Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

Atomic-level structure and deformation in metallic glasses

Metallic glasses (MGs) are a relatively new class of materials discovered in 1960 and lauded for its high strengths and superior elastic properties. Three major obstacles prevent their widespread use as engineering materials for nanotechnology and industry: 1) their lack of plasticity mechanisms for deformation beyond the elastic limit, 2) their disordered atomic structure, which prevents effective study of their structure-to-property relationships, and 3) their poor glass forming ability, which limits bulk metallic glasses to sizes on the order of centimeters. We focused on understanding the first two major challenges by observing the mechanical properties of nanoscale metallic glasses in order to gain insight into its atomic-level structure and deformation mechanisms. We found that anomalous stable plastic flow emerges in room-temperature MGs at the nanoscale in wires as little as ~100 nanometers wide regardless of fabrication route (ion-irradiated or not). To circumvent experimental challenges in characterizing the atomic-level structure, extensive molecular dynamics simulations were conducted using approximated (embedded atom method) potentials to probe the underlying processes that give rise to plasticity in nanowires. Simulated results showed that mechanisms of relaxation via the sample free surfaces contribute to tensile ductility in these nanowires. Continuing with characterizing nanoscale properties, we studied the fracture properties of nano-notched MGnanowires and the compressive response of MG nanolattices at cryogenic (~130 K) temperatures. We learned from these experiments that nanowires are sensitive to flaws when the (amorphous) microstructure does not contribute stress concentrations, and that nano-architected structures with MG nanoribbons are brittle at low temperatures except when elastic shell buckling mechanisms dominate at low ribbon thicknesses (~20 nm), which instead gives rise to fully recoverable nanostructures regardless of temperature. Finally, motivated by understanding structure-to-property relationships in MGs, we studied the disordered atomic structure using a combination of in-situ X-ray tomography and X-ray diffraction in a diamond anvil cell and molecular dynamics simulations. Synchrotron X-ray experiments showed the progression of the atomic-level structure (in momentum space) and macroscale volume under increasing hydrostatic pressures. Corresponding simulations provided information on the real space structure, and we found that the samples displayed fractal scaling (r^d ∝ V, d < 3) at short length scales (< ~8 Å), and exhibited a crossover to a homogeneous scaling (d = 3) at long length scales. We examined this underlying fractal structure of MGs with parallels to percolation clusters and discuss the implications of this structural analogy to MG properties and the glass transition phenomenon.