We describe micro-western arrays, which enable quantitative, sensitive and high-throughput assessment of protein abundance and modifications following electrophoretic separation of micro-arrayed cell lysates. This method allowed us to measure 91 phosphosites on 67 proteins at six time points following stimulation with five EGF concentrations in A431 human carcinoma cells. We inferred the connectivities among 15 phosphorylation sites across 10 receptor tyrosine kinases (RTK) and 2 sites from Src kinase using Bayesian network modeling and two mutual information-based methods; the three inference methods yielded significant 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.

SUMMARY 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.

Caffeic acid phenethyl ester (CAPE) is a bioactive component derived from honeybee hive propolis. CAPE has been shown to have anti-mitogenic, anti-carcinogenic, 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 CAPE’s effects 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 CAPE’s effect on gene expression, protein signaling, and transcriptional regulatory networks using Micro-Western Arrays and PCR arrays. We built a model of CAPE’s impact on cell signaling which suggested that it acted through inhibition of Akt-related protein signaling networks. Over-expression of Akt1 or cMyc, a downstream target of Akt signaling, significantly blocked the anti-proliferative 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 AMPK and Akt signaling networks.

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.

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. (Mol Cancer Res 2008;6(6):885 -91)

These data demonstrate that the combination of rapamycin and enzastaurin disrupts critical oncogenic pathways in SCCHN and has efficacy in preclinical models.

No abstract

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.