Is there a relationship between repopulation and hypoxia/reoxygenation? Results from human carcinoma of the cervix

Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices

PURPOSE

Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images.

METHODS

We propose a macroscale model of tumor evolution based on three dynamics, namely active portion, necrotic portion, and oxygenation. The model parameters were assessed on the volume size of seven cervical cancer patients administered with 28 fractions of intensity modulated radiation therapy (IMRT) (1.8 Gy/fraction). For each patient, five Doppler ultrasound tests were acquired before, during, and after the treatment. The lesion was manually contoured by an expert physician using 4D View^® (General Electric Company - Fairfield, Connecticut, United States), which automatically provided the overall tumor volume size along with three vascularization and/or blood flow indices. Volume data only were fed to the model for training purpose, while the predicted oxygenation was compared a posteriori to the measured Doppler indices.

RESULTS

The model was able to fit the tumor volume evolution within 8% error (range: 3-8%). A strong correlation between the intrapatient longitudinal indices from Doppler measurements and oxygen predicted by the model (about 90% or above) was found in three cases. Two patients showed an average correlation value (50-70%) and the remaining two presented poor correlations. The latter patients were the ones featuring the smallest tumor reduction throughout the treatment, typical of hypoxic conditions. Moreover, the average oxygenation value predicted by the model was close to the average vascularization-flow index (average difference: 7%).

CONCLUSIONS

The results suggest that the modeled relation between tumor evolution and oxygen dynamics was reasonable enough to provide realistic oxygenation curves in five cases (correlation greater than 50%) out of seven. In case of nonresponsive tumors, the model failed in predicting the oxygenation trend while succeeded in reproducing the average oxygenation value according to the mean vascularization-flow index. Despite the need for deeper investigations, the outcomes of the present work support the hypothesis that a simple macroscale model of tumor response to radiotherapy is able to predict the tumor oxygenation. The possibility of an objective and quantitative validation on imaging data discloses the possibility to translate them as decision support tools in clinical practice and to move a step forward in the treatment personalization.

Kinetic Models for Predicting Cervical Cancer Response to Radiation Therapy on Individual Basis Using Tumor Regression Measured In Vivo With Volumetric Imaging

This article describes a macroscopic mathematical modeling approach to capture the interplay between solid tumor evolution and cell damage during radiotherapy. Volume regression profiles of 15 patients with uterine cervical cancer were reconstructed from serial cone-beam computed tomography data sets, acquired for image-guided radiotherapy, and used for model parameter learning by means of a genetic-based optimization. Patients, diagnosed with either squamous cell carcinoma or adenocarcinoma, underwent different treatment modalities (image-guided radiotherapy and image-guided chemo-radiotherapy). The mean volume at the beginning of radiotherapy and the end of radiotherapy was on average 23.7 cm(3) (range: 12.7-44.4 cm(3)) and 8.6 cm(3) (range: 3.6-17.1 cm(3)), respectively. Two different tumor dynamics were taken into account in the model: the viable (active) and the necrotic cancer cells. However, according to the results of a preliminary volume regression analysis, we assumed a short dead cell resolving time and the model was simplified to the active tumor volume. Model learning was performed both on the complete patient cohort (cohort-based model learning) and on each single patient (patient-specific model learning). The fitting results (mean error: ∼ 16% and ∼ 6% for the cohort-based model and patient-specific model, respectively) highlighted the model ability to quantitatively reproduce tumor regression. Volume prediction errors of about 18% on average were obtained using cohort-based model computed on all but 1 patient at a time (leave-one-out technique). Finally, a sensitivity analysis was performed and the data uncertainty effects evaluated by simulating an average volume perturbation of about 1.5 cm(3) obtaining an error increase within 0.2%. In conclusion, we showed that simple time-continuous models can represent tumor regression curves both on a patient cohort and patient-specific basis; this discloses the opportunity in the future to exploit such models to predict how changes in the treatment schedule (number of fractions, doses, intervals among fractions) might affect the tumor regression on an individual basis.

Modeling the Interplay Between Tumor Volume Regression and Oxygenation in Uterine Cervical Cancer During Radiotherapy Treatment

This paper describes a patient-specific mathematical model to predict the evolution of uterine cervical tumors at a macroscopic scale, during fractionated external radiotherapy. The model provides estimates of tumor regrowth and dead-cell reabsorption, incorporating the interplay between tumor regression rate and radiosensitivity, as a function of the tumor oxygenation level. Model parameters were estimated by minimizing the difference between predicted and measured tumor volumes, these latter being obtained from a set of 154 serial cone-beam computed tomography scans acquired on 16 patients along the course of the therapy. The model stratified patients according to two different estimated dynamics of dead-cell removal and to the predicted initial value of the tumor oxygenation. The comparison with a simpler model demonstrated an improvement in fitting properties of this approach (fitting error average value <5%, p < 0.01), especially in case of tumor late responses, which can hardly be handled by models entailing a constant radiosensitivity, failing to model changes from initial severe hypoxia to aerobic conditions during the treatment course. The model predictive capabilities suggest the need of clustering patients accounting for cancer cell line, tumor staging, as well as microenvironment conditions (e.g., oxygenation level).

Onset time of tumor repopulation for cervical cancer: first evidence from clinical data

PURPOSE

Accelerated tumor repopulation has significant implications in low-dose rate (LDR) brachytherapy. Repopulation onset time remains undetermined for cervical cancer. The purpose of this study was to determine the onset time of accelerated repopulation in cervical cancer, using clinical data.

METHODS AND MATERIALS

The linear quadratic (LQ) model extended for tumor repopulation was used to analyze clinical data and magnetic resonance imaging-based three-dimensional tumor volumetric regression data from 80 cervical cancer patients who received external beam radiotherapy (EBRT) and LDR brachytherapy. The LDR dose was converted to EBRT dose in 1.8-Gy fractions by using the LQ formula, and the total dose ranged from 61.4 to 99.7 Gy. Patients were divided into 11 groups according to total dose and treatment time. The tumor control probability (TCP) was calculated for each group. The least χ(2) method was used to fit the TCP data with two free parameters: onset time (T(k)) of accelerated repopulation and number of clonogens (K), while other LQ model parameters were adopted from the literature, due to the limited patient data.

RESULTS

Among the 11 patient groups, TCP varied from 33% to 100% as a function of radiation dose and overall treatment time. Higher dose and shorter treatment duration were associated with higher TCP. Using the LQ model, we achieved the best fit with onset time T(k) of 19 days and K of 139, with uncertainty ranges of (11, 22) days for T(k) and (48, 1822) for K, respectively.

CONCLUSION

This is the first report of accelerated repopulation onset time in cervical cancer, derived directly from clinical data by using the LQ model. Our study verifies the fact that accelerated repopulation does exist in cervical cancer and has a relatively short onset time. Dose escalation may be required to compensate for the effects of tumor repopulation if the radiation therapy course is protracted.

Predicting outcomes in cervical cancer: a kinetic model of tumor regression during radiation therapy

Applications of mathematical modeling can improve outcome predictions of cancer therapy. Here we present a kinetic model incorporating effects of radiosensitivity, tumor repopulation, and dead-cell resolving on the analysis of tumor volume regression data of 80 cervical cancer patients (stages 1B2-IVA) who underwent radiation therapy. Regression rates and derived model parameters correlated significantly with clinical outcome (P < 0.001; median follow-up: 6.2 years). The 6-year local tumor control rate was 87% versus 54% using radiosensitivity (2-Gy surviving fraction S(2) < 0.70 vs. S(2) > or = 0.70) as a predictor (P = 0.001) and 89% vs. 57% using dead-cell resolving time (T(1/2) < 22 days versus T(1/2) > or = 22 days, P < 0.001). The 6-year disease-specific survival was 73% versus 41% with S(2) < 0.70 versus S(2) > or = 0.70 (P = 0.025), and 87% vs. 52% with T(1/2) < 22 days versus T(1/2) > or = 22 days (P = 0.002). Our approach illustrates the promise of volume-based tumor response modeling to improve early outcome predictions that can be used to enable personalized adaptive therapy.

Differentiation status of human squamous cell carcinoma xenografts does not appear to correlate with the repopulation capacity of clonogenic tumour cells during fractionated irradiation

PURPOSE

To investigate the magnitude and kinetics of repopulation in a moderately well differentiated UT-SCC-14 human squamous cell carcinoma [hSCC] in nude mice. This question is of interest because clinical data indicate a higher repopulation capacity in those SCC that have preserved characteristics of differentiation, which appears to be in contrast to results on FaDu and GL hSCC previously reported from this laboratory.

METHODS AND MATERIALS

UT-SCC-14 tumours were transplanted subcutaneously into the right hind leg of NMRI nu/nu mice. Fractionated radiation treatments were delivered, either under clamped hypoxia at 5.4 Gy/fraction or under ambient conditions (consistent with an OER of 2.7). Tumours were irradiated every day, every 2nd day, or every 3rd day with 6, 12 or 18 fractions. 1, 2 or 3 days after the last fraction, graded top-up-doses under clamped conditions were given for the purpose of estimating the 50% tumour control dose (TCD50). A total of 22 TCD50 assays were performed and analysed using maximum likelihood techniques.

RESULTS

The data demonstrate a slow but significant repopulation of clonogenic cells during fractionated irradiation of UT-SCC-14 hSCC. The results under hypoxic conditions are consistent with a constant repopulation rate, with a clonogenic doubling time (Tclon) of 15.6 days (95% CI: 9.7, 21.4). This contrasts with ambient conditions where Tclon was 68.5 days (95% CI: 124, 161). Both Tclon values are longer than the 6-day volume doubling time of untreated tumours.

CONCLUSIONS

Less pronounced repopulation for irradiation under ambient compared to clamped hypoxic conditions might be explained by preferential survival of hypoxic and therefore non-proliferating clonogenic cells. Taken together with previous studies on poorly differentiated FaDu and moderately well differentiated GL hSCC, the results are consistent with considerable variability in the magnitude and kinetics of repopulation in different experimental squamous cell carcinomas, and with a relationship between reoxygenation and repopulation during fractionated irradiation. The differentiation status of hSCC growing in nude mice does not to appear to correlate with the proliferative capacity of clonogenic tumour cells during treatment. The results do not support the hypothesis gained from clinical data of higher repopulation in well-differentiated tumours.

Effect of reoxygenation on the hypoxia-induced up-regulation of serine protease inhibitor PAI-1 in head and neck cancer cells

In squamous cell carcinoma of the head and neck (SCCHN), hypoxia is considered a crucial physiological modulator for malignant progression, wherebythe plasminogen activation system is involved in overlapping functions such as moulding of the extracellular matrix, cell proliferation and signal transduction. Little is known about the effects of reoxygenation on the plasminogen activation system in SCCHN cells. Three human SCCHN cell lines (BHY, CAL27, FaDu) and a non-transformed human fibroblast cell line (VH7) were exposed to hypoxic (<0.5% O(2)) conditions for up to 72 h and subsequently reoxygenated at normoxic conditions for 24 h. Urokinase-type plasminogen activator (uPA) and plasminogen activator inhibitor-1 (PAI-1) protein concentration and former protein activity were determined by ELISA and complex ELISA, respectively. Reoxygenation induced significant changes in cell-associated and secreted PAI-1 protein compared to the normoxic control. Significant increase in cell-associated and secreted uPA protein after reoxygenation was only observed for some of the cell lines. Determination of uPA-PAI-1 complex formation revealed the release of active protein into the cell supernatant. The beneficial role of reoxygenation during radiation therapy is widely accepted. However, reoxygenation does not seem to counteract the effects induced by hypoxia on the plasminogen activation system. Fatally irradiated reoxygenat- ed tumour cells might still produce sufficient amounts of 'harmful' protein and thus initiate a path for invasion and metastasis for surviving tumour cells.

Cell kinetics

Cell kinetic concepts have pervaded radiation therapy since the early part of the 20th century and have been instrumental in the development of modern radiotherapy. In this review, the fundamental radiobiological concepts that have been developed based on cell kinetic knowledge will be revisited and discussed in the context of contemporary radiation therapy. This will include how the proliferation characteristics, variation in sensitivity during the cell cycle and the extent of radiation-induced cell cycle delay translate into a variable time for the expression of damage, how cell kinetics interacts with hypoxia and how the response to fractionated radiation schedules is influenced by cell kinetics in terms of repair, redistribution, reoxygenation and repopulation. The promise of combining radiation with new biologically targeted agents and the potential of non-invasive positron emission tomography imaging of proliferation are areas where cell kinetics will continue to influence radiotherapy practice.

Comparison between pimonidazole binding, oxygen electrode measurements, and expression of endogenous hypoxia markers in cancer of the uterine cervix

BACKGROUND

Although tumor hypoxia has been associated with a more aggressive phenotype and lower cure rate, there is no consensus as to the method best suited for routine measurement. Binding of the chemical hypoxia marker, pimonidazole, and expression of the endogenous hypoxia markers HIF-1alpha and CAIX were compared for their ability to detect hypoxia in tumor biopsies from 67 patients with advanced carcinoma of the cervix.

METHODS

Two biopsies were taken one day after administration of pimonidazole and were analyzed for pimonidazole binding using flow cytometry or immunohistochemistry. CAIX and HIF-1alpha expression and degree of colocalization were measured in sequential antibody-stained sections. Patient subsets were examined for tumor oxygen tension using an Eppendorf electrode, S phase DNA content, or change in HIF-1alpha expression over the course of treatment.

RESULTS

Approximately 6% of the tumor area stained positive for pimonidazole, HIF-1alpha, or CAIX. The CAIX positive fraction correlated with the pimonidazole positive fraction (r = 0.60). Weaker but significant correlations were observed between pimonidazole and HIF-1alpha (r = 0.31) and CAIX and HIF-1alpha (r = 0.41). Taking the extent of marker colocalization into consideration increased the confidence that all markers were identifying hypoxic regions. Over 65% of stained areas showed a high degree of colocalization with the other markers. Oxygen microelectrode measurements and S phase fraction were not correlated with the hypoxic fraction measured using the three hypoxia markers. HIF-1alpha levels tended to decrease with time after the start of therapy.

CONCLUSIONS

Endogenous hypoxia marker binding shows reasonable agreement, in extent and location, with binding of pimonidazole. CAIX staining pattern is a better match to the pimonidazole staining pattern than is HIF-1alpha, and high CAIX expression in the absence (or low levels) of HIF-1alpha may indicate a different biology.

Dose escalation to combat hypoxia in prostate cancer: a radiobiological study on clinical data

Earlier studies have demonstrated that hypoxic regions exist in human prostate cancer and the degree of hypoxia correlates with the treatment outcome of radiotherapy. Using the concept of the clinical oxygen enhancement ratio (COER), the linear-quadratic (LQ) model was extended to account for the effect of tumour hypoxia. The clinical data collected at the Fox Chase Cancer Center for prostate cancer were analysed based on the LQ model as well as the tumour control probability (TCP) model. The LQ and TCP parameters (alpha = 0.15 Gy (-1), alpha/beta = 3.1 Gy and the number of clonogens K = 10(6) approximately 10(7) cells) determined in earlier studies were used to derive the COER for prostate cancer: COER = 1.4 with a standard confidence interval (CI) of (1.2, 1.8). The result is consistent with the in vitro OER measurements of human tumour cell lines under chronic hypoxia conditions. This implies that a higher dose is needed to overcome tumour hypoxia. For prostate tumours, the prescription dose required to overcome tumour hypoxia is 165 Gy (CI: 153 approximately 186 Gy) for permanent 125I implants and 88 Gy (CI: 74 approximately 118 Gy) in 2 Gy fractions for external-beam radiotherapy. The impact of LQ parameters on the calculations of COER and dose escalation was discussed. This study provides a preliminary estimate of the dose escalation needed to overcome tumour hypoxia based on clinical data. More clinical data with better statistics and longer follow-up time are required to further tune the radiobiological modelling of hypoxia for prostate cancer.

Changes in the tumor microenvironment during low-dose-rate permanent seed implantation iodine-125 brachytherapy

PURPOSE

There is a lack of data regarding how the tumor microenvironment (e.g., perfusion and oxygen partial pressure [pO2]) changes in response to low-dose-rate (LDR) brachytherapy. This may be why some clinical issues remain unresolved, such as the appropriate use of adjuvant external beam radiation therapy (EBRT). The purpose of this work was to obtain some basic preclinical data on how the tumor microenvironment evolves in response to LDR brachytherapy.

METHODS AND MATERIALS

In an experimental mouse tumor, pO2 (measured by electron paramagnetic resonance) and perfusion (measured by dynamic contrast-enhanced magnetic resonance imaging) were monitored as a function of time (0-6 days) and distance (0-2 mm and 2-4 mm) from an implanted 0.5 mCi iodine-125 brachytherapy seed.

RESULTS

For most of the experiments, including controls, tumors remained hypoxic at all times. At distances of 2-4 mm from radioactive seeds ( approximately 1.5 Gy/day), however, there was an early, significant increase in pO2 within 24 h. The pO2 in that region remained elevated through Day 3. Additionally, the perfusion in that region was significantly higher than for controls starting at Day 3.

CONCLUSION

It may be advantageous to give adjuvant EBRT shortly (approximately 1 to 2 days) after commencement of clinical LDR brachytherapy, when the pO2 in the spatial regions between seeds should be elevated. If chemotherapy is given adjuvantly, it may best be administered just a little later (approximately 3 or 4 days) after the start of LDR brachytherapy, when perfusion should be elevated.