Systematic verification of upstream regulators of a computable cellular proliferation network model on non-diseased lung cells using a dedicated dataset.

We recently constructed a computable cell proliferation network (CPN) model focused on lung tissue to unravel complex biological processes and their exposure-related perturbations from molecular profiling data. The CPN consists of edges and nodes representing upstream controllers of gene expression largely generated from transcriptomics datasets using Reverse Causal Reasoning (RCR). Here, we report an approach to biologically verify the correctness of upstream controller nodes using a specifically designed, independent lung cell proliferation dataset. Normal human bronchial epithelial cells were arrested at G1/S with a cell cycle inhibitor. Gene expression changes and cell proliferation were captured at different time points after release from inhibition. Gene set enrichment analysis demonstrated cell cycle response specificity via an overrepresentation of proliferation related gene sets. Coverage analysis of RCR-derived hypotheses returned statistical significance for cell cycle response specificity across the whole model as well as for the Growth Factor and Cell Cycle sub-network models.

A modular cell-type focused inflammatory process network model for non-diseased pulmonary tissue.

Exposure to environmental stressors such as cigarette smoke (CS) elicits a variety of biological responses in humans, including the induction of inflammatory responses. These responses are especially pronounced in the lung, where pulmonary cells sit at the interface between the body's internal and external environments. We combined a literature survey with a computational analysis of multiple transcriptomic data sets to construct a computable causal network model (the Inflammatory Process Network (IPN)) of the main pulmonary inflammatory processes. The IPN model predicted decreased epithelial cell barrier defenses and increased mucus hypersecretion in human bronchial epithelial cells, and an attenuated pro-inflammatory (M1) profile in alveolar macrophages following exposure to CS, consistent with prior results. The IPN provides a comprehensive framework of experimentally supported pathways related to CS-induced pulmonary inflammation. The IPN is freely available to the scientific community as a resource with broad applicability to study the pathogenesis of pulmonary disease.

Construction of a computable network model for DNA damage, autophagy, cell death, and senescence.

Towards the development of a systems biology-based risk assessment approach for environmental toxicants, including tobacco products in a systems toxicology setting such as the "21st Century Toxicology", we are building a series of computable biological network models specific to non-diseased pulmonary and cardiovascular cells/tissues which capture the molecular events that can be activated following exposure to environmental toxicants. Here we extend on previous work and report on the construction and evaluation of a mechanistic network model focused on DNA damage response and the four main cellular fates induced by stress: autophagy, apoptosis, necroptosis, and senescence. In total, the network consists of 34 sub-models containing 1052 unique nodes and 1538 unique edges which are supported by 1231 PubMed-referenced literature citations. Causal node-edge relationships are described using the Biological Expression Language (BEL), which allows for the semantic representation of life science relationships in a computable format. The Network is provided in .XGMML format and can be viewed using freely available network visualization software, such as Cytoscape.

Towards the validation of a lung tumorigenesis model with mainstream cigarette smoke inhalation using the A/J mouse.

A generally accepted and validated laboratory model for smoking-associated pulmonary tumorigenesis would be useful for both basic and applied research applications, such as the development of early diagnostic endpoints or the evaluation of modified risk tobacco products, respectively. The A/J mouse is susceptible for developing both spontaneous and induced lung adenomas and adenocarcinomas, and increased lung tumor multiplicities were also observed in previous cigarette smoke inhalation studies. The present study was designed to collect data useful towards the validation of an 18-month mainstream smoke (MS) inhalation model. Male and female A/J mice were exposed whole-body at three MS concentration levels for 6h/day, and the results were compared to a previous study in the same laboratory and with a similar design. A linear MS concentration-dependent increase in lung tumorigenesis was observed with similar slopes for both sexes and both studies and a maximal 5-fold increase in multiplicity beyond sham control. The minimal detectable difference in lung tumor multiplicity for the current study was 37%. In the larynx, papillomas were detectable in all MS-exposed groups in a non-concentration dependent manner. No other extra-pulmonary MS-dependent neoplastic lesions were found. Gene expression signatures of lung tumor tissues allowed a clear differentiation of sham- and high dose MS-exposed mice. In combination with data from previous smoke inhalation studies with A/J mice, the current data suggest that this model for MS inhalation-induced pulmonary tumorigenesis is reliable and relevant, two crucial requirements towards validation of such a model.

Construction of a computable cell proliferation network focused on non-diseased lung cells.

BACKGROUND: Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work. RESULTS: To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data. CONCLUSIONS: To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.

Improved cellular pharmacokinetics and pharmacodynamics underlie the wide anticancer activity of sagopilone.

Sagopilone (ZK-EPO) is the first fully synthetic epothilone undergoing clinical trials for the treatment of human tumors. Here, we investigate the cellular pathways by which sagopilone blocks tumor cell proliferation and compare the intracellular pharmacokinetics and the in vivo pharmacodynamics of sagopilone with other microtubule-stabilizing (or tubulin-polymerizing) agents. Cellular uptake and fractionation/localization studies revealed that sagopilone enters cells more efficiently, associates more tightly with the cytoskeleton, and polymerizes tubulin more potently than paclitaxel. Moreover, in contrast to paclitaxel and other epothilones [such as the natural product epothilone B (patupilone) or its partially synthetic analogue ixabepilone], sagopilone is not a substrate of the P-glycoprotein efflux pumps. Microtubule stabilization by sagopilone caused mitotic arrest, followed by transient multinucleation and activation of the mitochondrial apoptotic pathway. Profiling of the proapoptotic signal transduction pathway induced by sagopilone with a panel of small interfering RNAs revealed that sagopilone acts similarly to paclitaxel. In HCT 116 colon carcinoma cells, sagopilone-induced apoptosis was partly antagonized by the knockdown of proapoptotic members of the Bcl-2 family, including Bax, Bak, and Puma, whereas knockdown of Bcl-2, Bcl-X(L), or Chk1 sensitized cells to sagopilone-induced cell death. Related to its improved subcellular pharmacokinetics, however, sagopilone is more cytotoxic than other epothilones in a large panel of human cancer cell lines in vitro and in vivo. In particular, sagopilone is highly effective in reducing the growth of paclitaxel-resistant cancer cells. These results underline the processes behind the therapeutic efficacy of sagopilone, which is now evaluated in a broad phase II program.

Characterization of new estrogen receptor destabilizing compounds: effects on estrogen-sensitive and tamoxifen-resistant breast cancer.

BACKGROUND: Antiestrogens of the selective estrogen receptor modulator (SERM) type, such as tamoxifen, have two major limitations: their mixed agonist and antagonist profile and the development of tumor resistance. We characterized two new pure antiestrogens-ZK-703 and ZK-253-that belong to the class of specific estrogen receptor destabilizers (SERDs), which includes fulvestrant, and compared their activity with that of fulvestrant and tamoxifen. METHODS: Effects of antiestrogens on the growth of estrogen-dependent breast tumors in vivo were determined using several mouse xenograft models (including the tamoxifen-sensitive tumors MCF7, T47D, and MV3366 and the tamoxifen-resistant tumors ZR75-1 and MCF7/TAM) and chemically induced (nitrosomethyl urea [NMU] and dimethylbenzanthracene [DMBA]) rat breast cancer models (groups of 10 animals). We determined the initial response and effects on hormone receptor levels and the time to relapse after treatment (i.e., time to reach a predetermined tumor size threshold). Estrogen receptor (ER) levels were determined by immunoassay. RESULTS: ZK-703 (administered subcutaneously) and ZK-253 (administered orally) were more effective than tamoxifen or fulvestrant at inhibiting the growth of ER-positive breast cancer in all xenograft models. For example, MCF7 tumors relapsed (i.e., reached the size threshold) in 10 weeks in mice treated with tamoxifen but in 30 weeks in mice treated with ZK-703. ZK-703 and ZK-253 also prevented further tumor progression in tamoxifen-resistant breast cancer models to a similar extent (more than 30 weeks in mice with ZR75-1 and MCF7/TAM tumors). In the chemically induced rat breast cancer models, orally administered ZK-703 and ZK-253 caused a nearly complete (>80%) inhibition of tumor growth. ER levels were dramatically reduced in MCF7 tumors after 5 weeks of ZK-703 treatment compared with ER levels in vehicle-treated tumors; by contrast, ER levels in tamoxifen-treated tumors were higher than those in control tumors. CONCLUSION: ZK-703 and ZK-253 are potent, long-term inhibitors of growth in both tamoxifen-sensitive and tamoxifen-resistant breast cancer models.

Estrogen/EGF receptor interactions in breast cancer: rationale for new therapeutic combination strategies.

In the therapy of estrogen receptor (ER) positive human mammary carcinomas, the treatment with the antiestrogen tamoxifen has been well established. However, the development of hormone resistance is an important factor in breast cancer progression against endocrine therapy. The presence of the receptor for EGF (EGFR) correlates with lack of response towards antiestrogen therapy. The EGFR is not only involved in tumor cell growth, survival signaling, cell migration, metastasis formation and angiogenesis, but also seems to confer reduced responses of tumor cells towards anti-hormones. Concomitant inhibition of both, the receptors for estrogen and EGF may be necessary to improve breast cancer therapy.

Studies on the development of resistance to the pure antiestrogen Faslodex in three human breast cancer cell lines.

In order to understand the mechanisms underlying the development of resistance to a pure antiestrogen we established three human breast carcinoma cell lines resistant to ZM 182780 (ZM) (Faslodex). Long-term cultivation of the ERalpha-positive, 17beta-estradiol (E(2))-responsive cell lines T47D, ZR-75-1, and MCF-7 with the pure antiestrogen ZM 182780 resulted in the T47D-r, ZR-75-1-r, and MCF-7-r cell lines, which proliferate continuously in the presence of 10(-6)M ZM 182780. The resulting antiestrogen-resistant cells grow equally well in medium with or without E(2) and in medium with or without ZM 182780 indicating that they are no longer estrogen-responsive. ERalpha expression was lost at the protein level in all three resistant cell lines. At the mRNA level, the ERalpha was only faintly detectable in T47D-r, whereas a weak signal was seen in ZR-75-1-r and MCF-7-r. By reverse transcription-polymerase chain reaction (RT-PCR) the ERbeta was detectable in the antiestrogen-sensitive and -resistant breast cancer cell lines, however, ZR75-1-r contained the smallest signal for ERbeta. In all three antiestrogen-resistant cells the PR was undetectable, whereas binding of epidermal growth factor (EGF) and protein expression of epidermal growth factor receptor (EGFR) were increased. To analyse alterations in the gene expression pattern in more detail Atlas arrays were hybridised with RNA isolated from T47D-r and T47D and the two Ca2+-binding proteins calgranulin A and B were found to be up-regulated in T47D-r compared to T47D. Calgranulin A and B were also both up-regulated in ZR-75-1-r and MCF-7-r compared to their antiestrogen-sensitive counterparts. Loss of ERalpha expression may be linked to the acquisition of antiestrogen resistance and enhanced expression of the EGFR and of proteins of the S100 family of Ca2+-binding proteins which may contribute to the outgrowth of resistant cells.

EGF receptor targeting in therapy-resistant human tumors.

The development of resistance against cytotoxic or endocrine therapy limits the number of chemotherapeutic compounds used in the clinic. The receptor for EGF (EGFR) is not only involved in survival signaling, cell migration, metastasis formation and angiogenesis, but also confers reduced responses of tumor cells towards cytotoxic compounds or radiation. Clinical trials designed to combine EGFR inhibitors with standard chemo- or radiation therapy have been successful. Elucidation of some of the molecular mechanisms of EGFR-mediated chemoresistance may lead to novel treatment approaches against molecules linked to EGFR signal transduction. In human breast carcinomas, the presence of EGFR correlates with lack of response towards anti-estrogen therapy suggesting the concomitant inhibition of both the receptors for estrogen and EGF to improve breast cancer therapy.