Investigating the relative biological effectiveness of clinically relevant photon energies and the intrinsic radiosensitivity of human cancer cell lines towards biologically informed radiotherapy treatments
Bibliographic record
Abstract
With more than half of cancer patients undergoing ionizing radiation at some point in their treatment, radiotherapy stands as a crucial and fundamental modality in cancer management. Despite technological advancements, the difference in effectiveness between photon sources with variable energies remains inadequately characterized. Current standards, such as those recommended by the International Commission on Radiological Protection (ICRP), assign relative biological effectiveness (RBE) of unity to all photon sources, a simplification that overlooks significant biological variability. The biological response to radiation quality is also influenced by a cancer’s inherent sensitivity to radiation, influenced by its proficiency in recovering from the damage incurred by the ionizing radiation. Therefore, this thesis aims to characterize the variable RBE for clinically relevant photon sources and explores DNA repair capacity as a biomarker for intrinsic radiosensitivity in cancer cells.In the first part of this thesis, the RBE of clinically relevant high and low photon energies was characterized in vitro for three human cancer cell lines: HCT116 (colorectal), HeLa (cervical), and PC3 (prostate). Cells were irradiated using 6 MV x-rays from a linear accelerator, an 192Ir brachytherapy source, and 225 kVp and 50 kVp orthovoltage x-rays. Cell survival post-irradiation was assessed using clonogenic assays, and survival fractions were fitted using the linear quadratic model. Our findings revealed that cell-killing efficiency increased with decreasing photon energy. Using 225 kVp x-rays as the reference, the RBEs for HCT116 with 6 MV x-rays, 192Ir, and 50 kVp x-rays were 0.89 ± 0.03, 0.95 ± 0.03, and 1.24 ± 0.04, respectively. For HeLa, the RBEs were 0.95 ± 0.04, 0.97 ± 0.05, and 1.09 ± 0.03, and for PC3, the RBEs were 0.84 ± 0.01, 0.84 ± 0.01, and 1.13 ± 0.02, respectively. In the second part of the thesis, we measured the DNA repair kinetics following sublethal damage in four human cancer cell lines (HCT116, HT29, HeLa, and PC3) to investigate molecular mechanisms for variable cell survival further. Cells were subjected to split-dose irradiations of 4 Gy of 225 kVp x-rays delivered in 2 × 2 Gy fractions at varying time increments (0 - 10 hours) between fractions. Resultant survival fractions assessed with clonogenic assays were plotted as a function of inter-fraction time and fitted with the Lea-Catcheside modified linear-quadratic model. The estimated repair half-lives for the four cancer lines corroborate the surviving fraction at 2 Gy (SF2Gy) measured in our RBE studies, with HT29 being most radioresistant (Trepair = 64 ± 21 min), followed by HeLa (Trepair = 118 ± 61 min), PC3 (Trepair = 120 ± 18 min), and HCT116 (Trepair = 215 ± 87 min) being the most radiosensitive. An observed correlation between repair half-lives and SF2Gy lends a viable possibility for using DNA repair kinetics as a new biomarker for intrinsic radiosensitivity.This research highlights the need to consider photon energy-specific RBEs and DNA repair capacities in radiotherapy planning. By refining our understanding of these factors, we can enhance the precision of cancer treatments, improve therapeutic ratios, and ultimately achieve better patient outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".