This week in MathOnco 209
4 dimensional spheroids, bayesian inference, math models of leukemia, senescence, somatic evolution, and more...
“This week in Mathematical Oncology” — May 12, 2022
> mathematical-oncology.org
From the editor:
This week’s issue is a long one! 4 dimensional spheroids, bayesian inference, math models of leukemia, senescence, somatic evolution, and more. Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
A stochastic mathematical model of 4D tumour spheroids with real-time fluorescent cell cycle labelling
Jonah J. Klowss, Alexander P. Browning, Ryan J. Murphy, Elliot J. Carr, Michael J. Plank, Gency Gunasingh, Nikolas K. Haass† and Matthew J. SimpsonMathematical models of leukaemia and its treatment: a review
S. Chulián, Á. Martínez-Rubio, M. Rosa, V. M. Pérez-GarcíaBayesian inference using Hamiltonian Monte-Carlo algorithm for nonlinear joint modeling in the context of cancer immunotherapy
Marion Kerioui, Francois Mercier, Julie Bertrand, Coralie Tardivon, René Bruno, Jérémie Guedj, Solène DesméeTumor Growth Inhibition-Overall Survival (TGI-OS) Model for Subgroup Analysis Based on Post-Randomization Factors: Application for Anti-drug Antibody (ADA) Subgroup Analysis of Atezolizumab in the IMpower150 Study
Kenta Yoshida, Phyllis Chan, Mathilde Marchand, Rong Zhang, Benjamin Wu, Marcus Ballinger, Nitzan Sternheim, Jin Y. Jin & René BrunoAssociation Between Tumor Size Kinetics and Survival in Patients With Urothelial Carcinoma Treated With Atezolizumab: Implication for Patient Follow-Up
Coralie Tardivon, Solène Desmée, Marion Kerioui, René Bruno, Benjamin Wu, France Mentré, François Mercier, Jérémie GuedjSenescent cell turnover slows with age providing an explanation for the Gompertz law
Omer Karin, Amit Agrawal, Ziv Porat, Valery Krizhanovsky, Uri AlonThe Structure of Optimal Protocols for a Mathematical Model of Chemotherapy with Antiangiogenic Effects
Urszula Ledzewicz, Heinz SchättlerTumor microenvironment as a metapopulation model: the effects of angiogenesis, emigration and treatment modalities
Anni S. Halkola, Tero Aittokallio, Kalle ParvinenTumour immunotherapy: lessons from predator–prey theory
Phineas T. Hamilton, Bradley R. Anholt, Brad H. NelsonThe translational challenges of precision oncology
Oriol Pich, Chris Bailey, Thomas B.K. Watkins, Simone Zaccaria, Mariam Jamal-Hanjani, Charles SwantonData-rich spatial profiling of cancer tissue: Astronomy informs Pathology
Alexander S. Szalay, Janis M. Taube
A Simulator for Somatic Evolution Study Design
Arjun Srivatsa, Haoyun Lei, Russell SchwartzA combined experimental-computational approach uncovers a role for the Golgi matrix protein Giantin in breast cancer progression
Salim Ghannoum, Damiano Fantini, Muhammad Zahoor, Veronika Reiterer, …, Lina Prasmickaite, Gunhild Mari Mælandsmo, Alvaro Köhn-Luque, Hesso Farhan
2022 PhysiCell workshop & hackathon
”PhysiCell is an open source agent-based framework for simulating cells as they live and interact in dynamical environments. It has been used extensively to study cancer biology, immunology, and other complex multicellular systems. Paul Macklin is running a virtual workshop and hackathon to teach PhysiCell July 24-30. Participants will learn to build agent-based models, integrate intracellular models in each cell agent, and visualize results. Sessions will also introduce a new modeling language to accelerate work. Morning tutorial sessions are available without participation limit, while up to 30 applicants will be accepted for a mentored hackathon. Targeted funding is available to increase diversity, equity, and inclusion. For best consideration, apply by May 31st at https://www.github.com/PhysiCell-Training/ws2022.”Scientist or artist? How I realized I don’t have to choose
Science Careers
Asma Bashir: And now, if someone asks me whether I’m more of a scientist or an artist, I very proudly say, “Both.”
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: This artwork shows the growth of spheroids at four timepoints, representing work from our recently published paper in the Journal of the Royal Society Interface. Each spheroid image is composed of two halves: in vitro experimental images (upper half above white line); and simulations of our new individual-based model (lower half below white line). Colours in the images represent cell-cycle status, with G1 phase (red), eS phase (yellow), and S/G2/M phase (green). Images at later times show spheroids with an outer proliferative region, an intermediate region dominated by G1-arrested cells, and a necrotic core. In our work, we take advantage of real-time fluorescent cell cycle imaging to identify the cycling status and position of individual cells to develop the first stochastic individual-based model (IBM) of a 4D tumour spheroid. Our study shows that simulations of our IBM are consistent with experimental data for a human melanoma cell line. The IBM also allows us to extract quantitative information that is difficult to estimate experimentally, such as nutrient availability within the spheroid.
Created by: Jonah J. Klowss, Ryan J. Murphy & Matthew J. Simpson
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PhD fellow position in mathematical health and disease modeling, Roskilde University (Morten Andersen) - Deadline: 5/7/2022
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