This week in MathOnco 206
Tumor heterogeneity, lineage tracing, growth models, radiotherapy, markov chain models, and more.
“This week in Mathematical Oncology” — Apr. 21, 2022
From the editor:
Thanks for opening this week’s edition of the mathematical oncology newsletter. This week you’ll find tumor heterogeneity, lineage tracing, growth models, radiotherapy, markov chain models, and more.
Quantifying Tumor Heterogeneity via MRI Habitats to Characterize Microenvironmental Alterations in HER2+ Breast Cancer
Anum S. Kazerouni, David A. Hormuth II, Tessa Davis, Meghan J. Bloom, Sarah Mounho, Gibraan Rahman, John Virostko, Thomas E. Yankeelov, Anna G. Sorace
Lineage tracing in human tissues
Calum Gabbutt, Nicholas A Wright, Ann Marie Baker, Darryl Shibata, Trevor A Graham
Computational Model of Heterogeneity in Melanoma: Designing Therapies and Predicting Outcomes
Arran Hodgkinson, Dumitru Trucu, Matthieu Lacroix, Laurent Le Cam, Ovidiu Radulescu
Comparison of classical tumour growth models for patient derived and cell-line derived xenografts using the nonlinear mixed-effects framework
Dimitrios Voulgarelis, Krishna C. Bulusu, James W. T. Yates
Somatic mutation: What shapes the mutational landscape of normal epithelia?
Joanna C. Fowler, Philip H. Jones
Assessing the importance of resistance, persistence and hyper-mutation for antibiotic treatment success with stochastic modelling
Christopher Witzany, Roland R. Regoes, Claudia Igler
Markov chains improve the significance computation of overlapping genome annotations
Askar Gafurov, Broňa Brejová, Paul Medvedev
Allopatric divergence of cooperators confers cheating resistance and limits the effects of a defector mutation
Kaitlin A. Schaal, Yuen-Tsu Nicco Yu, Marie Vasse, Gregory J. Velicer
Mathematical models of tumor volume dynamics in response to radiotherapy
Nuverah Mohsin, Heiko Enderling, Renee Brady-Nicholls, Mohammad U. Zahid
Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumor cells
Darshak K. Bhatt, Thijs Janzen, Toos Daemen, Franz J. Weissing
Mapping phenotypic heterogeneity in melanoma onto the epithelial-hybrid-mesenchymal axis
Maalavika Pillai, Gouri Rajaram, Pradipti Thakur, Nilay Agarwal, Srinath Muralidharan, Ankita Ray, Jason A Somarelli, Mohit Kumar Jolly
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Caption: In our recent paper, we employed quantitative MRI to characterize intra- and inter-tumoral heterogeneity in a murine model of HER2+ breast cancer. This artwork pairs our in vivo and ex vivo measurements, showing MRI-derived tumor subregions (i.e., habitats) alongside immunofluorescence images of the same lesion. Using MRI data acquired prior to treatment, we identified whole-tumor phenotypes that exhibited differential response to treatments, suggesting that baseline phenotypes can predict therapy response.
Created by: Anum Kazerouni
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