Phosphoproteomics: A possible route to novel biomarkers of breast cancer

Quantitative Phosphoproteomics and Acetylomics of Safranal Anticancer Effects in Triple-Negative Breast Cancer Cells

Safranal, as an aroma in saffron, is one of the cytotoxic compounds in saffron that causes cell death in triple-negative breast cancer cells. Our recent research reported the anti-cancer effects of safranal, which further demonstrated its impact on protein translation, mitochondrial dysfunction, and DNA fragmentation. To better understand the underlying mechanisms, we identified acetylated and phosphorylated peptides in safranal-treated cancer cells. We conducted a comprehensive phosphoproteomics and acetylomics analysis of safranal-treated MDA-MB-231 cells by using a combination of TMT labeling and enrichment methods including titanium dioxide and immunoprecipitation. We provide a wide range of phosphoproteome regulation in different signaling pathways that are disrupted by safranal treatment. Safranal influences the phosphorylation level on proteins involved in DNA replication and repair, translation, and EGFR activation/accumulation, which can lead the cells into apoptosis. Safranal causes DNA damage which is followed by the activation of cell cycle checkpoints for DNA repair. Over time, checkpoints and DNA repair are inhibited and cells are under a mitotic catastrophe. Moreover, safranal prevents repair by the hypo-acetylation of H4 and facilitates the transcription of proapoptotic genes by hyper-acetylation of H3, which push the cells to the brink of death.

The G Protein-Coupled Estrogen Receptor Agonist G-1 Inhibits Nuclear Estrogen Receptor Activity and Stimulates Novel Phosphoproteomic Signatures

Estrogen exerts cellular effects through both nuclear (ESR1 and ESR2) and membrane-bound estrogen receptors (G-protein coupled estrogen receptor, GPER); however, it is unclear if they act independently or engage in crosstalk to influence hormonal responses. To investigate each receptor's role in proliferation, transcriptional activation, and protein phosphorylation in breast cancer cells (MCF-7), we employed selective agonists for ESR1 propyl-pyrazole-triol (PPT), ESR2 diarylpropionitrile (DPN), and GPER (G-1) and also determined the impact of xenoestrogens bisphenol-A (BPA) and genistein on these effects. As anticipated, 17β-estradiol (E2), PPT, DPN, BPA, and genistein each enhanced proliferation and activation of an ERE-driven reporter gene whereas G-1 had no significant impact. However, G-1 significantly reduced E2-, PPT-, DPN-, BPA-, and genistein-induced proliferation and ERE activation at doses greater than 500 nM indicating that G-1 mediated inhibition is not ESR isotype specific. As membrane receptors initiate cascades of phosphorylation events, we performed a global phosphoproteomic analysis on cells exposed to E2 or G-1 to identify potential targets of receptor crosstalk via downstream protein phosphorylation targets. Of the 211 phosphorylated proteins identified, 40 and 13 phosphoproteins were specifically modified by E2 and G-1, respectively. Subnetwork enrichment analysis revealed several processes related to cell cycle were specifically enriched by G-1 compared with E2. Further there existed a number of newly identified proteins that were specifically phosphorylated by G-1. These phosphorylation networks highlight specific proteins that may modulate the inhibitory effects of G-1 and suggest a novel role for interference with nuclear receptor activity driven by E2 and xenoestrogens.

Label-free LC-MS analysis of HER2+ breast cancer cell line response to HER2 inhibitor treatment

BACKGROUND

Human epidermal growth-factor receptor (HER)-2 is overexpressed in 25 % of breast-cancers and is associated with an aggressive form of the disease with significantly shortened disease free and overall survival. In recent years, the use of HER2-targeted therapies, monoclonal-antibodies and small molecule tyrosine-kinase inhibitors has significantly improved the clinical outcome for HER2-positive breast-cancer patients. However, only a fraction of HER2-amplified patients will respond to therapy and the use of these treatments is often limited by tumour drug insensitivity or resistance and drug toxicities. Currently there is no way to identify likely responders or rational combinations with the potential to improve HER2-focussed treatment outcome.

METHODS

In order to further understand the molecular mechanisms of treatment-response with HER2-inhibitors, we used a highly-optimised and reproducible quantitative label-free LC-MS strategy to characterize the proteomes of HER2-overexpressing breast-cancer cell-lines (SKBR3, BT474 and HCC1954) in response to drug-treatment with HER2-inhibitors (lapatinib, neratinib or afatinib).

RESULTS

Following 12 ours treatment with different HER2-inhibitors in the BT474 cell-line; compared to the untreated cells, 16 proteins changed significantly in abundance following lapatinib treatment (1 μM), 21 proteins changed significantly following neratinib treatment (150 nM) and 38 proteins changed significantly following afatinib treatment (150 nM). Whereas following 24 hours treatment with neratinib (200 nM) 46 proteins changed significantly in abundance in the HCC1954 cell-line and 23 proteins in the SKBR3 cell-line compared to the untreated cells. Analysing the data we found that, proteins like trifunctional-enzyme subunit-alpha, mitochondrial; heterogeneous nuclear ribonucleoprotein-R and lamina-associated polypeptide 2, isoform alpha were up-regulated whereas heat shock cognate 71 kDa protein was down-regulated in 3 or more comparisons.

CONCLUSION

This proteomic study highlights several proteins that are closely associated with early HER2-inhibitor response and will provide a valuable resource for further investigation of ways to improve efficacy of breast-cancer treatment.

Construction and Deciphering of Human Phosphorylation-Mediated Signaling Transduction Networks

Protein phosphorylation is the most abundant reversible covalent modification. Human protein kinases participate in almost all biological pathways, and approximately half of the kinases are associated with disease. PhoSigNet was designed to store and display human phosphorylation-mediated signal transduction networks, with additional information related to cancer. It contains 11 976 experimentally validated directed edges and 216 871 phosphorylation sites. Moreover, 3491 differentially expressed proteins in human cancer from dbDEPC, 18 907 human cancer variation sites from CanProVar, and 388 hyperphosphorylation sites from PhosphoSitePlus were collected as annotation information. Compared with other phosphorylation-related databases, PhoSigNet not only takes the kinase-substrate regulatory relationship pairs into account, but also extends regulatory relationships up- and downstream (e.g., from ligand to receptor, from G protein to kinase, and from transcription factor to targets). Furthermore, PhoSigNet allows the user to investigate the impact of phosphorylation modifications on cancer. By using one set of in-house time series phosphoproteomics data, the reconstruction of a conditional and dynamic phosphorylation-mediated signaling network was exemplified. We expect PhoSigNet to be a useful database and analysis platform benefiting both proteomics and cancer studies.

Environmental stress affects the activity of metabolic and growth factor signaling networks and induces autophagy markers in MCF7 breast cancer cells

Phosphoproteomic techniques are contributing to our understanding of how signaling pathways interact and regulate biological processes. This technology is also being used to characterize how signaling networks are remodeled during disease progression and to identify biomarkers of signaling pathway activity and of responses to cancer therapy. A potential caveat in these studies is that phosphorylation is a very dynamic modification that can substantially change during the course of an experiment or the retrieval and processing of cellular samples. Here, we investigated how exposure of cells to ambient conditions modulates phosphorylation and signaling pathway activity in the MCF7 breast cancer cell line. About 1.5% of 3,500 sites measured showed a significant change in phosphorylation extent upon exposure of cells to ambient conditions for 15 min. The effects of this perturbation in modifying phosphorylation patterns did not involve random changes due to stochastic activation of kinases and phosphatases. Instead, exposure of cells to ambient conditions elicited an environmental stress reaction that involved a coordinated response to a metabolic stress situation, which included: (1) the activation of AMPK; (2) the inhibition of PI3K, AKT, and ERK; (3) an increase in markers of protein synthesis inhibition at the level of translation elongation; and (4) an increase in autophagy markers. We also observed that maintaining cells in ice modified but did not completely abolish this metabolic stress response. In summary, exposure of cells to ambient conditions affects the activity of signaling networks previously implicated in metabolic and growth factor signaling. Mass spectrometry data have been deposited to the ProteomeXchange with identifier PXD000472.

Phosphoproteomics-based network medicine

One of the major tasks of phosphoproteomics is providing potential biomarkers for either diagnosis or drug targets in medical applications. Because most complex diseases are due to the actions of multiple genes/proteins, the identification of complex phospho-signatures containing multiple phosphorylation events within phosphoproteomics-based networks generates more efficient and robust biomarkers than a single, differentially phosphorylated substrate or site. Here, we briefly summarize the current efforts and progress in this newly emerging field of phosphoproteomics-based network medicine by reviewing the computational (re)construction of phosphorylation-mediated signaling networks from unannotated phosphoproteomic data, the discovery of robust network phospho-signatures and the application of these signatures for classifying cancers and predicting drug responses. The challenges as well as the potential advantages are evaluated and discussed. Although the current techniques are at present far from mature, we believe that such a systematic approach as we describe can generate more useful and robust biomarkers for biomedical usage, even at the current stage of development.