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
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

  1. 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. Bild

  2. OptiDose: Computing the Individualized Optimal Drug Dosing Regimen Using Optimal Control
    Freya Bachmann, Gilbert Koch, Marc Pfister, Gabor Szinnai, Johannes Schropp

  3. Calibrating models of cancer invasion: parameter estimation using approximate Bayesian computation and gradient matching
    Yunchen Xiao, Len Thomas, Mark A. J. Chaplain

  4. Scientific 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 Geris

  5. Computational 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. Neel

  6. Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
    Abdulhamed Alsisi, Raluca Eftimie, Dumitru Trucu

  7. A Mathematical Study of the Influence of Hypoxia and Acidity on the Evolutionary Dynamics of Cancer
    Giada Fiandaca, Marcello Delitala, Tommaso Lorenzi

  8. Biologically-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

  1. A Markov chain model of cancer treatment
    Peter Bayer, Joel S Brown, Johan Dubbeldam, Mark Broom

  2. Principles 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. Mischel

  3. Evolutionary 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

  1. 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.

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