Proteogenomic analysis of the autoreactive B cell repertoire in blood and tissues of patients with Sjögren's syndrome.

OBJECTIVE: To comparatively analyse the aberrant affinity maturation of the antinuclear and rheumatoid factor (RF) B cell repertoires in blood and tissues of patients with Sjögren's syndrome (SjS) using an integrated omics workflow. METHODS: Peptide sequencing of anti-Ro60, anti-Ro52, anti-La and RF was combined with B cell repertoire analysis at the DNA, RNA and single cell level in blood B cell subsets, affected salivary gland and extranodal marginal zone lymphomas of mucosa-associated lymphoid tissue (MALT) of patients with SjS. RESULTS: Affected tissues contained anti-Ro60, anti-Ro52, anti-La and RF clones as a small part of a polyclonal infiltrate. Anti-Ro60, anti-La and anti-Ro52 clones outnumbered RF clones. MALT lymphoma tissues contained monoclonal RF expansions. Autoreactive clones were not selected from a restricted repertoire in a circulating B cell subset. The antinuclear antibody (ANA) repertoires displayed similar antigen-dependent and immunoglobulin (Ig) G1-directed affinity maturation. RF clones displayed antigen-dependent, IgM-directed and more B cell receptor integrity-dependent affinity maturation. This coincided with extensive intra-clonal diversification in RF-derived lymphomas. Regeneration of clinical disease manifestations after rituximab coincided with large RF clones, which not necessarily belonged to the lymphoma clone, that displayed continuous affinity maturation and intra-clonal diversification. CONCLUSION: The ANA and RF repertoires in patients with SjS display tissue-restricted, antigen-dependent and divergent affinity maturation. Affinity maturation of RF clones deviates further during RF clone derived lymphomagenesis and during regeneration of the autoreactive repertoire after temporary disruption by rituximab. These data give insight into the molecular mechanisms of autoreactive inflammation in SjS, assist MALT lymphoma diagnosis and allow tracking its response to rituximab.

IRF8 is a transcriptional activator of CD37 expression in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) represents the most common form of non-Hodgkin lymphoma (NHL) that is still incurable in a large fraction of patients. Tetraspanin CD37 is highly expressed on mature B lymphocytes, and multiple CD37-targeting therapies are under clinical development for NHL. However, CD37 expression is nondetectable in ∼50% of DLBCL patients, which correlates with inferior treatment outcome, but the underlying mechanisms for differential CD37 expression in DLBCL are still unknown. Here, we investigated the regulation of the CD37 gene in human DLBCL at the (epi-)genetic and transcriptional level. No differences were observed in DNA methylation within the CD37 promoter region between CD37-positive and CD37-negative primary DLBCL patient samples. On the contrary, CD37-negative DLBCL cells specifically lacked CD37 promoter activity, suggesting differential regulation of CD37 gene expression. Using an unbiased quantitative proteomic approach, we identified transcription factor IRF8 to be significantly higher expressed in nuclear extracts of CD37-positive as compared with CD37-negative DLBCL. Direct binding of IRF8 to the CD37 promoter region was confirmed by DNA pulldown assay combined with mass spectrometry and targeted chromatin immunoprecipitation (ChIP). Functional analysis indicated that IRF8 overexpression enhanced CD37 protein expression, while CRISPR/Cas9 knockout of IRF8 decreased CD37 levels in DLBCL cell lines. Immunohistochemical analysis in a large cohort of primary DLBCL (n = 206) revealed a significant correlation of IRF8 expression with detectable CD37 levels. Together, this study provides new insight into the molecular mechanisms underlying differential CD37 expression in human DLBCL and reveals IRF8 as a transcriptional regulator of CD37 in B-cell lymphoma.

Ras-mediated deregulation of the circadian clock in cancer.

Circadian rhythms are essential to the temporal regulation of molecular processes in living systems and as such to life itself. Deregulation of these rhythms leads to failures in biological processes and eventually to the manifestation of pathological phenotypes including cancer. To address the questions as to what are the elicitors of a disrupted clock in cancer, we applied a systems biology approach to correlate experimental, bioinformatics and modelling data from several cell line models for colorectal and skin cancer. We found strong and weak circadian oscillators within the same type of cancer and identified a set of genes, which allows the discrimination between the two oscillator-types. Among those genes are IFNGR2, PITX2, RFWD2, PPARγ, LOXL2, Rab6 and SPARC, all involved in cancer-related pathways. Using a bioinformatics approach, we extended the core-clock network and present its interconnection to the discriminative set of genes. Interestingly, such gene signatures link the clock to oncogenic pathways like the RAS/MAPK pathway. To investigate the potential impact of the RAS/MAPK pathway - a major driver of colorectal carcinogenesis - on the circadian clock, we used a computational model which predicted that perturbation of BMAL1-mediated transcription can generate the circadian phenotypes similar to those observed in metastatic cell lines. Using an inducible RAS expression system, we show that overexpression of RAS disrupts the circadian clock and leads to an increase of the circadian period while RAS inhibition causes a shortening of period length, as predicted by our mathematical simulations. Together, our data demonstrate that perturbations induced by a single oncogene are sufficient to deregulate the mammalian circadian clock.

Integrated analysis of microRNA and mRNA expression: adding biological significance to microRNA target predictions.

Current microRNA target predictions are based on sequence information and empirically derived rules but do not make use of the expression of microRNAs and their targets. This study aimed to improve microRNA target predictions in a given biological context, using in silico predictions, microRNA and mRNA expression. We used target prediction tools to produce lists of predicted targets and used a gene set test designed to detect consistent effects of microRNAs on the joint expression of multiple targets. In a single test, association between microRNA expression and target gene set expression as well as the contribution of the individual target genes on the association are determined. The strongest negatively associated mRNAs as measured by the test were prioritized. We applied our integration method to a well-defined muscle differentiation model. Validation of our predictions in C2C12 cells confirmed predicted targets of known as well as novel muscle-related microRNAs. We further studied associations between microRNA-mRNA pairs in human prostate cancer, finding some pairs that have been recently experimentally validated by others. Using the same study, we showed the advantages of the global test over Pearson correlation and lasso. We conclude that our integrated approach successfully identifies regulated microRNAs and their targets.