Search

Background: The immune checkpoint, indoleamine 2,3-dioxygenase 1, is under investigation as target of novel immunotherapies for cancers, including head and neck squamous cell carcinomas (HNSCC). The aim of our study was to analyze DNA methylation of the encoding gene (IDO1) in HNSCC. Methods: Methylation of three CpG sites within the promoter, promoter flank, and gene body was investigated and correlated with mRNA expression, immune cell infiltration, mutational burden, human papillomavirus (HPV)-status, and overall survival in a cohort of N = 528 HNSCC patients obtained from The Cancer Genome Atlas. In addition, IDO1 immunohistochemistry and DNA methylation analysis was performed in an independent cohort of N = 138 HNSCC samples. Findings: Significant inverse correlations of IDO1 methylation and IDO1 mRNA expression were found in the promoter and promoter flank region (Spearman's ρ = −0.163 and ρ = −0.377, respectively) while a positive correlation was present in the gene body (ρ = 0.502; all P

// Diane Goltz 1, * , Heidrun Gevensleben 2, * , Joern Dietrich 3 , Friederike Schroeck 3 , Luka de Vos 3 , Freya Droege 4 , Glen Kristiansen 2 , Andreas Schroeck 3 , Jennifer Landsberg 5 , Friedrich Bootz 3 and Dimo Dietrich 3 1 Institute of Pathology, University Hospital Cologne, Cologne, Germany 2 Institute of Pathology, University Hospital Bonn, Bonn, Germany 3 Department of Otolaryngology, Head and Neck Surgery, University Hospital Bonn, Bonn, Germany 4 Ear, Nose and Throat Clinic, University Hospital Essen, Essen, Germany 5 Department of Dermatology and Allergy, University of Bonn, Bonn, Germany * These authors contributed equally to this work Correspondence to: Dimo Dietrich, email: dimo.dietrich@gmail.com Keywords: PD-1, PDCD1, HPV, head and neck squamous cell carcinoma, DNA methylation Received: March 02, 2017 Accepted: April 11, 2017 Published: April 21, 2017 ABSTRACT 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 (m PDCD1 ) 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, m PDCD1 was strongly associated with the human papilloma virus (HPV) status. Materials and Methods: m PDCD1 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 The T cell immunoglobulin and mucin-domain containing-3 receptor TIM-3 (also known as hepatitis A virus cellular receptor 2, encoded by HAVCR2) and its ligand galectin 9 (LGALS9) are promising targets for immune checkpoint inhibition immunotherapies. However, little is known about epigenetic regulation of the encoding genes. This study aimed to investigate the association of TIM-3 and LGALS9 DNA methylation with gene expression, patients’ survival, as well as molecular and immune correlates in malignant melanoma. Results Methylation of all six TIM-3 CpGs correlated significantly with TIM-3 mRNA levels (P ≤ 0.05). A strong inverse correlation (Spearman’s ρ = − 0.49) was found in promoter regions, while a strong positive correlation (ρ = 0.63) was present in the gene body of TIM-3. High TIM-3 mRNA expression (hazard ratio (HR) = 0.88, 95% confidence interval (CI) [0.81–0.97], P = 0.007) was significantly associated with better overall survival. Seven of the eight LGALS9 CpG sites correlated significantly with LGALS9 mRNA levels (P ≤ 0.003). Methylation at five CpG sites showed a strong inverse correlation (Spearman’s ρ = − 0.67) and at two sites a weak positive correlation (Spearman’s ρ = 0.15). High LGALS9 mRNA expression was significantly associated with increased overall survival (HR = 0.83, 95%CI [0.75–0.93], P = 0.001). In addition, we found significant correlations between TIM-3 and LGALS9 methylation and mRNA expression with immune cell infiltrates and significant differences among distinct immune cell subsets. Conclusions Our study points toward an epigenetic regulation of TIM-3 and LGALS9 via DNA methylation and might provide an avenue for the development of a predictive biomarker for response to immune checkpoint blockade.

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. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Recent years have witnessed the groundbreaking success of immune checkpoint blockage (ICB) in metastasized malignant melanoma. However, biomarkers predicting the response to ICB are still urgently needed. In the present study, we investigated CTLA4 promoter methylation (mCTLA4) in 470 malignant melanoma patients from The Cancer Genome Atlas (non-ICB cohort) and in 50 individuals with metastasized malignant melanomas under PD-1/CTLA-4-targeted immunotherapy (ICB cohort). mCTLA4 levels were quantified using the Infinium HumanMethylation450 BeadChip (non-ICB cohort) and methylation-specific quantitative real-time PCR in DNA formalin-fixed and paraffin-embedded tissues (ICB cohort). Methylation levels were associated with molecular and clinicopathological variables and analyzed with respect to response (irRECIST) and overall survival. CTLA-4 mRNA and mCTLA4 showed a significant inverse correlation (non-ICB cohort: Spearman's ρ = -0.416, P < 0.001). In ICB-treated melanoma patients, low mCTLA4 was further strongly correlated with response to therapy (P = 0.009, ANOVA) and overall survival (hazard ratio = 2.06 [95% CI: 1.29-3.29], P = 0.003). Our data strongly support the assumption that mCTLA4 predicts response to both anti-PD-1 and anti-CTLA-4 targeted ICB in melanoma and provides paramount information for the selection of patients likely to respond to ICB.

Background Patients with squamous cell cancer of the head and neck region (HNSCC) are at risk for disease recurrence and metastases, even after initial successful therapy. A tissue-based biomarker could be beneficial to guide treatment as well as post-treatment surveillance. Gene methylation status has been recently identified as powerful prognostic biomarker in HNSCC. We therefore evaluated the methylation status of the homeobox gene PITX1 and the adjacent long intergenic non-coding RNA (lincRNA) C5orf66-AS1 in publicly available datasets. Methods Gene methylation and expression data from 528 patients with HNSCC included in The Cancer Genome Atlas (TCGA, there obtained by using the Infinium HumanMethylation450 BeadChip Kit) were evaluated and methylation and expression levels of PITX1 and lincRNA C5orf66-AS1 was correlated with overall survival and other parameters. Thus, ten beads targeting PITX1 exon 3 and three beads targeting lincRNA C5orf66-AS1 were identified as significant candidates. The mean methylation of these beads was used for further correlation and the median was employed for dichotomization. Results Both PITX1 exon 3 and lincRNA C5orf66-AS1 were significantly higher methylated in tumor tissue than in normal adjacent tissue (NAT) (PITX1 exon 3: tumor tissue 58.1%, NAT: 31.7%, p

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.

Summary: The Sample avAILability system—SAIL—is a web based application for searching, browsing and annotating biological sample collections or biobank entries. By providing individual-level information on the availability of specific data types (phenotypes, genetic or genomic data) and samples within a collection, rather than the actual measurement data, resource integration can be facilitated. A flexible data structure enables the collection owners to provide descriptive information on their samples using existing or custom vocabularies. Users can query for the available samples by various parameters combining them via logical expressions. The system can be scaled to hold data from millions of samples with thousands of variables. Availability: SAIL is available under Aferro-GPL open source license: https://github.com/sail. Contact: gostev@ebi.ac.uk, support@simbioms.org Supplementary information: Supplementary data are available at Bioinformatics online and from http://www.simbioms.org.