of 0.1~0.3× low-coverage whole-genome sequencing can be used to detect bladder cancer CNAs in urine sediment DNA. This method provides a promising method for noninvasive diagnosis of bladder cancer, but still needs further verification in a larger sample size.