Dynamics of mRNA and polysomal abundance in early 3T3-L1 adipogenesis.

BACKGROUND: Adipogenesis is a complex process, in which immature pre-adipocytes change morphology, micro-anatomy and physiology to become mature adipocytes. These store and accumulate fat and release diverse hormones. Massive changes in protein content and protein composition of the transforming cell take place within a short time-frame.In a previous study we analyzed changes in the abundance of free and polysomal, i.e. ribosome bound, RNAs in the first hours of adipogenesis in the murine cell line 3T3-L1. Here we analyze changes of mRNA levels and their potential contribution to the changing protein pool by determination of mRNA levels and ribosome binding to mRNAs in 3T3-L1 cells stimulated for adipogenesis. We grouped mRNA species into categories with respect to up- or down-regulated transcription and translation and analyzed the groups regarding specific functionalities based on Gene Ontology (GO). RESULTS: A shift towards up-regulation of gene expression in early adipogenesis was detected. Genes up-regulated at the transcriptional (TC:up) and translational (TL:up) level (TC:up/TL:up) are very likely involved in control and logistics of translation. Many of them are known to contain a TOP motif. In the TC:up/TL:unchanged group we detected most of the metal binding proteins and metal transporters. In the TC:unchanged/TL:up group several factors of the olfactory receptor family were identified, while in TC:unchanged/TL:down methylation and repair genes are represented. In the TC:down/TL:up group we detected many signaling factors. The TC:down/TL:unchanged group mainly consists of regulatory factors. CONCLUSIONS: Within the first hours of adipogenesis, changes in transcriptional and translational regulation take place. Notably, genes with a specific biological or molecular function tend to cluster in groups according to their transcriptional and translational regulation.

Tumor specimen cold ischemia time impacts molecular cancer drug target discovery.

Tumor tissue collections are used to uncover pathways associated with disease outcomes that can also serve as targets for cancer treatment, ideally by comparing the molecular properties of cancer tissues to matching normal tissues. The quality of such collections determines the value of the data and information generated from their analyses including expression and modifications of nucleic acids and proteins. These biomolecules are dysregulated upon ischemia and decompose once the living cells start to decay into inanimate matter. Therefore, ischemia time before final tissue preservation is the most important determinant of the quality of a tissue collection. Here we show the impact of ischemia time on tumor and matching adjacent normal tissue samples for mRNAs in 1664, proteins in 1818, and phosphosites in 1800 cases (tumor and matching normal samples) of four solid tumor types (CRC, HCC, LUAD, and LUSC NSCLC subtypes). In CRC, ischemia times exceeding 15 min impacted 12.5% (mRNA), 25% (protein), and 50% (phosphosites) of differentially expressed molecules in tumor versus normal tissues. This hypoxia- and decay-induced dysregulation increased with longer ischemia times and was observed across tumor types. Interestingly, the proteomics analysis revealed that specimen ischemia time above 15 min is mostly associated with a dysregulation of proteins in the immune-response pathway and less so with metabolic processes. We conclude that ischemia time is a crucial quality parameter for tissue collections used for target discovery and validation in cancer research.

Novel polysome messages and changes in translational activity appear after induction of adipogenesis in 3T3-L1 cells.

BACKGROUND: Control of translation allows for rapid adaptation of the cell to stimuli, rather than the slower transcriptional control. We presume that translational control is an essential process in the control of adipogenesis, especially in the first hours after hormonal stimulation. 3T3-L1 preadipocytes were cultured to confluency and adipogenesis was induced by standard protocols using a hormonal cocktail. Cells were harvested before and 6 hours after hormonal induction. mRNAs attached to ribosomes (polysomal mRNAs) were separated from unbound mRNAs by velocity sedimentation. Pools of polysomal and unbound mRNA fractions were analyzed by microarray analysis. Changes in relative abundance in unbound and polysomal mRNA pools were calculated to detect putative changes in translational activity. Changes of expression levels of selected genes were verified by qPCR and Western blotting. RESULTS: We identified 43 genes that shifted towards the polysomal fraction (up-regulated) and 2 genes that shifted towards free mRNA fraction (down-regulated). Interestingly, we found Ghrelin to be down-regulated. Up-regulated genes comprise factors that are nucleic acid binding (eIF4B, HSF1, IRF6, MYC, POLR2a, RPL18, RPL27a, RPL6, RPL7a, RPS18, RPSa, TSC22d3), form part of ribosomes (RPL18, RPL27a, RPL6, RPL7a, RPS18, RPSa), act on the regulation of translation (eIF4B) or transcription (HSF1, IRF6, MYC, TSC22d3). Others act as chaperones (BAG3, HSPA8, HSP90ab1) or in other metabolic or signals transducing processes. CONCLUSIONS: We conclude that a moderate reorganisation of the functionality of the ribosomal machinery and translational activity are very important steps for growth and gene expression control in the initial phase of adipogenesis.

A new analysis approach of epidermal growth factor receptor pathway activation patterns provides insights into cetuximab resistance mechanisms in head and neck cancer.

The pathways downstream of the epidermal growth factor receptor (EGFR) have often been implicated to play crucial roles in the development and progression of various cancer types. Different authors have proposed models in cell lines in which they study the modes of pathway activities after perturbation experiments. It is prudent to believe that a better understanding of these pathway activation patterns might lead to novel treatment concepts for cancer patients or at least allow a better stratification of patient collectives into different risk groups or into groups that might respond to different treatments. Traditionally, such analyses focused on the individual players of the pathways. More recently in the field of systems biology, a plethora of approaches that take a more holistic view on the signaling pathways and their downstream transcriptional targets has been developed. Fertig et al. have recently developed a new method to identify patterns and biological process activity from transcriptomics data, and they demonstrate the utility of this methodology to analyze gene expression activity downstream of the EGFR in head and neck squamous cell carcinoma to study cetuximab resistance. Please see related article: http://www.biomedcentral.com/1471-2164/13/160.

Multi-omic based molecular profiling of advanced cancer identifies treatable targets and improves survival in individual patients.

A proof-of-concept study was conducted to assess whether patients with advanced stage IV cancer for whom predominantly no standard therapy was available could benefit from comprehensive molecular profiling of their tumor tissue to provide targeted therapy. Tumor samples of 83 patients were collected under highly standardized conditions and analyzed using immunohistochemistry, next-generation sequencing and phosphoprotein profiling. Expression and phosphorylation of key oncogenic pathways were measured to identify targets at the (phospho-) proteomic level. At genomic level, 50 oncogenes and tumor suppressor genes were analyzed. Based on molecular profiling, targeted therapies were decided by the attending oncologist. Accordingly, 28 patients who met the defined criteria fell in two equal-sized groups. One group received targeted therapies while the other did not. Following six months of treatment, disease control was achieved by 49% of patients receiving targeted therapy (complete remission, 14%; partial remission, 21%; stable disease, 14%; disease progression, 36%; death, 14%) and 21% of patients receiving non-targeted therapy (stable disease, 21%; disease progression, 64%; death, 14%). Individual patients experienced dramatic responses to a therapy which otherwise would not have been applied. This approach clarifies the value of multi-omic molecular profiling for cancer diagnostics.

Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data.

In this chapter, we describe an approach to reconstruct cellular signaling networks based on measurements of protein activation after different stimulation experiments. As experimental platform reverse-phase protein arrays (RPPA) are used. RPPA allow the measurement of proteins and phosphoproteins across many samples in parallel with minimal sample consumption using a panel of highly target protein-specific antibodies. Functional interactions of proteins are modeled using a Boolean network. We describe the Boolean network reconstruction approach ddepn (dynamic deterministic effects propagation networks), which uses time course data to derive protein interactions based on perturbation experiments. We explain how the method works, give a practical application example, and describe how the results can be interpreted. Furthermore prior knowledge on signaling pathways is essential for network reconstruction. Here we describe the use of our software rBiopaxParser to integrate prior knowledge on protein signaling available in public databases. All applied methods are freely available as open-source R software packages. We describe the preparation of RPPA data as well as all relevant programming steps to format the RPPA data, to infer the prior knowledge, and to reconstruct and analyze the protein signaling networks.

mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer.

Intrinsic and acquired resistance to the monoclonal antibody drug trastuzumab is a major problem in the treatment of HER2-positive breast cancer. A deeper understanding of the underlying mechanisms could help to develop new agents. Our intention was to detect genes and single nucleotide polymorphisms (SNPs) affecting trastuzumab efficiency in cell culture. Three HER2-positive breast cancer cell lines with different resistance phenotypes were analyzed. We chose BT474 as model of trastuzumab sensitivity, HCC1954 as model of intrinsic resistance, and BTR50, derived from BT474, as model of acquired resistance. Based on RNA-Seq data, we performed differential expression analyses on these cell lines with and without trastuzumab treatment. Differentially expressed genes between the resistant cell lines and BT474 are expected to contribute to resistance. Differentially expressed genes between untreated and trastuzumab treated BT474 are expected to contribute to drug efficacy. To exclude false positives from the candidate gene set, we removed genes that were also differentially expressed between untreated and trastuzumab treated BTR50. We further searched for SNPs in the untreated cell lines which could contribute to trastuzumab resistance. The analysis resulted in 54 differentially expressed candidate genes that might be connected to trastuzumab efficiency. 90% of 40 selected candidates were validated by RT-qPCR. ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line. GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed. Additionally, we inferred SNPs in HCC1954 for CAV1, PTGS2, IL8 and IGFBP3. The latter also had a variation in BTR50. 20% of the validated subset have already been mentioned in literature. For half of them we called and analyzed SNPs. These results contribute to a better understanding of trastuzumab action and resistance mechanisms.

Boolean ErbB network reconstructions and perturbation simulations reveal individual drug response in different breast cancer cell lines.

BACKGROUND: Despite promising progress in targeted breast cancer therapy, drug resistance remains challenging. The monoclonal antibody drugs trastuzumab and pertuzumab as well as the small molecule inhibitor erlotinib were designed to prevent ErbB-2 and ErbB-1 receptor induced deregulated protein signalling, contributing to tumour progression. The oncogenic potential of ErbB receptors unfolds in case of overexpression or mutations. Dimerisation with other receptors allows to bypass pathway blockades. Our intention is to reconstruct the ErbB network to reveal resistance mechanisms. We used longitudinal proteomic data of ErbB receptors and downstream targets in the ErbB-2 amplified breast cancer cell lines BT474, SKBR3 and HCC1954 treated with erlotinib, trastuzumab or pertuzumab, alone or combined, up to 60 minutes and 30 hours, respectively. In a Boolean modelling approach, signalling networks were reconstructed based on these data in a cell line and time course specific manner, including prior literature knowledge. Finally, we simulated network response to inhibitor combinations to detect signalling nodes reflecting growth inhibition. RESULTS: The networks pointed to cell line specific activation patterns of the MAPK and PI3K pathway. In BT474, the PI3K signal route was favoured, while in SKBR3, novel edges highlighted MAPK signalling. In HCC1954, the inferred edges stimulated both pathways. For example, we uncovered feedback loops amplifying PI3K signalling, in line with the known trastuzumab resistance of this cell line. In the perturbation simulations on the short-term networks, we analysed ERK1/2, AKT and p70S6K. The results indicated a pathway specific drug response, driven by the type of growth factor stimulus. HCC1954 revealed an edgetic type of PIK3CA-mutation, contributing to trastuzumab inefficacy. Drug impact on the AKT and ERK1/2 signalling axes is mirrored by effects on RB and RPS6, relating to phenotypic events like cell growth or proliferation. Therefore, we additionally analysed RB and RPS6 in the long-term networks. CONCLUSIONS: We derived protein interaction models for three breast cancer cell lines. Changes compared to the common reference network hint towards individual characteristics and potential drug resistance mechanisms. Simulation of perturbations were consistent with the experimental data, confirming our combined reverse and forward engineering approach as valuable for drug discovery and personalised medicine.

RPPanalyzer toolbox: an improved R package for analysis of reverse phase protein array data.

Analysis of large-scale proteomic data sets requires specialized software tools, tailored toward the requirements of individual approaches. Here we introduce an extension of an open-source software solution for analyzing reverse phase protein array (RPPA) data. The R package RPPanalyzer was designed for data preprocessing followed by basic statistical analyses and proteomic data visualization. In this update, we merged relevant data preprocessing steps into a single user-friendly function and included a new method for background noise correction as well as new methods for noise estimation and averaging of replicates to transform data in such a way that they can be used as input for a new time course plotting function. We demonstrate the robustness of our enhanced RPPanalyzer platform by analyzing longitudinal RPPA data of MET receptor signaling upon stimulation with different hepatocyte growth factor concentrations.

Human migratory meniscus progenitor cells are controlled via the TGF-ß pathway.

Degeneration of the knee joint during osteoarthritis often begins with meniscal lesions. Meniscectomy, previously performed extensively after meniscal injury, is now obsolete because of the inevitable osteoarthritis that occurs following this procedure. Clinically, meniscus self-renewal is well documented as long as the outer, vascularized meniscal ring remains intact. In contrast, regeneration of the inner, avascular meniscus does not occur. Here, we show that cartilage tissue harvested from the avascular inner human meniscus during the late stages of osteoarthritis harbors a unique progenitor cell population. These meniscus progenitor cells (MPCs) are clonogenic and multipotent and exhibit migratory activity. We also determined that MPCs are likely to be controlled by canonical transforming growth factor ß (TGF-ß) signaling that leads to an increase in SOX9 and a decrease in RUNX2, thereby enhancing the chondrogenic potential of MPC. Therefore, our work is relevant for the development of novel cell biological, regenerative therapies for meniscus repair.

Extrinsic and intrinsic regulation of DOR/TP53INP2 expression in mice: effects of dietary fat content, tissue type and sex in adipose and muscle tissues.

BACKGROUND: DOR/TP53INP2 acts both at the chromosomal level as a nuclear co-factor e.g. for the thyroid hormone receptor and at the extrachromosomal level as an organizing factor of the autophagosome. In a previous study, DOR was shown to be down-regulated in skeletal muscle of obese diabetic Zucker fa/fa rats. METHODS: To identify sites of differential DOR expression in metabolically active tissues, we measured differences in DOR expression in white adipose tissue (WAT), brown adipose tissue (BAT), skeletal muscle (SM) and heart muscle (HM) by qPCR. To assess whether DOR expression is influenced in the short term by nutritional factors, NMRI mice were fed different fat rich diets (fat diet, FD: 18% or high fat diet, HFD: 80% fat) for one week and DOR expression was compared to NMRI mice fed a control diet (normal diet, ND: 3.3% fat). Additionally, DOR expression was measured in young (45 days old) and adult (100 days old) genetically obese (DU6/DU6i) mice and compared to control (DUKs/DUKsi) animals. RESULTS: ANOVA results demonstrate a significant influence of diet, tissue type and sex on DOR expression in adipose and muscle tissues of FD and HFD mice. In SM, DOR expression was higher in HFD than in FD male mice. In WAT, DOR expression was increased compared to BAT in male FD and HFD mice. In contrast, expression levels in female mice were higher in BAT for both dietary conditions.DOR expression levels in all tissues of 100 days old genetically obese animals were mainly influenced by sex. In HM, DOR expression was higher in male than female animals. CONCLUSIONS: DOR expression varies under the influence of dietary fat content, tissue type and sex. We identified target tissues for further studies to analyze the specific function of DOR in obesity. DOR might be part of a defense mechanism against fat storage in high fat diets or obesity.