This week in MathOnco 271

Adaptive therapy, evolutionary dynamics, oncolytic virus therapy, clonal fitness, and more

“This week in Mathematical Oncology” — October 5, 2023

> mathematical-oncology.org

From the editor:

This week we have articles on adaptive therapy, evolutionary dynamics, oncolytic virus therapy, clonal fitness, and more…

Enjoy,

Jeffrey West
jeffrey.west@moffitt.org

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1. Treatment of evolving cancers will require dynamic decision support
   Maximilian Strobl, Jill Gallaher, Mark Robertson-Tessi, Jeffrey West, Alexander RA Anderson

2. cloneRate: fast estimation of single-cell clonal dynamics using coalescent theory
   Brian Johnson, Yubo Shuai, Jason Schweinsberg, Kit Curtius

3. Optimal Treatment of Prostate Cancer Based on State Constraint
   Wenhui Luo, Xuewen Tan, Xiufen Zou, Qing Tan

4. Investigation of evolutionary dynamics for drug resistance in 3D spheroid model system using cellular barcoding technology
   Gizem Damla Yalcin, Kubra Celikbas Yilmaz, Tugce Dilber, Ahmet Acar

5. Tumour Growth Mechanisms Determine Effectiveness of Adaptive Therapy in Glandular Tumours
   Rui Zhen Tan

6. Mathematical Modeling of Oncolytic Virus Therapy Reveals Role of the Immune Response
   Ela Guo, Hana M. Dobrovolny

1. Patient-specific computational forecasting of prostate cancer growth during active surveillance using an imaging-informed biomechanistic model
   Guillermo Lorenzo, Jon S. Heiselman, Michael A. Liss, Michael I. Miga, Hector Gomez, Thomas E. Yankeelov, Alessandro Reali, Thomas J. R. Hughes

2. A resource-based mechanistic framework for castration-resistant prostate cancer (CRPC)
   B. Vibishan, B.V. Harshavardhan, Sutirth Dey

3. Clonal fitness decline in somatic differentiation hierarchies
   Iftikhar Ahmed, David Dingli, Weini Huang, Benjamin Werner

4. Mitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion
   Irina Kareva, Jana Gevertz

5. A new universal system of tree shape indices
   Robert Noble, Kimberley Verity

1. Tumor heterogeneity impairs immunogenicity in mismatch repair deficient tumors
   James L. Reading, Deborah R. Caswell & Charles Swanton

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. This week’s artwork:

Based on the paper: The shape of cancer relapse: Topological data analysis predicts recurrence in paediatric acute lymphoblastic leukaemia published in PLoS Computational Biology

Artist: Salvador Chulián (@SalvadorChulian)

Caption: Does blood have a shape?”. We consider the Shape of Cancer Relapse: using bone marrow samples from acute lymphoblastic leukemia (ALL) patients, we use methods from topological data analysis (TDA), which quantifies shapes in data, to predict known outcomes at the time of diagnosis. Given that ALL therapy fails in approximately 20% of these patients, we were able to distinguish isolated data islands and empty spaces in the immunophenotypic space of CD10, CD20, CD38 and CD45. In the light of TDA analyses and machine learning, we reduced the four-dimensional shape characteristics, and were able to perform high-accuracy predictions of relapse in children and adolescents with ALL. This work also covers the issue August 2023 in PLoS Computational Biology.

Visit the mathematical oncology page to view jobs, meetings, and special issues. We will post new additions here, but the full list can found at mathematical-oncology.org.

1. Jobs

• Postdoctoral Research Scientist in Deconstructing organisational principles of tumour microenvironments through spatial data analysis and computational modelling (Dr Xiao Fu; CRUK Beatson Institute, Glasgow Scotland)

2. Conferences / Meetings

• Computational models of life: From molecular biology to digital twins

3. Special issues

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