Tumor migration and invasion are key pathological processes that contribute to cell metastasis as well as treatment failure in patients with malignant tumors. However, the mechanisms governing tumor cell migration remain poorly understood. By analyzing the tumor-related database and tumor cell lines, we found that preoptic regulatory factor-2 (Porf-2) is downexpressed in both neuroblastoma and glioma. Using in vitro assays, our data demonstrated that the expression of Porf-2 inhibits tumor cell migration both in neuroblastoma and glioma cell lines. Domain-mutated Porf-2 plasmids were then constructed, and it was found that the GAP domain, which plays a role in the inactivation of Rac1, is the functional domain for inhibiting tumor cell migration. Furthermore, by screening potential downstream effectors, we found that Porf-2 can reduce MMP-2 and MMP-9 expression. Overexpression of MMP-2 blocked the inhibitory effect of Porf-2 in tumor cell migration both in vitro and in vivo. Taken together, we show for the first time that Porf-2 is capable of suppressing tumor cell migration via its GAP domain and the downregulation of MMP-2/9, suggesting that targeting Porf-2 could be a promising therapeutic strategy for nervous system tumors.

Long non-coding RNA small nucleolar RNA host gene 5 (lncRNA SNHG5) has been reported to participate in the occurrence and development of glioma.

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PurposeThe purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients.MethodsA total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients’ different clinical characteristics.ResultsPreoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707–0.839) and 0.745 (95% CI 0.637–0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups.ConclusionsPreoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.