Methylation of L1RE1, RARB, and RASSF1 function as possible biomarkers for the differential diagnosis of lung cancer.

BACKGROUND: Lung cancer is the major cause of cancer-related deaths worldwide. Differential diagnosis can be difficult, especially when only small samples are available. Epigenetic changes are frequently tissue-specific events in carcinogenesis and hence may serve as diagnostic biomarkers. MATERIAL AND METHODS: 138 representative formalin-fixed, paraffin-embedded (FFPE) tissues (116 lung cancer cases and 22 benign controls) were used for targeted DNA methylation analysis via pyrosequencing of ten literature-derived methylation markers (APC, CDH1, CDKN2A, EFEMP1, FHIT, L1RE1, MGMT, PTEN, RARB, and RASSF1). Methylation levels were analyzed with the Classification and Regression Tree Algorithm (CART), Conditional Interference Trees (ctree) and ROC. Validation was performed with additional 27 lung cancer cases and 38 benign controls. TCGA data for 282 lung cancer cases was included in the analysis. RESULTS: CART and ctree analysis identified the combination of L1RE1 and RARB as well as L1RE1 and RASSF1 as independent methylation markers with high discriminative power between tumor and benign tissue (for each combination, 91% specificity and 100% sensitivity). L1RE1 methylation associated significantly with tumor type and grade (p<0.001) with highest methylation in the control group. The opposite was found for RARB (p<0.001). RASSF1 methylation increased with tumor type and grade (p<0.001) with strongest methylation in neuroendocrine tumors (NET). CONCLUSION: Hypomethylation of L1RE1 is frequent in tumors compared to benign controls and associates with higher grade, whereas increasing methylation of RARB is an independent marker for tumors and higher grade. RASSF1 hypermethylation was frequent in tumors and most prominent in NET making it an auxiliary marker for separation of NSCLC and NET. L1RE1 in combination with either RARB or RASSF1 could function as biomarkers for separating lung cancer and non-cancerous tissue and could be useful for samples of limited size such as biopsies.

MDM2 is an important prognostic and predictive factor for platin-pemetrexed therapy in malignant pleural mesotheliomas and deregulation of P14/ARF (encoded by CDKN2A) seems to contribute to an MDM2-driven inactivation of P53.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a highly aggressive tumour that is first-line treated with a combination of cisplatin and pemetrexed. Until now, predictive and prognostic biomarkers are lacking, making it a non-tailored therapy regimen with unknown outcome. P53 is frequently inactivated in MPM, but mutations are extremely rare. MDM2 and P14/ARF are upstream regulators of P53 that may contribute to P53 inactivation. METHODS: A total of 72 MPM patients were investigated. MDM2 immunoexpression was assessed in 65 patients. MDM2 and P14/ARF mRNA expression was analysed in 48 patients of the overall collective. The expression results were correlated to overall survival (OS) and progression-free survival (PFS). RESULTS: OS and PFS correlated highly significantly with MDM2 mRNA and protein expression, showing a dismal prognosis for patients with elevated MDM2 expression (for OS: Score (logrank) test: P⩽0.002, and for PFS: Score (logrank) test; P<0.007). MDM2 was identified as robust prognostic and predictive biomarker for MPM on the mRNA and protein level. P14/ARF mRNA expression reached no statistical significance, but Kaplan-Meier curves distinguished patients with low P14/ARF expression and hence shorter survival from patients with higher expression and prolonged survival. CONCLUSIONS: MDM2 is a prognostic and predictive marker for a platin-pemetrexed therapy of patients with MPMs. Downregulation of P14/ARF expression seems to contribute to MDM2-overexpression-mediated P53 inactivation in MPM patients.

Evaluation of stable isotope fingerprinting techniques for the assessment of the predominant methanogenic pathways in anaerobic digesters.

Laboratory biogas reactors were operated under various conditions using maize silage, chicken manure, or distillers grains as substrate. In addition to the standard process parameters, the hydrogen and carbon stable isotopic composition of biogas was analyzed to estimate the predominant methanogenic pathways as a potential process control tool. The isotopic fingerprinting technique was evaluated by parallel analysis of mcrA genes and their transcripts to study the diversity and activity of methanogens. The dominant hydrogenotrophs were Methanomicrobiales, while aceticlastic methanogens were represented by Methanosaeta and Methanosarcina at low and high organic loading rates, respectively. Major changes in the relative abundance of mcrA transcripts were observed compared to the results obtained from DNA level. In agreement with the molecular results, the isotope data suggested the predominance of the hydrogenotrophic pathway in one reactor fed with chicken manure, while both pathways were important in the other reactors. Short-term changes in the isotopic composition were followed, and a significant change in isotope values was observed after feeding a reactor digesting maize silage. This ability of stable isotope fingerprinting to follow short-term activity changes shows potential for indicating process failures and makes it a promising technology for process control.