BackgroundThe CRISPR/Cas9 technology is nowadays a common tool for genome editing to achieve new insights into, for example, diagnostics and therapeutics in cancer and genetic disorders. Cell proliferation and anticancer drug response studies are widely used to evaluate the impact of editing. However, these assays are often time‐consuming, expensive, and reproducibility is an issue. To overcome this, we developed a fast and cheap assay that combines a fully automated multispectral fluorescence microscopy platform with a nuclei staining and open‐source software analysis.MethodsHere, we generated different LEDGF/p75 model cell lines to validate the effect on proliferation and chemosensitivity. Therefore, a fast protocol for an optimized all‐in‐one attempt for cytotoxicity screenings and proliferation analysis of adherent cells in a 96‐well plate format was established using differential staining with two fluorescent dyes (Hoechst 33342 and propidium iodide) for live/dead cell discrimination. Subsequently, an automated cell nuclei count and analysis were performed using bioimage informatics.ResultsWith the new established assay technology, up to 50,000 cells/well can be detected and analyzed in a 96‐well plate, resulting in a fast and accurate verification of viability and proliferation with consistency of 98% compared to manual counting. Our screening revealed that LEDGF depletion using CRISPR/Cas9 showed a diminished proliferation and chemosensitivity independent of cell line origin. Moreover, LEDGF depletion caused a significant increase in 𝛾H2AX foci, indicating a substantial increase in DNA double strand breaks. LEDGF/p75 overexpression enhanced proliferation and chemoresistance underlining the role of LEDGF in DNA damage response.ConclusionIndependent of cancer cell type, LEDGF/p75 is a central player in DNA damage repair and is implicated in chemoresistance. Moreover, our automated fluorescence biosensor technology allowed fast and reliable data acquisition without any fixation or additional washing steps. Additionally, data analysis was implemented using the modular open‐source software that can be adapted as needed.