Limits...
The Role of Oxygen in Avascular Tumor Growth.

Grimes DR, Kannan P, McIntyre A, Kavanagh A, Siddiky A, Wigfield S, Harris A, Partridge M - PLoS ONE (2016)

Bottom Line: These describe the basic rate of growth well, but do not offer an explicitly mechanistic explanation.The model is fitted to growth curves for a range of cell lines and derived values of OCR are validated using clinical measurement.Finally, we illustrate how changes in OCR due to gemcitabine treatment can be directly inferred using this model.

View Article: PubMed Central - PubMed

Affiliation: Cancer Research UK/MRC Oxford Institute for Radiation Oncology, Gray Laboratories, University of Oxford, Old Road Campus, Oxford, OX3 7DQ, United Kingdom.

ABSTRACT
The oxygen status of a tumor has significant clinical implications for treatment prognosis, with well-oxygenated subvolumes responding markedly better to radiotherapy than poorly supplied regions. Oxygen is essential for tumor growth, yet estimation of local oxygen distribution can be difficult to ascertain in situ, due to chaotic patterns of vasculature. It is possible to avoid this confounding influence by using avascular tumor models, such as tumor spheroids, a much better approximation of realistic tumor dynamics than monolayers, where oxygen supply can be described by diffusion alone. Similar to in situ tumours, spheroids exhibit an approximately sigmoidal growth curve, often approximated and fitted by logistic and Gompertzian sigmoid functions. These describe the basic rate of growth well, but do not offer an explicitly mechanistic explanation. This work examines the oxygen dynamics of spheroids and demonstrates that this growth can be derived mechanistically with cellular doubling time and oxygen consumption rate (OCR) being key parameters. The model is fitted to growth curves for a range of cell lines and derived values of OCR are validated using clinical measurement. Finally, we illustrate how changes in OCR due to gemcitabine treatment can be directly inferred using this model.

No MeSH data available.


Related in: MedlinePlus

Theoretical best fits for (a) MDA-MB-231 (b) U-87 and (c) Hamster V-79 spheroids.Data for the V-79 cells is from previously published investigations by Freyer [4] and standard errors are not shown on this plot. (d) SCC-25. While best fits are shown in this figure, there are several possible combinations of diffusion limit (rl) and doubling time (td) that produce similarly high co-efficients of determination so these results may not be uniquely determined.
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pone.0153692.g003: Theoretical best fits for (a) MDA-MB-231 (b) U-87 and (c) Hamster V-79 spheroids.Data for the V-79 cells is from previously published investigations by Freyer [4] and standard errors are not shown on this plot. (d) SCC-25. While best fits are shown in this figure, there are several possible combinations of diffusion limit (rl) and doubling time (td) that produce similarly high co-efficients of determination so these results may not be uniquely determined.

Mentions: Theoretically derived growth curves were fit to experimental data for a range of cells lines, and from the best fit parameters used to estimate OCR a and average cellular doubling time td. This analysis imposes a constraint condition on the data ofG=log2VmaxVmin,(13)where Vmax is the maximum spheroid volume at the end of the growth period and Vmin the initial volume at t = 0. For model fitting purposes, the condition G ≥ 2 ensures that a least two cell doubling times of td have transpired and avoids over-fitting. Such a consideration ruled out the use of certain cell lines such as T-47D (ductal carcinoma) as volume increases were too small for analysis over the growth period. Growth curves were fitted for three distinct cell lines; MDA-MB-231 Breast adenocarcinoma, U-87 Glioblastoma, and SCC-25 squamous cell carcinoma. Fits were also obtained on previously published data by Freyer [4, 17] for V-79 hamster fibroblast cells. This data was selected as it is relatively long range (60 days) and plateau effects can be readily observed. Fig 3 shows the ideal theoretical fits for these curves which yields the greatest co-efficient of determination, indicating that the model fits the data extremely well. Error bars on the time axis are a day to capture uncertainty on exact time which growth curves were measured on a daily basis. It is important to note however that doubling time td and diffusion limit are degenerate parameters and there exist a considerable range of parameters which will yield similar fits. This degeneracy is explored further in the discussion.


The Role of Oxygen in Avascular Tumor Growth.

Grimes DR, Kannan P, McIntyre A, Kavanagh A, Siddiky A, Wigfield S, Harris A, Partridge M - PLoS ONE (2016)

Theoretical best fits for (a) MDA-MB-231 (b) U-87 and (c) Hamster V-79 spheroids.Data for the V-79 cells is from previously published investigations by Freyer [4] and standard errors are not shown on this plot. (d) SCC-25. While best fits are shown in this figure, there are several possible combinations of diffusion limit (rl) and doubling time (td) that produce similarly high co-efficients of determination so these results may not be uniquely determined.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835055&req=5

pone.0153692.g003: Theoretical best fits for (a) MDA-MB-231 (b) U-87 and (c) Hamster V-79 spheroids.Data for the V-79 cells is from previously published investigations by Freyer [4] and standard errors are not shown on this plot. (d) SCC-25. While best fits are shown in this figure, there are several possible combinations of diffusion limit (rl) and doubling time (td) that produce similarly high co-efficients of determination so these results may not be uniquely determined.
Mentions: Theoretically derived growth curves were fit to experimental data for a range of cells lines, and from the best fit parameters used to estimate OCR a and average cellular doubling time td. This analysis imposes a constraint condition on the data ofG=log2VmaxVmin,(13)where Vmax is the maximum spheroid volume at the end of the growth period and Vmin the initial volume at t = 0. For model fitting purposes, the condition G ≥ 2 ensures that a least two cell doubling times of td have transpired and avoids over-fitting. Such a consideration ruled out the use of certain cell lines such as T-47D (ductal carcinoma) as volume increases were too small for analysis over the growth period. Growth curves were fitted for three distinct cell lines; MDA-MB-231 Breast adenocarcinoma, U-87 Glioblastoma, and SCC-25 squamous cell carcinoma. Fits were also obtained on previously published data by Freyer [4, 17] for V-79 hamster fibroblast cells. This data was selected as it is relatively long range (60 days) and plateau effects can be readily observed. Fig 3 shows the ideal theoretical fits for these curves which yields the greatest co-efficient of determination, indicating that the model fits the data extremely well. Error bars on the time axis are a day to capture uncertainty on exact time which growth curves were measured on a daily basis. It is important to note however that doubling time td and diffusion limit are degenerate parameters and there exist a considerable range of parameters which will yield similar fits. This degeneracy is explored further in the discussion.

Bottom Line: These describe the basic rate of growth well, but do not offer an explicitly mechanistic explanation.The model is fitted to growth curves for a range of cell lines and derived values of OCR are validated using clinical measurement.Finally, we illustrate how changes in OCR due to gemcitabine treatment can be directly inferred using this model.

View Article: PubMed Central - PubMed

Affiliation: Cancer Research UK/MRC Oxford Institute for Radiation Oncology, Gray Laboratories, University of Oxford, Old Road Campus, Oxford, OX3 7DQ, United Kingdom.

ABSTRACT
The oxygen status of a tumor has significant clinical implications for treatment prognosis, with well-oxygenated subvolumes responding markedly better to radiotherapy than poorly supplied regions. Oxygen is essential for tumor growth, yet estimation of local oxygen distribution can be difficult to ascertain in situ, due to chaotic patterns of vasculature. It is possible to avoid this confounding influence by using avascular tumor models, such as tumor spheroids, a much better approximation of realistic tumor dynamics than monolayers, where oxygen supply can be described by diffusion alone. Similar to in situ tumours, spheroids exhibit an approximately sigmoidal growth curve, often approximated and fitted by logistic and Gompertzian sigmoid functions. These describe the basic rate of growth well, but do not offer an explicitly mechanistic explanation. This work examines the oxygen dynamics of spheroids and demonstrates that this growth can be derived mechanistically with cellular doubling time and oxygen consumption rate (OCR) being key parameters. The model is fitted to growth curves for a range of cell lines and derived values of OCR are validated using clinical measurement. Finally, we illustrate how changes in OCR due to gemcitabine treatment can be directly inferred using this model.

No MeSH data available.


Related in: MedlinePlus