Cancer refers to a group of diseases containing more than 200 different subtypes. Cancer is a heterogeneous disease by nature, meaning that there are differences among tumors of the same type in different patients, and there are differences among cancer cells within a single tumor of one patient. Since cancer is not a single disease, nor does it have a single cause, it proves to be incredibly hard to diagnose and treat. The ability to study cellular markers, cell and tissue spatial arrangement, and gene function are all integral parts of cancer diagnostic and treatment efforts.
Here, I first present a review of current techniques for quantitative tissue imaging at cellular resolution. I broadly divide current imaging techniques into three categories: fluorescence-based, mass spectrometry-based, and sequencing-based. In this work, I primarily concentrate on fluorescence-based methods, with the focus being on our recently developed theory Multiplexing using Spectral Imaging and Combinatorics (MuSIC). The basis for MuSIC is to create combinations of fluorescent molecules (whether it be small molecule fluorophores or fluorescent proteins) to create unique spectral signatures.
I then present a protocol for labeling antibodies with combinations of small molecule fluorophores, which I refer to as MuSIC probes. I use fluorescent oligonucleotides (oligos) to arrange the fluorophores at specified distances and orientations from one another in order to produce complex fluorescence spectra when the probe is excited. This labeling protocol is demonstrated using a 3-probe experimental setup, bound to Protein A beads, and analyzed via spectral flow cytometry. When translating this method to staining human cells, our staining intensity was not comparable to that of a conventional antibody labeling kit. Therefore, next I present an improved method to label antibodies with MuSIC probes with increased signal intensity. I re-arrange the oligo-fluorophore arrangement of the MuSIC probe to emit an increased fluorescent signal. Then I validate this approach by comparing the staining intensity of MuSIC probe-labeled antibodies to a conventional antibody labeling kit using human peripheral blood mononuclear cells.
Lastly, I present simulation theories for the multiplexing capabilities of MuSIC probes for various biological and diagnostic applications. First, I present a theory for high-throughput genetic interaction screening using MuSIC probes generated from 18 currently available fluorescent proteins. Simulation studies based on constraints of current spectral flow cytometry equipment suggest our ability to perform genetic interaction screens at the human genome-scale. Finally, I adapt this simulation protocol to generate MuSIC probes from 30 currently available small-molecule fluorophores. Using the same constraints as before, I predict that I can perform cell-type profiling of 200+ analytes.
I hope that the work presented here provides a foundation for the use of combination probes for various biological and disease applications and ultimately help to better diagnose and treat different types of cancer
