DNA methylation transcriptionally regulates the putative tumor cell growth suppressor ZNF677 in non-small cell lung cancers

In our study, we investigated the role of ZNF677 in non-small cell lung cancers (NSCLC). By comparing ZNF677 expression in primary tumor (TU) and in the majority of cases also of corresponding non-malignant lung tissue (NL) samples from > 1,000 NSCLC patients, we found tumor-specific downregulation of ZNF677 expression (adjusted p-values < 0.001). We identified methylation as main mechanism for ZNF677 downregulation in NSCLC cells and we observed tumor-specific ZNF677 methylation in NSCLC patients (p < 0.0001). In the majority of TUs, ZNF677 methylation was associated with loss of ZNF677 expression. Moreover, ZNF677 overexpression in NSCLC cells was associated with reduced cell proliferation and cell migration. ZNF677 was identified to regulate expression of many genes mainly involved in growth hormone regulation and interferon signalling. Finally, patients with ZNF677 methylated TUs had a shorter overall survival compared to patients with ZNF677 not methylated TUs (p = 0.013). Overall, our results demonstrate that ZNF677 is trancriptionally regulated by methylation in NSCLCs, suggest that ZNF677 has tumor cell growth suppressing properties in NSCLCs and that ZNF677 methylation might serve as prognostic parameter in these patients

Wiener klinische Wochenschrift / Management of malignant pleural mesothelioma part 3 : Data from the Austrian Mesothelioma Interest Group (AMIG) database

Background Malignant pleural mesothelioma (MPM) is a rare but aggressive tumor originating from the pleural cavity with a strong link to previous asbestos exposure. In order to determine the demographics, diagnostics, therapeutic strategies, and prognosis of MPM patients in Austria, the Austrian Mesothelioma Interest Group (AMIG) was founded in 2011. In this report the data from the AMIG MPM database collected to date are reported. Methods A prospective observational registry was initiated, including patients with histologically verified MPM diagnosed and treated at specialized centers in Austria. Patient inclusion started in January 2011 and follow-up was completed until September 2015. Results A total number of 210 patients were included. There were 167 male and 43 female patients with a mean age of 67.0 years (SD 11.3) at the time of diagnosis. Asbestos exposure was confirmed in 109 (69.4 %) patients. The histological subtype was epithelioid in 141 (67.2 %), sarcomatoid in 16 (7.6 %), biphasic in 28 (13.3 %), and MPM not otherwise specified in 25 (11.9 %) patients. Of the patients, 30 (14.3 %) received best supportive care (BSC) only, 71 (33.8 %) chemotherapy (CHT) alone, four (1.9 %) radiotherapy (RT) alone, 23 (11.9 %) CHT/RT, two (0.9 %) surgery alone, and 76 (36.2 %) curative surgery within a multimodality treatment (MMT), which was more frequently performed for patients younger than 65 years and with early-stage disease (I + II). Median overall survival (OS) was 19.1 months (95 % CI 14.723.5). The 1, 3, and 5year OS rates were 66 %, 30 %, and 23 %, respectively, and OS was significantly better in patients undergoing surgery within MMT (5-year survival 5 % vs. 40 %, p = 0.001). Conclusion Patients with earlier disease stages, younger age, good performance status, and epithelioid histology were more likely to undergo MMT including surgery, which resulted in a more favorable outcome.(VLID)348028

Identification of psychiatric disorder subtypes from functional connectivity patterns in resting-state electroencephalography

The understanding and treatment of psychiatric disorders, which are known to be neurobiologically and clinically heterogeneous, could benefit from the data-driven identification of disease subtypes. Here, we report the identification of two clinically relevant subtypes of post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) on the basis of robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the default mode network. We identified the disease subtypes by analysing, via unsupervised and supervised machine learning, the power-envelope-based connectivity of signals reconstructed from high-density resting-state electroencephalography in four datasets of patients with PTSD and MDD, and show that the subtypes are transferable across independent datasets recorded under different conditions. The subtype whose functional connectivity differed most from those of healthy controls was less responsive to psychotherapy treatment for PTSD and failed to respond to an antidepressant medication for MDD. By contrast, both subtypes responded equally well to two different forms of repetitive transcranial magnetic stimulation therapy for MDD. Our data-driven approach may constitute a generalizable solution for connectome-based diagnosis

Genome-wide CpG island methylation analyses in non-small cell lung cancer patients

DNA methylation is part of the epigenetic gene regulation complex, which is relevant for the pathogenesis of cancer. We performed a genome-wide search for methylated CpG islands in tumors and corresponding non-malignant lung tissue samples of 101 stages IIII non-small cell lung cancer (NSCLC) patients by combining methylated DNA immunoprecipitation and microarray analysis. Overall, we identified 2414 genomic positions differentially methylated between tumor and non-malignant lung tissue samples. Ninety-seven percent of them were found to be tumor-specifically methylated. Annotation of these genomic positions resulted in the identification of 477 tumor-specifically methylated genes of which many are involved in regulation of gene transcription and cell adhesion. Tumor-specific methylation was confirmed by a gene-specific approach. In the majority of tumors, methylation of certain genes was associated with loss of their protein expression determined by immunohistochemistry. Treatment of NSCLC cells with epigenetically active drugs resulted in upregulated expression of many tumor-specifically methylated genes analyzed by gene expression microarrays suggesting that about one-third of these genes are transcriptionally regulated by methylation. Moreover, comparison of methylation results with certain clinicopathological characteristics of the patients suggests that methylation of HOXA2 and HOXA10 may be of prognostic relevance in squamous cell carcinoma (SCC) patients. In conclusion, we identified a large number of tumor-specifically methylated genes in NSCLC patients. Expression of many of them is regulated by methylation. Moreover, HOXA2 and HOXA10 methylation may serve as prognostic parameters in SCC patients. Overall, our findings emphasize the impact of methylation on the pathogenesis of NSCLCs

Additional file 1: Table S1. of SPAG6 and L1TD1 are transcriptionally regulated by DNA methylation in non-small cell lung cancers

Description of NSCLC cell lines used in this study. Information about histology, origin and disease stage of donors was obtained from ATCC catalogue ( https://www.lgcstandards-atcc.org ). EGFR, KRAS and TP53 mutational status and MET amplification according to supplementary references (1–3). *activating EGFR mutation in exon 19 (E746-E749 del), **activating EGFR mutation in exon 21 (L858R). N/A, not available; wt, wildtype; mut, mutated. Table S2. Clinico-pathological characteristics of 983 NSCLC patients. Overview of gender, histology, stage of disease and ethnicity of NSCLC patients obtained from TCGA database and used for mutation and copy number changes analyses of SPAG6 and L1TD1 is shown. ADC, adenocarcinoma; SCC, squamous cell carcinoma. Clinical data based on Caleydo software version 16/04/14. Table S3. Primer sequences. Summary of oligonucleotide sequences used for mRNA expression, MS-HRM, BGS analyses and construction of pCMV6-GFP expression vector. Y, random integration of C or T in fwd primer; R, random integration of G or A in rev primer. Table S4. Methylation of SPAG6 and L1TD1 in tumor cells of other tumor types. *Morphology, histology and origin of cell lines according to ATCC catalogue ( https://www.lgcstandards-atcc.org ). Percentage of methylation was calculated as described previously (4). (DOCX 33 kb

Additional file 4: Figure S3. of SPAG6 and L1TD1 are transcriptionally regulated by DNA methylation in non-small cell lung cancers

SPAG6 and L1TD1 SNVs and deletions in NSCLC patients. TCGA LUAD and LUSC datasets were analysed with Caleydo software (version April 2014). Mutation of TP53 was used to demonstrate reliability of TCGA data analysis. ADC, adenocarcinoma patients; SCC, squamous carcinoma patients. (TIF 90 kb