RESUMO
BACKGROUND: Despite advancements in neonatal care, germinal matrix-intraventricular hemorrhage impacts 20% of very preterm infants, exacerbating their neurological prognosis. Understanding its complex, multifactorial pathophysiology and rapid onset remains challenging. This study aims to link specific cord blood biomolecules at birth with post-natal germinal matrix-intraventricular hemorrhage onset. METHODS: A monocentric, prospective case-control study was conducted at Rouen University Hospital from 2015 to 2020. Premature newborns ( < 30 gestational age) were included and cord blood was sampled in the delivery room. A retrospective matching procedure was held in 2021 to select samples for proteomic and metabolomic analysis of 370 biomolecules. RESULTS: 26 patients with germinal matrix-intraventricular hemorrhage cases and 60 controls were included. Clinical differences were minimal, except for higher invasive ventilation rates in the germinal matrix-intraventricular hemorrhage group. Germinal matrix-intraventricular hemorrhage newborns exhibited lower phosphatidylcholine levels and elevated levels of four proteins: BOC cell adhesion-associated protein, placental growth factor, Leukocyte-associated immunoglobulin-like receptor 2, and tumor necrosis factor-related apoptosis-inducing ligand receptor 2. CONCLUSION: This study identifies biomolecules that may be linked to subsequent germinal matrix-intraventricular hemorrhage, suggesting heightened vascular disruption risk as an independent factor. These results need further validation but could serve as early germinal matrix-intraventricular hemorrhage risk biomarkers for future evaluations. IMPACT: Decrease in certain phosphatidylcholines and increase in four proteins in cord blood at birth may be linked to subsequent germinal matrix-intraventricular hemorrhage in premature newborns. The four proteins are BOC cell adhesion-associated protein, placental growth factor, leukocyte-associated immunoglobulin-like receptor 2, and TNF-related apoptosis-inducing ligand receptor 2. This biological imprint could point toward higher vascular disruption risk as an independent risk factor for this complication and with further validations, could be used for better stratification of premature newborns at birth.
Assuntos
Biomarcadores , Sangue Fetal , Lactente Extremamente Prematuro , Humanos , Recém-Nascido , Estudos de Casos e Controles , Biomarcadores/sangue , Feminino , Masculino , Estudos Prospectivos , Sangue Fetal/metabolismo , Sangue Fetal/química , Proteômica , Hemorragia Cerebral Intraventricular/sangue , Idade Gestacional , Metabolômica , Doenças do Prematuro/sangue , Estudos RetrospectivosRESUMO
Monitoring tumor evolution and predicting survival using non-invasive liquid biopsy is an unmet need for glioblastoma patients. The era of proteomics and metabolomics blood analyzes, may help in this context. A case-control study was conducted. Patients were included in the GLIOPLAK trial (ClinicalTrials.gov Identifier: NCT02617745), a prospective bicentric study conducted between November 2015 and December 2022. Patients underwent biopsy alone and received radiotherapy and temozolomide. Blood samples were collected at three different time points: before and after concomitant radiochemotherapy, and at the time of tumor progression. Plasma samples from patients and controls were analyzed using metabolomics and proteomics, generating 371 omics features. Descriptive, differential, and predictive analyses were performed to assess the relationship between plasma omics feature levels and patient outcome. Diagnostic performance and longitudinal variations were also analyzed. The study included 67 subjects (34 patients and 33 controls). A significant differential expression of metabolites and proteins between patients and controls was observed. Predictive models using omics features showed high accuracy in distinguishing patients from controls. Longitudinal analysis revealed temporal variations in a few omics features including CD22, CXCL13, EGF, IL6, GZMH, KLK4, and TNFRSP6B. Survival analysis identified 77 omics features significantly associated with OS, with ERBB2 and ITGAV consistently linked to OS at all timepoints. Pathway analysis revealed dynamic oncogenic pathways involved in glioblastoma progression. This study provides insights into the potential of plasma omics features as biomarkers for glioblastoma diagnosis, progression and overall survival. Clinical implication should now be explored in dedicated prospective trials.