CellPrint scientists are exploiting the single-cell resolution and high sensitivity of CellPrint™ to formulate novel insights about pathogenesis and to advance drug discovery and development. An important element of these efforts is the quantitative assessment of changes in molecular expression induced by therapeutic agents. A study on the effect of the experimental cancer drug ABT-263 (Navitoclax) on molecular expression in CD19+ B cells illustrates the strengths of the platform. In this study, CellPrint™ was used to assess the effect of ABT-263 on the expression of 25 molecules from apoptotic and signaling pathways.
Results for three particular analytes in representative clinical samples are shown in the figure below. CellPrint scientists discerned the existence of a rare cell population (marked by red arrows) comprising 1-3% of the treated B cells in which the expression of the three analytes was unaffected by treatment with ABT-263. In contrast, they determined that expression of the three analytes in the main B cell population decreased markedly after treatment. The unique capabilities illustrated in this study, to precisely assess the effect of therapeutic agents on molecular expression and to distinguish cellular populations based on differences in responses, illustrate important features of the CellPrint™ platform that are being leveraged to advance drug discovery and development.
• This figure shows the expression level of three analytes in CD19+ B cells from representative clinical samples. For illustrative purposes these results were selected from a study of 25 molecules in clinical samples from 29 healthy persons.
• Each axis reflects analytes expression as measured by median fluorescence ratio. Each data point represents a single B cell.
• Red arrows mark a rare B cell population that was revealed by CellPrint™. Expression of the three molecules in this rare population was unaffected by treatment with ABT-263.
For the purposes of distinguishing cell populations based on the expression of multiple molecules that are known or suspected of involvement in a biological process, CellPrint scientists are using a statistical method known as principle component analysis (PCA) in concert with uniquely precise assessments from the CellPrint™ platform. This approach provides a signature of molecular expression for a defined cell population and has numerous uses in advancing drug discovery and development including: unraveling the pathogenesis of complex diseases, identifying disease subtypes, stratifying patients for optimizing therapy, predicting responsiveness to specific medications, predicting disease progression, and diagnosing diseases that do not yet have well understood biomarkers.
CellPrint scientists applied this approach using the expression data for all 25 molecules and 29 cell donors from the study described above and generated molecular expression signatures for three CD19+ B cell populations: untreated, treated / main population, and treated / rare population. As shown in the figure below, the signature for untreated cells (each blue data point representing one of the cell donors) shows minimal overlap with the signature of treated cells from the main population (each orange data point representing one of the cell donors), indicating a profound change in the expression of the 25 molecules after treatment with ABT-263. However, the signature for untreated cells shows almost complete overlap with the signature of treated cells from the rare population (each green data point representing one of the cell donors), indicating minimal change in molecular expression after treatment.
Example: Use of CellPrint™ in Concert with Principle Component Analysis (PCA) to Distinguish Cellular Populations
• This figure shows the application CellPrint™ in concert with principle component analysis (PCA) to generate signatures of molecular expression for cell populations. The study examined the effect of ABT-263 on the expression of 25 molecules in CD19+ B cells from 29 healthy cell donors.
• Each data point represents differentially treated groups (i.e., untreated, treated / main population, or treated / rare population) from one healthy donor.