Multiplexed angiogenic biomarker quantification on single cells

Clinical and biomedical research seeks single-cell quantification to better understand their roles in a complex, multi-cell environment. Recently, quantification of vascular endothelial growth factor receptors (VEGFRs) provided important insights into endothelial cell (EC) characteristics and response in tumor microenvironments. However, data on other angiogenic receptors, such as platelet derived growth factor receptors (PDGFRs), Tie receptors, are also necessary for the development of an accurate angiogenesis model. To gain insights on the involvement of these angiogenic receptors in angiogenesis, I develop a method to quantify receptor concentrations as well as the cell-by-cell heterogeneity. I establish protocols to measure cell membrane VEGFR, NRP1, Tie2, and PDGFR concentration on several cell and tissue models including human dermal fibroblasts (HDFs) in vitro, a 2D endothelial/fibroblast co-culture model in vitro, and a patient-derived xenograft (PDX) model of glioblastoma (GBM). I demonstrate VEGF-A165-mediated downregulation of membrane PDGFRα (~25%) and PDGFRβ (~30%) on HDFs, following a 24-hour treatment. This supports the idea that VEGF-A165 acts independently of VEGFRs to signal through PDGFRα and PDGFRβ. I uncover high intratumoral heterogeneity within the GBM PDX model, with tumor EC-like subpopulations having high concentrations of membrane VEGFR1, VEGFR2, EGFR, IGFR, and PDGFRs. To gain greater insights into cell heterogeneity and examine angiogenic signaling pathways as a whole, I utilize the unique spectral properties of quantum dots (Qdots), and combines Qdots with qFlow cytometry, to dually quantify VEGFR1 and VEGFR2 on human umbilical vein endothelial cells (HUVECs). To enable this quantification, I reduce nonspecific binding between Qdot-conjugated antibodies and cells, identify optimal labeling conditions, and establish that 800 – 20,000 is the dynamic range where accurate Qdot-enabled quantification can be achieved. Through these optimizations we demonstrate measurement of 1,100 VEGFR1 and 6,900 VEGFR2 per HUVEC. 24 h VEGF-A165 treatment induce ~90% upregulation of VEGFR1 and ~30% downregulation of VEGFR2 concentration. We further analyze HUVEC heterogeneity and observe that 24 h VEGF-A165 treatment induces ~15% decrease in VEGFR2 heterogeneity. Overall, we demonstrate experimental and analysis strategies for quantifying two or more RTKs at single-level using Qdots, which will provide new insights into biological systems

Predicting angiogenic receptor trafficking and signaling via computational systems biology

Angiogenesis is defined as the growth of new blood vessels from preexisting vessels. Systematic regulation of angiogenesis could lead to new treatments of vascular diseases and cancer. As such, vascular endothelial growth factor (VEGF), a potent angiogenic growth factor, offers a promising therapeutic target. Despite this promise, VEGF targeted therapies are not clinically effective for many pathologies, such as breast cancer. Thus, a better understanding of the VEGF network for regulating angiogenesis, along with identifying key nodes controlling angiogenesis within this network, are necessary to provide effective VEGF therapeutics. Systems biology, defined as applying experiment and computational modeling to understand a biological system, can readily define this VEGF-angiogenesis network. In this dissertation, I provide an overview of how computational systems biology has been used to provide basic biological insights into angiogenesis, explore anti-angiogenic therapeutic options for cancer, and pro-angiogenic therapeutic options for vascular disease. Using systems biology, I have previously predicted that VEGFR1 acts as a predictive biomarker of anti-VEGF efficacy in breast cancer. Particularly, tumor endothelial cell subpopulations exhibiting high VEGFR1 levels result in ineffective anti-VEGF treatment. These high VEGFR1 subpopulations are characterized by a high amount of VEGF-VEGFR1 complex formation, and subsequently high VEGF-VEGFR1 internalization. The high VEGF-VEGFR1 complex formation implies a possible VEGFR1 signaling role beyond its classically defined decoy status. In this dissertation, I introduce a computational approach that accurately predicts the cell response elicited via VEGFR1 signaling. I show that VEGFR1 promotes cell migration through PLCγ and PI3K pathways, and promotes cell proliferation through a PLCγ pathway. These results provide new biological insight into VEGFR1 signaling and angiogenesis while offering a system for directing angiogenesis. Cell subpopulations expressing high VEGFR1 levels are characterized by a large amount of VEGF-VEGFR1 internalization. Thus, endocytosis may regulate VEGFR1 signaling; indeed, intracellular-based receptor signaling has recently emerged as a key component in mediating cell responses for receptor tyrosine kinases (RTKs). However, how endocytosis fundamentally mediates signaling for any RTK remains poorly defined. Understanding how endocytosis fundamentally directs intracellular receptor signaling requires receptor-specific endocytosis mechanisms to be delineated. This delineation requires identifying the signaling mechanisms common to all receptor types. To this end, I conduct a computational meta-analysis predicting endocytic compartment signaling across eight RTKs, and identify their common signaling mechanisms. I find that endocytic vesicles are the primary cell signaling compartment; over 43% total receptor phosphorylation occurs within the endocytic vesicle compartment for all eight RTKs. Conversely, all RTKs exhibit low membrane-based receptor signaling, exhibiting < 1% total receptor phosphorylation. Mechanistically, this high RTK phosphorylation within endocytic vesicles may be attributed to their low volume, which facilitates an enriched ligand concentration. The late endosome and nucleus are also important contributors to receptor signaling, where 26% and 18% average receptor phosphorylation occurs, respectively. Furthermore, nuclear translocation requires late endosomal transport; blocking receptor trafficking from late endosomes to the nucleus reduces nuclear signaling 96%. These findings can be applied to understand specific RTK signaling functions in terms of cell response, and optimize RTK therapeutics targeting endocytic pathways. Overall, I reveal the role of VEGFR1 and its signaling mechanisms, which is essential information to the field of angiogenesis. This information advances angiogenesis therapeutics by identifying the VEGF-VEGFR1 signaling axis as an essential target. I identify the primary adapters that can be targeted to critically regulate VEGF-VEGFR1 signaling, and endocytic compartmentalization that can be targeted for tuning receptor signaling. Furthermore, the computational techniques I develop advance the field of systems biology by delineating the signal-to-response of receptor signaling, improving receptor investigation by allowing adapter phosphorylation and cell responses to be quantified simultaneously, in addition to compartmentalized receptor signaling. These computational techniques improve disease treatment by allowing optimal receptor signaling targets to be identified quickly. Additionally, unknown receptor signaling can be mapped from adapter phosphorylation to cell response. These computational techniques can be integrated into multiscale computational models to provide clinically relevant, patient-specific platforms for directing disease treatment

Genomic Data-Based Models of Growth Factor Signaling for Personalized Cancer Therapy Selection

The genetic heterogeneity of cancer creates patient-to-patient variability that makes it difficult to predict whether the patient will respond to a treatment. This is particularly true for VEGF-targeting therapies, for which, in some cancers, response rates have typically been low and overall survival has only been extended slightly if at all. Development of predictive biomarkers for VEGF-targeting therapies has traditionally focused either on measurement of VEGF family ligand concentrations in the plasma or on tumor-derived transcriptomic data. Here, we incorporate both of these types of information into a whole-body computational model of the kinetic interactions between VEGF ligands and receptors. Gene expression data from a population of cancer patients allows us to create a virtual population where the effects of multiple VEGF-targeting drugs can be tested. This approach allows us to limit our analysis to relevant genes instead of the entire genome and allows us to incorporate mechanistic information, both of which should lead to models with better reproducibility. We first examined patterns of expression of VEGF ligands and receptors as well as a related family, the Semaphorins. Several previously defined subtypes of cancer were associated with pro-angiogenic alterations in the expression of these genes. Multivariate biomarkers based on VEGF and Semaphorin gene expression were, in some cases, able to provide better separation of patients according to prognosis. These results provide clinically relevant subtypes and highlight the role that Semaphorins may play in processes that drive tumor angiogenesis and progression. We then used gene expression data to create three virtual populations: patients with breast, kidney, or prostate cancers. Drug response metrics in these populations allowed us to determine characteristics of patients that make them more responsive to treatments. We found that the best biomarkers of response differed between cancer types. This approach can be applied to other families of growth factors as well. Here, we demonstrate its application to the EGFR/ErbB family

"The Effect of Arylhydrazone of Active Methylene Compounds on GBM Cell Lines"

Glioblastoma (GBM), a WHO grade IV glioma, is the most common and one of the malignant types of central nervous system tumors in adults. The resistance of GBM cells to antineoplastic agents has been the biggest obstacle in the treatment of GBM tumors. The temozolomide, a frontline GBM chemotherapy drug, has increased the median survival of the patients approximately for one and a half years only. Therefore, there is a need for the development of a novel anti-GBM drug that increases the median survival of the GBM patients with fewer side effects. The hydrazone derivatives inhibit the growth and proliferation of GBM tumors. In this study, arylhydrazone of active methylene compounds (AHAMCs) was examined using GBM cell lines U87 and LN229. The antitumor activity of AHAMC compound R234 was investigated by performing cytotoxic assay and dose- and time-dependent assay. To ascertain whether the R234 compound obstructs the cell cycle progression, GBM cells were stained with the propidium iodide (PI) dye and analyzed using cellProfiler software. To improve the quality of the segmentation several combinations of thresholding strategies and thresholding methods were tested for both the cell lines. The global and adaptive thresholding strategies and Otsu’s and maximum correlation thresholding (MCT) methods that returned comparable segmentation results were selected. Further, segmentation results of the selected thresholding strategies and methods were compared by calculating the false negatives (FN) and false positives (FP) for each combination manually. Finally, the segmentation results obtained from the combination of global strategy and MCT method were chosen for the intensity measurement. The cells were then grouped into the different phases of the cell cycle from the histogram of PI intensities. The proportions of the cells in each phase of the cell cycle show that the R234 arrests the cell cycle at the G2/M phase in both cell lines. Overall, the results suggest that the R234 compound exerts its cytotoxic activity by arresting the cell cycle at the G2/M phase

Study of Anti-proliferative Activity of Cucurbitacins Inspired Estrone Analogs on Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is considered the third leading cause of death from cancer. Overall survival rate is significantly low, due to the emerging resistance to chemotherapeutic agents and lack of selectivity. Recent studies have demonstrated that epidermal growth factor receptor (EGFR) is a promising molecular target for cancer therapy, especially HCC. Current studies showed that cucurbitacins are potent anticancer compounds which target EGFR. This prompted us to investigate the antiproliferative activity of novel cucurbitacins inspired estrone analogs (CIEA) against sensitive and resistant HepG2 cell lines. Anti-proliferation activity of 20 CIEA analogs were examined against HepG2 using MTT assay and showed that antiproliferative activity of analogs MMA132, and MMA102 IC50 are 2μM, and 3 μM respectively in comparison to Erlotinib 25 μM. Study of the mechanism of anti-proliferation effects of these novel analogs was elucidated. Western blot analysis showed that MMA132, and MMA102 significantly inhibit EGFR/pEGFR, RAF/pRAF, MEK/pMEK, and ERK/PERK. Cell cycle analysis on HepG2 cell line revealed that MMA132 and MMA102 arrested the cells at G1 phase and inhibited the HepG2 cell migration after 24 hr. MMA132 induced apoptosis through activation of caspase 3,9 and inhibition of PARP. Treatment of HepG2-R (Erlotinib resistant) with MMA132 and MMA102 showed that these two novel drug candidates still possessing potent anti-proliferation activities against HepG2-R. Further characterization of the anti-proliferation of these lead compounds was demonstrated through mapping the change in EGFR signaling pathway (ERK, pERK, RAS, AKT and MEK) by western blot, cell cycle analysis, demonstrated that MMA132 and MMA102 stop the cell cycle of HepG2-R at G2 phase and inhibited cell migration after 48hrs. HepG2-R cell line significantly expressed MRP2 in comparing to sensitive cells. Moreover, MK571(MRP2 inhibitor) showed an inhibitory effect on resistant HepG2-R cancer cell lines. Combination of MMA132 with MK571 (13 μM and 15 μM respectively) showed a significant increase in the cytotoxicity of MK571 from 18.5 μM to 10 μM. In conclusion, our study documented the discovery of novel estrone analogs as potential drug candidates for treatment of HCC and promising chemotherapeutic agent toward HepG2 resistant to erlotinib

EPMA position paper in cancer:current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision

The HBP1 tumor suppressor is a negative epigenetic regulator of MYCN driven neuroblastoma through interaction with the PRC2 complex

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Molecular Imaging

The present book gives an exceptional overview of molecular imaging. Practical approach represents the red thread through the whole book, covering at the same time detailed background information that goes very deep into molecular as well as cellular level. Ideas how molecular imaging will develop in the near future present a special delicacy. This should be of special interest as the contributors are members of leading research groups from all over the world