Clinical and prognostic significance of detecting CEA, EGFR, LunX, c-met and EpCAM mRNA-positive cells in the peripheral blood, tumor-draining blood and bone marrow of non-small cell lung cancer patients.

Background: Surgical treatment of early-stage non-small cell lung cancer (NSCLC) yields highest expectations for recovery. However, the frequency of further disease progression remains high since micro-metastatic disease may be undetected by conventional diagnostic methods. We test the presence and prognostic impact of circulating tumor cells (CTCs) in peripheral blood (PB), tumor-draining pulmonary blood (TDB) and bone marrow (BM) samples from NSCLC patients. Methods: The presence of circulating/disseminated tumor cells (CTCs/DTCs) was detected by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) analysis in PB, TDB and BM samples before surgery in 119 stage IA-IIIA NSCLC patients (Clinical Trial NS10285). Results: NSCLC patients with the presence of carcinoembryonic antigen (CEA) mRNA-positive CTCs/DTCs in TDB and BM had significantly shorter cancer-specific survival (CSS) (P<0.013, resp. P<0.038). Patients with the presence of epithelial cellular adhesion molecule (EpCAM) mRNA-positive CTCs in TDB samples had significantly shorter CSS and disease-free survival (DFS) (P<0.031, resp. P<0.045). A multivariate analysis identified the presence of CEA mRNA-positive CTCs in the PB as an independent negative prognostic factor for DFS (P<0.005). No significant correlation of CTCs/DTCs presence and other prognostic factors was found. Conclusions: In NSCLC patients undergoing radical surgery, the presence of CEA and EpCAM mRNA-positive CTCs/DTCs is associated with poorer survival.

Recent Advances in Methods for Circulating Tumor Cell Detection.

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.

Cannabinoid receptor 2 expression in early-stage non-small cell lung cancers identifies patients with good prognosis and longer survival.

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.

Transcriptomic Profiling Revealed Lnc-GOLGA6A-1 as a Novel Prognostic Biomarker of Meningioma Recurrence.

BACKGROUND: Meningioma is the most common primary central nervous system neoplasm, accounting for about a third of all brain tumors. Because their growth rates and prognosis cannot be accurately estimated, biomarkers that enable prediction of their biological behavior would be clinically beneficial. OBJECTIVE: To identify coding and noncoding RNAs crucial in meningioma prognostication and pathogenesis. METHODS: Total RNA was purified from formalin-fixed and paraffin-embedded tumor samples of 64 patients with meningioma with distinct clinical characteristics (16 recurrent, 30 nonrecurrent with follow-up of >5 years, and 18 with follow-up of <5 years without recurrence). Transcriptomic sequencing was performed using the HiSeq 2500 platform (Illumina), and biological and functional differences between meningiomas of different types were evaluated by analyzing differentially expression of messenger RNA (mRNA) and long noncoding RNA (IncRNA). The prognostic value of 11 differentially expressed RNAs was then validated in an independent cohort of 90 patients using reverse transcription quantitative (real-time) polymerase chain reaction. RESULTS: In total, 69 mRNAs and 108 lncRNAs exhibited significant differential expression between recurrent and nonrecurrent meningiomas. Differential expression was also observed with respect to sex (12 mRNAs and 59 lncRNAs), World Health Organization grade (58 mRNAs and 98 lncRNAs), and tumor histogenesis (79 mRNAs and 76 lncRNAs). Lnc-GOLGA6A-1, ISLR2, and AMH showed high prognostic power for predicting meningioma recurrence, while lnc-GOLGA6A-1 was the most significant factor for recurrence risk estimation (1/hazard ratio = 1.31; P = .002). CONCLUSION: Transcriptomic sequencing revealed specific gene expression signatures of various clinical subtypes of meningioma. Expression of the lnc-GOLGA61-1 transcript was found to be the most reliable predictor of meningioma recurrence.

Primary pneumococcal peritonitis with a fulminant course.

INTRODUCTION: Primary peritonitis is an inflammation of the peritoneal cavity in the absence of a localized intra-abdominal source. It is included in the differential diagnosis of acute abdomen and can be potentially life-threatening. Pneumococci were a frequent pathogen causing primary peritonitis especially in the preantibiotic era. Nowadays, they act as an uncommon primary pathogen. Pneumococcal peritonitis in adults is more frequently seen in cases of liver cirrhosis with ascites and other pre-existing conditions. Primary pneumococcal peritonitis is uncommon in healthy individuals and therefore its diagnosis is difficult. Secondary peritonitis has to be excluded. CASE REPORT: A 36-year-old woman was admitted to our surgery department with symptoms of severe sepsis. She reported a sudden onset of diffuse abdominal pain and was eight weeks after delivery per vias naturales. A computed tomography scan of the abdomen with intravenous contrast has not demonstrated any pathology explaining the condition of our patient. Empiric anti-microbial therapy with broad-spectrum antibiotics was commenced and a laparotomy was performed, which also did not reveal any source of infection. Purulent odorless fluid was found in the peritoneal cavity. Peritoneal lavage with an antiseptic was performed. Cultures from peritoneal fluid demonstrated a monobacterial growth of Streptococcus pneumoniae. The condition of our patient improved after continued adequate antibiotic therapy and lavage. CONCLUSION: Primary pneumococcal peritonitis is difficult to diagnose in healthy individuals, since it is mimicking secondary peritonitis that has to be excluded. A clinical diagnose without surgical intervention is impossible in most cases. Surgical treatment has an important role in both the diagnosis and management of primary pneumococcal peritonitis, same as adequate antibiotic therapy. Primary peritonitis should be a part of the differential diagnosis of patients presenting with acute abdominal pain.

Identification and Validation of Circulating Micrornas as Prognostic Biomarkers in Pancreatic Ductal Adenocarcinoma Patients Undergoing Surgical Resection.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal and aggressive cancers with a less than 6% five-year survival rate. Circulating microRNAs (miRNAs) are emerging as a useful tool for non-invasive diagnosis and prognosis estimation in the various cancer types, including PDAC. Our study aimed to evaluate whether miRNAs in the pre-operative blood plasma specimen have the potential to predict the prognosis of PDAC patients. In total, 112 PDAC patients planned for surgical resection were enrolled in our prospective study. To identify prognostic miRNAs, we used small RNA sequencing in 24 plasma samples of PDAC patients with poor prognosis (overall survival (OS) < 16 months) and 24 plasma samples of PDAC patients with a good prognosis (OS > 20 months). qPCR validation of selected miRNA candidates was performed in the independent cohort of PDAC patients (n = 64). In the discovery phase of the study, we identified 44 miRNAs with significantly different levels in the plasma samples of the group of good and poor prognosis patients. Among these miRNAs, 23 showed lower levels, and 21 showed higher levels in plasma specimens from PDAC patients with poor prognosis. Eleven miRNAs were selected for the validation, but only miR-99a-5p and miR-365a-3p were confirmed to have significantly lower levels and miR-200c-3p higher levels in plasma samples of poor prognosis cases. Using the combination of these 3-miRNA levels, we were able to identify the patients with poor prognosis with sensitivity 85% and specificity 80% (Area Under the Curve = 0.890). Overall, 3-miRNA prognostic score associated with OS was identified in the pre-operative blood plasma samples of PDAC patients undergoing surgical resection. Following further independent validations, the detection of these miRNA may enable identification of PDAC patients who have no survival benefit from the surgical treatment, which is associated with the high morbidity rates.

Identification of Meningioma Patients at High Risk of Tumor Recurrence Using MicroRNA Profiling.

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.