MBMethPred: a computational framework for the accurate classification of childhood medulloblastoma subgroups using data integration and AI-based approaches.

Childhood medulloblastoma is a malignant form of brain tumor that is widely classified into four subgroups based on molecular and genetic characteristics. Accurate classification of these subgroups is crucial for appropriate treatment, monitoring plans, and targeted therapies. However, misclassification between groups 3 and 4 is common. To address this issue, an AI-based R package called MBMethPred was developed based on DNA methylation and gene expression profiles of 763 medulloblastoma samples to classify subgroups using machine learning and neural network models. The developed prediction models achieved a classification accuracy of over 96% for subgroup classification by using 399 CpGs as prediction biomarkers. We also assessed the prognostic relevance of prediction biomarkers using survival analysis. Furthermore, we identified subgroup-specific drivers of medulloblastoma using functional enrichment analysis, Shapley values, and gene network analysis. In particular, the genes involved in the nervous system development process have the potential to separate medulloblastoma subgroups with 99% accuracy. Notably, our analysis identified 16 genes that were specifically significant for subgroup classification, including EP300, CXCR4, WNT4, ZIC4, MEIS1, SLC8A1, NFASC, ASCL2, KIF5C, SYNGAP1, SEMA4F, ROR1, DPYSL4, ARTN, RTN4RL1, and TLX2. Our findings contribute to enhanced survival outcomes for patients with medulloblastoma. Continued research and validation efforts are needed to further refine and expand the utility of our approach in other cancer types, advancing personalized medicine in pediatric oncology.

Whole Exome Sequencing of an X-linked Thrombocytopenia Patient with Normal Sized Platelets.

Wiskott-Aldrich Syndrome (WAS) is a rare X-linked recessive Primary Immunodeficiency (PID) caused by mutations in WAS gene which encodes a protein known as WASp. WASp plays important roles in cytoskeletal functions that compromise multiple aspects of normal cellular activity including proliferation, phagocytosis, immune synapse formation, adhesion and directed migration. WASp defect particularly causes platelets abnormality which is presented in forms of decrease of Mean Platelet Volume (MPV) and thrombocytopenia in most WAS conditions; nevertheless, some studies reported WAS patients with a normal or large size of platelets in recent years. This phenomenon is unique and the exact mechanism of thrombocytopenia with a normal or large size of platelets is still unknown. In this study, Next Generation Sequencing (NGS) was utilized to discover the causing mutation in WAS gene; furthermore, an attempt was made to evaluate the possibility of other mutations or genes especially WASp interacting proteins and inherited platelet disorder genes in patient clinical symptoms for the purpose of understanding the origin of such unique symptom and to perform further analysis if it is required. Therefore, clinical manifestations and immunologic functions of the patient were checked and Whole Exome Sequencing (WES) was performed to analyze all exonic variations which can be associated with patient phenotypes. Finally, a novel de novo mutation in WAS gene which truncates WASp to half of its normal size was determined as the only cause of clinical manifestation.

Collagen coated electrospun polyethersulfon nanofibers improved insulin producing cells differentiation potential of human induced pluripotent stem cells.

Given the current conditions of life, one of the problems that the world is facing and is rapidly expanding is diabetes. The existing treatment methods are not responsive to these patients. Today, due to the advent of tissue engineering, cell and stem cell therapies, there are many hopes for treating these patients. In the present study, Polyethersulfone (PES) nanofibers were fabricated by electrospinning and then coated by collagen (PES-collagen), since this protein is abundant at the pancreatic extracellular matrix. After scaffold characterization, pancreatic differentiation potential of human induced pluripotent stem cells (hiPSCs) was investigated when cultured on PES-collagen by RT-qPCR, Immunofluorescence staining and insulin and C-peptide release assays. Pancreatic genes and proteins in cultured iPSCs on PES-collagen were expressed significantly higher than those cultured on culture plate as 2 D control group. Although differentiated cells in both groups are functional and secrete C-peptide and insulin in response to glucose challenges according to the immunoassay result. Considered together, PES-collagen demonstrated that it can be effective during pancreatic differentiation of the stem cells and can also be considered as a promising candidate for use in pancreatic tissue engineering application.