Identification of Novel Protein Expression Changes Following Cisplatin Treatment and Application to Combination Therapy.

Determining the effect of chemotherapeutic treatment on changes in protein expression can provide important targets for overcoming resistance. Due to challenges in simultaneously measuring large numbers of proteins, a paucity of data exists on global changes. To overcome these challenges, we utilized microwestern arrays that allowed us to measure the abundance and modification state of hundreds of cell signaling and transcription factor proteins in cells following drug exposure. HapMap lymphoblastoid cell lines (LCLs) were exposed to cisplatin, a chemotherapeutic agent commonly used to treat testicular, head and neck, non-small cell lung, and gynecological cancers. We evaluated the expression of 259 proteins following 2, 6, and 12 h of cisplatin treatment in two LCLs with discordant sensitivity to cisplatin. Of these 259 proteins, 66 displayed significantly different protein expression changes (p < 0.05). Fifteen of these proteins were evaluated in a second pair of LCLs with discordant sensitivities to cisplatin; six demonstrated significant differences in expression. We then evaluated a subset of 63 proteins in a second set of LCLs with discordant sensitivity, and 40% of those that were significant in the first pair were also significant in the second part with concordant directionality (p < 0.05). We functionally validated one of the top proteins identified, PDK1, and demonstrated a synergistic relationship between cisplatin and a PDK1 inhibitor in multiple lung cancer lines. This study highlights the potential for identifying novel targets through an understanding of cellular changes in protein expression and modification following drug treatments.

Microwestern Arrays for Systems-Level Analysis of SH2 Domain-Containing Proteins.

The Microwestern Array (MWA) method combines the scalability and miniaturization afforded by the Reverse Phase Lysate Array (RPLA) approach with the electrophoretic separation characteristic of the Western blot. This technology emulates the creation of an array of small Western blots on a single sheet of nitrocellulose allowing for the sensitive and quantitative measurement of hundreds of proteins from hundreds of cell lysates with minimal cost and maximal accuracy, precision, and reproducibility. The MWA is a versatile technology that can be easily configured for purposes such as antibody screening, cell signaling network inference, protein modification/phenotype regression analysis, and genomic/proteomic relationships. Accordingly, configurations for the MWA can be optimized for maximal numbers of proteins analyzed from small numbers of cell lysates, for small numbers of antibodies against large numbers of cell lysates, or for maximal resolution of protein size achieved by increased electrophoretic separation distance. For example, on a single gel, 6 samples can be printed 96 times if a few samples need to be assayed with a large number of antibodies. Alternatively, up to 100 samples can be assayed with four antibodies on a single gel. Intermediate configurations are also discussed.The efficiency of the MWA is orders of magnitude greater in reagents, labor, and time required per data point relative to the standard Western blotting method and orders of magnitude more sensitive than standard mass spectrometry methods. The MWA is therefore a very attractive approach for capturing global changes in protein abundances and modifications including tyrosine phosphorylation and SH2 domain binding sites.

The DIONESUS algorithm provides scalable and accurate reconstruction of dynamic phosphoproteomic networks to reveal new drug targets.

Many drug candidates fail in clinical trials due to an incomplete understanding of how small-molecule perturbations affect cell phenotype. Cellular responses can be non-intuitive due to systems-level properties such as redundant pathways caused by co-activation of multiple receptor tyrosine kinases. We therefore created a scalable algorithm, DIONESUS, based on partial least squares regression with variable selection to reconstruct a cellular signaling network in a human carcinoma cell line driven by EGFR overexpression. We perturbed the cells with 26 diverse growth factors and/or small molecules chosen to activate or inhibit specific subsets of receptor tyrosine kinases. We then quantified the abundance of 60 phosphosites at four time points using a modified microwestern array, a high-confidence assay of protein abundance and modification. DIONESUS, after being validated using three in silico networks, was applied to connect perturbations, phosphorylation, and cell phenotype from the high-confidence, microwestern dataset. We identified enhancement of STAT1 activity as a potential strategy to treat EGFR-hyperactive cancers and PTEN as a target of the antioxidant, N-acetylcysteine. Quantification of the relationship between drug dosage and cell viability in a panel of triple-negative breast cancer cell lines validated proposed therapeutic strategies.

A systems approach to integrative biology: an overview of statistical methods to elucidate association and architecture.

An organism's ability to maintain a desired physiological response relies extensively on how cellular and molecular signaling networks interpret and react to environmental cues. The capacity to quantitatively predict how networks respond to a changing environment by modifying signaling regulation and phenotypic responses will help inform and predict the impact of a changing global enivronment on organisms and ecosystems. Many computational strategies have been developed to resolve cue-signal-response networks. However, selecting a strategy that answers a specific biological question requires knowledge both of the type of data being collected, and of the strengths and weaknesses of different computational regimes. We broadly explore several computational approaches, and we evaluate their accuracy in predicting a given response. Specifically, we describe how statistical algorithms can be used in the context of integrative and comparative biology to elucidate the genomic, proteomic, and/or cellular networks responsible for robust physiological response. As a case study, we apply this strategy to a dataset of quantitative levels of protein abundance from the mussel, Mytilus galloprovincialis, to uncover the temperature-dependent signaling network.

Enhanced prediction of Src homology 2 (SH2) domain binding potentials using a fluorescence polarization-derived c-Met, c-Kit, ErbB, and androgen receptor interactome.

Many human diseases are associated with aberrant regulation of phosphoprotein signaling networks. Src homology 2 (SH2) domains represent the major class of protein domains in metazoans that interact with proteins phosphorylated on the amino acid residue tyrosine. Although current SH2 domain prediction algorithms perform well at predicting the sequences of phosphorylated peptides that are likely to result in the highest possible interaction affinity in the context of random peptide library screens, these algorithms do poorly at predicting the interaction potential of SH2 domains with physiologically derived protein sequences. We employed a high throughput interaction assay system to empirically determine the affinity between 93 human SH2 domains and phosphopeptides abstracted from several receptor tyrosine kinases and signaling proteins. The resulting interaction experiments revealed over 1000 novel peptide-protein interactions and provided a glimpse into the common and specific interaction potentials of c-Met, c-Kit, GAB1, and the human androgen receptor. We used these data to build a permutation-based logistic regression classifier that performed considerably better than existing algorithms for predicting the interaction potential of several SH2 domains.

Comprehensive binary interaction mapping of SH2 domains via fluorescence polarization reveals novel functional diversification of ErbB receptors.

First-generation interaction maps of Src homology 2 (SH2) domains with receptor tyrosine kinase (RTK) phosphosites have previously been generated using protein microarray (PM) technologies. Here, we developed a large-scale fluorescence polarization (FP) methodology that was able to characterize interactions between SH2 domains and ErbB receptor phosphosites with higher fidelity and sensitivity than was previously achieved with PMs. We used the FP assay to query the interaction of synthetic phosphopeptides corresponding to 89 ErbB receptor intracellular tyrosine sites against 93 human SH2 domains and 2 phosphotyrosine binding (PTB) domains. From 358,944 polarization measurements, the affinities for 1,405 unique biological interactions were determined, 83% of which are novel. In contrast to data from previous reports, our analyses suggested that ErbB2 was not more promiscuous than the other ErbB receptors. Our results showed that each receptor displays unique preferences in the affinity and location of recruited SH2 domains that may contribute to differences in downstream signaling potential. ErbB1 was enriched versus the other receptors for recruitment of domains from RAS GEFs whereas ErbB2 was enriched for recruitment of domains from tyrosine and phosphatidyl inositol phosphatases. ErbB3, the kinase inactive ErbB receptor family member, was predictably enriched for recruitment of domains from phosphatidyl inositol kinases and surprisingly, was enriched for recruitment of domains from tyrosine kinases, cytoskeletal regulatory proteins, and RHO GEFs but depleted for recruitment of domains from phosphatidyl inositol phosphatases. Many novel interactions were also observed with phosphopeptides corresponding to ErbB receptor tyrosines not previously reported to be phosphorylated by mass spectrometry, suggesting the existence of many biologically relevant RTK sites that may be phosphorylated but below the detection threshold of standard mass spectrometry procedures. This dataset represents a rich source of testable hypotheses regarding the biological mechanisms of ErbB receptors.

Caffeic acid phenethyl ester suppresses the proliferation of human prostate cancer cells through inhibition of p70S6K and Akt signaling networks.

Caffeic acid phenethyl ester (CAPE) is a bioactive component derived from honeybee hive propolis. CAPE has been shown to have antimitogenic, anticarcinogenic, and other beneficial medicinal properties. Many of its effects have been shown to be mediated through its inhibition of NF-κB signaling pathways. We took a systematic approach to uncover the effects of CAPE from hours to days on the signaling networks in human prostate cancer cells. We observed that CAPE dosage dependently suppressed the proliferation of LNCaP, DU-145, and PC-3 human prostate cancer cells. Administration of CAPE by gavage significantly inhibited the tumor growth of LNCaP xenografts in nude mice. Using LNCaP cells as a model system, we examined the effect of CAPE on gene expression, protein signaling, and transcriptional regulatory networks using micro-Western arrays and PCR arrays. We built a model of the impact of CAPE on cell signaling which suggested that it acted through inhibition of Akt-related protein signaling networks. Overexpression of Akt1 or c-Myc, a downstream target of Akt signaling, significantly blocked the antiproliferative effects of CAPE. In summary, our results suggest that CAPE administration may be useful as an adjuvant therapy for prostate and potentially other types of cancers that are driven by the p70S6K and Akt signaling networks.

Systematic discovery of TLR signaling components delineates viral-sensing circuits.

Deciphering the signaling networks that underlie normal and disease processes remains a major challenge. Here, we report the discovery of signaling components involved in the Toll-like receptor (TLR) response of immune dendritic cells (DCs), including a previously unkown pathway shared across mammalian antiviral responses. By combining transcriptional profiling, genetic and small-molecule perturbations, and phosphoproteomics, we uncover 35 signaling regulators, including 16 known regulators, involved in TLR signaling. In particular, we find that Polo-like kinases (Plk) 2 and 4 are essential components of antiviral pathways in vitro and in vivo and activate a signaling branch involving a dozen proteins, among which is Tnfaip2, a gene associated with autoimmune diseases but whose role was unknown. Our study illustrates the power of combining systematic measurements and perturbations to elucidate complex signaling circuits and discover potential therapeutic targets.

Effect of complementary pathway blockade on efficacy of combination enzastaurin and rapamycin.

BACKGROUND: Rapamycin is an mTOR inhibitor with preclinical efficacy in squamous cell carcinoma of the head and neck (SCCHN). However, mTOR inhibitors also increase Akt activity in SCCHN cell lines, which would promote survival and oncogenesis. Enzastaurin is an AGC kinase inhibitor with nanomolar inhibitory concentrations for Akt and protein kinase C (PKC). Moreover, Akt and PKC inhibitors have demonstrated efficacy in SCCHN. METHODS: We hypothesized that the combination of rapamycin and enzastaurin would be more effective than either agent alone. RESULTS: Rapamycin and enzastaurin generally inhibited putative targets in SCCHN cell lines in culture. In mice xenografted with CAL27 cells, rapamycin and enzastaurin produced growth delay. In contrast, the combination of rapamycin and enzastaurin caused regression of CAL27 tumors with evidence of inhibition of putative targets, survival, angiogenesis and proliferation. CONCLUSION: These data demonstrate that the combination of rapamycin and enzastaurin disrupts critical oncogenic pathways in SCCHN and has efficacy in preclinical models.

Systems analysis of EGF receptor signaling dynamics with microwestern arrays.

We describe microwestern arrays, which enable quantitative, sensitive and high-throughput assessment of protein abundance and modifications after electrophoretic separation of microarrayed cell lysates. This method allowed us to measure 91 phosphosites on 67 proteins at six time points after stimulation with five epidermal growth factor (EGF) concentrations in A431 human carcinoma cells. We inferred the connectivities among 15 phosphorylation sites in 10 receptor tyrosine kinases (RTKs) and two sites from Src kinase using Bayesian network modeling and two mutual information-based methods; the three inference methods yielded substantial agreement on the network topology. These results imply multiple distinct RTK coactivation mechanisms and support the notion that small amounts of experimental data collected from phenotypically diverse network states may enable network inference.

Systems-level analysis of ErbB4 signaling in breast cancer: a laboratory to clinical perspective.

Although expression of the ErbB4 receptor tyrosine kinase in breast cancer is generally regarded as a marker for favorable patient prognosis, controversial exceptions have been reported. Alternative splicing of ErbB4 pre-mRNAs results in the expression of distinct receptor isoforms with differential susceptibility to enzymatic cleavage and different downstream signaling protein recruitment potential that could affect tumor progression in different ways. ErbB4 protein expression from nontransfected cells is generally low compared with ErbB1 in most cell lines, and much of our knowledge of the role of ErbB4 in breast cancer is derived from the ectopic overexpression of the receptor in non-breast-derived cell lines. One of the primary functions of ErbB4 in vivo is in the maturation of mammary glands during pregnancy and lactation induction. Pregnancy and extended lactation durations have been correlated with reduced risk of breast cancer, and the role of ErbB4 in tumor suppression may therefore be linked with its role in lactation. Most reports are consistent with a role for ErbB4 in reversing growth stimuli triggered by other ErbB family members during puberty. In this report, we provide a systems-level examination of several reports highlighting the seemingly opposing roles of ErbB4 in breast cancer and potential explanations for the discrepancies and draw the conclusion that future studies examining the function of ErbB4 in breast cancer should also take into account the pregnancy history, lactation status, and hormone supplementation or ablation history of the patient from whom the tumor or tumor cells are derived.

Cytosolic prion protein toxicity is independent of cellular prion protein expression and prion propagation.

Prion diseases are transmissible neurodegenerative diseases caused by a conformational isoform of the prion protein (PrP), a host-encoded cell surface sialoglycoprotein. Recent evidence suggests a cytosolic fraction of PrP (cyPrP) functions either as an initiating factor or toxic element of prion disease. When expressed in cultured cells, cyPrP acquires properties of the infectious conformation of PrP (PrP(Sc)), including insolubility, protease resistance, aggregation, and toxicity. Transgenic mice (2D1 and 1D4 lines) that coexpress cyPrP and PrP(C) exhibit focal cerebellar atrophy, scratching behavior, and gait abnormalities suggestive of prion disease, although they lack protease-resistant PrP. To determine if the coexpression of PrP(C) is necessary or inhibitory to the phenotype of these mice, we crossed Tg1D4(Prnp(+/+)) mice with PrP-ablated mice (TgPrnp(o/o)) to generate Tg1D4(Prnp(o/o)) mice and followed the development of disease and pathological phenotype. We found no difference in the onset of symptoms or the clinical or pathological phenotype of disease between Tg1D4(Prnp(+/+)) and Tg1D4(Prnp(o/o)) mice, suggesting that cyPrP and PrP(C) function independently in the disease state. Additionally, Tg1D4(Prnp(o/o)) mice were resistant to challenge with mouse-adapted scrapie (RML), suggesting cyPrP is inaccessible to PrP(Sc). We conclude that disease phenotype and cellular toxicity associated with the expression of cyPrP are independent of PrP(C) and the generation of typical prion disease.