The Single Cell World’s Post

💡 As I dive into the world of single-cell analysis, I’ve noticed ongoing confusion between inferring cellular function from gene expression data and directly measuring it. While sequencing technologies offer valuable insights into gene activity, they don’t fully capture the spectrum of functional outcomes at the single cell level. Most single cell readouts focus on genomic or transcriptomic data, meaning that cellular function is often inferred rather than directly measured. This reliance on indirect data requires additional secondary screens, adding complexity and extends time to an already lengthy discovery process. Directly measuring cellular function such as biomolecule secretion, cell-cell interactions, and cytotoxicity, would provide crucial insights on the complexity of cell heterogeneity. Regardless of the therapeutic modality, whether cell therapy, checkpoint inhibitor, or antibody-based treatments, all these rely on modulating cellular functions to achieve their therapeutic effects. Therefore, cellular function is a critical parameter for evaluating the effectiveness of therapies in preclinical studies as early on as possible. Could incorporating direct functional assessments at the single cell level be a game-changer for researchers and industry scientists in the next wave of therapeutic development and discoveries?