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Tomaszewski, M. R.

Publications and source records attributed to Tomaszewski, M. R..

3 recordsLinked to original sources

Cycling hypoxia selects for constitutive HIF stabilization

Tumors experience temporal and spatial fluctuations in oxygenation. Hypoxia inducible transcription factors (HIF-) in tumor cells are stabilized in response to low levels of oxygen and induce angiogenesis to re-supply oxygen. HIF- stabilization is typically facultative, induced by hypoxia and reduced by normoxia. In some cancers, however, HIF- stabilization becomes constitutive even under normoxia, a condition known as pseudohypoxia. Herein, we develop a mathematical model that predicts the effects of fluctuating levels of oxygen availability on stabilization of HIF- and its client proteins based on fitness. The model shows that facultative regulation of HIF- always promotes greater cell fitness than constitutive regulation. However, cell fitness is nearly identical regardless of HIF- regulation strategy when there are rapid periodic fluctuations in oxygenation. Furthermore, the model predicts that stochastic changes in oxygenation favor facultative HIF- regulation. We conclude that rapid and regular cycling of oxygenation levels selects for pseudohypoxia.

cancer biology

Targeting hypoxic habitats with hypoxia pro-drug evofosfamide in preclinical models of sarcoma

Hypoxic regions (habitats) within tumors are heterogeneously distributed and can be widely variant. Hypoxic habitats are generally pan-therapy resistant. For this reason, hypoxia-activated prodrugs (HAPs) have been developed to target these resistant volumes. The HAP evofosfamide (TH-302) has shown promise in preclinical and early clinical trials of sarcoma. However, in a phase III clinical trial, TH-302 did not improve survival in combination with doxorubicin (dox), most likely due to a lack of patient stratification based on hypoxic status. Herein, our goal was to develop deep-learning (DL) models to identify hypoxic habitats, using multiparametric (mp) MRI and co-registered histology, and to non-invasively monitor response to TH-302 in a patient-derived xenograft (PDX) of rhabdomyosarcoma and a syngeneic model of fibrosarcoma (RIF-1). A DL convolutional neural network showed strong correlations (>0.81) between the true hypoxic portion in histology and the predicted hypoxic portion in multiparametric MRI. TH-302 monotherapy or in combination with Dox delayed tumor growth and increased survival in the hypoxic PDX model (p<0.05), but not in the RIF-1 model, which had lower volume of hypoxic habitats. Control studies showed that RIF-1 resistance was due to hypoxia and not to other causes. Notably, PDX tumors developed resistance to TH-302 under prolonged treatment. In conclusion, response to TH-302 can be attributed to differences in hypoxia status prior therapy. Development of non-invasive MR imaging to assess hypoxia is crucial in determining the effectiveness of TH-302 therapy and to follow response. In further studies, our approach can be used to better plan therapeutic schedules to avoid resistance. One Sentence SummaryDevelopment of non-invasive MR imaging to assess hypoxia is crucial in determining the effectiveness of TH-302 therapy and to follow response.

cancer biology

T2 heterogeneity provides a sensitive measure of early tumor response to radiotherapy

PurposeExternal beam radiotherapy (XRT) is a widely used cancer treatment, yet responses vary dramatically between patients. These differences are not accounted for in clinical practice, in part due to a lack of sensitive biomarkers of early response. In this work, we test the hypothesis that quantification of intratumor heterogeneity is a sensitive and robust biomarker of early response to XRT. A novel Magnetic Resonance Imaging (MRI) approach is proposed, utilizing histogram analysis of clinically-used T2 relaxation measurements to assess early changes in the tumor heterogeneity following irradiation in murine models of pancreatic cancer, indicative of radiotherapy response. Methods and MaterialsDynamic Magnetic Resonance T2 relaxation imaging was performed every 72h following 10 Gy dose XRT in two murine models of pancreatic cancer. Proposed biomarker of radiotherapy response was compared with tumor growth kinetics, and biological validation was performed through quantitative histology analysis. ResultsQuantification of tumor T2 interquartile range (IQR) as a measure of histogram width showed excellent sensitivity for detection of XRT-induced tumor changes as early as 72h after treatment, outperforming whole tumor T2 and Diffusion weighted MRI metrics. This response was observed both in quantitative T2 maps and in T2-weighted images that are routine in clinical practice. Histological comparison revealed the T2 IQR provides a measure of spatial heterogeneity in tumor cell density, related to radiation-induced necrosis. The early IQR changes were found to presage subsequent tumor volume changes in two distinct pancreatic models, suggesting promise for treatment response prediction. The metric showed excellent test-retest robustness. ConclusionsOur preclinical findings indicate that spatial heterogeneity analysis of T2 MRI can provide a sensitive and readily translatable method for early radiotherapy response assessment in pancreatic cancer. We propose that this will be useful in adaptive radiotherapy, specifically in MRI-guided treatment paradigms.

biophysics