High-Content and High-Throughput Clonogenic Survival Assay Using Fluorescence Barcoding

SIMPLE SUMMARY: The Clonogenic Survival Assay (CSA) is pivotal in gauging cell survival and proliferative capacity in oncology research. However, it’s limited by its binary output and its time- and labor-intensive nature. We developed LeGO-CSA, a refined version of CSA, utilizing imaging of cell nuclei tagged with fluorescent markers which encode red, green, blue fluorescent proteins and their variations. This facilitates both high-content and high-throughput analysis, delivering a potent tool for cancer research, promising heightened accuracy and efficiency, with the potential to expedite drug discovery and offer deeper insights into cellular dynamics in cancer. This transformative approach can revolutionize cancer research methodologies, making them more efficient and insightful. ABSTRACT: The Clonogenic Survival Assay (CSA) is a fundamental tool employed to assess cell survival and proliferative potential in cancer research. Despite its importance, CSA faces limitations, primarily its time- and labor-intensive nature and its binary output. To overcome these limitations and enhance CSA’s utility, several approaches have been developed, focusing on increasing the throughput. However, achieving both high-content and high-throughput analyses simultaneously has remained a challenge. In this paper, we introduce LeGO-CSA, an extension of the classical CSA that employs the imaging of cell nuclei barcoded with fluorescent lentiviral gene ontology markers, enabling both high-content and high-throughput analysis. To validate our approach, we contrasted it with results from a classical assay and conducted a proof-of-concept screen of small-molecule inhibitors targeting various pathways relevant to cancer treatment. Notably, our results indicate that the classical CSA may underestimate clonogenicity and unveil intriguing aspects of clonal cell growth. We demonstrate the potential of LeGO-CSA to offer a robust approach for assessing cell survival and proliferation with enhanced precision and throughput, with promising implications for accelerating drug discovery and contributing to a more comprehensive understanding of cellular behavior in cancer.