Thiocyanates (SCN-) are ubiquitous in nature. There are indispensable part of host defense system that act as a substrate for lactoperoxidase (LPO). In our study we present initial data on SCN- concentration in saliva of CF patients in comparison to healthy non-smokers and healthy smokers. 5 ml of saliva was collected from each subject to a sterile tube and thiocyanate concentration was measured in each sample. The results of the measurements are presented on Fig. 1. Mean concentration of SCN- in saliva of CF patients was 0.031 +/- 0.0052 g/l, in healthy non-smokers 0.039 +/- 0.0048 g/l and in healthy smokers 0.048 +/- 0.0161 g/l. The differences between each group were statistically significant. Studies on larger group of patients and probably on different material (BALF or induced sputum) should present interesting data complementing the in vitro studies.

Advances in molecular analyses based on high-throughput technologies can contribute to a more accurate classification of non–small cell lung cancer (NSCLC), as well as a better prediction of both the disease course and the efficacy of targeted therapies. Here we set out to analyze whether global gene expression profiling performed in a group of early-stage NSCLC patients can contribute to classifying tumor subtypes and predicting the disease prognosis. Gene expression profiling was performed with the use of the microarray technology in a training set of 108 NSCLC samples. Subsequently, the recorded findings were validated further in an independent cohort of 44 samples. We demonstrated that the specific gene patterns differed significantly between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC) samples. Furthermore, we developed and validated a novel 53-gene signature distinguishing SCC from AC with 93% accuracy. Evaluation of the classifier performance in the validation set showed that our predictor classified the AC patients with 100% sensitivity and 88% specificity. We revealed that gene expression patterns observed in the early stages of NSCLC may help elucidate the histological distinctions of tumors through identification of different gene-mediated biological processes involved in the pathogenesis of histologically distinct tumors. However, we showed here that the gene expression profiles did not provide additional value in predicting the progression status of the early-stage NSCLC. Nevertheless, the gene expression signature analysis enabled us to perform a reliable subclassification of NSCLC tumors, and it can therefore become a useful diagnostic tool for a more accurate selection of patients for targeted therapies.

Abstract. The epigenetic inactivation of tumor suppressor genes may play an important role in the development and progression of many cancer types, including lung cancer. Therefore, we investigated the association between the aberrant promoter methylation of 2 genes: the Death-Associated Protein Kinase (DAPK) and the Ras Association Domain Family 1A (RASSF1A) by using methylation-specific PCR, and the clinicopathological features and prognosis in 70 radically resected non-small cell lung cancers (NSCLCs). Hypermethylation of the DAPK and RASSF1A promoters was found in 24 (34%), and in 18 (26%) tumor DNA samples, respectively. Regarding different clinicopathological features of NSCLCs, the DAPK promoter methylation was more frequently observed in squamous cell carcinoma (46%) than in adenocarcinoma (25%) and large cell carcinoma (22%), but there were no significant statistical differences (p=0.3). On the other hand, a statistically significant trend was observed between the RASSF1A methylation and a histological type of tumor (p=0.06). 45% of adenocarcinoma tumors showed RASSF1A promoter methylation in comparison to 17% of squamous cell carcinomas and 22% of large cell carcinomas. When both markers were analyzed according to the tumor-node-metastasis (TNM) staging system, no statistically significant differences were observed between stage I, II and IIIa, and the DAPK (p=0.2) and RASSF1A methylation (p=0.1). In comparison, when stage I and II were grouped together and considered vs. stage IIIa, a significant association between RASSF1A methylation and the TNM was found (p=0.03). The group of patients with tumors showing DAPK promoter methylation had significantly poorer overall survival rates (p=0.02) than the patients with tumors that did not show DAPK promoter methylation. However, the association between the RASSF1A promoter methylation status and the overall survival rates was not statistically significant (p=0.48). In conclusion, this paper supports the importance of epigenetic gene regulation in lung cancer progression and prognosis.

No abstract

Targeted therapy of non-small cell lung cancer (NSCLC) demands a more accurate tumor classification that is crucial for patient selection in personalized treatment. MicroRNAs constitute a promising class of biomarkers and a helpful tool for the distinction between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC). The aim of this study was to evaluate the impact of two different normalization strategies, using U6 snRNA and hsa-miR-103 as reference genes, on hsa-miR-205 and hsa-miR-21 expression levels, in terms of the classification of subtypes of NSCLC. By means of a quantitative real-time polymerase chain reaction (qRT-PCR) microRNA expression levels were evaluated in a classification set of 98 surgically resected NSCLC fresh-frozen samples, and validated findings in an independent set of 42 NSCLC samples. The microRNA expression levels were exploited to develop a diagnostic test using two data normalization strategies. The performance of microRNA profiling in different normalization methods was compared. We revealed the microRNA-based qRT-PCR tests to be appropriate measures for distinguishing between AC and SCC (the concordance of histologic diagnoses and molecular methods greater than 88%). Performance evaluation of microRNA tests, based on the two normalization strategies, showed that the procedure using hsa-miR-103 as reference target has a slight advantage (sensitivity 83.33 and 100% in classification and validation set, respectively) compared to U6 snRNA. Molecular tests based on microRNA expression allow a reliable classification of subtypes for NSCLC and can constitute a useful diagnostic strategy in patient selection for targeted therapy.