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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. 

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.

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.

Cancer immunotherapy approaches, such as adoptive cell transfer (ACT), proved effective against many cancer types. Yet, post-treatment analyses of ACT have suggested that efficacy may be enhanced by increasing the percentage of neoantigen-reactive T cells in the infused product. Neoantigens are new proteins that form on cancer cells when certain mutations occur in tumor DNA. Current techniques for identifying neoantigen-specific TCRs in T cell expression are labor-intensive, time-consuming and technically challenging.

Advanced colorectal carcinoma is currently incurable, and new therapies are urgently needed. Ephrin (Eph) receptors are a clinically relevant class of receptor tyrosine kinases. Related signaling pathways are associated with oncogenesis of a number of cancers. NCI investigators found that phosphotyrosine-dependent Eph receptor signaling sustains colorectal carcinoma cell survival, thereby uncovering a survival pathway active in colorectal carcinoma cells.

The Transforming Growth Factor Beta (TGF-ß) ligands (i.e., TGF-ß1, -ß2, -ß3) are key regulatory proteins in animal physiology. Disruption of normal TGF-ß signaling is associated with many diseases from cancer to fibrosis. In mice and humans, TGF-ß activates TGF-ß receptors (e.g., TGFBR1), which activates SMAD proteins that alter gene expression and contribute to tumorigenesis.  Reliable animal models are essential for the study of TGF-ß signaling.

Cytokines are a broad category of intercellular signaling proteins that are critical for intercellular communication in human health and disease. However, systematic profiling of cytokine signaling activities has remained challenging due to the short half-lives of cytokines, and the pleiotropic functions and redundancy of cytokine activities within specific cellular contexts.

The use of tumor transcriptomics for precision oncology has made significant advances, mainly by identifying cancer driver genes or actionable mutations for treatment with targeted therapies.  However, this strategy misses out on broader genetic interactions that could reveal additional biologically testable biomarkers for therapy response prediction and inform the selection of more effective drugs for targeted treatment.

The development of precision medicine approaches for DLBCL (Diffuse Large B Cell Lymphoma) is complicated by its genetic, phenotypic and clinical heterogeneity. Current classification methods do not fully explain the observed differences in clinical outcomes to current chemotherapy and targeted therapy. Therefore, better analytical methods to classify and predict DLBCL patients’ treatment response are needed.

The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect tumor growth and clinical outcome. Recent studies using fluorescence-activated cell sorting (FACS) and single-cell RNA sequencing (RNAseq) to elucidate tissue composition and cell-cell interactions in the TME led to improved biomarkers of patient response and new treatment opportunities. However, the use of FACS is limited to simultaneously measuring the expression of a few protein markers, whereas the use of single-cell RNAseq has been limited due to cost and scarcity of fresh tumor biopsies.