BACKGROUND Meningioma growth rates are highly variable, even within benign subgroups, with some remaining stable, whereas others grow rapidly. OBJECTIVE To identify molecular-genetic markers for more accurate prediction of meningioma recurrence and better-targeted therapy. METHODS Microarrays identified microRNA (miRNA) expression in primary and recurrent meningiomas of all World Health Organization (WHO) grades. Those found to be deregulated were further validated by quantitative real-time polymerase chain reaction in a cohort of 172 patients. Statistical analysis of the resulting dataset revealed predictors of meningioma recurrence. RESULTS Adjusted and nonadjusted models of time to relapse identified the most significant prognosticators to be miR-15a-5p, miR-146a-5p, and miR-331-3p. The final validation phase proved the crucial significance of miR-146a-5p and miR-331-3p, and clinical factors such as type of resection (total or partial) and WHO grade in some selected models. Following stepwise selection in a multivariate model on an expanded cohort, the most predictive model was identified to be that which included lower miR-331-3p expression (hazard ratio [HR] 1.44; P < .001) and partial tumor resection (HR 3.90; P < .001). Moreover, in the subgroup of total resections, both miRNAs remained prognosticators in univariate models adjusted to the clinical factors. CONCLUSION The proposed models might enable more accurate prediction of time to meningioma recurrence and thus determine optimal postoperative management. Moreover, combining this model with current knowledge of molecular processes underpinning recurrence could permit the identification of distinct meningioma subtypes and enable better-targeted therapies.

Circulating tumor cells (CTCs) are released from primary tumors and transported through the body via blood or lymphatic vessels before settling to form micrometastases under suitable conditions. Accordingly, several studies have identified CTCs as a negative prognostic factor for survival in many types of cancer. CTCs also reflect the current heterogeneity and genetic and biological state of tumors; so, their study can provide valuable insights into tumor progression, cell senescence, and cancer dormancy. Diverse methods with differing specificity, utility, costs, and sensitivity have been developed for isolating and characterizing CTCs. Additionally, novel techniques with the potential to overcome the limitations of existing ones are being developed. This primary literature review describes the current and emerging methods for enriching, detecting, isolating, and characterizing CTCs.

Background: Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related death with a 5-year survival of only 21%. Reliable prognostic and/or predictive biomarkers are needed to improve NSCLC patient stratification, particularly in curative disease stages. Since the endogenous cannabinoid system is involved in both carcinogenesis and anticancer immune defense, we hypothesized that tumor tissue expression of cannabinoid 1 and 2 receptors (CB1 and CB2) may affect survival.Methods: Tumor tissue samples collected from 100 NSCLC patients undergoing radical surgery were analyzed for CB1 and CB2 gene and protein expression using the quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). The gene and protein expression data were correlated with disease stage, histology, tumor grading, application of chemotherapy, and survival.Additional paired tumor and normal tissue samples of 10 NSCLC patients were analyzed independently for comparative analysis of CB1 and CB2 gene expression.Results: Patients with tumors expressing the CB2 gene had significantly longer overall survival (OS) (P<0.001), cancer specific survival (CSS) (P=0.002), and disease-free survival (DFS) (P<0.001). They also presented with fewer lymph node metastases at the time of surgery (P=0.011). A multivariate analysis identified CB2 tumor tissue gene expression as a positive prognostic factor for CSS [hazard ratio (HR) =0.274; P=0.013] and DFS (HR =0.322; P=0.009), and increased CSS. High CB2 gene and protein expression were detected in 79.6% and 31.5% of the tested tumor tissue samples, respectively. Neither CB1 gene nor CB1 or CB2 protein expression affected survival. When comparing paired tumor and tumor-free lung tissue samples, we observed reduced CB1 (P=0.008) and CB1 (P=0.056) gene expression in tumor tissues. Conclusions:In NSCLC patients undergoing radical surgery, expression of the CB1 and CB2 receptor genes is significantly decreased in neoplastic versus tumor-free lung tissue. CB2 tumor tissue gene expression is strongly associated with longer survival (OS, CSS, DFS) and fewer lymph node metastases at the time of surgery. More studies are needed to evaluate its role as a biomarker in NSCLC and to investigate the potential use of CB2 modulators to treat or prevent lung cancers.