Tailoring the best treatments to cancer patients remains a highly important endeavor in the oncology field. However, personalized treatment courses are challenging to determine, and technologies or methods that can successfully be employed for precision oncology are lacking.

Biological nanoparticles, like extracellular vesicles (EVs), possess unique biological characteristics making them attractive therapeutic agents, targets, or disease biomarkers. However, their use is hindered by the lack of tools available to accurately detect, sort, and analyze. Flow cytometers are used to sort and study individual cells. But, they are unable to detect and sort nanomaterials smaller than 200 nanometers with single epitope sensitivity.

Multi-parameter flow cytometry has been extensively used in multiple disciplines of biological discoveries, including immunology and cancer research. However, the disadvantage of traditional flow cytometry platforms using excitation lasers and fluorescence detectors is spectral overlap when using multiple dyes on the same biological sample. Metaethical compensation of spectral overlap could only be effective to a certain degree. Mass cytometry is advantageous compared to flow cytometry but is pricey and requires highly skilled operators. 

Extracellular Vesicles (EVs), including exosomes and microvesicles, are nanometer-sized membranous vesicles that can carry different types of cargos, such as proteins, nucleic acids and metabolites. EVs are produced and released by most cell types. They act as biological mediators for intercellular communication via delivery of their cargos. This unique ability spurred translational research interest for targeted delivery of therapeutic molecules to treat a wide range of diseases. EVs also contain interesting information of their specific cellular origin.

Human papillomavirus (HPV) has been associated with the cause of several cancer types, including cervical, anal, and head and neck cancers. There has been great success in preventing HPV infections with the development of prophylactic HPV vaccines, Gardasil and Cervarix. However, these vaccines have only been shown to prevent HPV infection and not treat those already infected with HPV. These vaccines elicit antibody responses to late HPV genes, and thus would not be effective in treating established tumors.

Patients with chemotherapy-refractory, diffuse large B-cell lymphoma (DLBCL) have poor prognoses. CD19 and CD20 are promising targets for the treatment of B-Cell malignancies. However, despite the initial promising results from anti-CD19 CAR therapy, only 30-35% of patients with DLBCL achieve remissions lasting longer than 2-3 years after anti-CD19 CAR T-cell therapy. Relapse and non-response are likely due to diminished CD19 expression after anti-CD19 therapy and low expression of CD19 in some lymphomas. 

Measuring and mapping nervous tissue microstructure noninvasively is a long sought-after goal in neuroscience. Clinically, several neuropathologies such as cancer and stroke, are associated with changes in tissue microstructure. Diffusion tensor imaging (DTI), which models diffusion anisotropy, is an ideal imaging modality to elucidate these changes. However, DTI provides a mean diffusion tensor averaged over the entire MRI voxel. This has limitations when applied to heterogeneous neural tissue.

Immunotherapy is a cutting-edge new category of treatment that aims to harness and, in some cases, modify the patient’s own immune cells to improve their ability to cure diseases. It can be an effective approach for a variety of conditions, ranging from cancer to inflammatory diseases.  However, a number of obstacles to the overall success of immunotherapy still exist.  For example, reactivity against a target antigen can be attenuated or the lifespan of the “modified” immune cells can be too short.