MIPS Molecular Imaging Program at Stanford
Center for Cancer Nanotechnology Excellence Focused on Therapy Response



Project Interactions

The above figure shows the intersections between the six projects. The interactions between the projects are grouped by project components with similar line patterns.

  • Nanotechnology Development:Projects 1 and 2 will synergistically coordinate the nanofabrication and nanosensor development aspects of their respective projects to determine the best nanosensor methods. Project 5 will closely coordinate the development of functionalized quantum dots (qdots) for protein targeting.
  • Functionalized Quantum Dots: Project 6 will receive biologically targeted qdots from Project 5 for the integration of in vivo imaging into a mouse model platform.
  • Protein Patterns and Reagents: Project 6 will provide mouse lymphoma model tissue/serum samples to Project 4 for protein profiling. Project 4 will internally develop prostate cancer mouse models and will identify protein patterns. *Project 3 will provide human lymphoma tissue/serum samples to Project 4 for potential profiling in future years. Project 4 will develop aptamers to target proteins and will work with Project 5 to develop antibodies to target proteins that will go to Projects 1 and 2 for ex vivo nanosenor development.
  • Integrated Mouse Models: Project 6 will work with ex vivo nanosensors from Projects 1 and 2, and a prostate cancer mouse model from Project 4, for integration of ex vivo nanosensors and in vivo molecular imaging into the complete testing platform.
  • Protein Phosphorylation Detection: *Project 3 will develop methods to study protein phosphorylation using Raman sensors nanotechnology and will analyze human lymphoma samples. These lymphoma samples will also be given to Project 4 for future use in protein profiling. Project 6 will provide some lymphoma mouse model samples to *Project 3 for future use in detecting protein phosphorylation.

We are developing nanosensors for ex vivo protein analysis and nanoparticles for in vivo molecular imaging, thereby combining the advantages of both major strategies. We are also making significant progress in developing and validating nanoparticles for optical molecular imaging using quantum dots that can predict and monitor therapy response in animal models. These discoveries should lead to new methods of testing drug efficacy in small animal cancer models, thereby accelerating the process of bringing improved drugs to the clinic. Our newly developed nanoparticles also have the potential to benefit intraoperative staging and to aid in the early diagnosis of cancer.

Based on magneto-nanosensors, nanotube/nanowire sensors, and Raman nanosensors, our unique nanotechnology platforms will allow the investigation of proteins from tissue and blood from pre- and posttreatment cancer patients to predict which patients will most likely respond or are responding to specific anti-cancer therapies. In our current research efforts, we will be testing patient tumor/serum samples from SPORE and other clinical studies along with mouse models of cancer. The cancer-related biochemical pathways targeted will be the her-kinase axis, with prostate cancer as the initial focus, and CD20 receptor/c-myc oncogene, with lymphoma as the second major focus. First, we will use mass spectrometry to characterize tumors/serum for protein profiles, and then we will develop corresponding antibodies/aptamers that will be linked to nanosensors for high sensitivity target cell surface antigens and potentially intracellular targets. All of these endeavors will be research projects. We will leverage resources in our three cancer centers, as well as the three additional cores in nanofabrication, nanocharacterization, and bioinformatics/biostatistics.

We are highly optimistic that our proposed work will help ongoing efforts to bring nanotechnology into the routine arsenal of cancer biologists and oncologists for improved patient management.

Research Project 1 - Magneto-Nano Protein Chip and Multiplex Sorter for Monitoring Tumor Markers
(S. Wang Project Leader; B. Bales; B. Wilson)

This project will develop novel protein nanotechnology platforms based on magneto-nano technology. These magneto nanosensors are derived from state-of-the-art devices that are used to read magnetic information encoded on hard disk drives at very high data density. They function by exhibiting significant resistance changes that are induced solely by external magnetic fields and are therefore insensitive to solution conditions such as buffers, pH, or ionic strength. Biological sensing is accomplished by affinity labeling both the sensor surface and magnetic nanoparticles to attach simultaneously to distinct domains of specifically targeted biological molecules. The magneto nanosensor then detects the attachment of the biomolecules through the magnetic field induced by the magnetic nanoparticles. For sufficiently smaller sensors and appropriate magnetic nanoparticle tags, affinity bonding due to a single, specific molecule can be detected as a simple change in the sensor electrical resistance so that expensive excitation sources or remote sensors are not required. In addition, a multiplexed magnetic sorting system based on novel synthetic magnetic nanoparticles will be developed to capture circulating tumor targets in human serum samples. These nanotechnologies can detect target molecules down to a single molecule level and will enable physicians to monitor patient response to a given cancer therapy and to detect cancers in the early stages.

To compare the advantages of a magneto-nano platform vs. a nanotube/nanowire platform, this project will interact significantly with Research Project 2. Our project will interact with Project 4 to provide the appropriate aptamers/antibodies to link the magnet-nano chips and the secretomics work. Our secretomic analysis will also be joined to the magnetic cell sorting work. We will align our project with Research Project 6 to provide a prototype magneto nanosensor that will be validated in an integrated mouse model platform. In completing our research, we will be collaborating with Dr. Amit Kulkarni and other members of GE Global Research (GE) to leverage GE's work in improved magnetic nanoparticles. Furthermore, our Research Project 1 will use Cores 1 (Stanford Nanocharacterization Lab); 2 (Service Facility for Fabricated Nanostructures); and 3 (Bioinformatics and Biostatistics Resource).

Research Project 2 - Multiplex Nanotube Based on Protein Nano-Arrays for Cancer Research
(H. Dai Project Leader; D. Felsher; P.J. Utz)

Chemically derived nanomaterials offer a unique route to novel nanostructure with useful properties for advanced miniature devices. Single-walled carbon nanotube (SWNT) and semiconductor nanowires are such an example. SWNTs are quasi-one-dimensional wires with diameters on the order of 2 nm, exhibiting interesting electrical properties useful for transistors, logic, and memory elements. Furthermore, nanotube electronic devices also have significant potential for sensor devices with advanced characteristics. This project will develop protein nanosensors based on nanotube/nanowire platforms by building controlled SWNT structures at the wafer scale to obtain massive arrays of nanosensor devices and to detect biological peptides/proteins.

To compare advantages of a magneto nano platform vs. a nanotube/nanowire platform, this project will interact significantly with Research Project 1. This project will also overlap with Research Project 4, which will provide the appropriate aptamers/antibodies to link the nanotube/nanowire sensors. Research Project 6 will provide our project with nanotube/nanowire sensors that will be validated in an integrated mouse model platform. Also, this research project will use Cores 1 (Stanford Nanocharacterization Lab) and 2 (Service Facility for Fabricated Nanostructures) as well as Core 3 (Bioinformatics and Biostatics Resource).

*Research Project 3 - Multiparameter Nanoparticle Detection of Phosphoproteins
(G. Nolan Project Leader)

This project will utilize raman spectroscopy and nanoparticles for multiplexed detection of phosphoproteins. Subcellular localization, or the activation state, is considered to be a reflection of a cell's capabilities or functions. Many of these events are relatively transitory-such as some phosphorylation of proteins in cell signaling cascades. Also, some of the relevant cell populations are so rare, and the proteins driving their function in such low abundance, that performing a standard biochemical analysis on them is nearly impossible. Remodeling of such cell signaling mechanisms is what drives disease processes. Therefore, to understand how signaling networks are remodeled in diseased cells, complex populations of such cells must be measured and phenotyped not only for their cell lineage status, but also for their relative activation state.

In this project, we will develop novel methods for studying intracellular protein phosphorylation events using the newly developed composite organic-inorganic nanoparticles (COINs), with unique raman spectroscopic signatures and phosphospecific antibodies. We will use Core 1 to characterize the COINs. We will also work closely with oncologists to collect and analyze the human tissue/serum data of lymphoma patients undergoing treatment with Rituxan and CHOP. The lymphoma samples for proteomics analysis will be provided by Research Project 4. Eventually, this project will network with Research Project 6 to study lymphoma mouse models. In our studies, we will also rely heavily on Core 3 (Bioinformatics and Biostatics Resource) to do our modeling of Bayesian networks inference algorithms for unprecedented and rapid determination of signaling discordances in diseased cell subsets, which will lead to new therapeutic modalities. Our predominantly cancer biology and oncology team will receive significant engineering/nanotechnology guidance for the raman sensors through direct collaborations with other members of the CCNE-TR consortium.

Research Project 4 - Proteomic Predictors of Clinical Outcome of Targeted Therapies in Prostate Cancer
(D. Agus Project Leader; P. Mallick Co-Leader; S. Hanash Co-Leader; A. Ellington; J. Katz; M. McIntosh)

This project will empirically-derive estimates of proteomic variation in the a) intracellular signaling proteome; b) cell-surface proteome; c) the secretory proteome; and the d) plasma/serum in response to axis-targeted therapies. These estimates of proteomic variation will be integrated by bioinformatics analysis to identify reagents for ex vivo nanosensors and in vivo nanoimaging to help assess which individuals, with cancer, are likely to respond to pathway-directed therapies. A significant part of our efforts will rely on the latest advances in mass spectrometry technology.

This project will provide Research Projects 1 and 2 with aptamers/antibodies for linking to their nanoarrays based on mouse and human blood/tissue analysis for the her-kinase axis in prostate cancer and eventually for lymphoma. Because Research Project 1 is also developing nanoparticle-based systems for detecting and sorting proteins and cells, it may give us the opportunity to increase sensitivity and throughput of our detection systems for secreted factors or to enrich low yield proteins for analysis in Research Project 4. Our project will further augment Research Project 1 by linking secretomic analysis with magnetic cell sorting technologies while also providing aptamers/antibodies for biological modification of quantum dots in Research Project 5. Finally, Research Project 4 will interact with Research Project 3 to develop human lymphoma samples for proteomic analysis and with Research Project 6 to utilize mouse tissue/blood samples for proteomic analysis and to image prostate cancer models with biologically modified nanoparticles.

In our research for this project, we will make significant use of Core 3 (Bioinformatics and Biostatistics Resource) because we need to track patient outcomes; standardize clinical and tumor molecule annotation with the NCI Thesaurus; and mine proteomics data for statistically significant differential protein expression pre- and posttreatment and for robust proteomic patterns predictive of treatment response.

Research Project 5 - Biological Modification of Quantum Dots for In Vivo Imaging
(A. Wu Project Leader; J. Rao; Z. Cheng)

This project will focus on the biological modification of qdots for the detection of biomarkers for cancer imaging. The peptide toolkit strategy permits ready modification of qdots with peptides or engineered antibodies that bind specifically to cancer targets. This project will initially modify qdots with engineered antibody fragments specific for known targets that are expressed in prostate cancer and lymphoma. As multiple-wavelength NIR qdots become available and as informative cell-surface targets are identified in Research Project 4, we will use our findings to help modify these NIR qdots with antibody ligands for multiple-parameter imaging. This project will also build on the expertise in RGD peptide targeting of agB3 integrin to develop qdots for imaging tumor neovasculature and to cultivate a novel strategy for increasing tumor cell-specific uptake of qdots for signal amplification. We will also ascertain the biochemical, biophysical, and optical properties of the biologically modified qdots, and we will evaluate their facility in binding to appropriate markers on prostate and other cancer cell lines in cell culture.

Our biomarker specific qdots will be used in Research Project 6 for small animal imaging studies. Our project will also utilize Cores 3 (Bioinformatics and Biostatistics Resource) for biostatistical help and 1 (Stanford Nanocharacterization Lab) for characterization by light scattering. In support of our research efforts, Dr. S.S. Gambhir will provide molecular imaging and oncology expertise to our basic science team of investigators.

Research Project 6 - Mouse Cancer Models for Integrated Tissue/Serum Proteomics and Molecular Imaging
(S.S. Gambhir Project Leader and S. Yazdanfar Co-Leader)

This project will use mouse models of cancer for integrating ex vivo protein nanosensors and in vivo molecular imaging to predict and monitor responses to anti-neoplastic therapies. In the course of our research, we will test existing small animal optical imaging equipment and work with GE Global Research to develop new imaging equipment. We will also use targeted qdots to image cell surface targets in living mice. Specifically, we will use a prostate cancer mouse model to test ex vivo protein nanosensors and in vivo qdots to study how the two strategies can be used together to improve the prediction and monitoring of therapies. Also, our research will involve using mouse models of lymphoma to look for protein patterns in tumor tissue and serum that are useful for predicting and monitoring response to therapies.

Our Research Project 6 will interact significantly with the other five research projects. In conducting our research, we will test nanosensor arrays developed in Research Projects 1 and 2 in mouse cancer models, and we will provide mouse tumor tissue/serum to Research Project 3 for studying the phosphorylation of proteins that may prove useful in monitoring therapy. In conjunction with Research Project 4 and using tumor/tissue serum, we will determine if protein patterns can be found that are useful for predicting and monitoring response to therapies using a lymphoma mouse model. Through a prostate cancer model developed in Project 4, our research will also test both the ex vivo protein nanosensors and qdots used in molecular imaging. Finally, we will collaborate with Research Project 5 in using biologically modified qdots for imaging in small animal models of lymphoma.

Core 3 (Bioinformatics and Biostatistics Resource) will provide our project with key resources such as data management, general biostatistical support, and, through Project 4, protein pattern discoveries that are predictive of therapy response. Through the leadership of Drs. Filkins and Yazdanfar, General Electric Global Research (GE) will provide critical support for developing new optical imaging hardware with improved temporal resolution for imaging small animals with multiple fluorescent sources such as multicolor qdots.

*Project 3 evolved into other areas and is no longer continuing with the CCNE-TR grant

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