The latest medical research on Biochemical Genetics

VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and hematological features. Nevertheless, these criteria lack significance to discriminate VEXAS from other inflammatory conditions at the screening step. This work hence first focused on singling out dysplastic features indicative of the syndrome among peripheral blood (PB) polymorphonuclears (PMN). A deep learning algorithm is then proposed for automatic detection of these features.

A multicentric dataset, comprising 9514 annotated PMN images was gathered, including UBA1 mutated VEXAS (n = 25), UBA1 wildtype myelodysplastic (n = 14), and UBA1 wildtype cytopenic patients (n = 25). Statistical analysis on a subset of patients was performed to screen for significant abnormalities. Detection of these features on PB was then automated with a convolutional neural network (CNN) for multilabel classification.

Significant differences were observed in the proportions of PMNs with pseudo-Pelger, nuclear spikes, vacuoles, and hypogranularity between patients with VEXAS and both cytopenic and myelodysplastic controls. Automatic detection of these abnormalities yielded AUCs in the range [0.85-0.97] and a F1-score of 0.70 on the test set. A VEXAS screening score was proposed, leveraging the model outputs and predicting the UBA1 mutational status with 0.82 sensitivity and 0.71 specificity on the test patients.

This study suggests that computer-assisted analysis of PB smears, focusing on suspected VEXAS cases, can provide valuable insights for determining which patients should undergo molecular testing. The presented deep learning approach can help hematologists direct their suspicions before initiating further analyses.

Epigenetics has been shown to be relevant in oncology: BMI1 overexpression has been reported in leukemias, EZH2 mutations have been found in follicular lymphoma, and USP22 seems to stabilize BMI1 protein. In this study, we measured the expression of BMI1, EZH2, and USP22 in lymph nodes from 56 diffuse large B-cell lymphoma (DLBCL) patients.

A new multiplex digital droplet PCR (ddPCR) has been set up to measure the expression of 4 genes (BMI1, EZH2, USP22, and GAPDH) in the same reaction on RNA extracted from paraffin-embedded tissues.

The specificity of ddPCR was confirmed by a 100% alignment on the BLAST platform and its repeatability demonstrated by duplicates. A strict correlation between expression of BMI1 and EZH2 and BMI1 and USP22 has been found, and high expression of these genes was correlated with extra-nodal lymphomas. Progression-free survival (PFS) and overall survival (OS) were conditioned by IPI, bone marrow infiltration, and the complete response achievement. High levels of BMI1 and USP22 did not condition the response to therapy, but impaired the PFS, especially for patients defined at "high risk" based on the cell of origin (no germinal center [GCB]), high BCL2 expression, and IPI 3-5. In this subgroup, the probability of relapse/progression was twice higher than that of patients carrying low BMI1 and USP22 levels.

High expression of BMI1 and of USP22 might be a poor prognostic factor in DLBCL, and might represent the target for novel inhibitors.

The burgeoning field of regenerative medicine has significantly advanced with recent findings on biotherapies using human platelet lysates (HPLs), derived from clinical-grade platelet concentrates (PCs), for treating brain disorders. These developments have opened new translational research avenues to explore the neuroprotective effects of platelet-extracellular vesicles (PEVs). Their potential in managing neurodegenerative conditions like traumatic brain injury (TBI) and Parkinson's disease (PD) warrants further exploration. We aimed here to characterize the composition of a PEV preparation isolated from platelet concentrate (PC) supernatant, and determine its neuroprotective potential and neurorestorative effects in cellular and animal models of TBI and PD.

We isolated PEVs from the supernatant of clinical-grade PC collected from healthy blood donors utilizing high-speed centrifugation. PEVs were characterized by biophysical, biochemical, microscopic, and LC-MS/MS proteomics methods to unveil biological functions. Their functionality was assessed in vitro using SH-SY5Y neuronal cells, LUHMES dopaminergic neurons, and BV-2 microglial cells, and in vivo by intranasal administration in a controlled cortical impact (CCI)-TBI model using 8-weeks-old male C57/BL6 mice, and in a PD model induced by MPTP in 5-month-old male C57/BL6 mice.

PEVs varied in size from 50 to 350 nm, predominantly around 200 nm, with concentrations ranging between 1010 and 1011/mL. They expressed specific platelet membrane markers, exhibited a lipid bilayer by cryo-electron microscopy and, importantly, showed low expression of pro-coagulant phosphatidylserine. LC-MS/MS indicated a rich composition of trophic factors, including neurotrophins, anti-inflammatory agents, neurotransmitters, and antioxidants, unveiling their multifaceted biological functions. PEVs aided in the restoration of neuronal functions in SH-SY5Y cells and demonstrated remarkable neuroprotective capabilities against erastin-induced ferroptosis in dopaminergic neurons. In microglial cells, they promoted anti-inflammatory responses, particularly under inflammatory conditions. In vivo, intranasally delivered PEVs showed strong anti-inflammatory effects in a TBI mouse model and conserved tyrosine hydroxylase expression of dopaminergic neurons of the substantia nigra in a PD model, leading to improved motor function.

The potential of PEV-based therapies in neuroprotection opens new therapeutic avenues for neurodegenerative disorders. The study advocates for clinical trials to establish the efficacy of PEV-based biotherapies in neuroregenerative medicine.