Metastatic seeding is driven by cell-intrinsic and environmental cues, yet the contribution of biomechanics is poorly known. We aim to elucidate the impact of blood flow on the arrest and the extravasation of circulating tumor cells (CTCs) in vivo. Using the zebrafish embryo, we show that arrest of CTCs occurs in vessels with favorable flow profiles where flow forces control the adhesion efficacy of CTCs to the endothelium. We biophysically identified the threshold values of flow and adhesion forces allowing successful arrest of CTCs. In addition, flow forces fine-tune tumor cell extravasation by impairing the remodeling properties of the endothelium. Importantly, we also observe endothelial remodeling at arrest sites of CTCs in mouse brain capillaries. Finally, we observed that human supratentorial brain metastases preferably develop in areas with low perfusion. These results demonstrate that hemodynamic profiles at metastatic sites regulate key steps of extravasation preceding metastatic outgrowth.

Shwachman-Diamond syndrome (SDS) (OMIM #260400) is a rare inherited bone marrow failure syndrome (IBMFS) that is primarily characterized by neutropenia and exocrine pancreatic insufficiency. Seventy-five to ninety percent of patients have compound heterozygous loss-of-function mutations in the Shwachman-Bodian-Diamond syndrome (SBDS) gene. Using trio whole-exome sequencing (WES) in an SBDS-negative SDS family and candidate gene sequencing in additional SBDS-negative SDS cases or molecularly undiagnosed IBMFS cases, we identified 3 independent patients, each of whom carried a de novo missense variant in SRP54 (encoding signal recognition particle 54 kDa). These 3 patients shared congenital neutropenia linked with various other SDS phenotypes. 3D protein modeling revealed that the 3 variants affect highly conserved amino acids within the GTPase domain of the protein that are critical for GTP and receptor binding. Indeed, we observed that the GTPase activity of the mutated proteins was impaired. The level of SRP54 mRNA in the bone marrow was 3.6-fold lower in patients with SRP54-mutations than in healthy controls. Profound reductions in neutrophil counts and chemotaxis as well as a diminished exocrine pancreas size in a SRP54-knockdown zebrafish model faithfully recapitulated the human phenotype. In conclusion, autosomal dominant mutations in SRP54, a key member of the cotranslation protein-targeting pathway, lead to syndromic neutropenia with a Shwachman-Diamond-like phenotype.

The Protein Data Bank (PDB) has been processed to extract a screening protein library (sc-PDB) of 2148 entries. A knowledge-based detection algorithm has been applied to 18,000 PDB files to find regular expressions corresponding to either protein, ions, co-factors, solvent, or ligand atoms. The sc-PDB database comprises high-resolution X-ray structures of proteins for which (i) a well-defined active site exists, (ii) the bound-ligand is a small molecular weight molecule. The database has been screened by an inverse docking tool derived from the GOLD program to recover the known target of four unrelated ligands. Both the database and the inverse screening procedures are accurate enough to rank the true target of the four investigated ligands among the top 1% scorers, with 70-100 fold enrichment with respect to random screening. Applying the proposed screening procedure to a small-sized generic ligand was much less accurate suggesting that inverse screening shall be reserved to rather selective compounds.

BackgroundMicroRNAs (miRNAs) are endogenous 21 to 23-nucleotide RNA molecules that regulate protein-coding gene expression in plants and animals via the RNA interference pathway. Hundreds of them have been identified in the last five years and very recent works indicate that their total number is still larger. Therefore miRNAs gene discovery remains an important aspect of understanding this new and still widely unknown regulation mechanism. Bioinformatics approaches have proved to be very useful toward this goal by guiding the experimental investigations.ResultsIn this work we describe our computational method for miRNA prediction and the results of its application to the discovery of novel mammalian miRNAs. We focus on genomic regions around already known miRNAs, in order to exploit the property that miRNAs are occasionally found in clusters. Starting with the known human, mouse and rat miRNAs we analyze 20 kb of flanking genomic regions for the presence of putative precursor miRNAs (pre-miRNAs). Each genome is analyzed separately, allowing us to study the species-specific identity and genome organization of miRNA loci. We only use cross-species comparisons to make conservative estimates of the number of novel miRNAs. Our ab initio method predicts between fifty and hundred novel pre-miRNAs for each of the considered species. Around 30% of these already have experimental support in a large set of cloned mammalian small RNAs. The validation rate among predicted cases that are conserved in at least one other species is higher, about 60%, and many of them have not been detected by prediction methods that used cross-species comparisons. A large fraction of the experimentally confirmed predictions correspond to an imprinted locus residing on chromosome 14 in human, 12 in mouse and 6 in rat. Our computational tool can be accessed on the world-wide-web.ConclusionOur results show that the assumption that many miRNAs occur in clusters is fruitful for the discovery of novel miRNAs. Additionally we show that although the overall miRNA content in the observed clusters is very similar across the three considered species, the internal organization of the clusters changes in evolution.

BackgroundIn addition to acting as an RNA quality control pathway, nonsense-mediated mRNA decay (NMD) plays roles in regulating normal gene expression. In particular, the extent to which alternative splicing is coupled to NMD and the roles of NMD in regulating uORF containing transcripts have been a matter of debate. ResultsIn order to achieve a greater understanding of NMD regulated gene expression we used 2D-DiGE proteomics technology to examine the changes in protein expression induced in HeLa cells by UPF1 knockdown. QPCR based validation of the corresponding mRNAs, in response to both UPF1 knockdown and cycloheximide treatment, identified 17 bona fide NMD targets. Most of these were associated with bioinformatically predicted NMD activating features, predominantly upstream open reading frames (uORFs). Strikingly, however, the majority of transcripts up-regulated by UPF1 knockdown were either insensitive to, or even down-regulated by, cycloheximide treatment. Furthermore, the mRNA abundance of several down-regulated proteins failed to change upon UPF1 knockdown, indicating that UPF1's role in regulating mRNA and protein abundance is more complex than previously appreciated. Among the bona fide NMD targets, we identified a highly conserved AS-NMD event within the 3' UTR of the HNRNPA2B1 gene. Overexpression of GFP tagged hnRNP A2 resulted in a decrease in endogenous hnRNP A2 and B1 mRNA with a concurrent increase in the NMD sensitive isoforms.ConclusionsDespite the large number of changes in protein expression upon UPF1 knockdown, a relatively small fraction of them can be directly attributed to the action of NMD on the corresponding mRNA. From amongst these we have identified a conserved AS-NMD event within HNRNPA2B1 that appears to mediate autoregulation of HNRNPA2B1 expression levels.

Inherent immune suppression represents a major challenge in the treatment of human cancer. The extracellular matrix molecule tenascin-C promotes cancer by multiple mechanisms, yet the roles of tenascin-C in tumor immunity are incompletely understood.Using a 4NQO-induced oral squamous cell carcinoma (OSCC) model with abundant and absent tenascin-C, we demonstrated that tenascin-C enforced an immune suppressive lymphoid stroma via CCL21/CCR7 signaling, leading to increased metastatic tumors. Through TLR4, tenascin-C increased expression of CCR7 in CD11c+ myeloid cells. By inducing CCL21 in lymphatic endothelial cells via integrin  and binding to CCL21, tenascin-C immobilized CD11c+ cells in the stroma. Inversion of the lymph node-to-tumor CCL21 gradient, recruitment of T regulatory cells, high expression of anti-inflammatory cytokines and matrisomal components were hallmarks of the tenascin-C-instructed lymphoid stroma. Ablation of tenascin-C or CCR7 blockade inhibited the lymphoid immune suppressive stromal properties, reducing tumor growth, progression and metastasis. Thus, targeting CCR7 could be relevant in human head and neck tumors as high tenascin-C expression and an immune suppressive stroma correlate to poor patient survival.

Our finding confirms the genetic/clinical heterogeneity of the disorder; corroborated by previous identification of ADCY5 mutations in one family with dyskinesia-facial myokymia and in two unrelated sporadic cases of paxoysmal choreic/dystonia-facial myokymia; ADCY5's high expression in the striatum and movement disorders in ADCY5-deficient mice. Hence ADCY5 genetic analyses may be relevant in the diagnostic workup of unexplained early-onset hyperkinetic movement disorders.

Protein-based virtual screening of chemical libraries is a powerful technique for identifying new molecules that may interact with a macromolecular target of interest. Because of docking and scoring limitations, it is more difficult to apply as a lead optimization method because it requires that the docking/scoring tool is able to propose as few solutions as possible and all of them with a very good accuracy for both the protein-bound orientation and the conformation of the ligand. In the present study, we present a consensus docking approach (ConsDock) that takes advantage of three widely used docking tools (Dock, FlexX, and Gold). The consensus analysis of all possible poses generated by several docking tools is performed sequentially in four steps: (i) hierarchical clustering of all poses generated by a docking tool into families represented by a leader; (ii) definition of all consensus pairs from leaders generated by different docking programs; (iii) clustering of consensus pairs into classes, represented by a mean structure; and (iv) ranking the different means starting from the most populated class of consensus pairs. When applied to a test set of 100 protein-ligand complexes from the Protein Data Bank, ConsDock significantly outperforms single docking with respect to the docking accuracy of the top-ranked pose. In 60% of the cases investigated here, ConsDock was able to rank as top solution a pose within 2 A RMSD of the X-ray structure. It can be applied as a postprocessing filter to either single- or multiple-docking programs to prioritize three-dimensional guided lead optimization from the most likely docking solution.