Comparative computational analysis to distinguish mesenchymal stem cells from fibroblasts

IntroductionMesenchymal stem cells (MSCs) are considered to be the most promising stem cell type for cell-based therapies in regenerative medicine. Based on their potential to home to diseased body sites following a therapeutically application, these cells could (i) differentiate then into organ-specific cell types to locally restore injured cells or, most prominently, (ii) foster tissue regeneration including immune modulations more indirectly by secretion of protective growth factors and cytokines. As tissue-resident stem cells of mesenchymal origin, these cells are morphologically and even molecularly- at least concerning the classical marker genes- indistinguishable from similar lineage cells, particularly fibroblasts.MethodsHere we used microarray-based gene expression and global DNA methylation analyses as well as accompanying computational tools in order to specify differences between MSCs and fibroblasts, to further unravel potential identity genes and to highlight MSC signaling pathways with regard to their trophic and immunosuppressive action.ResultsWe identified 1352 differentially expressed genes, of which in the MSCs there is a strong signature for e.g., KRAS signaling, known to play essential role in stemness maintenance, regulation of coagulation and complement being decisive for resolving inflammatory processes, as well as of wound healing particularly important for their regenerative capacity. Genes upregulated in fibroblasts addressed predominately transcription and biosynthetic processes and mapped morphological features of the tissue. Concerning the cellular identity, we specified the already known HOX code for MSCs, established a potential HOX code for fibroblasts, and linked certain HOX genes to functional cell-type-specific properties. Accompanied methylation profiles revealed numerous regions, especially in HOX genes, being differentially methylated, which might provide additional biomarker potential.DiscussionConclusively, transcriptomic together with epigenetic signatures can be successfully be used for the definition (cellular identity) of MSCs versus fibroblasts as well as for the determination of the superior functional properties of MSCs, such as their immunomodulatory potential

Can nanolites enhance eruption explosivity?

Degassing dynamics play a crucial role in controlling the explosivity of magma at erupting volcanoes. Degassing of magmatic water typically involves bubble nucleation and growth, which drive magma ascent. Crystals suspended in magma may influence both nucleation and growth of bubbles. Micron- to centimeter-sized crystals can cause heterogeneous bubble nucleation and facilitate bubble coalescence. Nanometer-scale crystalline phases, so-called “nanolites”, are an underreported phenomenon in erupting magma and could exert a primary control on the eruptive style of silicic volcanoes. Yet the influence of nanolites on degassing processes remains wholly uninvestigated. In order to test the influence of nanolites on bubble nucleation and growth dynamics, we use an experimental approach to document how nanolites can increase the bubble number density and affect growth kinetics in a degassing nanolite-bearing silicic magma. We then examine a compilation of these values from natural volcanic rocks from explosive eruptions leading to the inference that some very high naturally occurring bubble number densities could be associated with the presence of magmatic nanolites. Finally, using a numerical magma ascent model, we show that for reasonable starting conditions for silicic eruptions, an increase in the resulting bubble number density associated with nanolites could push an eruption that would otherwise be effusive into the conditions required for explosive behavior

Caprin-1, a novel Cyr61-interacting protein, promotes osteosarcoma tumor growth and lung metastasis in mice

Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents. More than 30% of patients develop lung metastasis, which is the leading cause of mortality. Recently, the extracellular matrix protein Cyr61 has been recognized as a malignancy promoting protein in OS mouse model with prognostic potential in human OS. In this study, we aimed at the identification of novel Cyr61-interacting proteins. Here we report that Cyr61 associates with Caprin-1, and confocal microscopy showed that stable ectopic expression of Caprin-1 leads to the formation of stress granules containing Caprin-1 and Cyr61, confers resistance to cisplatin-induced apoptosis, and resulted in constitutive phosphorylation of Akt and ERK1/2. Importantly, ectopic expression of Caprin-1 dramatically enhanced primary tumor growth, remarkably increased lung metastatic load in a SCID intratibial OS mouse model, and decreased significantly (p<0.0018) the survival of the mice. Although Caprin-1 expression, evaluated with a tissue microarray including samples from 59 OS patients, failed to be an independent predictor for the patients' outcome in this limited cohort of patients, increased Caprin-1 expression indicated a tendency to shortened overall survival, and more strikingly, Cyr61/Caprin-1 co-expression was associated with worse survival than that observed for patients with tumors expressing either Cyr61 or Caprin-1 alone or none of these proteins. The findings imply that Caprin-1 may have a metastasis promoting role in OS and show that through resistance to apoptosis and via the activation of Akt and ERK1/2 pathways, Caprin-1 is significantly involved in the development of OS metastasis

Auto-granulation of particle surfaces during Surtseyan eruptions

[Abstract unavailable

SDHA gain-of-function engages inflammatory mitochondrial retrograde signaling via KEAP1-Nrf2.

Whether screening the metabolic activity of immune cells facilitates discovery of molecular pathology remains unknown. Here we prospectively screened the extracellular acidification rate as a measure of glycolysis and the oxygen consumption rate as a measure of mitochondrial respiration in B cells from patients with primary antibody deficiency. The highest oxygen consumption rate values were detected in three study participants with persistent polyclonal B cell lymphocytosis (PPBL). Exome sequencing identified germline mutations in SDHA, which encodes succinate dehydrogenase subunit A, in all three patients with PPBL. SDHA gain-of-function led to an accumulation of fumarate in PPBL B cells, which engaged the KEAP1-Nrf2 system to drive the transcription of genes encoding inflammatory cytokines. In a single patient trial, blocking the activity of the cytokine interleukin-6 in vivo prevented systemic inflammation and ameliorated clinical disease. Overall, our study has identified pathological mitochondrial retrograde signaling as a disease modifier in primary antibody deficiency

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment