Related Experiment Video For DSB formation
Updated: Jun 6, 2025

Immunofluorescence Microscopy of γH2AX and 53BP1 for Analyzing the Formation and Repair of DNA Double-strand Breaks
Published on: November 3, 2017
Heterogeneous Formation of DNA Double-Strand Breaks and Cell-Free DNA in Leukemia T-Cell Line and Human Peripheral
Christian Linke1,2, Thilo von Hänisch1, Julia Schröder1
1Department of Hematology and Oncology, Center for Translational Medicine, University Hospital Brandenburg, Brandenburg Medical School Theodor Fontane, 14770 Brandenburg an der Havel, Germany.
Background:
Improving precision medicine in chemotherapy requires highly sensitive and easily applicable diagnostic tools. In addition, non-invasive molecular real-time monitoring of cytotoxic response is highly desirable. Here, we employed the kinetics of DNA double-strand breaks (DSB) and cell-free DNA (cfDNA) in a cell model of topoisomerase II-inhibitors in T cell leukemia (Jurkat cells) compared to normal cells (peripheral blood mononuclear cells, PBMCs).
Methods:
We applied automated microscopy to quantify immuno-stained phosphorylated H2AX (γH2AX) as a marker for either DNA damage response (DDR) or cell death and quantitative PCR-based analysis of nuclear and mitochondrial cfDNA concentrations.
Results:
Jurkat cells displayed a DDR to cytotoxic drug treatment significantly earlier than PBMCs, and etoposide (ETP) induced DSB formation faster than doxorubicin (DOX) in both Jurkat and PBMCs. Jurkat cells exhibited an earlier cytotoxic response compared to PBMC, with a significantly increased mitochondrial cfDNA formation after 2 h of DOX application. In PBMCs, increased cell death was detected after 4 h of incubation with ETP, whereas DOX treatment was less effective.
Conclusions:
Both automated microscopy and mitochondrial cfDNA quantification analysis indicate that (malignant) Jurkat cells are more sensitive to DOX than (healthy) PBMC. Our real-time approach can improve DDR inducing drug selection and adaptation in cancer therapy and aids in decisions for optimal patient biosampling.
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