This week in MathOnco 167
Parameter estimation, optimal strategies, vasculature, Markov chain modeling, and evolutionary tracking
“This week in Mathematical Oncology” — Newsletter
June 24, 2021
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jeffrey.west@moffitt.org
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From the editor:
This week we’ve attached many new papers, but also a few papers we found out about during SMB2021. Enjoy!
-Jeffrey West
Serial single-cell genomics reveals convergent subclonal evolution of resistance as patients with early-stage breast cancer progress on endocrine plus CDK4/6 therapy
Jason I. Griffiths, Jinfeng Chen, Patrick A. Cosgrove, Anne O’Dea, …, Frederick R. Adler, Adam L. Cohen, Jeffrey T. Chang, Qamar J. Khan, Andrea H. BildOptiDose: Computing the Individualized Optimal Drug Dosing Regimen Using Optimal Control
Freya Bachmann, Gilbert Koch, Marc Pfister, Gabor Szinnai, Johannes SchroppCalibrating models of cancer invasion: parameter estimation using approximate Bayesian computation and gradient matching
Yunchen Xiao, Len Thomas, Mark A. J. ChaplainScientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: building model credibility
Flora T. Musuamba, Ine Skottheim Rusten, Raphaëlle Lesage, Giulia Russo, Roberta Bursi, … Enrico Dall’ara, Blanca Rodriguez, Francesco Pappalardo, Liesbet GerisComputational modeling of ovarian cancer dynamics suggests optimal strategies for therapy and screening
Shengqing Gu, Stephanie Lheureux, Azin Sayad, Paulina Cybulska, …, Marcus Q. Bernardini, Barry Rosen, Amit Oza, Myles Brown, Benjamin G. NeelNon-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
Abdulhamed Alsisi, Raluca Eftimie, Dumitru TrucuA Mathematical Study of the Influence of Hypoxia and Acidity on the Evolutionary Dynamics of Cancer
Giada Fiandaca, Marcello Delitala, Tommaso LorenziBiologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data
David A. Hormuth II, Caleb M. Phillips, Chengyue Wu, Ernesto A. B. F. Lima, Guillermo Lorenzo, Prashant K. Jha, Angela M. Jarrett, J. Tinsley Oden, Thomas E. Yankeelov
A Markov chain model of cancer treatment
Peter Bayer, Joel S Brown, Johan Dubbeldam, Mark BroomPrinciples of ecDNA random inheritance drive rapid genome change and therapy resistance in human cancers
Joshua T. Lange, Celine Y. Chen, Yuriy Pichugin, Liangqi Xie, …, Vineet Bafna, Anton G. Henssen, Benjamin Werner, Paul S. MischelEvolutionary tracking of cancer haplotypes at single-cell resolution
Marc J Williams, Tyler Funnell, Ciara H O’Flanagan, Andrew McPherson, …, Nicholas Ceglia, IMAXT consortium, Samuel Aparicio, Sohrab P. Shah
Sensing change: how cells respond to environmental variability
Caroline Wood, Society for Experimental Biology
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 Dr Jason Griffths:
Caption: Cell cycle inhibitor therapies have shown promise in treating metastatic estrogen receptor positive breast cancers. However, its efficacy in treating potentially curable earlier stage tumors is highly variable. To understand the cancer cell phenotypes that convey resistance, we analyzed the gene expression of individual cancer cells extracted from patient biopsies before, during and after treatment. Using hierarchical models, we uncovered that as tumors become resistant (from figure’s left (sensitive) to right (resistant)), estrogen receptor signalling (pink points) is reduced and cancer cells upregulate alternative growth factor receptors (purple points). This activates alternate pathways transducing the proliferative signal to the nucleus (white versus red core), allowing cell cycle inhibition to be bypassed and jointly conveys resistance to standard of care estrogen therapies. See the full publication in Nature Cancer.
Created by Jason Griffiths – City of Hope National Medical Center and Department of Mathematics at the University of Utah.
“A mathematician, like a painter or poet, is a maker of patterns,” wrote the British mathematician G. H. Hardy. In Do Not Erase, photographer Jessica Wynne presents remarkable examples of this idea through images of mathematicians’ chalkboards.”
Buy the book here.
Networks in Cancer: From Symmetry Breaking to Targeted Therapy
Guest Editor: Cristian Axenie, Roman Bauer, María Rodríguez MartínezUnderstanding the Evolutionary Dynamics and Ecology of Cancer in Treatment Resistance
Guest Editor: David BasantaFrontiers in quantitative cancer modeling
Guest Editors: Mohit Kumar Jolly, Heiko Enderling
Mathematical Immuno-Oncology postdoc (Kasia Rejniak, Moffitt)
Research Fellow in Computational Systems Biology Cancer Research (Simon Mitchell)
PhD student - Measuring cancer evolution in a changing tumour microenvironment (Xiaowei Jiang)
Postdoctoral Scholar - Genetics and Genome Sciences (Christopher McFarland)
Postdoc on colorectal cancer evolution or cancer immunotherapy (Ivana Bozic)
Postdoc on cancer/immune modeling and machine learning (Eduardo Sontag)
Early Stage Researcher: Evolutionary therapy in ovarian cancer (Ben Werner)
Research Associate - Biostatistician (University of Manchester)
Systems Biology Modeler Positions in Biopharma Consulting Company (Helen Moore)
Math/statistical models of stem cell lineage dynamics and cancer genomics - Postdoc (Adam MacLean)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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