bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 4883: Peptide-based PET imaging agents using novel bifunctional chelates and 64Cu
Authors: Gill Rajanvir K. , Wong May , Sutherland Brent , Ng Sylvia , Bensimon Corrine , Jurek Paul , Kiefer Garry , Yapp Donald T.T. , Ferreira Cara 
Published: June 2012

Abstract
Introduction: Developing peptide-based PET imaging agents would be highly advantageous due to their high affinity and specificity. Two novel bifunctional chelates (BFC), PCTA and Oxo-DO3A, have previously been used to label antibodies with 64Cu. Complexation of 64Cu with PCTA and Oxo-DO3A was more efficient than with DOTA; the PCTA and OXO-DO3A complexes were also more stable and had more favourable pharmacokinetics[1]. Similarly, PCTA was also found to complex 68Ga more efficiently than DOTA[2]. The utility of PCTA and Oxo-DO3A for radiolabeling peptides specific for tumour angiogenesis processes were further investigated.
Methods: The receptor number and affinity of RGD peptides were determined in mouse vascular endothelial cells. Mouse vascular endothelial cells were grown and varying amounts of I-125 echistatin were added to 1 million cells until receptors were saturated. A competitive binding assay, where a set amount of I-125 echistatin was added to the cells in the presence of unlabeled peptides, confirmed the specificity of the peptides for the target. In vivo studies were carried out in HT29 human colorectal tumors grown subcutaneously in RAG2M mice. 64Cu radiolabeled bioconjugates of PCTA, Oxo-DO3A and DOTA were injected with and without excess cyclo-(RGDyK) peptide. The amount of activity in the blood, tumor, liver, kidney and muscle was measured and compared to each of the BFC.
Results: The binding assay revealed the saturation of mouse vascular endothelial cells was achieved when 0.8µci of I-125 echistatin was added. The competitive binding assay indicated an IC50 at a concentration of 9pM of DOTA-RGD. In vivo biodistribution studies showed good tumor to blood ratios for all of the 64Cu radiolabeled bioconjugates and better tumor to muscle ratios for the 64Cu radiolabeled bioconjugates of PCTA and Oxo-DO3A.
Conclusion: The bifunctional chelates PCTA and Oxo-DO3A were found to be effective for radiolabeling peptides with 64Cu; the resulting complexes appear to be more stable than those of DOTA. The data show that PCTA and Oxo-DO3A radiolabel peptides more efficiently than DOTA, and that the resulting complexes are more stable. Angiogenesis in HT-29 tumours was also imaged successfully using the peptides labeled with PCTA and Oxo-DO3A.
References:
1. C.L. Ferreira, D.T.T. Yapp. E. Lamsa, M. Gleave, C. Bensimon, P. Jurek, G.E. Kiefer, Nucl. Med. Biol. 35: 875-882 (2008)
2. C.L. Ferreira, E. Lamsa, M. Woods, Y. Duan, P. Fernando, C. Bensimon, M. Kordos, K. Guenther, P. Jurek, G.E. Kiefer, Bioconj. Chem. 21: 531-536 (2010)
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4883. doi:10.1158/1538-7445.AM2011-4883
Abstract 4899: Development of a quantitative measurement of p53 – p53 antibody interactions
Authors: Atha Donald H. , Reipa Vytas 
Published: June 2012

Abstract
We are developing methods to quantify antibody interactions that includes a quartz crystal microbalance (QCM) system to measure, on a molecular basis, the interaction of p53 and anti-p53 antibodies. Previously, as a model system, we developed a reference device consisting of p53 protein (human wild type), characterized by mass spectroscopy and immobilized at various concentrations on a glass slide. The device is designed as a reference control to be used with immunohistochemical (IHC) assays that incorporate commercially available anti-p53 antibodies and probes. In the current study, we compared three different monoclonal antibodies (clones: BP53.12, PAb 1801 and DO-1) for their ability to detect p53 in HT1080 cells. Both visible microscopy (diaminobenzidine probe) and flow cytometry (AlexaFluor 488 probe) showed significant increases in staining intensity compared to controls without primary antibody. However, quantification of these observations requires direct measurement of the concentration of the p53 and the concentrations and specificities of the antibodies. For this the p53 protein is covalently immobilized on glass coated quartz crystals and the resonance frequency shift is followed in-situ. The functionalized sensor is then incubated with the anti-p53 antibody, which provides a direct gravimetric measure of antibody-antigen binding. This allows the comparison of the surface immobilized protein concentrations with those previously obtained by fluorescence measurement. The p53 functionalized QCM system offers an independent measure of surface immobilized protein concentration and is essential in the development of our IHC calibration prototypes. These results also provide a benchmark for comparing systems that may be used in developing molecular diagnostic assays such as aspiration biopsy analysis and the detection of biomarker proteins in blood and urine.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4899. doi:10.1158/1538-7445.AM2011-4899
Abstract 4900: Development of a method for metabolomics and histology of tissue biopsies
Authors: Brown Meredith V. , Adam Klaus-Peter , Shuster Jeffrey R. , Troyer Dean A. , Lawton Kay A. 
Published: June 2012

Abstract
Metabolomics, the global study of small molecules in a biological sample, is performed with the goal of extracting, identifying, and quantifying metabolites. As such, the technology is ideal for identifying biomarkers for diagnostics and drug therapy. One of the limitations with the current practice for metabolite extraction is that sample destruction precludes additional uses of the sample. This is particularly troublesome for high value samples with limited availability, such as clinical tumor biopsies. Clinical biopsies are taken in order to histologically diagnose and gauge cancer aggressiveness. Thus, physically disrupting these valuable samples is not ideal, even though quantitative metabolomic data could enhance histopathologic evaluation. In order to improve the amount of information obtained from patient biopsies, we have developed a method (termed PReservation by Extraction and Fixation, PREF) by which metabolite extraction simultaneously preserves the tissue for histological analysis. Briefly, upon sample collection, the biopsy is placed directly in methanol. Methanol incubation serves to recover metabolites, precipitate proteins, and fix the tissue. Following overnight incubation, the solvent is removed, evaporated to dryness, and reconstituted in a proprietary mixture of recovery standards. The needle biopsies are placed in biopsy bags and cassettes and transferred to Molecular Fixative until processed for histology. Solvent sample aliquots are taken for analysis on GC/MS and LC/MS platforms. Raw mass spectrometry data files are automatically extracted using a proprietary informatics system that includes peak identification and compound identification software. Compared to the current state of the art method for metabolite extraction, PREF recovers equivalent numbers and types of biochemicals from the tissue specimen. Furthermore, PREF preserves the tissue biopsy sample such that cellular architecture is retained, allowing for pathological analysis by chemical staining (hematoxylin & eosin) and antibody binding (immunohistochemistry). We have developed a non-destructive method for efficient metabolite extraction from tumor biopsies combined with preservation of the tissue for histological analysis. It is our hope that this novel method will augment the current histopathologic diagnosis and classification of tumors through quantitative measures of biochemicals in the same tissue. Given that certain biochemicals have been shown to correlate with disease aggressiveness, it is likely that this method will be valuable in helping to differentiate cancer aggressiveness.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4900. doi:10.1158/1538-7445.AM2011-4900
Abstract 491: Defining the origins of ras/p53 mediated squamous cell carcinoma
Authors: White Andrew C. , Tran Kathy , Khuu Joan , Lowry Bill 
Published: June 2012

Abstract
The precise identity of cancer cells of origin and the molecular events of tumor initiation in epidermal squamous cell carcinoma (SCC) are unknown. Here we show that malignancy potential is related to the developmental capacity of the initiating cancer cell in a genetically defined, intact, and inducible in vivo model. Specifically, these data demonstrate that hair follicle stem cells (SCs) serve as cancer cells of origin when oncogenic Kras is expressed and p53 is ablated, whereas their more developmentally restricted progeny, the transit amplifying (TA) cells, are unable to generate even benign tumors in the same genetic context. Employing a temporal model of tumorigenesis in situ, we highlight the phenotypes of cancer progression from hair follicle SCs including hyperplasia, dysplasia, epithelial to mesenchymal transition, and SCC formation. Furthermore, we provide insights into the inability of hair follicle TA cells to respond to tumorigenic stimuli.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 491. doi:10.1158/1538-7445.AM2011-491
Abstract 4910: Unveiling the role of network and systems biology in pancreatic cancer drug discovery
Authors: Azmi Asfar S. , Philip Philip A. , Choi Minsig , Shields Anthony F. , Sarkar Fazlul H. , Mohammad Ramzi M. 
Published: June 2012

Abstract
Over the last half decade our laboratory has extensively worked on the preclinical development of small molecule inhibitor of HDM2 (MI-219-Ascenta Therapeutics) in multiple tumor models with especial emphasis on the intractable pancreatic cancer (PC). During this discourse we have observed significant anti-tumor activity when MI-219 was given with oxaliplatin that lead to tumor free survival in 50% of the animals. However, not much is known about the exact mechanism behind this synergy. Here we applied a network-centric approach to identify the global expression changes and the networks involved in this two drug combination without losing the key molecular details. Gene analysis of wt-p53 capan-2 cells shows that MI-219 alone induces a minimal alteration (only 48 genes). Oxaliplatin (a cytotoxic drug) treatment, on the other hand showed alterations of 700 genes. However, the combination of MI-219-oxaliplatin resulted in emergence of 286 synergy unique genes. Principal component analysis revealed that each drug treatment had unique global gene signatures. Further analysis of the synergy unique genes revealed the presence of 14 statistically enriched functional pathways. Overall, the central p53 activity hub was found to be supported by 5 crucial players; CREBBP which is ubiquitously expressed in PC and is involved in the transcriptional co-activation of p53. CARF that is responsible for p53 stability along with NF-κB and EGR1 tumor suppressor modules, all positively affecting p53 re-activation that drives cells towards apoptosis. Additionally, our analysis revealed a novel role of hepatocyte nuclear factor alpha (HNF4α) in aiding this synergy. In addition to PC, the gene signatures could be verified and validated at the RNA and protein level in multiple wt-p53 solid tumor cell lines like MCF-7 for breast and HCT-116 for Colon. siRNA knockdown of key network genes abrogated apoptotic potential of MI-219-oxaliplatin in all three cell lines and confirmed their key role in the observed anticancer effects of this combination. Our findings show that Network and Systems biology can be utilized in identification of crucial driver genes and help in the design of drug combinations in a genetically pre-defined subset of patients that would positively impact treatment outcome.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4910. doi:10.1158/1538-7445.AM2011-4910
Abstract 4912: A network model of circulating tumor cell dynamics: Uncovering the mechanism of metastasis
Authors: Scott Jacob G. , Kuhn Peter , Anderson Alexander R A , Newton Paul 
Published: June 2012

Abstract
Background: Hematogenous metastasis is a poorly understood process that accounts for the lion's share of cancer death. We hypothesize that this process can be explained by circulating tumor cells (CTCs). We endeavor to deconvolute this complex process by means of a mathematical model of CTC population dynamics within the human vascular system.
Methods: We have represented the human vasculature as a network with organs represented as nodes and vascular connections as directed edges and written a system of Ordinary Differential Equations to model the dynamics of circulating tumor cells (CTCs) as they populate the body from a source tumor. We have introduced several novel concepts such as a ‘filtration fraction’ which represents the fraction of CTCs that arrest in a given organ, the ‘shedding rate’ which represents the rate at which a primary tumor sheds CTCs into the vasculature and a ‘clearance rate’ which represents the combined effects of CTC apoptosis and immune clearance.
Experimental parametrization of this model is accomplished through a clinical trial at The Scripps Institute during which we measure CTC concentrations at each of the most highly connected nodes at several time points before and after definitive surgery for – to include the portal vein, the superior vena cava, peripheral venous and peripheral arterial blood.
Results: Initial exploration of the model using clinical data for validation has shown that certain tumor types follow flow driven patterns of metastasis while others seem to ignore the logical spread (e.g. prostate cancer spreading to the bone does not follow the flow directed network while sarcoma to the lungs does). Reasons for this dichotomy are as of yet unknown, though we suspect that both CTC heterogeneity and some form of biological signaling response are at play. We will utilize our theoretical model to investigate this dichotomy by explicitly incorporating CTC heterogeneity and by making specific biological, phenotypic observations of CTCs from different points in the network.
Conclusion: We present the first network based, filter and flow model of CTC dynamics. The act of building the theoretical model and comparing it to clinical data alone has inspired several biological hypotheses and we look forward to testing more specific questions through clinical studies.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4912. doi:10.1158/1538-7445.AM2011-4912
Abstract 4914: A novel integrative network study identifies key genes and pathways in the progression of Hepatitis C virus induced hepatocellular carcinoma
Authors: Zhao Zhongming , Zheng Siyuan 
Published: June 2012

Abstract
Hepatocellular carcinoma (HCC) is the third most common cause of cancer mortality in the world. Incidence of hepatitis C virus (HCV) induced hepatocellular carcinoma (HCC) has been increasing in the United States and Europe during recent years. Although HCV-associated HCC shares many pathological characteristics with other types of HCC, the molecular mechanisms underlying its progression remain elusive. To investigate the underlying pathology, we developed a systematic approach to identify deregulated biological networks in HCC by integrating gene expression profiles with high-throughput protein-protein interaction data. This integrative approach to searching for deregulated networks during each pathological stage is different from typical search of common pathway resources like Gene Ontology or KEGG biochemical pathways. It has at least two advantages: 1) a high throughput protein interaction network covers more genes; and 2) the resulting network gives gene interaction information, which provides a simpler framework to explore the functional associations between genes and generate new biological hypotheses. By comparing sets of consecutive pathological stages, we identified four networks in five groups of samples corresponding to normal, cirrhosis, dysplasia, early HCC and advanced HCC. The functional annotation of each network demonstrates a high degree of consistency with current knowledge of HCC. By assembling these functions into a modular map, we were able to depict the stepwise pathways that are dysregulated in HCV-induced hepatocarcinogenesis. Additionally, these networks enable us to identify important genes and pathways by developmental stage, such as LCK signaling pathways in cirrhosis, MMP genes and TIMP genes in dysplastic liver, and CDC2-mediated cell cycle signaling in early and advanced HCC. CDC2 (alternative symbol CDK1), a regulatory gene in cell cycle control, is particularly interesting due to its topological position in temporally deregulated networks. Our study uncovers a temporal spectrum of functional deregulation, and prioritizes key genes and pathways in the progression of HCV induced HCC. These findings present a wealth of information for further investigation.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4914. doi:10.1158/1538-7445.AM2011-4914
Abstract 4920: Integrative identification of stochastically activated signaling sub-networks in individual cancer cells
Authors: Sergio Iadevaia , Ram Prahlad 
Published: June 2012

Abstract
Traditional studies on signal transduction are focused on measuring the average levels of proteins in populations of isogenic cells to determine the regulatory properties of cell signaling networks and design effective intervention strategies for cancer therapy. However, the average protein levels measured in populations of cells may be quite different from the protein levels measured in individual cells. Signaling differentiation in individual cells is often associated with stochastic events that may activate different cellular sub-networks at different times to generate diverse responses. It is therefore critical to elucidate these stochastic events to design therapeutic interventions that may effectively inhibit abnormal signaling sub-networks in individual cells. In this work, we analyzed the epidermal growth factor (EGF) signaling network in the MDA-MB468 breast cancer cell line and the insulin-like growth factor (IGF-1) signaling network in the MBA-MB231 breast cancer cell line. We measured the average changes in the phosphorylation of proteins after EGF or IGF-1 stimulation using reverse-phase protein arrays (RPPA). We developed a detailed mathematical model to predict the deterministic and stochastic dynamics of EGF and IGF-1 signaling networks. We used particle swarm optimization to train the deterministic model to predict the average transient changes in the phosphorylation of proteins measured by RPPA and infer the unknown model parameters. Using the estimated model parameters, we implemented the stochastic model to predict the transient changes in the phosphorylation of proteins in individual cells. The modeling results showed that protein phosphorylation in individual cells could attain levels that were several fold higher or lower that those attained by the average cell in the population. We used a multicolor fluorescence-activated cell sorter (FACS) to measure the distribution in the phosphorylation of protein after EGF or IGF-1 stimulation and experimentally validate the modeling predictions. We finally compared the overall signal transduction of individual cells whose protein phosphorylation attained higher and lower levels to computationally identify cellular sub-networks that were differentially activated. The integrative approach described here is therefore a useful tool for computationally predicting the stochastic events responsible for signaling differentiation in individual cells and optimizing experimental intervention strategies for cancer therapy.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4920. doi:10.1158/1538-7445.AM2011-4920