Circulating tight junction proteins mirror blood-brain barrier integrity in leukaemia central nervous system metastasis.

The aim of this study was to evaluate the clinical significance of circulating tight junction (TJ) proteins as biomarkers reflecting of leukaemia central nervous system (CNS) metastasis. TJs [claudin5 (CLDN5), occludin (OCLN) and ZO-1] concentrations were measured in serum and cerebrospinal fluid (CSF) samples obtained from 45 leukaemia patients. Serum ZO-1 was significantly higher (p < 0.05), but CSF ZO-1 levels were not significantly higher in the CNS leukaemia (CNSL) compared to the non-CNSL. The CNSL patients also had a lower CLDN5/ZO1 ratio in both serum and CSF than in non-CNSL patients (p < 0.05). The TJ index was negatively associated with WBCCSF , ALBCSF and BBB values in leukaemia patients. Among all of the parameters studied, CLDN5CSF had the highest specificity in discriminating between CNSL and non-CNSL patients. Therefore, analysing serum and CSF levels of CLDN5, OCLN and the CLDN5/ZO1 ratio is valuable in evaluating the potential of leukaemia CNS metastasis. Copyright © 2016 John Wiley & Sons, Ltd.

The prognostic significance of serum and cerebrospinal fluid MMP-9, CCL2 and sVCAM-1 in leukemia CNS metastasis.

Metastasis to the central nervous system (CNS) is the primary obstacle in leukemia treatment. Matrix metalloproteinase-9 (MMP-9), chemokine ligand-2 (CCL2) and soluble vascular adhesion molecule-1 (sVCAM-1) play crucial roles in tumor cell adhesion, motivation and survival, but their roles in leukemia CNS metastasis remain to be elucidated. We investigated the prognostic significance of serum and cerebrospinal fluid (CSF) MMP-9, CCL2 and sVCAM-1 in leukemia patients to explore their potential as predictive biomarkers of the development of CNS leukemia (CNSL). MMP-9, CCL2 and sVCAM-1 were measured in paired CSF and serum samples collecting from 33 leukemia patients with or without CNS metastasis. Other risk factors related to CNSL prognosis were also analyzed. sVCAM-1Serum and CCL2Serum/CSF were significantly higher in the CNSL group than in the non-CNSL group and the controls (p < 0.05). MMP-9Serum was insignificantly lower in the CNSL group than in the non-CNSL group and the controls (p > 0.05). No differences were found for the sVCAM-1Serum, CCL2Serum, and MMP-9Serum levels between non-CNSL patients and controls (p > 0.05). MMP-9CSF was significantly higher in the CNSL group than both the non-CNSL and the control groups (p < 0.05). The indexes of sVCAM-1, CCL2, and MMP-9 in the CNSL group were lower than in the controls (p < 0.05). Positive correlations were determined between the MMP-9CSF and the ALBCSF/BBB value/WBCCSF, between sVCAM-1Serum and the WBCCSF/BBB value. Negative correlations existed between MMP-9Serum and the ALBCSF/BBB value/WBCCSF, and between the CCL2 index and ALBCSF. sVCAM-1Serum was positively associated with event-free survival (EFS), and patients with higher levels of ALBCSF, MMP-9CSF/Serum, CCL2CSF/Serum, and sVCAM-1CSF/Serum had shorter EFS. MMP-9CSF, CCL2CSF and sVCAM-1CSF are the first three principal components analyzed by cluster and principal component analysis. Our data suggest that MMP-9, CCL2 and sVCAM-1 in the CSF may be more potent than serum in predicting the possibility of leukemia metastatic CNS and the outcome of CNSL patients.

Risk Factors and Predictive Nomogram for Survival in Elderly Patients with Brain Glioma.

OBJECTIVE: To determine the factors that contribute to the survival of elderly individuals diagnosed with brain glioma and develop a prognostic nomogram. METHODS: Data from elderly individuals (age ≥65 years) histologically diagnosed with brain glioma were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. The dataset was randomly divided into a training cohort and an internal validation cohort at a 6:4 ratio. Additionally, data obtained from Tangdu Hospital constituted an external validation cohort for the study. The identification of independent prognostic factors was achieved through the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, enabling the construction of a nomogram. Model performance was evaluated using C-index, ROC curves, calibration plot and decision curve analysis (DCA). RESULTS: A cohort of 20 483 elderly glioma patients was selected from the SEER database. Five prognostic factors (age, marital status, histological type, stage, and treatment) were found to significantly impact overall survival (OS) and cancer-specific survival (CSS), with tumor location emerging as a sixth variable independently linked to CSS. Subsequently, nomogram models were developed to predict the probabilities of survival at 6, 12, and 24 months. The assessment findings from the validation queue indicate a that the model exhibited strong performance. CONCLUSION: Our nomograms serve as valuable prognostic tools for assessing the survival probability of elderly glioma patients. They can potentially assist in risk stratification and clinical decision-making.