Refining risk prediction in pediatric acute lymphoblastic leukemia through DNA methylation profiling.

Acute lymphoblastic leukemia (ALL) is the most prevalent cancer in children, and despite considerable progress in treatment outcomes, relapses still pose significant risks of mortality and long-term complications. To address this challenge, we employed a supervised machine learning technique, specifically random survival forests, to predict the risk of relapse and mortality using array-based DNA methylation data from a cohort of 763 pediatric ALL patients treated in Nordic countries. The relapse risk predictor (RRP) was constructed based on 16 CpG sites, demonstrating c-indexes of 0.667 and 0.677 in the training and test sets, respectively. The mortality risk predictor (MRP), comprising 53 CpG sites, exhibited c-indexes of 0.751 and 0.754 in the training and test sets, respectively. To validate the prognostic value of the predictors, we further analyzed two independent cohorts of Canadian (n = 42) and Nordic (n = 384) ALL patients. The external validation confirmed our findings, with the RRP achieving a c-index of 0.667 in the Canadian cohort, and the RRP and MRP achieving c-indexes of 0.529 and 0.621, respectively, in an independent Nordic cohort. The precision of the RRP and MRP models improved when incorporating traditional risk group data, underscoring the potential for synergistic integration of clinical prognostic factors. The MRP model also enabled the definition of a risk group with high rates of relapse and mortality. Our results demonstrate the potential of DNA methylation as a prognostic factor and a tool to refine risk stratification in pediatric ALL. This may lead to personalized treatment strategies based on epigenetic profiling.

Sar1b transgenic male mice are more susceptible to high-fat diet-induced obesity, insulin insensitivity and intestinal chylomicron overproduction.

In the intracellular secretory network, nascent proteins are shuttled from the endoplasmic reticulum to the Golgi by transport vesicles requiring Sar1b, a small GTPase. Mutations in this key enzyme impair intestinal lipid transport and cause chylomicron retention disease. The main aim of this study was to assess whether Sar1b overexpression under a hypercaloric diet accelerated lipid production and chylomicron (CM) secretion, thereby inducing cardiometabolic abnormalities. To this end, we generated transgenic mice overexpressing human Sar1b (Sar1b(+/+)) using pBROAD3-mcs that features the ubiquitous mouse ROSA26 promoter. In response to a high-fat diet (HFD), Sar1b(+/+) mice displayed significantly increased body weight and adiposity compared with Sar1b(+/+) mice under the same regimen or with wild-type (WT) mice exposed to chow diet or HFD. Furthermore, Sar1b(+/+) mice were prone to liver steatosis as revealed by significantly elevated hepatic triglycerides (TG) and cholesterol in comparison with WT animals. They also exhibited augmented levels of plasma TG along with alterations in fatty acid composition. Concomitantly, they showed susceptibility to develop insulin insensitivity and they responded abnormally to oral glucose tolerance test. Finally, Sar1b(+/+) mice that have been treated with Triton WR-1330 (to inhibit TG catabolism) and orotic acid (to block secretion of very low-density lipoprotein by the liver) responded more efficiently to fat meal tests as reflected by the rise in plasma TG and CM concentrations, indicating exaggerated intestinal fat absorption. These results suggest that Sar1b(+/+) under HFD can elicit cardiometabolic traits as revealed by incremental weight gain, fat deposition, dyslipidemia, hepatic steatosis, insulin insensitivity and intestinal fat absorption.