Germline variation in the 3'-untranslated region of the POU2AF1 gene is associated with susceptibility to lymphoma

The Role of the Transcriptional Coactivator BOB.1/OBF.1 in Adaptive Immunity

BOB.1/OBF.1 is a transcriptional coactivator involved in octamer-dependent transcription. Thereby, BOB.1/OBF.1 is involved in the transcriptional regulation of genes important for lymphocyte physiology. BOB.1/OBF.1-deficient mice reveal multiple B- and T-cell developmental defects. The most prominent defect of these mice is the complete absence of germinal centers (GCs) resulting in severely impaired T-cell-dependent immune responses. In humans, BOB.1/OBF.1 is associated with several autoimmune and inflammatory diseases but also linked to liquid and solid tumors. Although its role for B-cell development is relatively well understood, its exact role for the GC reaction and T-cell biology has long been unclear. Here, the contribution of BOB.1/OBF.1 for B-cell maturation is summarized, and recent findings regarding its function in GC B- as well as in various T-cell populations are discussed. Finally, a detailed perspective on how BOB.1/OBF.1 contributes to different pathologies is provided.

The TiHoCL panel for canine lymphoma: a feasibility study integrating functional genomics and network biology approaches for comparative oncology targeted NGS panel design

Targeted next-generation sequencing (NGS) enables the identification of genomic variants in cancer patients with high sensitivity at relatively low costs, and has thus opened the era to personalized human oncology. Veterinary medicine tends to adopt new technologies at a slower pace compared to human medicine due to lower funding, nonetheless it embraces technological advancements over time. Hence, it is reasonable to assume that targeted NGS will be incorporated into routine veterinary practice in the foreseeable future. Many animal diseases have well-researched human counterparts and hence, insights gained from the latter might, in principle, be harnessed to elucidate the former. Here, we present the TiHoCL targeted NGS panel as a proof of concept, exemplifying how functional genomics and network approaches can be effectively used to leverage the wealth of information available for human diseases in the development of targeted sequencing panels for veterinary medicine. Specifically, the TiHoCL targeted NGS panel is a molecular tool for characterizing and stratifying canine lymphoma (CL) patients designed based on human non-Hodgkin lymphoma (NHL) research outputs. While various single nucleotide polymorphisms (SNPs) have been associated with high risk of developing NHL, poor prognosis and resistance to treatment in NHL patients, little is known about the genetics of CL. Thus, the ~100 SNPs featured in the TiHoCL targeted NGS panel were selected using functional genomics and network approaches following a literature and database search that shielded ~500 SNPs associated with, in nearly all cases, human hematologic malignancies. The TiHoCL targeted NGS panel underwent technical validation and preliminary functional assessment by sequencing DNA samples isolated from blood of 29 lymphoma dogs using an Ion Torrent™ PGM System achieving good sequencing run metrics. Our design framework holds new possibilities for the design of similar molecular tools applied to other diseases for which limited knowledge is available and will improve drug target discovery and patient care.

Double-edged sword role of miRNA-633 and miRNA-181 in human cancers

Understanding the function and mode of operation of microRNAs (miRNAs) in cancer is of growing interest. The short non-coding RNAs known as miRNAs, which target mRNA in multicellular organisms, are described as controlling essential cellular processes. The miR-181 family and miR-633 are well-known miRNAs that play a key role in the development and metastasis of tumor cells. They may facilitate either tumor-suppressive or oncogenic function in malignant cells, according to mounting evidence. Metastatic cells that are closely linked to cancer cell migration, invasion, and angiogenesis can be identified by abnormal levels of miR-181 and miR-633. Numerous studies have demonstrated their capacity to control drug resistance, cell growth, apoptosis, and the epithelial-mesenchymal transition (EMT) and metastasis process. Interestingly, the levels of miR-181 and miR-633 and their potential target genes in the basic cellular process can vary depending on the type of cancer cells and their gene expression profile. Such miRNAs' interactions with other non-coding RNAs such as long non-coding RNAs and circular RNAs can influence tumor behaviors. Herein, we concentrated on the multifaceted roles of miR-181 and miR-633 and potential targets in human tumorigenesis, ranging from cell growth and metastasis to drug resistance.

The transcriptional program during germinal center reaction - a close view at GC B cells, Tfh cells and Tfr cells

The germinal center (GC) reaction is a key process during an adaptive immune response to T cell specific antigens. GCs are specialized structures within secondary lymphoid organs, in which B cell proliferation, somatic hypermutation and antibody affinity maturation occur. As a result, high affinity antibody secreting plasma cells and memory B cells are generated. An effective GC response needs interaction between multiple cell types. Besides reticular cells and follicular dendritic cells, particularly B cells, T follicular helper (Tfh) cells as well as T follicular regulatory (Tfr) cells are a key player during the GC reaction. Whereas Tfh cells provide help to GC B cells in selection processes, Tfr cells, a specialized subset of regulatory T cells (Tregs), are able to suppress the GC reaction maintaining the balance between immune activation and tolerance. The formation and function of GCs is regulated by a complex network of signals and molecules at multiple levels. In this review, we highlight recent developments in GC biology by focusing on the transcriptional program regulating the GC reaction. This review focuses on the transcriptional co-activator BOB.1/OBF.1, whose important role for GC B, Tfh and Tfr cell differentiation became increasingly clear in recent years. Moreover, we outline how deregulation of the GC transcriptional program can drive lymphomagenesis.

Identification of Signature Genes in the PD-1 Relative Gastric Cancer Using a Combined Analysis of Gene Expression and Methylation Data

BACKGROUND

The morbidity and mortality rates for gastric cancer (GC) rank second among all cancers, indicating the serious threat it poses to human health, as well as human life. This study aims to identify the pathways and genes as well as investigate the molecular mechanisms of tumor-related genes in gastric cancer (GC).

METHOD

We compared differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in gastric cancer and normal tissue samples using The Cancer Genome Atlas (TCGA) data. The Kyoto Encyclopedia of Gene and Genome (KEGG) and the Gene Ontology (GO) enrichment analysis' pathway annotations were conducted on DMGs and DEGs using a clusterProfiler R package to identify the important functions, as well as the biological processes and pathways involved. The intersection of the two was chosen and defined as differentially methylated and expressed genes (DMEGs). For DMEGs, we used the principal component analysis (PCA) to differentiate gastric cancer from adjacent samples. The linear discriminant analysis method was applied to categorize the samples using DMEGs methylation data and DMEGs expression profiles data and was validated using the leave-one-out cross-validation (LOOCV) method. We plotted the ROC curve for the classification and calculated the AUC (area under the ROC curve) value for a more intuitive view of the classification effect. We also used the NetworkAnalyst 3.0 tool to analyze DMEGs, using DrugBank to acquire information on protein-drug interactions and generate a network map of gene-drug interactions.

RESULTS

We identified a total of 971 DMGs in 188 PD-1 negative and 187 PD-1 positive gastric cancer samples obtained from TCGA. The KEGG and GO enrichment analysis showed the involvement of the regulation of ion transmembrane transport, collagen-containing extracellular matrix, cell-cell junction, and peptidase regulator activity. We simultaneously obtained 1,189 DEGs, out of which 986 were downregulated, while 203 were upregulated in tumors. The enriched analysis of the GO's and KEGG's pathways indicated that the most significant pathways included an intestinal immune network for IgA production, Staphylococcus aureus infection, cytokine-cytokine receptor interaction, and viral protein interaction with cytokine and cytokine receptor, which have previously been linked with gastric cancer. The compound DB01830 can bind well to the active site of the LCK protein and shows good stability, thus making it a potential inhibitor of the LCK protein. To observe the relationship between DMEGs' expression and prognosis, we observed 10 genes, among which were TRIM29, TSPAN8, EOMES, PPP1R16B, SELL, PCED1B, IYD, JPH1, CEACAM5, and RP11-44K6.2. Their high expressions were related to high risks. Besides, those genes were validated in different internal and external validation sets.

CONCLUSION

These results may provide potential molecular biological therapy for PD-1 negative gastric cancer.

The landscape and driver potential of site-specific hotspots across cancer genomes

Large sets of whole cancer genomes make it possible to study mutation hotspots genome-wide. Here we detect, categorize, and characterize site-specific hotspots using 2279 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes project and provide a resource of annotated hotspots genome-wide. We investigate the excess of hotspots in both protein-coding and gene regulatory regions and develop measures of positive selection and functional impact for individual hotspots. Using cancer allele fractions, expression aberrations, mutational signatures, and a variety of genomic features, such as potential gain or loss of transcription factor binding sites, we annotate and prioritize all highly mutated hotspots. Genome-wide we find more high-frequency SNV and indel hotspots than expected given mutational background models. Protein-coding regions are generally enriched for SNV hotspots compared to other regions. Gene regulatory hotspots show enrichment of potential same-patient second-hit missense mutations, consistent with enrichment of hotspot driver mutations compared to singletons. For protein-coding regions, splice-sites, promoters, and enhancers, we see an excess of hotspots associated with cancer genes. Interestingly, missense hotspot mutations in tumor suppressors are associated with elevated expression, suggesting localized amino-acid changes with functional impact. For individual non-coding hotspots, only a small number show clear signs of positive selection, including known sites in the TERT promoter and the 5' UTR of TP53. Most of the new candidates have few mutations and limited driver evidence. However, a hotspot in an enhancer of the oncogene POU2AF1, which may create a transcription factor binding site, presents multiple lines of driver-consistent evidence.

Identification of four genes associated with cutaneous metastatic melanoma

Background

Cutaneous melanoma is an aggressive cancer with increasing incidence and mortality rates worldwide. Metastasis is one of the primary elements that influence the prognosis of patients with cutaneous melanoma. This study aims to clarify the potential mechanism underlying the low survival rate of metastatic melanoma and to search for novel target genes to improve the survival rate of patients with metastatic tumors.

Methods

Gene expression dataset and clinical data were downloaded from The Cancer Genome Atlas portal. Differentially expressed genes (DEGs) were identified, and their functions were studied through gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. Survival and multivariate Cox regression analyses were used to screen out candidate genes that could affect the prognosis of patients with metastatic melanoma.

Results

After a series of comprehensive statistical analysis, 464 DEGs were identified between primary tumor tissues and metastatic tissues. Survival and multivariate Cox regression analyses revealed four vital genes, namely, POU2AF1, ITGAL, CXCR2P1, and MZB1, that affect the prognosis of patients with metastatic melanoma.

Conclusion

This study provides a new direction for studying the pathogenesis of metastatic melanoma. The genes related to cutaneous metastatic melanoma that affect the overall survival time of patients were identified.

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

Bronchiolitis obliterans syndrome (BOS), the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group), and 26 samples at or after BOS diagnosis (diagnosis group). An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group). We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1), T-cell leukemia/lymphoma protein 1A (TCL1A), and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01) and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.