Study of clustered damage in DNA after proton irradiation based on density-based spatial clustering of applications with noise algorithm_Journal of Biomedical Engineering

Authors：

TANG Jing ¹ , ZHANG Pengcheng ¹ , XIAO Qinfeng ¹ , LI Jie ² ,  GUI Zhiguo ¹

1. Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Taiyuan 030051, P.R.China;
2. Department of Radiation Oncology, Shanxi Provincial Cancer Hospital, Taiyuan 030013, P.R.China;

Corresponding author：

GUI Zhiguo, Email: gzgtg@163.com

Keywords：

density-based spatial clustering of applications with noise algorithm; probability and statistics; Monte Carlo track structure method; indirect damage; clustered DNA damage

DOI：

10.7507/1001-5515.201812008

Video：

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The deoxyribonucleic acid (DNA) molecule damage simulations with an atom level geometric model use the traversal algorithm that has the disadvantages of quite time-consuming, slow convergence and high-performance computer requirement. Therefore, this work presents a density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm based on the spatial distributions of energy depositions and hydroxyl radicals (·OH). The algorithm with probability and statistics can quickly get the DNA strand break yields and help to study the variation pattern of the clustered DNA damage. Firstly, we simulated the transportation of protons and secondary particles through the nucleus, as well as the ionization and excitation of water molecules by using Geant4-DNA that is the Monte Carlo simulation toolkit for radiobiology, and got the distributions of energy depositions and hydroxyl radicals. Then we used the damage probability functions to get the spatial distribution dataset of DNA damage points in a simplified geometric model. The DBSCAN clustering algorithm based on damage points density was used to determine the single-strand break (SSB) yield and double-strand break (DSB) yield. Finally, we analyzed the DNA strand break yield variation trend with particle linear energy transfer (LET) and summarized the variation pattern of damage clusters. The simulation results show that the new algorithm has a faster simulation speed than the traversal algorithm and a good precision result. The simulation results have consistency when compared to other experiments and simulations. This work achieves more precise information on clustered DNA damage induced by proton radiation at the molecular level with high speed, so that it provides an essential and powerful research method for the study of radiation biological damage mechanism.

Citation： TANG Jing, ZHANG Pengcheng, XIAO Qinfeng, LI Jie, GUI Zhiguo. Study of clustered damage in DNA after proton irradiation based on density-based spatial clustering of applications with noise algorithm. Journal of Biomedical Engineering, 2019, 36(4): 633-642. doi: 10.7507/1001-5515.201812008 Copy

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2.	Nikjoo H, Emfietzoglou D, Liamsuwan T, et al. Radiation track, DNA damage and response-a review. Rep Prog Phys, 2016, 79(11): 116601.
3.	Friedland W, Dingfelder M, Kundrat P, et al. Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC. Mutation Research, 2011, 711(1-2): 28-40.
4.	Nikjoo H, Uehara S, Wilson W E, et al. Track structure in radiation biology: theory and applications. Int J Radiat Biol, 1998, 73(4): 355-364.
5.	Francis Z, Villagrasa C, Clairand I. Simulation of DNA damage clustering after proton irradiation using an adapted DBSCAN algorithm. Comput Methods Programs Biomed, 2011, 101(3): 265-270.
6.	Ester M, Kriegel H P, Sander J, et al. A density-based algorithm for discovering clusters in large spatial databases with noise//The Second International Conference on Knowledge Discovery and Data Mining. 1996: 226-231.
7.	Dos Santos M, Villagrasa C, Clairand I A. Influence of the DNA density on the number of clustered damages created by protons of different energies. Nucl Instrum Methods Phys Res B, 2013, 298: 47-54.
8.	Leloup C, Garty G, Assaf G, et al. Evaluation of lesion clustering in irradiated plasmid DNA. Int J Radiat Biol, 2005, 81(1): 41-54.
9.	de Nardo L, Colautti P, Grosswendt B. Simulation of the measured ionisation-cluster distributions of alpha-particles in nanometric volumes of propane. Radiation Protection Dosimetry, 2006, 122(1-4): 427-431.
10.	Grosswendt B, Pszona S. The track structure of alpha-particles from the point of view of ionization-cluster formation in " nanometric” volumes of nitrogen. Radiat Environ Biophys, 2002, 41(2): 91-102.
11.	Kreipl M S, Friedland W, Paretzke H G. Time-and space-resolved Monte Carlo study of water radiolysis for photon, electron and ion irradiation. Radiat Environ Biophys, 2009, 48(1): 11.
12.	Karamitros M, Luan S, Bernal M A, et al. Diffusion-controlled reactions modeling in Geant4-DNA. J Comput Phys, 2014, 274: 841-882.
13.	Ballarini F, Biaggi M, Merzagora M, et al. Stochastic aspects and uncertainties in the prechemical and chemical stages of electron tracks in liquid water: a quantitative analysis based on Monte Carlo simulations. Radiat Environ Biophys, 2000, 39(3): 179-188.
14.	Milligan J R, Aguilera J A, Ward J F. Variation of single-strand break yield with scavenger concentration for plasmid DNA irradiated in aqueous solution. Radiat Res, 1993, 133(2): 151-157.
15.	Nikjoo H, O'neill P, Terrissol M, et al. Quantitative modelling of DNA damage using Monte Carlo track structure method. Radiat Environ Biophys, 1999, 38(1): 31-38.
16.	Francis Z, Stypczynska A. Clustering algorithms in radiobiology and DNA damage quantification. Data Security, Data Mining and Data Management: Technologies and Challenges, Nova Science Pub Inc, 2013.
17.	Meylan S, Incerti S, Karamitros M, et al. Simulation of early DNA damage after the irradiation of a fibroblast cell nucleus using Geant4-DNA. Sci Rep, 2017, 7(1): 11923.
18.	Nygren J, Ljungman M, Ahnstrom G. Chromatin structure and radiation-induced DNA strand breaks in human-cells-soluble scavengers and DNA-bound proteins offer a better protection against single-strand than double-strand breaks. Int J Radiat Biol, 1995, 68(1): 11-18.
19.	Friedland W, Jacob P, Bernhardt P, et al. Simulation of DNA damage after proton irradiation. Radiat Res, 2003, 159(3): 401-410.
20.	Friedland W, Schmitt E, Kundrát P, et al. Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping. Sci Rep, 2017, 7: 45161.
21.	Lampe N, Karamitros M, Breton V, et al. Mechanistic DNA damage simulations in Geant4-DNA part 1: a parameter study in a simplified geometry. Phys Med, 2018, 48: 135-145.
22.	Lampe N, Karamitros M, Breton V, et al. Mechanistic DNA damage simulations in Geant4-DNA part 2: electron and proton damage in a bacterial cell. Phys Med, 2018, 48: 146-155.
23.	de la Fuente Rosales L, Incerti S, Francis Z, et al. Accounting for radiation-induced indirect damage on DNA with the Geant 4-DNA code. Phys Medica, 2018, 51: 108-116.
24.	Balasubramanian B, Pogozelski W K, Tullius T D. DNA strand breaking by the hydroxyl radical is governed by the accessible surface areas of the hydrogen atoms of the DNA backbone. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95(17): 9738-9743.
25.	Nikjoo H, O'neill P, Wilson W E, et al. Computational approach for determining the spectrum of DNA damage induced by ionizing radiation. Radiat Res, 2001, 156(5): 577-583.
26.	Goodhead D T, Brenner D J. Estimation of a single property of low LET radiations which correlates with biological effectiveness. Phys Med Biol, 1983, 28(5): 485-492.
27.	Goodhead D T, Nikjoo H. Track structure analysis of ultrasoft X-rays compared to high- and low-LET radiations. Int J Radiat Biol, 1989, 55(4): 513-529.
28.	Nikjoo H, Goodhead D T, Charlton D E, et al. Energy deposition in small cylindrical targets by monoenergetic electrons. Int J Radiat Biol, 1991, 60(5): 739-756.
29.	Incerti S, Kyriakou I, Bernal M A, et al. Geant4‐DNA example applications for track structure simulations in liquid water: a report from the Geant4‐DNA project. Med Phys, 2018, 45(8): e722-e739.
30.	Bernal M A, Bordage M C, Brown J, et al. Track structure modeling in liquid water: a review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit. Phys Med, 2015, 31(8): 861-874.
31.	Incerti S, Ivanchenko A, Karamitros M, et al. Comparison of Geant4 very low energy cross section models with experimental data in water. Med Phys, 2010, 37(9): 4692-4708.
32.	Incerti S, Baldacchino G, Bernal M, et al. The geant4-DNA project. Int J Model Simul Sci Comput, 2010, 1(02): 157-178.
33.	Peukert D, Incerti S, Kempson I, et al. Validation and investigation of reactive species yields of Geant4‐DNA chemistry models. Med Phys, 2019, 46: 983-998.
34.	Nikjoo, O'neill P, Goodhead D T, et al. Computational modelling of low-energy electron-induced DNA damage by early physical and chemical events. Int J Radiat Biol, 1997, 71(5): 467-483.
35.	Valota A, Ballarini F, Friedland W, et al. Modelling study on the protective role of OH radical scavengers and DNA higher-order structures in induction of single- and double-strand break by gamma-radiation. Int J Radiat Biol, 2003, 79(8): 643-653.
36.	Prise K M. A review of dsb induction data for varying quality radiations. Int J Radiat Biol, 1998, 74(2): 173-184.

1. Kuzin A M. On the role of DNA in the radiation damage of the cell. Int J Radiat Biol, 1963, 6(3): 201-209.
2. Nikjoo H, Emfietzoglou D, Liamsuwan T, et al. Radiation track, DNA damage and response-a review. Rep Prog Phys, 2016, 79(11): 116601.
3. Friedland W, Dingfelder M, Kundrat P, et al. Track structures, DNA targets and radiation effects in the biophysical Monte Carlo simulation code PARTRAC. Mutation Research, 2011, 711(1-2): 28-40.
4. Nikjoo H, Uehara S, Wilson W E, et al. Track structure in radiation biology: theory and applications. Int J Radiat Biol, 1998, 73(4): 355-364.
5. Francis Z, Villagrasa C, Clairand I. Simulation of DNA damage clustering after proton irradiation using an adapted DBSCAN algorithm. Comput Methods Programs Biomed, 2011, 101(3): 265-270.
6. Ester M, Kriegel H P, Sander J, et al. A density-based algorithm for discovering clusters in large spatial databases with noise//The Second International Conference on Knowledge Discovery and Data Mining. 1996: 226-231.
7. Dos Santos M, Villagrasa C, Clairand I A. Influence of the DNA density on the number of clustered damages created by protons of different energies. Nucl Instrum Methods Phys Res B, 2013, 298: 47-54.
8. Leloup C, Garty G, Assaf G, et al. Evaluation of lesion clustering in irradiated plasmid DNA. Int J Radiat Biol, 2005, 81(1): 41-54.
9. de Nardo L, Colautti P, Grosswendt B. Simulation of the measured ionisation-cluster distributions of alpha-particles in nanometric volumes of propane. Radiation Protection Dosimetry, 2006, 122(1-4): 427-431.
10. Grosswendt B, Pszona S. The track structure of alpha-particles from the point of view of ionization-cluster formation in " nanometric” volumes of nitrogen. Radiat Environ Biophys, 2002, 41(2): 91-102.
11. Kreipl M S, Friedland W, Paretzke H G. Time-and space-resolved Monte Carlo study of water radiolysis for photon, electron and ion irradiation. Radiat Environ Biophys, 2009, 48(1): 11.
12. Karamitros M, Luan S, Bernal M A, et al. Diffusion-controlled reactions modeling in Geant4-DNA. J Comput Phys, 2014, 274: 841-882.
13. Ballarini F, Biaggi M, Merzagora M, et al. Stochastic aspects and uncertainties in the prechemical and chemical stages of electron tracks in liquid water: a quantitative analysis based on Monte Carlo simulations. Radiat Environ Biophys, 2000, 39(3): 179-188.
14. Milligan J R, Aguilera J A, Ward J F. Variation of single-strand break yield with scavenger concentration for plasmid DNA irradiated in aqueous solution. Radiat Res, 1993, 133(2): 151-157.
15. Nikjoo H, O'neill P, Terrissol M, et al. Quantitative modelling of DNA damage using Monte Carlo track structure method. Radiat Environ Biophys, 1999, 38(1): 31-38.
16. Francis Z, Stypczynska A. Clustering algorithms in radiobiology and DNA damage quantification. Data Security, Data Mining and Data Management: Technologies and Challenges, Nova Science Pub Inc, 2013.
17. Meylan S, Incerti S, Karamitros M, et al. Simulation of early DNA damage after the irradiation of a fibroblast cell nucleus using Geant4-DNA. Sci Rep, 2017, 7(1): 11923.
18. Nygren J, Ljungman M, Ahnstrom G. Chromatin structure and radiation-induced DNA strand breaks in human-cells-soluble scavengers and DNA-bound proteins offer a better protection against single-strand than double-strand breaks. Int J Radiat Biol, 1995, 68(1): 11-18.
19. Friedland W, Jacob P, Bernhardt P, et al. Simulation of DNA damage after proton irradiation. Radiat Res, 2003, 159(3): 401-410.
20. Friedland W, Schmitt E, Kundrát P, et al. Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping. Sci Rep, 2017, 7: 45161.
21. Lampe N, Karamitros M, Breton V, et al. Mechanistic DNA damage simulations in Geant4-DNA part 1: a parameter study in a simplified geometry. Phys Med, 2018, 48: 135-145.
22. Lampe N, Karamitros M, Breton V, et al. Mechanistic DNA damage simulations in Geant4-DNA part 2: electron and proton damage in a bacterial cell. Phys Med, 2018, 48: 146-155.
23. de la Fuente Rosales L, Incerti S, Francis Z, et al. Accounting for radiation-induced indirect damage on DNA with the Geant 4-DNA code. Phys Medica, 2018, 51: 108-116.
24. Balasubramanian B, Pogozelski W K, Tullius T D. DNA strand breaking by the hydroxyl radical is governed by the accessible surface areas of the hydrogen atoms of the DNA backbone. Proceedings of the National Academy of Sciences of the United States of America, 1998, 95(17): 9738-9743.
25. Nikjoo H, O'neill P, Wilson W E, et al. Computational approach for determining the spectrum of DNA damage induced by ionizing radiation. Radiat Res, 2001, 156(5): 577-583.
26. Goodhead D T, Brenner D J. Estimation of a single property of low LET radiations which correlates with biological effectiveness. Phys Med Biol, 1983, 28(5): 485-492.
27. Goodhead D T, Nikjoo H. Track structure analysis of ultrasoft X-rays compared to high- and low-LET radiations. Int J Radiat Biol, 1989, 55(4): 513-529.
28. Nikjoo H, Goodhead D T, Charlton D E, et al. Energy deposition in small cylindrical targets by monoenergetic electrons. Int J Radiat Biol, 1991, 60(5): 739-756.
29. Incerti S, Kyriakou I, Bernal M A, et al. Geant4‐DNA example applications for track structure simulations in liquid water: a report from the Geant4‐DNA project. Med Phys, 2018, 45(8): e722-e739.
30. Bernal M A, Bordage M C, Brown J, et al. Track structure modeling in liquid water: a review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit. Phys Med, 2015, 31(8): 861-874.
31. Incerti S, Ivanchenko A, Karamitros M, et al. Comparison of Geant4 very low energy cross section models with experimental data in water. Med Phys, 2010, 37(9): 4692-4708.
32. Incerti S, Baldacchino G, Bernal M, et al. The geant4-DNA project. Int J Model Simul Sci Comput, 2010, 1(02): 157-178.
33. Peukert D, Incerti S, Kempson I, et al. Validation and investigation of reactive species yields of Geant4‐DNA chemistry models. Med Phys, 2019, 46: 983-998.
34. Nikjoo, O'neill P, Goodhead D T, et al. Computational modelling of low-energy electron-induced DNA damage by early physical and chemical events. Int J Radiat Biol, 1997, 71(5): 467-483.
35. Valota A, Ballarini F, Friedland W, et al. Modelling study on the protective role of OH radical scavengers and DNA higher-order structures in induction of single- and double-strand break by gamma-radiation. Int J Radiat Biol, 2003, 79(8): 643-653.
36. Prise K M. A review of dsb induction data for varying quality radiations. Int J Radiat Biol, 1998, 74(2): 173-184.

Journal of Biomedical Engineering

Study of clustered damage in DNA after proton irradiation based on density-based spatial clustering of applications with noise algorithm

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