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Immune checkpoints are important targets for immunotherapies. However, knowledge on the epigenetic modification of immune checkpoint genes is sparse. In the present study, we investigated promoter methylation of CTLA4, PD-L1, PD-L2, and PD-1 in diffuse lower-grade gliomas (LGG) harboring isocitrate dehydrogenase (IDH) mutations with regard to mRNA expression levels, clinicopathological parameters, previously established methylation subtypes, immune cell infiltrates, and survival in a cohort of 419 patients with IDH-mutated LGG provided by The Cancer Genome Atlas. PD-L1, PD-L2, and CTLA-4 mRNA expression levels showed a significant inverse correlation with promoter methylation (PD-L1: p=0.005; PD-L2: p < 0.001; CTLA-4: p b 0.001). Furthermore, immune checkpoint methylation was significantly associated with age (PD-L2: p = 0.003; PD-1: p = 0.015), molecular alterations, i.e. MGMT methylation (PD-L1: p < 0.001; PD-L2: p < 0.001), ATRX mutations (PD-L2: p < 0.001, PD-1: p = 0.001), and TERT mutations (PD-L1: p= 0.035, PD-L2: p < 0.001, PD-1: p b 0.001, CTLA4: p < 0.001) as well a smethylation subgroups and immune cell infiltrates. In multivariate Cox proportional hazard analysis, PD-1 methylation qualified as strong prognostic factor (HR = 0.51 [ 0.34-0.76], p=0.001). Our findings suggest an epigenetic regulation of immune checkpoint genes via DNA methylation in LGG. PD-1 methylation may assist the identification of patients that might benefit from an alternative treatment, particularly in the context of emerging immunotherapies. (c) 2018 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license

Background: Molecular biomarkers assisting risk-group assignment and subsequent treatment stratification are urgently needed for patients with squamous cell cancer of the head and neck region (HNSCC). Aberrant methylation is a frequent event in cancer and, therefore, a promising source for potential biomarkers. Here, the methylation status of the paired-like homeodomain transcription factor 3 (PITX3) was evaluated in HNSCC. Methods: Using a quantitative real-time PCR, PITX3 methylation was assessed in a cohort of 326 HNSCC patients treated for localized or locally advanced disease (training cohort). The results were validated with Infinium HumanMethylation450 BeadChip data from a 528 HNSCC patient cohort (validation cohort) generated by The Cancer Genome Atlas (TCGA) Research Network. Results: PITX3 methylation was significantly higher methylated in tumor compared to normal adjacent tissue (NAT; training cohort: median methylation NAT 32.3%, tumor 71.8%, p < 0.001; validation cohort: median methylation NAT 16.9%, tumor 35.9%, p < 0.001). PITX3 methylation was also significantly correlated with lymph node status both in the training (p = 0.006) and validation (p < 0.001) cohort. PITX3 methylation was significantly higher in HPV-associated (p16-positive) tumors compared to p16-negative tumors (training cohort: 73.7 vs. 66.2%, p = 0.013; validation cohort: 40.0 vs. 33.1%, p = 0.015). Hypermethylation was significantly associated with the risk of death (training cohort: hazard ratio (HR) = 1.80, [95% confidence interval (CI) 1.20-2.69], p = 0.005; validation cohort: HR = 1.43, [95% CI 1.05-1.95], p = 0.022). In multivariate Cox analyses, PITX3 added independent prognostic information. Messenger RNA (mRNA) expression analysis revealed an inverse correlation with PITX3 methylation in the TCGA cohort. Conclusions: PITX3 DNA methylation is an independent prognostic biomarker for overall survival in patients with HNSCC and might aid in the process of risk stratification for

Background: Biomarkers that facilitate the prediction of disease recurrence in head and neck squamous cell carcinoma (HNSCC) may enable physicians to personalize treatment. In the current study, DNA promoter methylation of programmed cell death 1 (PDCD1, PD-1) was evaluated as a prognostic biomarker in HNSCC patients. Results: High PDCD1 methylation (mPDCD1) was associated with a significantly shorter overall survival after surgical resection in both the discovery (HR = 2.24 [95% CI: 1.08-4.64], p = 0.029) and the validation cohort (HR = 1.54 [95% CI: 1.08-2.21], p = 0.017). In multivariate Cox proportional hazards analysis, PDCD1 methylation remained a significant prognostic factor for HNSCC (HR = 2.14 [95% CI: 1.19-3.84], p = 0.011). Further, mPDCD1 was strongly associated with the human papilloma virus (HPV) status. Materials and Methods: mPDCD1 was assessed retrospectively in a discovery cohort of 120 HNSCC patients treated at the University Hospital of Bonn and a validation cohort of 527 HNSCC cases analyzed by The Cancer Genome Atlas Research Network. Conclusions: PDCD1 methylation might aid the identification of HNSCC patients potentially benefitting from a radical or alternative treatment, particularly in the context of immunotherapies targeting PD-1/PD-L1.

Background Despite advances in combined modality therapy, outcomes in head and neck squamous cell cancer (HNSCC) remain dismal with five-year overall survival rates of less than 50%. Prognostic biomarkers are urgently needed to identify patients with a high risk of death after initial curative treatment. Methylation status of the paired-like homeodomain transcription factor 2 (PITX2) has recently emerged as a powerful prognostic biomarker in various cancers. In the present study, the clinical performance of PITX2 methylation was validated in a HNSCC cohort by means of an independent analytical platform (Infinium HumanMethylation450 BeadChip, Illumina, Inc.). Methods A total of 528 HNSCC patients from The Cancer Genome Atlas (TCGA) were included in the study. Death was defined as primary endpoint. PITX2 methylation was correlated with overall survival and clinicopathological parameters. Results PITX2 methylation was significantly associated with sex, tumor site, p16 status, and grade. In univariate Cox proportional hazards analysis, PITX2 hypermethylation analyzed as continuous and dichotomized variable was significantly associated with prolonged overall survival of HNSCC patients (continuous: hazard ratio (HR) = 0.19 [95% CI: 0.04-0.88], p = 0.034; dichotomized: HR = 0.52 [95% CI: 0.33-0.84], p = 0.007). In multivariate Cox analysis including established clinicopathological parameters, PITX2 promoter methylation was confirmed as prognostic factor (HR = 0.28 [95% CI: 0.09-0.84], p = 0.023). Conclusion Using an independent analytical platform, PITX2 methylation was validated as a prognostic biomarker in HNSCC patients, identifying patients that potentially benefit from intensified surveillance and/or administration of adjuvant/neodjuvant treatment, i.e. immunotherapy.

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase., De två första författarna delar förstaförfattarskapet.

A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.European Journal of Human Genetics advance online publication, 26 August 2015; doi:10.1038/ejhg.2015.165.