Evaluation of Cell Cycle Arrest in Estrogen Responsive MCF-7 Breast Cancer Cells: Pitfalls of the MTS Assay

Endocrine resistance is a major problem with anti-estrogen treatments and how to overcome resistance is a major concern in the clinic. Reliable measurement of cell viability, proliferation, growth inhibition and death is important in screening for drug treatment efficacy in vitro. This report describes and compares commonly used proliferation assays for induced estrogen-responsive MCF-7 breast cancer cell cycle arrest including: determination of cell number by direct counting of viable cells; or fluorescence SYBR®Green (SYBR) DNA labeling; determination of mitochondrial metabolic activity by 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay; assessment of newly synthesized DNA using 5-ethynyl-2′-deoxyuridine (EdU) nucleoside analog binding and Alexa Fluor® azide visualization by fluorescence microscopy; cell-cycle phase measurement by flow cytometry. Treatment of MCF-7 cells with ICI 182780 (Faslodex), FTY720, serum deprivation or induction of the tumor suppressor p14ARF showed inhibition of cell proliferation determined by the Trypan Blue exclusion assay and SYBR DNA labeling assay. In contrast, the effects of treatment with ICI 182780 or p14ARF-induction were not confirmed using the MTS assay. Cell cycle inhibition by ICI 182780 and p14ARF-induction was further confirmed by flow cytometric analysis and EdU-DNA incorporation. To explore this discrepancy further, we showed that ICI 182780 and p14ARF-induction increased MCF-7 cell mitochondrial activity by MTS assay in individual cells compared to control cells thereby providing a misleading proliferation readout. Interrogation of p14ARF-induction on MCF-7 metabolic activity using TMRE assays and high content image analysis showed that increased mitochondrial activity was concomitant with increased mitochondrial biomass with no loss of mitochondrial membrane potential, or cell death. We conclude that, whilst p14ARF and ICI 182780 stop cell cycle progression, the cells are still viable and potential treatments utilizing these pathways may contribute to drug resistant cells. These experiments demonstrate how the combined measurement of metabolic activity and DNA labeling provides a more reliable interpretation of cancer cell response to treatment regimens

Mass spectrometric techniques for protein characterisation and quantification in Saccharomyces cerevisiae

The aim of this study was to perform a large-scale examination of the proteome of yeast to identify native sites of protein methylation, while simultaneously exploring technical issues arising in the large-scale detection of protein modifications. This was done using various enrichment and separation methods, in conjunction with tandem mass spectrometry. This resulted in the identification of the largest number of native arginine methylation sites reported for this species. Specifically, this included 39 sites of arginine methylation on nine proteins, including six proteins for which no native methylation sites have previously been identified (Gar1p, Gbp2p, Dbp2p, Nab2p, Nop1p, Nsr1p). Subsequently, the Gar1p, Nop1p, Npl3p, Nsr1p, and Rps2p proteins were shown to be in vitro substrates of the Hmt1p methyltransferase. For lysine methylation, 15 sites on five proteins were identified, including novel sites of methylation heterogeneity on Tef1p. Technically, the identification of methylpeptides was shown to have an extremely high false discovery rate, and the factors for this are examined. It was confirmed that there is no evidence for the existence of enzyme-mediated methylation of glutamic or aspartic acid in yeast. This study also examined the system-wide consequences of the loss of Hmt1p-mediated arginine methylation via a proteomic analysis of Δhmt1 yeast. Strikingly, this revealed that arginine methylation plays a crucial role in phosphate regulation, and that arginine methylation can affect the stability of proteins in yeast likely through increasing their sensitivity to proteasomal degradation. Specifically, we observed that Dbp2p protein levels diminished at a slower rate upon cycloheximide exposure in Δhmt1 yeast, suggesting that a loss of methylation extends protein half-life. The Dbp2p and Psp2p proteins are also shown to be in vitro substrates of the Hmt1p methyltransferase, with the Dbp2p protein also shown to lose sites of native arginine methylation in Δhmt1 yeast. Finally, this study developed a novel proteogenomic approach to find missing open reading frames and their proteins in yeast. This resulted in the identification and validation of a small, novel protein-coding gene in yeast, dubbed YJR107C-A. The function of this protein is currently unknown. Together, this study substantially expanded the characterisation of native methylation sites in yeast, and demonstrates the utility of proteogenomic techniques in the continuing genome annotation of yeast

p14ARF post-transcriptional regulation of nuclear cyclin D1 in MCF-7 breast cancer cells: discrimination between a good and bad prognosis?

As part of a cell's inherent protection against carcinogenesis, p14ARF is upregulated in response to hyperproliferative signalling to induce cell cycle arrest. This property makes p14ARF a leading candidate for cancer therapy. This study explores the consequences of reactivating p14ARF in breast cancer and the potential of targeting p14ARF in breast cancer treatment. Our results show that activation of the p14ARF-p53-p21-Rb pathway in the estrogen sensitive MCF-7 breast cancer cells induces many hallmarks of senescence including a large flat cell morphology, multinucleation, senescence-associated-β-gal staining, and rapid G1 and G2/M phase cell cycle arrest. P14ARF also induces the expression of the proto-oncogene cyclin D1, which is most often associated with a transition from G1-S phase and is highly expressed in breast cancers with poor clinical prognosis. In this study, siRNA knockdown of cyclin D1, p21 and p53 show p21 plays a pivotal role in the maintenance of high cyclin D1 expression, cell cycle and growth arrest post-p14ARF induction. High p53 and p14ARF expression and low p21/cyclin D1 did not cause cell-cycle arrest. Knockdown of cyclin D1 stops proliferation but does not reverse senescence-associated cell growth. Furthermore, cyclin D1 accumulation in the nucleus post-p14ARF activation correlated with a rapid loss of nucleolar Ki-67 protein and inhibition of DNA synthesis. Latent effects of the p14ARF-induced cellular processes resulting from high nuclear cyclin D1 accumulation included a redistribution of Ki-67 into the nucleoli, aberrant nuclear growth (multinucleation), and cell proliferation. Lastly, downregulation of cyclin D1 through inhibition of ER abrogated latent recurrence. The mediation of these latent effects by continuous expression of p14ARF further suggests a novel mechanism whereby dysregulation of cyclin D1 could have a double-edged effect. Our results suggest that p14ARF induced-senescence is related to late-onset breast cancer in estrogen responsive breast cancers and/or the recurrence of more aggressive breast cancer post-therapy

MethylQuant: A Tool for Sensitive Validation of Enzyme-Mediated Protein Methylation Sites from Heavy-Methyl SILAC Data

The study of post-translational methylation is hampered by the fact that large-scale LC–MS/MS experiments produce high methylpeptide false discovery rates (FDRs). The use of heavy-methyl stable isotope labeling by amino acids in cell culture (heavy-methyl SILAC) can drastically reduce these FDRs; however, this approach is limited by a lack of heavy-methyl SILAC compatible software. To fill this gap, we recently developed MethylQuant. Here, using an updated version of MethylQuant, we demonstrate its methylpeptide validation and quantification capabilities and provide guidelines for its best use. Using reference heavy-methyl SILAC data sets, we show that MethylQuant predicts with statistical significance the true or false positive status of methylpeptides in samples of varying complexity, degree of methylpeptide enrichment, and heavy to light mixing ratios. We introduce methylpeptide confidence indicators, MethylQuant Confidence and MethylQuant Score, and demonstrate their strong performance in complex samples characterized by a lack of methylpeptide enrichment. For these challenging data sets, MethylQuant identifies 882 of 1165 true positive methylpeptide spectrum matches (i.e., >75% sensitivity) at high specificity (<2% FDR) and achieves near-perfect specificity at 41% sensitivity. We also demonstrate that MethylQuant produces high accuracy relative quantification data that are tolerant of interference from coeluting peptide ions. Together MethylQuant’s capabilities provide a path toward routine, accurate characterizations of the methylproteome using heavy-methyl SILAC

Linear regression analysis of Annexin and S100A protein expression 24h and 72h post p14ARF-p53-p21 activation.

<p>MCF-7 cells were treated with IPTG (5mM) to induce the p14ARF-p53 signaling pathway. A filtered set of 1265 proteins was analyzed for two independent biological experiments with technical replicates at 24h and 72h post activation. The correlation coefficient value for the 24h and 72h data for biological duplicate experiments showed a strong correlation (0.79 and 0.72 respectively). The black box highlights proteins significantly over-expressed p<0.05) post p14ARF-p53-p21 activation at 24h and maintained at 72h. The green box highlights proteins significantly downregulated at 24h and maintained at 72h post treatment. The red box highlights proteins significantly upregulated at 72h. The red cubes represent annexin proteins (A1, A2, A4, A6) significantly upregulated at 24h and maintained at 72h; the black cube represents annexin A9 significantly upregulated at 72h (P<0.05). Yellow cubes represent S100A10, S100A11 and S100A13 proteins significantly upregulated at 24h and maintained at 72h. Annexins A5, A7, A11, S100A6 and S100A14 are expressed and not regulated (between ratios 0.8–1.1). Inset: Western blot shows the expression of p14ARF and ER status in MCF-7 cells pre- and post IPTG and β-estradiol treatment at 24 h.</p

Cytoscape (GeneMANIA) analysis of Annexin and associated S100A partner overexpression: defining the consequent physical interactions, co-localization and genetic interactions post p14ARF induction.

<p>Cytoscape (GeneMANIA) analysis of Annexin and associated S100A partner overexpression: defining the consequent physical interactions, co-localization and genetic interactions post p14ARF induction.</p

Differential regulation of Annexin A1, A2, A5 and A6 expression at the transcriptional level in MCF-7 breast cancer cells.

<p>p14ARF expression was induced by the addition of 5mM IPTG for 15h. Quantitation of ANXA1, ANXA2, ANXA5 and ANXA6 expression was analyzed at 15h post p14ARF induction using the Taqman fast master mix and pre-optimized primer and probe sets. Data were normalized to levels of the reference gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Data have been expressed as fold change in expression post p14ARF induction by IPTG at the 15h time point relative to control (2^−ΔΔCt). Experiments were performed in duplicate in which each set of experiments contained technical triplicates. Statistical differences between groups were determined using a two tailed, paired t-test. *p < 0.02, **p < 0.003 respectively.</p

Annexin protein function(s) analyzed using the MetScape Plugin in Cytoscape.

<p>Annexin protein function(s) analyzed using the MetScape Plugin in Cytoscape.</p

Effect of p53 induced upregulation of individual annexins on patient prognosis.

<p>Kaplan-Meier analysis [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169925#pone.0169925.ref038" target="_blank">38</a>] was used to predict breast cancer patient survival (RFS, DMSF and OS) post p53-upregulation of individual annexins: ANXA1, ANXA2, ANXA4, ANXA6, ANXA9 and S100A10, S100A11 and S100A13. A comparison was made between ER+ patients (A), and a sub-set of patients with ER+/p53wt (B). A hazard ratio of 95% confidence intervals and the log-rank P-value (P<0.05) was determined for differences in survival for each treatment option outcome and the results are represented as a heat chart: green = positive prognosis; pink = negative prognosis and yellow neutral (the median was used as a cutoff). The number of patients in each treatment sample is shown. Abbreviations: RFS = Relapse free survival; DMFS = Distant metastasis free survival; OS = Overall survival; UNTR = untreated; Endo = endocrine; Tam = Tamoxifen, C and chemo = chemotherapy.</p