TTCA: an R package for the identification of differentially expressed genes in time course microarray data.

BACKGROUND: The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for detecting significant expression dynamics often fail when the expression dynamics show a large heterogeneity. Moreover, these methods often cannot cope with irregular and sparse measurements. RESULTS: The method proposed here is specifically designed for the analysis of perturbation responses. It combines different scores to capture fast and transient dynamics as well as slow expression changes, and performs well in the presence of low replicate numbers and irregular sampling times. The results are given in the form of tables including links to figures showing the expression dynamics of the respective transcript. These allow to quickly recognise the relevance of detection, to identify possible false positives and to discriminate early and late changes in gene expression. An extension of the method allows the analysis of the expression dynamics of functional groups of genes, providing a quick overview of the cellular response. The performance of this package was tested on microarray data derived from lung cancer cells stimulated with epidermal growth factor (EGF). CONCLUSION: Here we describe a new, efficient method for the analysis of sparse and heterogeneous time course data with high detection sensitivity and transparency. It is implemented as R package TTCA (transcript time course analysis) and can be installed from the Comprehensive R Archive Network, CRAN. The source code is provided with the Additional file 1.

Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells.

Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.

Downregulation of the TGFß Pseudoreceptor BAMBI in Non-Small Cell Lung Cancer Enhances TGFß Signaling and Invasion.

Non-small cell lung cancer (NSCLC) is characterized by early metastasis and has the highest mortality rate among all solid tumors, with the majority of patients diagnosed at an advanced stage where curative therapeutic options are lacking. In this study, we identify a targetable mechanism involving TGFß elevation that orchestrates tumor progression in this disease. Substantial activation of this pathway was detected in human lung cancer tissues with concomitant downregulation of BAMBI, a negative regulator of the TGFß signaling pathway. Alterations of epithelial-to-mesenchymal transition (EMT) marker expression were observed in lung cancer samples compared with tumor-free tissues. Distinct alterations in the DNA methylation of the gene regions encoding TGFß pathway components were detected in NSCLC samples compared with tumor-free lung tissues. In particular, epigenetic silencing of BAMBI was identified as a hallmark of NSCLC. Reconstitution of BAMBI expression in NSCLC cells resulted in a marked reduction of TGFß-induced EMT, migration, and invasion in vitro, along with reduced tumor burden and tumor growth in vivo In conclusion, our results demonstrate how BAMBI downregulation drives the invasiveness of NSCLC, highlighting TGFß signaling as a candidate therapeutic target in this setting. Cancer Res; 76(13); 3785-801. ©2016 AACR.

Erythropoietin improves the accumulation and therapeutic effects of carboplatin by enhancing tumor vascularization and perfusion.

Recombinant human erythropoietin (rhuEpo) is currently under debate for the treatment of chemotherapy-induced anemia due to clinical trials showing adverse effects in Epo-treated patients and the discovery of the erythropoietin-receptor (EpoR) in tumor and endothelial cells. Here, using Epo-Cy5.5 as theranostic near-infrared fluorescent probe we analyzed the effects of rhuEpo as co-medication to carboplatin in non-small-cell-lung-cancer (NSCLC)-xenografts with different tumor cell EpoR-expression (H838 ~8-fold higher than A549). Nude mice bearing subcutaneous A549 and H838 NSCLC-xenografts received either only carboplatin or carboplatin and co-medication of rhuEpo in two different doses. Tumor sizes and relative blood volumes (rBV) were longitudinally measured by 3D-contrast-enhanced ultrasound (3D-US). Tumoral EpoR-levels were determined by combined fluorescence molecular tomography (FMT)/ micro computed tomography (µCT) hybrid imaging. We found that rhuEpo predominantly acted on the tumor endothelium. In both xenografts, rhuEpo co-medication significantly increased vessel densities, diameters and the amount of perfused vessels. Accordingly, rhuEpo induced EpoR-phoshorylation and stimulated proliferation of endothelial cells. However, compared with solely carboplatin-treated tumors, tumor growth was significantly slower in the groups co-medicated with rhuEpo. This is explained by the Epo-mediated vascular remodeling leading to improved drug delivery as obvious by a more than 2-fold higher carboplatin accumulation and significantly enhanced tumor apoptosis. In addition, co-medication of rhuEpo reduced tumor hypoxia and diminished intratumoral EpoR-levels which continuously increased during carboplatin (Cp) -treatment. These findings suggest that co-medication of rhuEpo in well balanced doses can be used to improve the accumulation of anticancer drugs. Doses and indications may be personalized and refined using theranostic EpoR-probes.