“This week in Mathematical Oncology” — March 21, 2024
> mathematical-oncology.org
From the editor:
You may have noticed an additional author on recent issues of “This Week in Math Onco” — Franco Pradelli! He has been helping to automate some of the paper collection process for the newsletter, which led us to wonder if we could automatically collect all the past papers from the past six years, too (>1500 papers!).
Read the story in his recent blog post here, and download the official MathOnco LaTeX bibliography here. Give Franco a follow on Twitter/X @fpradelli94.
PS. I’m hiring! Click here for a postdoc position in my group.
Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
Enhanced perfusion following exposure to radiotherapy: A theoretical investigation
Jakub Köry, Vedang Narain, Bernadette J. Stolz, Jakob Kaeppler, Bostjan Markelc, Ruth J. Muschel, Philip K. Maini, Joe M. Pitt-Francis, Helen M. ByrneUsing birth-death processes to infer tumor subpopulation structure from live-cell imaging drug screening data
Chenyu Wu, Einar Bjarki Gunnarsson, Even Moa Myklebust, Alvaro Köhn-Luque, Dagim Shiferaw Tadele, Jorrit Martijn Enserink, Arnoldo Frigessi, Jasmine Foo, Kevin LederModeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent
Tuğba Akman, Lisa M. Arendt, Jürgen Geisler, Vessela N. Kristensen, Arnoldo Frigessi & Alvaro Köhn-LuqueA review of mechanistic learning in mathematical oncology
John Metzcar, Catherine R. Jutzeler, Paul Macklin, Alvaro Köhn-Luque, Sarah C. BrüningkThe bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous drug resistant disease
Ryan T. Bishop, Anna K. Miller, Matthew Froid, Niveditha Nerlakanti, …, Ariosto Siqueira Silva, Kenneth H. Shain, Conor C. Lynch & David BasantaMathematical modelling of clonal reduction therapeutic strategies in acute myeloid leukemia
Mia Brunetti, Isabella A. Iasenza, Adrianne L. Jenner, Noël J-M Raynal, Kolja Eppert, Morgan CraigThe evolutionary safety of mutagenic drugs should be assessed before drug approval
Gabriela Lobinska,Vyacheslav Tretyachenko,Orna Dahan,Martin A. Nowak ,Yitzhak Pilpel
Evolutionary double-bind treatment using radiotherapy and NK cell-based immunotherapy in prostate cancer
Kimberly A Luddy, Jeffrey West, Mark Robertson-Tessi, Bina Desai, Taylor M Burrsell, Sarah Barrett, Jacintha O'Sullivan, Laure Marignol, Robert Gatenby, Joel S Brown, Alexander RA Anderson, Cliona O'FarrellyA low-footprint, fluorescence-based bacterial time-kill assay for estimating dose-dependent cell death dynamics
Eshan S King, Anna E Stacey, Jacob G Scott
A .bib file to rule them all
The Mathematical Oncology Blog
Franco Pradelli: “All LaTex users know very well .bib files. These compact files allow writers worldwide to manage bibliographic references easily, reducing the burden of one of the most annoying aspects of being a scientist. But have you ever seen a .bib file containing more than 1500 references? I got this when I automatically scraped all the 285 issues of the MathOnco Newsletter — almost seven years of effort condensed in a single bib file.”
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: Diverse mutant selection windows shape spatial heterogeneity in evolving populations published in PLoS Computational Biology
Artist: Eshan S. King
Caption: Drug-resistant and drug-sensitive cancer cells respond to different concentrations of drugs in different ways. For instance, resistant cells may grow slower than sensitive cells when drug levels are low— we call this a cost to drug resistance. When considering how a single tumor may have multiple subtypes of cells with varying levels of resistance existing simultaneously, understanding how these different subtypes are selected during therapy becomes complicated. Furthermore, studies of drug diffusion in tumors have shown that the drug concentration may drop off steeply as distance from a blood vessel increases. Here, we sought to understand how different patterns of drug diffusion interact with variable drug sensitivities among different tumor subtypes. Using agent-based modeling, we simulated tumor evolution with different rates of drug diffusion. The top row of the picture shows the different drug diffusion profiles, with the rate of diffusion increasing from left to right. The bottom row shows multiple replicates of simulated tumors responding to the drug concentration profile above. This work suggests that drug diffusion may be a driver of tumor heterogeneity, potentially contributing to treatment failure.
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