The invasion of activated fibroblasts represents a key pathomechanism in fibrotic diseases, carcinogenesis and metastasis. Here, invading fibroblasts contribute to fibrotic extracellular matrix (ECM) formation and the initiation, progression, or resistance of cancer, respectively. To construct a transcriptome-wide signature of fibroblast invasion, we used a multiplex phenotypic 3D invasion assay using murine lung fibroblasts. Microarray-based gene expression profiles of invading and non-invading fibroblasts were highly distinct: 1049 genes were differentially regulated (>1.5-fold). An unbiased pathway analysis (Ingenuity) identified a significant enrichment for the functional clusters invasion of cells, idiopathic pulmonary fibrosis (IPF) and metastasis. Particularly, matrix metalloprotease13 (MMP13), transforming growth factor (TGF)1, Caveolin1 (Cav1), Phosphatase and Tensin Homolog (Pten), and secreted frizzled-related protein1 (Sfrp1) were among the highest regulated genes. In silico analysis by Ingenuity predicted TGF1, epidermal growth factor (EGF), fibroblast growth factor2 (FGF2), and platelet-derived growth factor (PDGF)-BB to induce invasion. As such, these growth factors were tested in the 3D invasion assay and displayed a significant induction of invasion, thus validating the transcriptome profile. Accordingly, our transcriptomic invasion signature describes the invading fibroblast phenotype in unprecedented detail and provides a tool for future functional studies of cell invasion and therapeutic modulation thereof.
Validated prediction of pro-invasive growth factors using a transcriptome-wide invasion signature derived from a complex 3D invasion assay.
Sex
View SamplesThe main aim of this study was to assess the changes in blood gene expression in UCB patients and to identify genes serving as biomarkers for UCB diagnosis and progression.
A Specific Blood Signature Reveals Higher Levels of S100A12: A Potential Bladder Cancer Diagnostic Biomarker Along With Urinary Engrailed-2 Protein Detection.
Age
View SamplesThis SuperSeries is composed of the SubSeries listed below.
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.
Age, Specimen part, Disease, Disease stage
View SamplesWe demonstrate a promising approach to identify robust molecular markers for targeted treatment of acute myeloid leukemia. We show that our method outperforms several state-of-the-art approaches in identifying molecular markers replicated in validation data and predicting drug sensitivity accurately.
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.
Age, Specimen part, Disease, Disease stage
View SamplesWe demonstrate a promising approach to identify robust molecular markers for targeted treatment of acute myeloid leukemia. We show that our method outperforms several state-of-the-art approaches in identifying molecular markers replicated in validation data and predicting drug sensitivity accurately. Finally, we identify SMARCA4 as a marker and driver of sensitivity to topoisomerase II inhibitors, mitoxantrone and etoposide, in AML by showing that cell lines transduced to have high SMARCA4 expression reveal dramatically increased sensitivity to these agents. Overall design: We measured the gene expression of samples from 30 different AML patients with acute myeloid leukemia in order to identify reliable gene expression markers for drug sensitivity. We used this dataset for validation. This Series represents 12 patient samples.
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia.
Age, Specimen part, Disease, Disease stage, Subject
View SamplesMsi2 is a critical regulatior of myeoid leukemia, and these data identify genes that are changed following Msi2 deletion in bcCML and de novo AML stem cells.
Tetraspanin 3 Is Required for the Development and Propagation of Acute Myelogenous Leukemia.
Specimen part
View SamplesCurrent preclinical models in tumor biology are limited in their ability to recapitulate relevant (patho-) physiological processes, including autophagy. Three-dimensional (3D) growth cultures have frequently been proposed to overcome the lack of correlation between two-dimensional (2D) monolayer cell cultures and human tumors in preclinical drug testing. Besides 3D growth, it is also advantageous to simulate shear stress, compound flux and removal of metabolites, e.g. via bioreactor systems, through which culture medium is constantly pumped at a flow rate reflecting physiological conditions. Here, we show that both Staticic 3D growth and 3D growth within a bioreactor system modulate key hallmarks of cancer cells, including proliferation and cell death as well as macroautophagy, a recycling pathway often activated by highly proliferative tumors to cope with metabolic stress. The autophagy-related gene expression profiles of 2D- and 3D-grown cells are substantially different, with the 3D-grown cells exhibiting an expression profile closely resembling the (patho-) physiological Statice of a tumor. Underscoring the importance of this pathway, autophagy-controlling transcription factors, such as TFEB and FOXO3, are upregulated in tumors, and 3D-grown cells have increased expression compared with cells grown in 2D conditions. Three-dimensional cultures depleted of the autophagy mediators BECN1, ATG5 or ATG7 or the transcription factor FOXO3, are more sensitive to cytotoxic treatment. Accordingly, combining cytotoxic treatment with compounds affecting late autophagic flux, such as chloroquine, renders the 3D-grown cells more susceptible to therapy and increases intracellular doxorubicin concentration to the level of 2D-grown cells. Altogether, 3D cultures are a valuable tool to study drug response of tumor cells, as these models recapitulate (patho-) physiologically relevant pathways, such as autophagy.
Three-dimensional tumor cell growth stimulates autophagic flux and recapitulates chemotherapy resistance.
Specimen part, Cell line
View SamplesTo identify gene expression that distinguishes hematopoietic cells that express PRAME from those that do not, normal CD34+ cells with forced PRAME expression were compared to cells without PRAME expression in culture over time (days 4, 7, 14) using Affymetrix HU-133A microarrays
The preferentially expressed antigen in melanoma (PRAME) inhibits myeloid differentiation in normal hematopoietic and leukemic progenitor cells.
Specimen part, Time
View SamplesThe prognosis of advanced stage neuroblastoma patients remains poor and, despite intensive therapy, the 5-year survival rate remains less than 50%. We previously identified histone deacetylase (HDAC) 8 as an indicator of poor clinical outcome and a selective drug target for differentiation therapy in vitro and in vivo. Here we performed kinome-wide RNAi screening to identify genes that are synthetically lethal with HDAC8 inhibitors. These experiments identified the neuroblastoma predisposition gene ALK as a candidate gene. Accordingly, the combination of the ALK/MET inhibitor crizotinib and selective HDAC8 inhibitors (3-6M PCI-34051 or 10M 20a) efficiently killed neuroblastoma cell lines carrying wildtype ALK (SK-N-BE(2)-C, IMR5/75), amplified ALK (NB-1), and those carrying the activating ALK F1174L mutation (Kelly), and, in cells carrying the activating R1275Q mutation (LAN-5), combination treatment decreased viable cell count. The effective dose of crizotinib in neuroblastoma cell lines ranged from 0.05M (ALK-amplified) to 0.8M (wildtype ALK). The combinatorial inhibition of ALK and HDAC8 also decreased tumor growth in an in vivo zebrafish xenograft model. Bioinformatic analyses revealed that the mRNA expression level of HDAC8 was significantly correlated with that of ALK in two independent patient cohorts, the Academic Medical Center cohort (n=88) and the German Neuroblastoma Trial cohort (n=649), and co-expression of both target genes identified patients with very poor outcome. Mechanistically, HDAC8 and ALK converge at the level of receptor tyrosine kinase (RTK) signaling and their downstream survival pathways, such as ERK signaling. Combination treatment of HDAC8 inhibitor with crizotinib efficiently blocked the activation of growth receptor survival signaling and shifted the cell cycle arrest and differentiation phenotype toward effective cell death of neuroblastoma cell lines, including sensitization of resistant models, but not of normal cells. These findings reveal combined targeting of ALK and HDAC8 as a novel strategy for the treatment of neuroblastoma.
A kinome-wide RNAi screen identifies ALK as a target to sensitize neuroblastoma cells for HDAC8-inhibitor treatment.
Specimen part
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Reduced chromatin binding of MYC is a key effect of HDAC inhibition in MYC amplified medulloblastoma.
Specimen part, Treatment
View Samples