MicroRNAs are key regulators of hepatocellular carcinoma (HCC) cell dissemination—what we learned from microRNA-494

Producción CientíficaHepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide, and it is well accepted that the poor outcome of HCC patients among others is caused by metastasis and tumor cell dissemination

Tumor cell load and heterogeneity estimation from diffusion-weighted MRI calibrated with histological data: an example from lung cancer

Producción CientíficaDiffusion-weighted magnetic resonance imaging (DWI) is a key non-invasive imaging technique for cancer diagnosis and tumor treatment assessment, reflecting Brownian movement of water molecules in tissues. Since densely packed cells restrict molecule mobility, tumor tissues produce usually higher signal (a.k.a. less attenuated signal) on isotropic maps compared with normal tissues. However, no general quantitative relation between DWI data and the cell density has been established. In order to link low-resolution clinical cross-sectional data with high-resolution histological information, we developed an image processing and analysis chain, which was used to study the correlation between the diffusion coefficient (D value) estimated from DWI and tumor cellularity from serial histological slides of a resected non-small cell lung cancer tumor. Color deconvolution followed by cell nuclei segmentation was performed on digitized histological images to determine local and cell-type specific 2d (two-dimensional) densities. From these, the 3d cell density was inferred by a model-based sampling technique, which is necessary for the calculation of local and global 3d tumor cell count. Next, DWI sequence information was overlaid with high-resolution CT data and the resected histology using prominent anatomical hallmarks for co-registration of histology tissue blocks and non-invasive imaging modalities' data. The integration of cell numbers information and DWI data derived from different tumor areas revealed a clear negative correlation between cell density and D value. Importantly, spatial tumor cell density can be calculated based on DWI data. In summary, our results demonstrate that tumor cell count and heterogeneity can be predicted from DWI data, which may open new opportunities for personalized diagnosis and therapy optimization

Patch-based nonlinear image registration for gigapixel whole slide images

Producción CientíficaImage registration of whole slide histology images allows the fusion of fine-grained information-like different immunohistochemical stains-from neighboring tissue slides. Traditionally, pathologists fuse this information by looking subsequently at one slide at a time. If the slides are digitized and accurately aligned at cell level, automatic analysis can be used to ease the pathologist's work. However, the size of those images exceeds the memory capacity of regular computers. Methods: We address the challenge to combine a global motion model that takes the physical cutting process of the tissue into account with image data that is not simultaneously globally available. Typical approaches either reduce the amount of data to be processed or partition the data into smaller chunks to be processed separately. Our novel method first registers the complete images on a low resolution with a nonlinear deformation model and later refines this result on patches by using a second nonlinear registration on each patch. Finally, the deformations computed on all patches are combined by interpolation to form one globally smooth nonlinear deformation. The NGF distance measure is used to handle multistain images. Results: The method is applied to ten whole slide image pairs of human lung cancer data. The alignment of 85 corresponding structures is measured by comparing manual segmentations from neighboring slides. Their offset improves significantly, by at least 15%, compared to the low-resolution nonlinear registration. Conclusion/Significance: The proposed method significantly improves the accuracy of multistain registration which allows us to compare different antibodies at cell level

Nuclear pore component Nup98 is a potential tumor suppressor and regulates posttranscriptional expression of select p53 target genes

The p53 tumor suppressor utilizes multiple mechanisms to selectively regulate its myriad target genes, which in turn mediate diverse cellular processes. Here, using conventional and single-molecule mRNA analyses, we demonstrate that the nucleoporin Nup98 is required for full expression of p21, a key effector of the p53 pathway, but not several other p53 target genes. Nup98 regulates p21 mRNA levels by a posttranscriptional mechanism in which a complex containing Nup98 and the p21 mRNA 3\u27UTR protects p21 mRNA from degradation by the exosome. An in silico approach revealed another p53 target (14-3-3sigma) to be similarly regulated by Nup98. The expression of Nup98 is reduced in murine and human hepatocellular carcinomas (HCCs) and correlates with p21 expression in HCC patients. Our study elucidates a previously unrecognized function of wild-type Nup98 in regulating select p53 target genes that is distinct from the well-characterized oncogenic properties of Nup98 fusion proteins

Elevated expression of c-kit in small venous malformations of blue rubber bleb nevus syndrome

The blue rubber bleb nevus syndrome (BRBNS, syn. bean syndrome) is a rare disease characterized by multiple cutaneous and gastrointestinal venous malformations associated with severe bleeding. However, the underlying molecular mechanisms are unknown and no targeted therapeutic approach exists to date. Here we report the case of a 19-year-old male patient with severe BRBNS in whom we analyzed the expression of tyrosine kinases frequently involved in tumor development by immunohistochemistry (vascular endothelial growth factor receptor-2, stem cell growth factor receptor (c-kit), platelet-derived growth factor receptor-β, and stem cell tyrosine kinase-1). A prominent expression of c-kit was detectable in smaller blood vessels, which also showed a moderate expression of the proliferation marker MIB1. Surprisingly, other growth factor receptors stained negatively. We therefore conclude that pharmacological inhibition of the c-kit signaling pathway in cavernous hemangiomas by selective kinase inhibitors may offer options in the treatment of BRBNS patients

Methylation in MIRLET7A3 Gene Induces the Expression of IGF-II and Its mRNA Binding Proteins IGF2BP-2 and 3 in Hepatocellular Carcinoma

miR-let-7a is a tumor suppressor miRNA with reduced expression in most cancers. Methylation of MIRLET7A3 gene was reported to be the cause of this suppression in several cancers; however, it was not explicitly investigated in hepatocellular carcinoma (HCC). We aimed at investigating miR-let-7a expression and molecular mode in HCC, identifying drug-targetable networks, which might be affected by its abundance. Our results illustrated a significant repression of miR-let-7a, which correlated with hypermethylation of its gene of origin MIRLRT7A3. This was further supported by the induction of miR-let-7a expression upon treatment of HCC cells with a DNA-methyltransferase inhibitor. Using a computational approach, insulin-like growth factor (IGF)-II and IGF-2 mRNA binding proteins (IGF2BP)-2/-3 were identified as potential targets for miR-let-7a that was further confirmed experimentally. Indeed, miR-let-7a mimics diminished IGF-II as well as IGF2BP-2/-3 expression. Direct binding of miR-let-7a to each respective transcript was confirmed using a luciferase reporter assay. In conclusion, this study suggests that DNA hypermethylation leads to epigenetic repression of miR-let-7a in HCC cells, which induces the oncogenic IGF-signaling pathway

Number of chemical compounds for each role in CCONT.

<p>Chemical compounds play different roles for the growth of cell lines. In column two we show how many compounds are necessary for describing a specific role. Column three shows the respective number of roles already present in EFO.</p

On the Ontology Based Representation of Cell Lines

<div><p>Cell lines are frequently used as highly standardized and reproducible <em>in vitro</em> models for biomedical analyses and assays. Cell lines are distributed by cell banks that operate databases describing their products. However, the description of the cell lines' properties are not standardized across different cell banks. Existing cell line-related ontologies mostly focus on the description of the cell lines' names, but do not cover aspects like the origin or optimal growth conditions. The objective of this work is to develop an ontology that allows for a more comprehensive description of cell lines and their metadata, which should cover the data elements provided by cell banks. This will provide the basis for the standardized annotation of cell lines and corresponding assays in biomedical research. In addition, the ontology will be the foundation for automated evaluation of such assays and their respective protocols in the future. To accomplish this, a broad range of cell bank databases as well as existing ontologies were analyzed in a comprehensive manner. We identified existing ontologies capable of covering different aspects of the cell line domain. However, not all data fields derived from the cell banks' databases could be mapped to existing ontologies. As a result, we created a new ontology called <em>cell culture ontology (CCONT)</em> integrating existing ontologies where possible. CCONT provides classes from the areas of cell line identification, origin, cell line properties, propagation and tests performed.</p> </div