This week in MathOnco 170

Growth dynamics, glucose availability, invasive leader cells, cancer incidence, and more...

“This week in Mathematical Oncology” — Newsletter
> mathematical-oncology.org
July 15, 2021

From the editor:
> jeffrey.west@moffitt.org

Hello,

Today’s issue contains articles on growth dynamics, glucose availability, invasive leader cells, cancer incidence, and more... Be sure to scroll to the Resources section to see the recently posted conferences and jobs (a PhD with Noemi Picco). We are nearing 1000 subscribers (!). Stay tuned for an exciting celebration...

- Jeffrey West

  1. Phenotypic variation modulates the growth dynamics and response to radiotherapy of solid tumours under normoxia and hypoxia
    G.L. Celora, H.M. Byrne, C. E. Zois, P. G. Kevrekidis

  2. Decoding leader cells in collective cancer invasion
    Samuel A. Vilchez Mercedes, Federico Bocci, Herbert Levine, José N. Onuchic, Mohit Kumar Jolly, Pak Kin Wong

  3. Viewing Cancer Through the Lens of Corruption: Using Behavioral Ecology to Understand Cancer
    Anuraag Bukkuri, Frederick Adler

  4. Emulating control arms for cancer clinical trials using external cohorts created from electronic health record-derived real world data
    Katherine Tan, Jonathan Bryan, Brian Segal, Lawrence Bellomo, Nate Nussbaum, Melisa Tucker, Aracelis Z. Torres, Carrie Bennette, William Capra, Melissa Curtis, Rebecca A. Miksad

  5. An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines
    Jianchen Yang, Jack Virostko, David A. Hormuth II, Junyan Liu, Amy Brock, Jeanne Kowalski, Thomas E. Yankeelov

  6. Dynamic behavior of prostate cancer cells under antitumor immunity and pulse vaccination in a random environment
    Huan Yang, Yuanshun Tan

  1. Discovering cancer driver genes and pathways using stochastic block model graph neural networks
    Viola Fanfani, Ramon Vinas Torne, Pietro Lio, Giovanni Stracquadanio

  2. Approximation of the age distribution of cancer incidence using a mutational model
    Alexandr N. Tetearing

The newsletter now has a dedicated homepage (thisweekmathonco.substack.com), which allows us to post cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group. Today’s submission was contributed by Giulia Celora:

Caption: In our recent work, we have developed a mathematical model to study how phenotypic heterogeneity affects tumour’s response to radiotherapy. In our model, a cell’s phenotype is described as a continuous variable ranging from stem-like resistant cells (red) to fully-differentiated sensitive cells (blue). Further, a cell phenotype is not static but rather changes in response to local oxygen levels. Our cover illustrates the effect of different oxygen dynamics on the evolution of tumour’s composition and size (white curve) during treatment (left: one dose; right: two doses). In the top row, oxygen levels remain high so that surviving cells transition from a stem-like (red) to a differentiated (blue) state after each radiation dose. In the bottom row, instead, radiation-induced damage of blood vessels results in transient exposure to low oxygen levels. Importantly, we see that now surviving cells maintain stem-like features making a second radiation dose less effective than in the well-oxygenated scenario. Overall, our results suggest that the interplay between oxygen and cell adaption might be key to understanding tumour dynamics in the absence and presence of treatment. Learn more about our work and how our findings apply to treatment planning here. Also, stay tuned for the upcoming spatially-resolved extension of the model.

Created by Giulia Celora

Non-Local Cell Adhesion Models
Symmetries and Bifurcations in 1-D

Authors: Buttenschoen, Andreas, Hillen, Thomas: “While deeply grounded in the biological application of cell adhesion and tissue formation, this monograph focuses on the mathematical analysis of non-local adhesion models. The novel aspect is the non-local term (an integral operator), which accounts for forces generated by long ranged cell interactions. The analysis of non-local models has started only recently, and it has become a vibrant area of applied mathematics.”

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.

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