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

> mathematical-oncology.org

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.

Jeffrey West
jeffrey.west@moffitt.org

1. 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

2. Lineage tracing in human tissues
   Calum Gabbutt, Nicholas A Wright, Ann Marie Baker, Darryl Shibata, Trevor A Graham

3. Computational Model of Heterogeneity in Melanoma: Designing Therapies and Predicting Outcomes
   Arran Hodgkinson, Dumitru Trucu, Matthieu Lacroix, Laurent Le Cam, Ovidiu Radulescu

4. 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

5. Somatic mutation: What shapes the mutational landscape of normal epithelia?
   Joanna C. Fowler, Philip H. Jones

1. Assessing the importance of resistance, persistence and hyper-mutation for antibiotic treatment success with stochastic modelling
   Christopher Witzany, Roland R. Regoes, Claudia Igler

2. Markov chains improve the significance computation of overlapping genome annotations
   Askar Gafurov, Broňa Brejová, Paul Medvedev

3. 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

4. Mathematical models of tumor volume dynamics in response to radiotherapy
   Nuverah Mohsin, Heiko Enderling, Renee Brady-Nicholls, Mohammad U. Zahid

5. 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

6. 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

1. Mathematical Oncology - Seminar Series

   mathematical-oncology.com/seminars
   “Are you aware of our seminars page? This is a curated list of relevant mathematical oncology seminar series. Click through to watch previously recorded seminars, or sign up for future alerts. Please let us know if you’d like to add a series to the list.”

The newsletter now has a dedicated homepage where we post the cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group.

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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