High CD206 levels in Hodgkin lymphoma-educated macrophages are linked to matrix-remodeling and lymphoma dissemination.

Macrophages (Mφ) are abundantly present in the tumor microenvironment and may predict outcome in solid tumors and defined lymphoma subtypes. Mφ heterogeneity, the mechanisms of their recruitment, and their differentiation into lymphoma-promoting, alternatively activated M2-like phenotypes are still not fully understood. Therefore, further functional studies are required to understand biological mechanisms associated with human tumor-associated Mφ (TAM). Here, we show that the global mRNA expression and protein abundance of human Mφ differentiated in Hodgkin lymphoma (HL)-conditioned medium (CM) differ from those of Mφ educated by conditioned media from diffuse large B-cell lymphoma (DLBCL) cells or, classically, by macrophage colony-stimulating factor (M-CSF). Conditioned media from HL cells support TAM differentiation through upregulation of surface antigens such as CD40, CD163, CD206, and PD-L1. In particular, RNA and cell surface protein expression of mannose receptor 1 (MRC1)/CD206 significantly exceed the levels induced by classical M-CSF stimulation in M2-like Mφ; this is regulated by interleukin 13 to a large extent. Functionally, high CD206 enhances mannose-dependent endocytosis and uptake of type I collagen. Together with high matrix metalloprotease9 secretion, HL-TAMs appear to be active modulators of the tumor matrix. Preclinical in ovo models show that co-cultures of HL cells with monocytes or Mφ support dissemination of lymphoma cells via lymphatic vessels, while tumor size and vessel destruction are decreased in comparison with lymphoma-only tumors. Immunohistology of human HL tissues reveals a fraction of cases feature large numbers of CD206-positive cells, with high MRC1 expression being characteristic of HL-stage IV. In summary, the lymphoma-TAM interaction contributes to matrix-remodeling and lymphoma cell dissemination.

FastqPuri: high-performance preprocessing of RNA-seq data.

BACKGROUND: RNA sequencing (RNA-seq) has become the standard means of analyzing gene and transcript expression in high-throughput. While previously sequence alignment was a time demanding step, fast alignment methods and even more so transcript counting methods which avoid mapping and quantify gene and transcript expression by evaluating whether a read is compatible with a transcript, have led to significant speed-ups in data analysis. Now, the most time demanding step in the analysis of RNA-seq data is preprocessing the raw sequence data, such as running quality control and adapter, contamination and quality filtering before transcript or gene quantification. To do so, many researchers chain different tools, but a comprehensive, flexible and fast software that covers all preprocessing steps is currently missing. RESULTS: We here present FastqPuri, a light-weight and highly efficient preprocessing tool for fastq data. FastqPuri provides sequence quality reports on the sample and dataset level with new plots which facilitate decision making for subsequent quality filtering. Moreover, FastqPuri efficiently removes adapter sequences and sequences from biological contamination from the data. It accepts both single- and paired-end data in uncompressed or compressed fastq files. FastqPuri can be run stand-alone and is suitable to be run within pipelines. We benchmarked FastqPuri against existing tools and found that FastqPuri is superior in terms of speed, memory usage, versatility and comprehensiveness. CONCLUSIONS: FastqPuri is a new tool which covers all aspects of short read sequence data preprocessing. It was designed for RNA-seq data to meet the needs for fast preprocessing of fastq data to allow transcript and gene counting, but it is suitable to process any short read sequencing data of which high sequence quality is needed, such as for genome assembly or SNV (single nucleotide variant) detection. FastqPuri is most flexible in filtering undesired biological sequences by offering two approaches to optimize speed and memory usage dependent on the total size of the potential contaminating sequences. FastqPuri is available at https://github.com/jengelmann/FastqPuri . It is implemented in C and R and licensed under GPL v3.

Cooperative STAT/NF-κB signaling regulates lymphoma metabolic reprogramming and aberrant GOT2 expression.

Knowledge of stromal factors that have a role in the transcriptional regulation of metabolic pathways aside from c-Myc is fundamental to improvements in lymphoma therapy. Using a MYC-inducible human B-cell line, we observed the cooperative activation of STAT3 and NF-κB by IL10 and CpG stimulation. We show that IL10 + CpG-mediated cell proliferation of MYClow cells depends on glutaminolysis. By 13C- and 15N-tracing of glutamine metabolism and metabolite rescue experiments, we demonstrate that GOT2 provides aspartate and nucleotides to cells with activated or aberrant Jak/STAT and NF-κB signaling. A model of GOT2 transcriptional regulation is proposed, in which the cooperative phosphorylation of STAT3 and direct joint binding of STAT3 and p65/NF-κB to the proximal GOT2 promoter are important. Furthermore, high aberrant GOT2 expression is prognostic in diffuse large B-cell lymphoma underscoring the current findings and importance of stromal factors in lymphoma biology.