Expression of submaxillary gland androgen-regulated protein 3A (SMR3A) in adenoid cystic carcinoma of the head and neck

Background: Adenoid cystic carcinoma of the head and neck (ACC) is a rare tumor entity which originates from the salivary glands. The prognosis remains poor, as the tumor tends to exhibit perineural invasion and frequently develops distant metastases. The submaxillary gland androgen-regulated protein 3A (SMR3A) belongs to a gene family producing opiorphin homologs and is physiologically secreted by salivary glands. Expression of SMR3A has been identified as an unfavorable risk factor in survival of patients with squamous cell carcinoma in the head and neck, but its value as a prognostic biomarker for ACC has not been addressed. Materials and Methods: Tissue sections from primary ACC (n=86) and healthy glandular tissue as reference, were stained by immunohistochemistry. SMR3A expression levels were correlated with clinical and pathological features, including overall survival. Results: All patients had undergone surgery and 67 received adjuvant radiotherapy. The median disease-free survival (DFS) was 37 months and the median overall survival (OS) was 75 months. Prominent SMR3A expression in tumor cells was found in 24 of 86 patients (27,9%), and was inversely correlated with a male gender (p=0.009). There was no significant correlation between SMR3A expression and DFS, metastasis-free survival or OS. Conclusion: Our data demonstrate for the first time decreased levels of SMR3A in ACC compared to normal glandular tissue. These data suggest a context-dependent regulation of SMR3A expression in the pathogenesis of distinct subtypes of head and neck tumors, and support the assumption that detection of SMR3A expression serves as a surrogate for aberrant differentiation into mucosal- or glandular-like cells in ACC and head and neck squamous cell carcinoma

Expression of Kallikrein-related peptidase 6 in primary mucosal malignant melanoma of the head and neck

Mucosal melanomas of the head and neck (MMHN) are aggressive tumors with poor prognosis, different opposed to cutaneous melanoma. In this study, we characterized primary mucosal malignant melanoma for the expression of Kallikrein-related peptidase 6 (KLK6), a member of the KLK family with relevance to the malignant phenotype in various cancer types including cutaneous melanoma. Paraffin-embedded MMHN of 22 patients were stained immunohistochemically for KLK6 and results were correlated with clinical and pathological data. In 77.3% (17/22) of MMHN cases, positive KLK6 staining was found. Staining pattern for tumor cells showed a predominant cytoplasmic staining. However, in six cases we also observed a prominent nuclear staining. MMHN with a high KLK6 expression showed significantly better outcome concerning local recurrence-free survival (p = 0.013) and nuclear KLK6 staining was significantly associated with the survival status (p = 0.027). Overexpression of KLK6 was detected in more than 70% of MMHN and approximately 40% of tumors showed a strong expression pattern. Correlation between clinical outcome of MMHN patients and overexpression of KLK6 has not been addressed so far. Our data demonstrate for the first time increased levels of KLK6 in MMHN and strengthen the hypothesis that there might be a context-specific regulation and function of KLK6 in mucosal melanoma

A proteomics sample metadata representation for multiomics integration and big data analysis

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.publishedVersio

Predicting Decisions in Human Social Interactions Using Real-Time fMRI and Pattern Classification

Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives

Synaptic processes and immune-related pathways implicated in Tourette syndrome

Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe