Chemokine-driven migration of inflammatory cells has been implicated in pathogenesis of atherosclerosis-associated conditions such as ischemic stroke and myocardial infarction. In this study, a candidate chemokine, monocyte chemoattractant protein (MCP)-1, was investigated in patients with both aforementioned manifestations of atheroslerotic inflammation. MCP-1 levels in serum were determined by ELISA in 40 healthy, control subjects (C), 40 patients with ischemic stroke (IS), and in 64 patients with myocardial infarction (MI). Statistical analysis utilised Mann-Whitney test, Fisher's exact test, and Spearman's rank correlation (P < .05). In comparison to control subjects (C; median/interquartile range: 239/126 pg/mL), MCP-1 serum levels were increased in both investigated patient cohorts (IS: 384/370, P < .001; MI: 360/200, P < .002). There was a substantial variability of MCP-1 serum levels, especially in the IS group. No relationship was observed between chemokine levels and atherosclerosis risk factors (hypertension, diabetes, smoking, and alcohol consumption), and MCP-1 was also not related to age or gender. Elevation of MCP-1 in circulation of patients with atherosclerosis-associated complications implicates this CC chemokine ligand (CCL)2 in inflammatory processes, which contribute to pathogenesis of myocardial infarction and ischemic stroke. Further investigations, including patient stratification, are however necessary to evaluate if MCP-1 can be utilised for clinical management of patients with these diseases.

Background Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma. Methods We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics. Results We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt’s lymphoma and particularly on ‘double-hit’ MYC and BCL2 transformed lymphomas. Conclusions The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities. Electronic supplementary material The online version of this article (10.1186/s13073-019-0637-7) contains supplementary material, which is available to authorized users.

Colorectal cancer (CRC) arising in Lynch syndrome (LS) comprises tumours with constitutional mutations in DNA mismatch repair genes. There is still a lack of whole-genome and transcriptome studies of LS-CRC to address questions about similarities and differences in mutation and gene expression characteristics between LS-CRC and sporadic CRC, about the molecular heterogeneity of LS-CRC, and about specific mechanisms of LS-CRC genesis linked to dysfunctional mismatch repair in LS colonic mucosa and the possible role of immune editing. Here, we provide a first molecular characterization of LS tumours and of matched tumour-distant reference colonic mucosa based on whole-genome DNA-sequencing and RNA-sequencing analyses. Our data support two subgroups of LS-CRCs, G1 and G2, whereby G1 tumours show a higher number of somatic mutations, a higher amount of microsatellite slippage, and a different mutation spectrum. The gene expression phenotypes support this difference. Reference mucosa of G1 shows a strong immune response associated with the expression of HLA and immune checkpoint genes and the invasion of CD4+ T cells. Such an immune response is not observed in LS tumours, G2 reference and normal (non-Lynch) mucosa, and sporadic CRC. We hypothesize that G1 tumours are edited for escape from a highly immunogenic microenvironment via loss of HLA presentation and T-cell exhaustion. In contrast, G2 tumours seem to develop in a less immunogenic microenvironment where tumour-promoting inflammation parallels tumourigenesis. Larger studies on non-neoplastic mucosa tissue of mutation carriers are required to better understand the early phases of emerging tumours.

Telomeres are the ends of eukaryotic chromosomes, consisting of consecutive short repeats that protect chromosome ends from degradation. Telomeres shorten with each cell division, leading to replicative cell senescence. Deregulation of telomere length homeostasis is associated with the development of various age-related diseases and cancers. A number of experimental techniques exist for telomere length measurement; however, until recently, the absence of tools for extracting telomere lengths from high-throughput sequencing data has significantly obscured the association of telomere length with molecular processes in normal and diseased conditions. We have developed Computel, a program in R for computing mean telomere length from whole-genome next-generation sequencing data. Computel is open source, and is freely available at https://github.com/lilit-nersisyan/computel. It utilizes a short-read alignment-based approach and integrates various popular tools for sequencing data analysis. We validated it with synthetic and experimental data, and compared its performance with the previously available software. The results have shown that Computel outperforms existing software in accuracy, independence of results from sequencing conditions, stability against inherent sequencing errors, and better ability to distinguish pure telomeric sequences from interstitial telomeric repeats. By providing a highly reliable methodology for determining telomere lengths from whole-genome sequencing data, Computel should help to elucidate the role of telomeres in cellular health and disease.

Background: For accuracy of quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR), normalisation with suitable reference genes is required. To date, no reference genes have been validated for expression studies of bronchoalveolar (BAL) cells. The aims of this study were to identify gene(s) with stable mRNA expression in BAL cells irrespective of gender, smoking, BAL cellular composition, lung pathology, treatment; and to assess the influence of reference genes on target gene expression data.

IntroductionAutoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms.MethodsOur study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies.Results and conclusionsThe results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

Gut microbiota-produced short chain fatty acids (SCFAs) play an important role in the normal human metabolism and physiology. Although the gradients of SCFAs from the large intestine, where they are largely produced, to the peripheral blood as well as the main routes of SCFA metabolism by different organs are known well for the healthy state, there is a paucity of information regarding how these are affected in disease. In particular, how the inflammation caused by infection or autoinflammatory disease affect the concentration of SCFAs in the peripheral venous blood. In this work, we revealed that diseases caused either by infectious agents (two Salmonella enterica serovars, S. Enteritidis, and S. Typhimurium) or by the exacerbation of an autoinflammatory disease, familial Mediterranean fever (FMF), both result in a significantly elevated systemic concentration of SCFAs. In the case of salmonellosis the concentration of SCFAs in peripheral blood was significantly and consistently higher, from 5- to 20-fold, compared to control. In the case of FMF, however, a significant increase of SCFAs in the peripheral venous blood was detected only in the acute phase of the disease, with a lesser impact in remission. It seems counterintuitive that the dysbiotic conditions, with a reduced number of gut microorganisms, produce such an effect. This phenomenon, however, must be appraised within the context of how the inflammatory diseases affect the normal physiology. We discuss a number of factors that may contribute to the “leak” and persistence of gut-produced SCFAs into the systemic circulation in infectious and autoinflammatory diseases.

Molecular mechanisms of lower-grade (II–III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.