RSS 1.0Clinical and Experimental Pharmacology Group
CEP incorporates teams in pre-clinical drug target validation and biomarker discovery.
Recent Submissions
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Reactivating HIF prolyl hydroxylases under hypoxia results in metabolic catastrophe and cell death.Cells exposed to low-oxygen conditions (hypoxia) alter their metabolism to survive. This response, although vital during development and high-altitude survival, is now known to be a major factor in the selection of cells with a transformed metabolic phenotype during tumorigenesis. It is thought that hypoxia-selected cells have increased invasive capacity and resistance to both chemo- and radiotherapies, and therefore represent an attractive target for antitumor therapy. Hypoxia inducible factors (HIFs) are responsible for the majority of gene expression changes under hypoxia, and are themselves controlled by the oxygen-sensing HIF prolyl hydroxylases (PHDs). It was previously shown that mutations in succinate dehydrogenase lead to the inactivation PHDs under normoxic conditions, which can be overcome by treatment with alpha-ketoglutarate derivatives. Given that solid tumors contain large regions of hypoxia, the reactivation of PHDs in these conditions could induce metabolic catastrophe and therefore prove an effective antitumor therapy. In this report we demonstrate that derivatized alpha-ketoglutarate can be used as a strategy for maintaining PHD activity under hypoxia. By increasing intracellular alpha-ketoglutarate and activating PHDs we trigger PHD-dependent reversal of HIF1 activation, and PHD-dependent hypoxic cell death. We also show that derivatized alpha-ketoglutarate can permeate multiple layers of cells, reducing HIF1alpha levels and its target genes in vivo.
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Detection of BRAF mutations in the tumour and serum of patients enrolled in the AZD6244 (ARRY-142886) advanced melanoma phase II study.BACKGROUND: This study investigated the potential clinical utility of circulating free DNA (cfDNA) as a source of BRAF mutation detection in patients enrolled into a phase II study of AZD6244, a specific MEK1/2 inhibitor, in patients with advanced melanoma. METHODS: BRAF mutations were detected using Amplification Refractory Mutation System allele-specific PCR. BRAF mutation status was assessed in serum-derived cfDNA from 126 patients enrolled into the study and from 94 matched tumour samples. RESULTS: Of 94 tumour samples, 45 (47.9%) were found to be BRAF mutation positive (BRAF+). Serum-derived cfDNA was BRAF+ in 33 of 126 (26.2%) samples, including in five samples for which tumour data were unavailable. Of BRAF+ tumours, 25 of 45 (55.6%) were BRAF+ in cfDNA. In three cases in which the tumour was negative, cfDNA was BRAF+. Progression-free survival (PFS) of patients with BRAF+ tumour and cfDNA was not significantly different compared with tumour BRAF+ but cfDNA BRAF-negative patients, indicating that cfDNA BRAF detection is not associated with poorer prognosis on PFS in stage III/IV advanced melanoma. CONCLUSIONS: These data demonstrate the feasibility of BRAF mutation detection in cfDNA of patients with advanced melanoma. Future studies should aim to incorporate BRAF mutation testing in cfDNA to further validate this biomarker for patient selection.
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A small molecule inhibitor of XIAP induces apoptosis and synergises with vinorelbine and cisplatin in NSCLC.Background:Evasion of apoptosis contributes to the pathogenesis of solid tumours including non-small cell lung cancer (NSCLC). Malignant cells resist apoptosis through over-expression of inhibitor of apoptosis proteins (IAPs), such as X-linked IAP (XIAP).Methods:A phenylurea-based small molecule inhibitor of XIAP, XIAP antagonist compound (XAC) 1396-11, was investigated preclincally to determine its ability to sensitise to clinically relevant cytotoxics, potentially allowing dose reduction while maintaining therapeutic efficacy.Results:XIAP protein expression was detected in six NSCLC cell lines examined. The cytotoxicity of XAC 1396-11 against cultured NSCLC cell lines in vitro was concentration- and time-dependent in both short-term and clonogenic assays. XAC 1396-11-induced apoptosis was confirmed by PARP cleavage and characteristic nuclear morphology. XAC 1396-11 synergised with vinorelbine+/-cisplatin in H460 and A549 NSCLC cells. The mechanism of synergy was enhanced apoptosis, shown by increased cleavage of caspase-3 and PARP and by the reversal of synergy by a pan-caspase inhibitor. Synergy between XAC 1396-11 and vinorelbine was augmented by optimising drug scheduling with superior effects when XAC 1396-11 was administered before vinorelbine.Conclusion:These preclinical data suggest that XIAP inhibition in combination with vinorelbine holds potential as a therapeutic strategy in NSCLC.British Journal of Cancer advance online publication, 10 November 2009; doi:10.1038/sj.bjc.6605418 www.bjcancer.com.
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Contribution of HIF-1 and drug penetrance to oxaliplatin resistance in hypoxic colorectal cancer cells.BACKGROUND: Hypoxia is as an indicator of poor treatment outcome. Consistently, hypoxic HCT116 colorectal cancer cells are resistant to oxaliplatin, although the mechanistic basis is unclear. This study sought to investigate the relative contribution of HIF-1 (hypoxia-inducible factor-1)-mediated gene expression and drug penetrance to oxaliplatin resistance using three-dimensional spheroids. METHODS: Hypoxia-inducible factor-1alpha function was suppressed by the stable expression of a dominant-negative form in HCT116 cells (DN). Cells were drug exposed as monolayer or multicellular spheroid cultures. Cells residing at differing oxygenation status were isolated from Hoechst 33342-treated spheroids using flow cytometry. Sub-populations were subjected to clonogenic survival assays and to Inductively-Coupled Plasma Mass Spectroscopy to determine oxaliplatin uptake. RESULTS: In spheroids, a sensitivity gradient (hypoxic
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Preclinical efficacy of the bioreductive alkylating agent RH1 against paediatric tumours.BACKGROUND: Despite substantial improvements in childhood cancer survival, drug resistance remains problematic for several paediatric tumour types. The urgent need to access novel agents to treat drug-resistant disease should be expedited by pre-clinical evaluation of paediatric tumour models during the early stages of drug development in adult cancer patients. METHODS/RESULTS: The novel cytotoxic RH1 (2,5-diaziridinyl-3-[hydroxymethyl]-6-methyl-1,4-benzoquinone) is activated by the obligate two-electron reductase DT-diaphorase (DTD, widely expressed in adult tumour cells) to a potent DNA interstrand cross-linker. In acute viability assays against neuroblastoma, osteosarcoma, and Ewing's sarcoma cell lines RH1 IC(50) values ranged from 1-200 nM and drug potency correlated both with DTD levels and drug-induced apoptosis. However, synergy between RH1 and cisplatin or doxorubicin was only seen in low DTD expressing cell lines. In clonogenic assays RH1 IC(50) values ranged from 1.5-7.5 nM and drug potency did not correlate with DTD level. In A673 Ewing's sarcoma and 791T osteosarcoma tumour xenografts in mice RH1 induced apoptosis 24 h after a single bolus injection (0.4 mg/kg) and daily dosing for 5 days delayed tumour growth relative to control. CONCLUSION: The demonstration of RH1 efficacy against paediatric tumour cell lines, which was performed concurrently with the adult Phase 1 Trial, suggests that this agent may have clinical usefulness in childhood cancer.
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Evaluation of circulating tumor cells and serological cell death biomarkers in small cell lung cancer patients undergoing chemotherapy.Serological cell death biomarkers and circulating tumor cells (CTCs) have potential uses as tools for pharmacodynamic blood-based assays and their subsequent application to early clinical trials. In this study, we evaluated both the expression and clinical significance of CTCs and serological cell death biomarkers in patients with small cell lung cancer. Blood samples from 88 patients were assayed using enzyme-linked immunosorbent assays for various cytokeratin 18 products (eg, M65, cell death, M30, and apoptosis) as well as nucleosomal DNA. CTCs (per 7.5 ml of blood) were quantified using Veridex CellSearch technology. Before therapeutic treatment, cell death biomarkers were elevated in patients compared with controls. CTCs were detected in 86% of patients; additionally, CD56 was detectable in CTCs, confirming their neoplastic origin. M30 levels correlated with the percentage of apoptotic CTCs. M30, M65, lactate dehydrogenase, and CTC number were prognostic for patient survival as determined by univariate analysis. Using multivariate analysis, both lactate dehydrogenase and M65 levels remained significant. CTC number fell following chemotherapy, whereas levels of serological cell death biomarkers peaked at 48 hours and fell by day 22, mirroring the tumor response. A 48-hour rise in nucleosomal DNA and M30 levels was associated with early response and severe toxicity, respectively. Our results provide a rationale to include the use of serological biomarkers and CTCs in early clinical trials of new agents for small cell lung cancer.
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Specific demonstration of drug-induced tumour cell apoptosis in human xenografts models using a plasma biomarker.Pharmacodynamic (PD) assays should be used before advancing new drugs to clinical trials. Most PD assays measure the response to drugs in tissue, a procedure which requires tissue biopsies. The M30-Apoptosense ELISA is a PD biomarker assay for the quantitative determination of caspase-cleaved cytokeratin 18 (CK18) released from apoptotic carcinoma cells into blood. We here demonstrate that whereas the M30-Apoptosense ELISA assay detects human caspase-cleaved CK18, the mouse and rat CK18 caspase cleavage products are detected with low affinity. The M30-Apoptosense ELISA therefore facilitates the determination of drug-induced apoptosis in human tumour xenografts in rodents using plasma samples, largely independently from host toxicity. Increases of caspase-cleaved CK18 were observed in plasma from different carcinoma xenograft models in response to anticancer drugs. The appearance caspase-cleaved CK18 in plasma was found to reflect formation of the caspase-cleaved epitope in FaDu head-neck carcinomas and in cultured cells. The M30-Apoptosense assay allows determination of tumour response in blood from xenograft models and from patients, providing a powerful tool for translational studies of anticancer drugs.
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To determine the cytotoxicity of chlorambucil and one of its nitro-derivatives, conjugated to prasterone and pregnenolone, towards eight human cancer cell-lines.Four ester prodrugs derived from the bifunctional alkylating agent chlorambucil, and one of its nitro-derivatives, 3-nitrochlorambucil conjugated to prasterone and pregnenolone, were synthesized and tested for their cytotoxic activity against eight human cell lines, using the standard MTT assay. A comparison between the esters and the controls, namely chlorambucil and 3-nitrochlorambucil would suggest that all four esters possess to varying degrees, specificity towards the breast adenocarcinoma cell line (MDA-mb468) than the other seven cells' lines tested. The overall findings are encouraging since it infers that these lipophilic esters not only have the ability to traverse specific cell membranes but also exhibit cytotoxicity towards most of the cell lines tested.
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Phase I trial of AEG35156 administered as a 7-day and 3-day continuous intravenous infusion in patients with advanced refractory cancer.PURPOSE: To establish the maximum-tolerated dose and evaluate tolerability, pharmacokinetics, pharmacodynamic effects, and antitumor activity of AEG35156, a second-generation antisense to X-linked inhibitor of apoptosis (XIAP) protein, in patients with advanced refractory malignant tumors. PATIENTS AND METHODS: This was a first-in-man, open-label, phase I dose-escalation study. AEG35156 was administered by continuous intravenous infusion over 7 days (7DI) or 3 days (3DI) of a 21-day treatment cycle. Dose escalation started at 48 mg/m(2)/d and continued until consistent dose-limiting toxicity (DLT) was observed. RESULTS: Thirty-eight patients were entered in seven cohorts. Grade 3 to 4 adverse events were uncommon and were predominantly abnormal laboratory values: elevated ALT, thrombocytopenia, and lymphopenia. DLTs comprised elevated hepatic enzymes, hypophosphatemia, and thrombocytopenia. The maximum-tolerated doses were defined as 125 mg/m(2)/d for the 7DI regimen and < or = 213 mg/m(2)/d for the 3DI schedule. AEG35156 area under the plasma concentration curve and peak plasma concentration increased proportionally with dose. Suppression of XIAP mRNA levels was maximal at 72 hours (mean suppression, 21%), and this coincided with a dramatic decrease in circulating tumor cells in a patient with non-Hodgkin's lymphoma. Two further patients had unconfirmed partial responses. Circulating biomarkers of cell death and apoptosis altered in association with drug infusion and toxicity. CONCLUSION: In this first-in-man study, AEG35156 was well tolerated, with predictable toxicities, pharmacokinetic properties, and clinical evidence of antitumor activity in patients with refractory lymphoma, melanoma, and breast cancer. Phase I/II trials of AEG35156 chemotherapy combinations are ongoing in patients with pancreatic, breast, non-small-cell lung cancer, acute myeloid leukemia, lymphoma, and solid tumors for which docetaxel is indicated.
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A validated gene expression profile for detecting clinical outcome in breast cancer using artificial neural networks.Gene expression microarrays allow for the high throughput analysis of huge numbers of gene transcripts and this technology has been widely applied to the molecular and biological classification of cancer patients and in predicting clinical outcome. A potential handicap of such data intensive molecular technologies is the translation to clinical application in routine practice. In using an artificial neural network bioinformatic approach, we have reduced a 70 gene signature to just 9 genes capable of accurately predicting distant metastases in the original dataset. Upon validation in a follow-up cohort, this signature was an independent predictor of metastases free and overall survival in the presence of the 70 gene signature and other factors. Interestingly, the ANN signature and CA9 expression also split the groups defined by the 70 gene signature into prognostically distinct groups. Subsequently, the presence of protein for the principal prognosticator gene was categorically assessed in breast cancer tissue of an experimental and independent validation patient cohort, using immunohistochemistry. Importantly our principal prognosticator, CA9, showed that it is capable of selecting an aggressive subgroup of patients who are known to have poor prognosis.
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An introduction to artificial neural networks in bioinformatics--application to complex microarray and mass spectrometry datasets in cancer studies.Applications of genomic and proteomic technologies have seen a major increase, resulting in an explosion in the amount of highly dimensional and complex data being generated. Subsequently this has increased the effort by the bioinformatics community to develop novel computational approaches that allow for meaningful information to be extracted. This information must be of biological relevance and thus correlate to disease phenotypes of interest. Artificial neural networks are a form of machine learning from the field of artificial intelligence with proven pattern recognition capabilities and have been utilized in many areas of bioinformatics. This is due to their ability to cope with highly dimensional complex datasets such as those developed by protein mass spectrometry and DNA microarray experiments. As such, neural networks have been applied to problems such as disease classification and identification of biomarkers. This review introduces and describes the concepts related to neural networks, the advantages and caveats to their use, examples of their applications in mass spectrometry and microarray research (with a particular focus on cancer studies), and illustrations from recent literature showing where neural networks have performed well in comparison to other machine learning methods. This should form the necessary background knowledge and information enabling researchers with an interest in these methodologies, but not necessarily from a machine learning background, to apply the concepts to their own datasets, thus maximizing the information gain from these complex biological systems.
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Quantitative proteomics analysis demonstrates post-transcriptional regulation of embryonic stem cell differentiation to hematopoiesis.Embryonic stem (ES) cells can differentiate in vitro to produce the endothelial and hematopoietic precursor, the hemangioblasts, which are derived from the mesoderm germ layer. Differentiation of Bry(GFP/+) ES cell to hemangioblasts can be followed by the expression of the Bry(GFP/+) and Flk1 genes. Proteomic and transcriptomic changes during this differentiation process were analyzed to identify mechanisms for phenotypic change during early differentiation. Three populations of differentiating Bry(GFP) ES cells were obtained by flow cytometric sorting, GFP-Flk1- (epiblast), GFP+Flk1- (mesoderm), and GFP+Flk1+ (hemangioblast). Microarray analyses and relative quantification two-dimensional LCLC-MS/MS on nuclear extracts were performed. We identified and quantified 2389 proteins, 1057 of which were associated to their microarray probe set. These included a variety of low abundance transcription factors, e.g. UTF1, Sox2, Oct4, and E2F4, demonstrating a high level of proteomic penetrance. When paired comparisons of changes in the mRNA and protein expression levels were performed low levels of correlation were found. A strong correlation between isobaric tag-derived relative quantification and Western blot analysis was found for a number of nuclear proteins. Pathway and ontology analysis identified proteins known to be involved in the regulation of stem cell differentiation, and proteins with no described function in early ES cell development were also shown to change markedly at the proteome level only. ES cell development is regulated at the mRNA and protein level.
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In silico screening and biological evaluation of inhibitors of Src-SH3 domain interaction with a proline-rich ligand.Src signalling and transduction are directly involved in cell growth, cell cycle, malignant transformation and cell migration, providing therapeutic opportunities through inhibition of Src. Here we report virtual screening for novel compounds that inhibit the Src-SH3 protein-protein interaction with a proline-rich peptide ligand. Computational docking of the ZINC compound database was performed using GOLD. Top-scoring compounds were assayed using a fluorescence polarization-based assay. A benzoquinoline derivative showed micromolar inhibition of binding between Src-SH3 and the proline-rich peptide. Several analogues were subsequently assayed showing the requirement of a linker between the benzoquinoline and phenyl rings, and electron donating substituents on the phenyl ring.
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Reciprocal relationship between expression of hypoxia inducible factor 1alpha (HIF-1alpha) and the pro-apoptotic protein bid in ex vivo colorectal cancer.Hypoxia inducible factor 1 (HIF-1) represses the transcription of pro-apoptotic bid in colorectal cancer cells in vitro. To assess the clinical relevance of this observation, HIF-1alpha and Bid were assessed in serial sections of 39 human colorectal adenocarcinomas by immunohistochemistry. In high HIF-1alpha nuclear-positive cell subpopulations, there was a significant reduction in Bid expression (ANOVA, P=0.04). Given the role of Bid in drug-induced apoptosis, these data add impetus to strategies targeting HIF-1 for therapeutic gain.
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Quantitative multiplexed quantum dot immunohistochemistry.Quantum dots are photostable fluorescent semiconductor nanocrystals possessing wide excitation and bright narrow, symmetrical, emission spectra. These characteristics have engendered considerable interest in their application in multiplex immunohistochemistry for biomarker quantification and co-localisation in clinical samples. Robust quantitation allows biomarker validation, and there is growing need for multiplex staining due to limited quantity of clinical samples. Most reported multiplexed quantum dot staining used sequential methods that are laborious and impractical in a high-throughput setting. Problems associated with sequential multiplex staining have been investigated and a method developed using QDs conjugated to biotinylated primary antibodies, enabling simultaneous multiplex staining with three antibodies. CD34, Cytokeratin 18 and cleaved Caspase 3 were triplexed in tonsillar tissue using an 8h protocol, each localised to separate cellular compartments. This demonstrates utility of the method for biomarker measurement enabling rapid measurement of multiple co-localised biomarkers on single paraffin tissue sections, of importance for clinical trial studies.
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Quantum dots light up pathology.Quantum dots (QDs) are novel nanocrystal fluorophores with extremely high fluorescence efficiency and minimal photobleaching. They also possess a constant excitation wavelength together with sharp and symmetrical tunable emission spectra. These unique optical properties make them near-perfect fluorescent markers and there has recently been rapid development of their use for bioimaging. QDs can be conjugated to a wide range of biological targets, including proteins, antibodies, and nucleic acid probes, rendering them of particular interest to pathology researchers. They have been used in multiplex immunohistochemistry and in situ hybridization, which when combined with multispectral imaging, has enabled quantitative measurement of gene expression in situ. QDs have also been used for live in vivo animal imaging and are now being applied to an ever-increasing range of biological problems. These are detailed in this review, which also acts to outline the important advances that have been made in their range of applications. The relative novelty of QDs can present problems in their practical use and guidelines for their application are given.
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Identification of gene transcript signatures predictive for estrogen receptor and lymph node status using a stepwise forward selection artificial neural network modelling approach.OBJECTIVE: The advent of microarrays has attracted considerable interest from biologists due to the potential for high throughput analysis of hundreds of thousands of gene transcripts. Subsequent analysis of the data may identify specific features which correspond to characteristics of interest within the population, for example, analysis of gene expression profiles in cancer patients to identify molecular signatures corresponding with prognostic outcome. These high throughput technologies have resulted in an unprecedented rate of data generation, often of high complexity, highlighting the need for novel data analysis methodologies that will cope with data of this nature. METHODS: Stepwise methods using artificial neural networks (ANNs) have been developed to identify an optimal subset of predictive gene transcripts from highly dimensional microarray data. Here these methods have been applied to a gene microarray dataset to identify and validate gene signatures corresponding with estrogen receptor and lymph node status in breast cancer. RESULTS: Many gene transcripts were identified whose expression could differentiate patients to very high accuracies based upon firstly whether they were positive or negative for estrogen receptor, and secondly whether metastasis to the axillary lymph node had occurred. A number of these genes had been previously reported to have a role in cancer. Significantly fewer genes were used compared to other previous studies. The models using the optimal gene subsets were internally validated using an extensive random sample cross-validation procedure and externally validated using a follow up dataset from a different cohort of patients on a newer array chip containing the same and additional probe sets. Here, the models retained high accuracies, emphasising the potential power of this approach in analysing complex systems. These findings show how the proposed method allows for the rapid analysis and subsequent detailed interrogation of gene expression signatures to provide a further understanding of the underlying molecular mechanisms that could be important in determining novel prognostic markers associated with cancer.
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Preclinical evaluation of M30 and M65 ELISAs as biomarkers of drug induced tumor cell death and antitumor activity.M30 and M65 are ELISAs that detect different circulating forms of cytokeratin 18. Using the aurora kinase inhibitor AZD1152 and the SW620 human colon cancer xenograft, experiments were conducted to qualify preclinically both assays as serologic biomarkers of cell death. Using two different apoptotic markers, the kinetics of cell death induced by AZD1152 was first characterized in vitro in three different cell lines and shown to peak 5 to 7 days after drug addition. Treatment of non-tumor-bearing rats with AZD1152 (25 mg/kg) produced no alterations in circulating baseline values of M30 and M65 antigens. In treated, tumor-bearing animals, M30 detected a 2- to 3-fold (P < 0.05) increase in plasma antigen levels by day 5 compared with controls. This correlated to a 3-fold increase in the number of apoptotic cells detected on day 5 in SW620 xenografts using immunohistochemistry. By contrast, M65 did not detect a drug-induced increase in circulating antigen levels at day 5. However, M65 plasma levels correlated to changes in tumor growth in control animals (r(2) = 0.93; P < 0.01) and also followed the magnitude of the temporal effect of AZD1152 on tumor growth. An intermediate but active dose of AZD1152 (12.5 mg/kg) produced a less significant increase in M30 plasma levels at day 5. It was also confirmed that the plasma profiles of M30 and M65 mirrored closely those measured in whole tumor lysates. We conclude that M30 is a pharmacodynamic biomarker of AZD1152-induced apoptosis in the SW620 xenograft model, whereas M65 is a biomarker of therapeutic response.
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Quantitative mass spectrometry-based techniques for clinical use: biomarker identification and quantification.The potential for development of personalised medicine through the characterisation of novel biomarkers is an exciting prospect for improved patient care. Recent advances in mass spectrometric (MS) techniques, liquid phase analyte separation and bioinformatic tools for high throughput now mean that this goal may soon become a reality. However, there are challenges to be overcome for the identification and validation of robust biomarkers. Bio-fluids such as plasma and serum are a rich source of protein, many of which may reflect disease status, and due to the ease of sampling and handling, novel blood borne biomarkers are very much sought after. MS-based methods for high throughput protein identification and quantification are now available such that the issues arising from the huge dynamic range of proteins present in plasma may be overcome, allowing deep mining of the blood proteome to reveal novel biomarker signatures for clinical use. In addition, the development of sensitive MS-based methods for biomarker validation may bypass the bottleneck created by the need for generation and usage of reliable antibodies prior to large scale screening. In this review, we discuss the MS-based methods that are available for clinical proteomic analysis and highlight the progress made and future challenges faced in this cutting edge area of research.
