MOTIFATOR: detection and characterization of regulatory motifs using prokaryote transcriptome data

Summary: Unraveling regulatory mechanisms (e.g. identification of motifs in cis-regulatory regions) remains a major challenge in the analysis of transcriptome experiments. Existing applications identify putative motifs from gene lists obtained at rather arbitrary cutoff and require additional manual processing steps. Our standalone application MOTIFATOR identifies the most optimal parameters for motif discovery and creates an interactive visualization of the results. Discovered putative motifs are functionally characterized, thereby providing valuable insight in the biological processes that could be controlled by the motif.

Tailoring CD19xCD3-DART exposure enhances T-cells to eradication of B-cell neoplasms.

Many patients with B-cell malignancies can be successfully treated, although tumor eradication is rarely achieved. T-cell-directed killing of tumor cells using engineered T-cells or bispecific antibodies is a promising approach for the treatment of hematologic malignancies. We investigated the efficacy of CD19xCD3 DART bispecific antibody in a broad panel of human primary B-cell malignancies. The CD19xCD3 DART identified 2 distinct subsets of patients, in which the neoplastic lymphocytes were eliminated with rapid or slow kinetics. Delayed responses were always overcome by a prolonged or repeated DART exposure. Both CD4 and CD8 effector cytotoxic cells were generated, and DART-mediated killing of CD4+ cells into cytotoxic effectors required the presence of CD8+ cells. Serial exposures to DART led to the exponential expansion of CD4 + and CD8 + cells and to the sequential ablation of neoplastic cells in absence of a PD-L1-mediated exhaustion. Lastly, patient-derived neoplastic B-cells (B-Acute Lymphoblast Leukemia and Diffuse Large B Cell Lymphoma) could be proficiently eradicated in a xenograft mouse model by DART-armed cytokine induced killer (CIK) cells. Collectively, patient tailored DART exposures can result in the effective elimination of CD19 positive leukemia and B-cell lymphoma and the association of bispecific antibodies with unmatched CIK cells represents an effective modality for the treatment of CD19 positive leukemia/lymphoma

Cancer cells exploit an orphan RNA to drive metastatic progression.

Here we performed a systematic search to identify breast-cancer-specific small noncoding RNAs, which we have collectively termed orphan noncoding RNAs (oncRNAs). We subsequently discovered that one of these oncRNAs, which originates from the 3' end of TERC, acts as a regulator of gene expression and is a robust promoter of breast cancer metastasis. This oncRNA, which we have named T3p, exerts its prometastatic effects by acting as an inhibitor of RISC complex activity and increasing the expression of the prometastatic genes NUPR1 and PANX2. Furthermore, we have shown that oncRNAs are present in cancer-cell-derived extracellular vesicles, raising the possibility that these circulating oncRNAs may also have a role in non-cell autonomous disease pathogenesis. Additionally, these circulating oncRNAs present a novel avenue for cancer fingerprinting using liquid biopsies

ABEMUS: platform specific and data informed detection of somatic SNVs in cfDNA

MOTIVATION: The use of liquid biopsies for cancer patients enables the non-invasive tracking of treatment response and tumor dynamics through single or serial blood drawn tests. Next generation sequencing assays allow for the simultaneous interrogation of extended sets of somatic single nucleotide variants (SNVs) in circulating cell free DNA (cfDNA), a mixture of DNA molecules originating both from normal and tumor tissue cells. However, low circulating tumor DNA (ctDNA) fractions together with sequencing background noise and potential tumor heterogeneity challenge the ability to confidently call SNVs. RESULTS: We present a computational methodology, called Adaptive Base Error Model in Ultra-deep Sequencing data (ABEMUS), which combines platform-specific genetic knowledge and empirical signal to readily detect and quantify somatic SNVs in cfDNA. We tested the capability of our method to analyze data generated using different platforms with distinct sequencing error properties and we compared ABEMUS performances with other popular SNV callers on both synthetic and real cancer patients sequencing data. Results show that ABEMUS performs better in most of the tested conditions proving its reliability in calling low variant allele frequencies somatic SNVs in low ctDNA levels plasma samples. AVAILABILITY: ABEMUS is cross-platform and can be installed as R package. The source code is maintained on Github at http://github.com/cibiobcg/abemus and it is also available at CRAN official R repository. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Rewiring Endothelial Sphingolipid Metabolism to Favor S1P Over Ceramide Protects From Coronary Atherosclerosis

Background: Growing evidence correlated changes in bioactive sphingolipids, particularly S1P (sphingosine-1-phosphate) and ceramides, with coronary artery diseases. Furthermore, specific plasma ceramide species can predict major cardiovascular events. Dysfunction of the endothelium lining lesion-prone areas plays a pivotal role in atherosclerosis. Yet, how sphingolipid metabolism and signaling change and contribute to endothelial dysfunction and atherosclerosis remain poorly understood. Methods: We used an established model of coronary atherosclerosis in mice, combined with sphingolipidomics, RNA-sequencing, flow cytometry, and immunostaining to investigate the contribution of sphingolipid metabolism and signaling to endothelial cell (EC) activation and dysfunction. Results: We demonstrated that hemodynamic stress induced an early metabolic rewiring towards endothelial sphingolipid de novo biosynthesis, favoring S1P signaling over ceramides as a protective response. This finding is a paradigm shift from the current belief that ceramide accrual contributes to endothelial dysfunction. The enzyme SPT (serine palmitoyltransferase) commences de novo biosynthesis of sphingolipids and is inhibited by NOGO-B (reticulon-4B), an ER membrane protein. Here, we showed that NOGO-B is upregulated by hemodynamic stress in myocardial EC of ApoE-/- mice and is expressed in the endothelium lining coronary lesions in mice and humans. We demonstrated that mice lacking NOGO-B specifically in EC (Nogo-A/BECKOApoE-/-) were resistant to coronary atherosclerosis development and progression, and mortality. Fibrous cap thickness was significantly increased in Nogo-A/BECKOApoE-/- mice and correlated with reduced necrotic core and macrophage infiltration. Mechanistically, the deletion of NOGO-B in EC sustained the rewiring of sphingolipid metabolism towards S1P, imparting an atheroprotective endothelial transcriptional signature. Conclusions: These data demonstrated that hemodynamic stress induced a protective rewiring of sphingolipid metabolism, favoring S1P over ceramide. NOGO-B deletion sustained the rewiring of sphingolipid metabolism toward S1P protecting EC from activation under hemodynamic stress and refraining coronary atherosclerosis. These findings also set forth the foundation for sphingolipid-based therapeutics to limit atheroprogression

Unsupervised discovery of tissue architecture in multiplexed imaging

Multiplexed imaging and spatial transcriptomics enable highly resolved spatial characterization of cellular phenotypes, but still largely depend on laborious manual annotation to understand higher-order patterns of tissue organization. As a result, higher-order patterns of tissue organization are poorly understood and not systematically connected to disease pathology or clinical outcomes. To address this gap, we developed an approach called UTAG to identify and quantify microanatomical tissue structures in multiplexed images without human intervention. Our method combines information on cellular phenotypes with the physical proximity of cells to accurately identify organ-specific microanatomical domains in healthy and diseased tissue. We apply our method to various types of images across healthy and disease states to show that it can consistently detect higher-level architectures in human tissues, quantify structural differences between healthy and diseased tissue, and reveal tissue organization patterns at the organ scale

A parallel, distributed-memory framework for comparative motif discovery

The increasing number of sequenced organisms has opened new possibilities for the computational discovery of cis-regulatory elements ('motifs') based on phylogenetic footprinting. Word-based, exhaustive approaches are among the best performing algorithms, however, they pose significant computational challenges as the number of candidate motifs to evaluate is very high. In this contribution, we describe a parallel, distributed-memory framework for de novo comparative motif discovery. Within this framework, two approaches for phylogenetic footprinting are implemented: an alignment-based and an alignment-free method. The framework is able to statistically evaluate the conservation of motifs in a search space containing over 160 million candidate motifs using a distributed-memory cluster with 200 CPU cores in a few hours. Software available from http://bioinformatics.intec.ugent.be/blsspeller

The novel lncRNA BlackMamba controls the neoplastic phenotype of ALK- anaplastic large cell lymphoma by regulating the DNA helicase HELLS.

The molecular mechanisms leading to the transformation of anaplastic lymphoma kinase negative (ALK-) anaplastic large cell lymphoma (ALCL) have been only in part elucidated. To identify new culprits which promote and drive ALCL, we performed a total transcriptome sequencing and discovered 1208 previously unknown intergenic long noncoding RNAs (lncRNAs), including 18 lncRNAs preferentially expressed in ALCL. We selected an unknown lncRNA, BlackMamba, with an ALK- ALCL preferential expression, for molecular and functional studies. BlackMamba is a chromatin-associated lncRNA regulated by STAT3 via a canonical transcriptional signaling pathway. Knockdown experiments demonstrated that BlackMamba contributes to the pathogenesis of ALCL regulating cell growth and cell morphology. Mechanistically, BlackMamba interacts with the DNA helicase HELLS controlling its recruitment to the promoter regions of cell-architecture-related genes, fostering their expression. Collectively, these findings provide evidence of a previously unknown tumorigenic role of STAT3 via a lncRNA-DNA helicase axis and reveal an undiscovered role for lncRNA in the maintenance of the neoplastic phenotype of ALK-ALCL