Impact of mutations in Toll-like receptor pathway genes on esophageal carcinogenesis.

Esophageal adenocarcinoma (EAC) develops in an inflammatory microenvironment with reduced microbial diversity, but mechanisms for these influences remain poorly characterized. We hypothesized that mutations targeting the Toll-like receptor (TLR) pathway could disrupt innate immune signaling and promote a microenvironment that favors tumorigenesis. Through interrogating whole genome sequencing data from 171 EAC patients, we showed that non-synonymous mutations collectively affect the TLR pathway in 25/171 (14.6%, PathScan p = 8.7x10-5) tumors. TLR mutant cases were associated with more proximal tumors and metastatic disease, indicating possible clinical significance of these mutations. Only rare mutations were identified in adjacent Barrett's esophagus samples. We validated our findings in an external EAC dataset with non-synonymous TLR pathway mutations in 33/149 (22.1%, PathScan p = 0.05) tumors, and in other solid tumor types exposed to microbiomes in the COSMIC database (10,318 samples), including uterine endometrioid carcinoma (188/320, 58.8%), cutaneous melanoma (377/988, 38.2%), colorectal adenocarcinoma (402/1519, 26.5%), and stomach adenocarcinoma (151/579, 26.1%). TLR4 was the most frequently mutated gene with eleven mutations in 10/171 (5.8%) of EAC tumors. The TLR4 mutants E439G, S570I, F703C and R787H were confirmed to have impaired reactivity to bacterial lipopolysaccharide with marked reductions in signaling by luciferase reporter assays. Overall, our findings show that TLR pathway genes are recurrently mutated in EAC, and TLR4 mutations have decreased responsiveness to bacterial lipopolysaccharide and may play a role in disease pathogenesis in a subset of patients

Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction.

Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-naïve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.We would like to acknowledge The Human Research Tissue Bank which is supported by the NIHR Cambridge Biomedical Research Centre ... This work has been supported by the research scholarship BO4097/1‐1 from the Deutsche Forschungsgemeinschaft (DFG) for JB, grant RG67258 of the National Institute for Health and Research (NIHR) and grant RG66287 of Cancer Research UK (CRUK) have been awarded to RCF

Dynamics of Transcription Regulation in Human Bone Marrow Myeloid Differentiation to Mature Blood Neutrophils.

Neutrophils are short-lived blood cells that play a critical role in host defense against infections. To better comprehend neutrophil functions and their regulation, we provide a complete epigenetic overview, assessing important functional features of their differentiation stages from bone marrow-residing progenitors to mature circulating cells. Integration of chromatin modifications, methylation, and transcriptome dynamics reveals an enforced regulation of differentiation, for cellular functions such as release of proteases, respiratory burst, cell cycle regulation, and apoptosis. We observe an early establishment of the cytotoxic capability, while the signaling components that activate these antimicrobial mechanisms are transcribed at later stages, outside the bone marrow, thus preventing toxic effects in the bone marrow niche. Altogether, these data reveal how the developmental dynamics of the chromatin landscape orchestrate the daily production of a large number of neutrophils required for innate host defense and provide a comprehensive overview of differentiating human neutrophils

Immune activation by DNA damage predicts response to chemotherapy and survival in oesophageal adenocarcinoma.

OBJECTIVE: Current strategies to guide selection of neoadjuvant therapy in oesophageal adenocarcinoma (OAC) are inadequate. We assessed the ability of a DNA damage immune response (DDIR) assay to predict response following neoadjuvant chemotherapy in OAC. DESIGN: Transcriptional profiling of 273 formalin-fixed paraffin-embedded prechemotherapy endoscopic OAC biopsies was performed. All patients were treated with platinum-based neoadjuvant chemotherapy and resection between 2003 and 2014 at four centres in the Oesophageal Cancer Clinical and Molecular Stratification consortium. CD8 and programmed death ligand 1 (PD-L1) immunohistochemical staining was assessed in matched resection specimens from 126 cases. Kaplan-Meier and Cox proportional hazards regression analysis were applied according to DDIR status for recurrence-free survival (RFS) and overall survival (OS). RESULTS: A total of 66 OAC samples (24%) were DDIR positive with the remaining 207 samples (76%) being DDIR negative. DDIR assay positivity was associated with improved RFS (HR: 0.61; 95% CI 0.38 to 0.98; p=0.042) and OS (HR: 0.52; 95% CI 0.31 to 0.88; p=0.015) following multivariate analysis. DDIR-positive patients had a higher pathological response rate (p=0.033), lower nodal burden (p=0.026) and reduced circumferential margin involvement (p=0.007). No difference in OS was observed according to DDIR status in an independent surgery-alone dataset.DDIR-positive OAC tumours were also associated with the presence of CD8+ lymphocytes (intratumoural: p<0.001; stromal: p=0.026) as well as PD-L1 expression (intratumoural: p=0.047; stromal: p=0.025). CONCLUSION: The DDIR assay is strongly predictive of benefit from DNA-damaging neoadjuvant chemotherapy followed by surgical resection and is associated with a proinflammatory microenvironment in OAC.This work was supported by the Gastrointestinal Cancer Research Charitable Fund administered by the Belfast Health and Social Care Trust, the Cancer Research UK Experimental Cancer Medicine Centre Initiative, Invest Northern Ireland and Almac Diagnostics. Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) was funded by a programme grant from Cancer Research UK (RG66287). We would like to thank the Human Research Tissue Bank, which is supported by the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre from Addenbrooke’s Hospital. Additional infrastructure support was provided from the CRUK funded Experimental Cancer Medicine Centre. RF has programmatic funding from the Medical Research Council and infrastructure support from the NIHR Biomedical Research Centre and the Cambridge Experimental Medicine Centre. Tissue samples used in this research were received from the Northern Ireland Biobank, which is funded by HSC Research and Development Division of the Public Health Agency in Northern Ireland and Cancer Research UK through the Belfast Cancer Research UK Centre and the Northern Ireland Experimental Cancer Medicine Centre; additional support was received from the Friends of the Cancer Centre. The Northern Ireland Molecular Pathology Laboratory has received funding from Cancer Research UK, the Friends of the Cancer Centre and the Sean Crummey Foundation. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no 721906. The OCCAMS Study Group is a multicentre UK collaboration

Bioinformatische Methoden zur Untersuchung von Chromatinregulation

Chromatin plays an essential role in transcriptional regulation and in defining cellular identity. Histones, which are the building blocks of chromatin, can be chemically modified with a diverse set of histone modifications. The histone modifications are placed, read or erased by proteins, called chromatin modifiers. Together, chromatin modifiers and histone modifications are components of a chromatin-signaling network involved in transcription and its regulation. The interactions between chromatin modifiers and histone modifications are often unknown, are based on the analysis of few genes or are studied in vitro. Further, the functional impact of each chromatin modifier or histone modifications on the whole chromatin signaling network are poorly understood. With the present thesis, we aim at improving our understanding of the interactions between chromatin modifiers and histone modifications and their function on a genome-wide scale. To this end, we apply computational methods to large sets of genome-wide DNA- protein binding data. From this data we reconstruct the interactions between chromatin modifiers and histone modifications leading to a global chromatin signaling network. First, we evaluate different network reconstruction methods that have been previously applied to genome-wide DNA-protein data on simulated and Drosophila data. Second, we provide a high-confidence backbone of the chromatin-signaling network at human promoters. We evaluate the detected interactions in the light of literature knowledge and generate novel biological hypotheses for unknown interactions. Finally, we investigate the differences and commonalities between the chromatin-signaling networks at different chromatin environments in mouse. This analysis results in a systems- level view on the different chromatin signaling interactions leading to novel hypotheses on the functional role of chromatin modifiers and histone modifications in defining the chromatin landscape.Chromatin spielt eine wichtige Rolle in der Transkriptionsregulation und der Definition von Zelltypen. Die Bausteine des Chromatins, die Histonproteine, können chemisch, mit sogenannten Histonmodifikationen, verändert werden. Die Histonmodifikationen selbst werden von sogenannten Chromatin-modifizierenden Proteinen katalysiert, gelesen oder entfernt. Beide Komponenten zusammen ergeben ein komplexes Chromatin-assoziiertes Signalnetzwerk, das maßgeblich am Transkriptionsprozess und seiner Regulierung beteiligt ist. Die spezifischen Interaktionen zwischen den Histonmodifikationen und den Chromatin- modifizierenden Proteinen sind jedoch meist unbekannt oder basieren auf einer gen-spezifischen oder in vitro Analyse. Des Weiteren ist meist die funktionale Bedeutung der einzelnen Interaktionen für das gesamte Chromatin-assoziierte Signalnetzwerk unzureichend bekannt. Die vorliegende Doktorarbeit hat als Zielsetzung die Interaktionen zwischen Chromatin-modifizierenden Proteinen und Histonmodifikationen, sowie deren Funktion genomweit zu charakterisieren. Mit Hilfe großer genomweiter DNA-Protein-Bindungsdatensätzen und computergestützter Methoden lassen sich die Interaktionen zwischen Chromatin- bindenden Proteinen rekonstruieren. Im ersten Teil der Arbeit werden verschiedene Methoden zur Netzwerkrekonstruktion, die für diesen Zweck in frühreren Publikationen verwendet wurden, auf simulierten Daten und Drosophila-Daten verglichen. Im zweiten Teil der Arbeit werden Interaktionen an humanen Promoteren rekonstruiert. Diese werden mit Hilfe einer Literatursuche evaluiert und dienen als Basis für neue biologische Hypothesen über bisher unbekannte Funktionen der Histonmodifikationen und Chromatin- modifizierenden Proteine. Im letzten Teil der Arbeit werden Gemeinsamkeiten und Unterschiede zwischen den Chromatin-assoziierten Netzwerken, die für unterschiedlichen Chromatinumgebungen rekonstruiert werden, untersucht. Aus dieser system-orientierten Analyse der Interaktionen lassen sich neue Hypothesen über die Funktion der Histonmodifikationen und den Chromatin- modifizierenden Proteinen bei der Definition verschiedener Chromatinumgebungen ableiten

The mutREAD method detects mutational signatures from low quantities of cancer DNA

Funder: We thank the Human Research Tissue Bank, which is supported by the UK National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, from Addenbrooke’s Hospital. Additional infrastructure support was provided from the Cancer Research UK–funded Experimental Cancer Medicine CentreAbstract: Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings

The mutREAD method detects mutational signatures from low quantities of cancer DNA

Sequencing tumour genomes can reveal information about the processes that drive the formation of cancer. Here, the authors describe a method that can detect these mutational signatures from small amounts of DNA and degraded samples