Comparison of DNA damage biomarker dynamics after induced DNA damage : Study of DNA damage biomarker expression and dynamics in cancer cells
Forsten, Sofia (2022-05-02)
Comparison of DNA damage biomarker dynamics after induced DNA damage : Study of DNA damage biomarker expression and dynamics in cancer cells
(02.05.2022)
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Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2022053141040
https://urn.fi/URN:NBN:fi-fe2022053141040
Tiivistelmä
To ensure genomic integrity and protect cells from a variety of DNA damaging agents, cells have developed a complex network called the DNA damage response (DDR). It monitors and ensures DNA integrity by coordinating DNA repair and activating cell cycle arrest to allow enough time for the repair. Loss-of function mutations of DNA repair factors can cause genetic disorders and increase susceptibility to cancer.
Cancer treatment with chemotherapeutic agents is based on the accumulation of DNA damage in cells, ultimately leading to cell death. Targeting the DNA damage response mechanisms by inhibiting specific proteins responsible for the DNA repair provides a more targeted treatment for specific cancer types. Currently there are four PARP inhibitors approved for the treatment of breast, ovarian and prostate cancer with BRCA1/2 or ATM mutations. PARP inhibitors exploit the concept of synthetic lethality where cancer cells with the mutations rely on certain DNA repair pathways for survival. Despite the efficacy of PARP inhibitors, resistance to them has been described. This implies the need for new treatments, but also for better prognostic, diagnostic and pharmacodynamic biomarkers that could predict patient sensitivity to PARP inhibitors or to other targeted treatments.
For this study, five proteins that are involved in DNA double strand break (DSB) repair were chosen to be compared. The aim of this study was to compare the dynamics and expression of gamma-H2AX (phosphorylated yH2AX), phosphorylated replication protein A (pRPA), phosphorylated Kruppel-associated box (KRAB)3-associated protein 1 (pKAP1), tumor suppressor P53-binding protein 1 (53BP1) and DNA repair protein RAD51 homolog (RAD51), and to find the best biomarker among them and the best analysis method to be used in drug discovery purposes.
The dynamics and expression of the biomarkers were studied by inducing DNA DSBs with mitomycin C in DLD-1 parental and DLD-1 BRCA2 knockout (KO) cells. The dynamics of each marker was also studied and compared after treating cells with PARP and ATR inhibitors. The spatiotemporal dynamics of these five markers was studied using fluorescence imaging and changes in protein levels were studied with Western blot.
These results indicate that there were differences between the markers in different conditions. To decide which of the markers was the best biomarker depended on the goal of the assay. To only determine the amount of DNA damage, yH2AX foci and 53BP1 foci number could be applied. If working with high concentrations of damaging agents then the increase in nuclear intensity in yH2AX, pRPA and pKAP1 signal could be used. RAD51 foci formation would be optimal for screening responsive cell lines to specific treatments or when analyzing the HR status of the cells.
To conclude, the results suggest that these proteins can be used as DNA damage biomarkers, but their wider use would still require further optimization. Depending on the goal, different marker and different analysis method will be optimal. Additionally, other cell lines should be added to the study to observe whether these results could be applied generally.
Cancer treatment with chemotherapeutic agents is based on the accumulation of DNA damage in cells, ultimately leading to cell death. Targeting the DNA damage response mechanisms by inhibiting specific proteins responsible for the DNA repair provides a more targeted treatment for specific cancer types. Currently there are four PARP inhibitors approved for the treatment of breast, ovarian and prostate cancer with BRCA1/2 or ATM mutations. PARP inhibitors exploit the concept of synthetic lethality where cancer cells with the mutations rely on certain DNA repair pathways for survival. Despite the efficacy of PARP inhibitors, resistance to them has been described. This implies the need for new treatments, but also for better prognostic, diagnostic and pharmacodynamic biomarkers that could predict patient sensitivity to PARP inhibitors or to other targeted treatments.
For this study, five proteins that are involved in DNA double strand break (DSB) repair were chosen to be compared. The aim of this study was to compare the dynamics and expression of gamma-H2AX (phosphorylated yH2AX), phosphorylated replication protein A (pRPA), phosphorylated Kruppel-associated box (KRAB)3-associated protein 1 (pKAP1), tumor suppressor P53-binding protein 1 (53BP1) and DNA repair protein RAD51 homolog (RAD51), and to find the best biomarker among them and the best analysis method to be used in drug discovery purposes.
The dynamics and expression of the biomarkers were studied by inducing DNA DSBs with mitomycin C in DLD-1 parental and DLD-1 BRCA2 knockout (KO) cells. The dynamics of each marker was also studied and compared after treating cells with PARP and ATR inhibitors. The spatiotemporal dynamics of these five markers was studied using fluorescence imaging and changes in protein levels were studied with Western blot.
These results indicate that there were differences between the markers in different conditions. To decide which of the markers was the best biomarker depended on the goal of the assay. To only determine the amount of DNA damage, yH2AX foci and 53BP1 foci number could be applied. If working with high concentrations of damaging agents then the increase in nuclear intensity in yH2AX, pRPA and pKAP1 signal could be used. RAD51 foci formation would be optimal for screening responsive cell lines to specific treatments or when analyzing the HR status of the cells.
To conclude, the results suggest that these proteins can be used as DNA damage biomarkers, but their wider use would still require further optimization. Depending on the goal, different marker and different analysis method will be optimal. Additionally, other cell lines should be added to the study to observe whether these results could be applied generally.