This week in MathOnco 146
Cell turnover, prisoner's dilemma, persistence, critique & response of adaptive therapy, building models
“This week in Mathematical Oncology” — Newsletter
Jan. 21, 2021
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jeffrey.west@moffitt.org
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From the editor:
Dear math oncology enthusiasts,
A new week, a new set of exciting math models!
Summary of contents (in order of appearance):
Estimates for rates of
cellular turnover
in healthy tissues, which may be useful for parameterizing models.
An article on
persistence
. While this publication utilizes continuous-time stochastic processes to study bacteria persistance, the tools may prove useful to cancer.
A mechanistic model of growth and dissemination used to predict overall survival in
Neuroblastoma
.
From my PhD advisor’s group, an game theory control paradigm of the classic
Prisoner’s Dilemma
(a commonly used game in math oncology).
Critique
and
response
of possibility of selection bias in Moffitt’s prostate cancer adaptive therapy trial.
The
paper
behind full 3D reconstruction (and awesome videos) of H&E slides at single-cell resolution, which made quite the splash
on Twitter
this week.
A few blog posts including the
role of maths
in biology, the unique
publishing strategy
at eLife, and
simple rules
to constructing math models.
…and more…
Enjoy!
-Jeffrey West
The distribution of cellular turnover in the human body
Ron Sender, Ron MiloPersistence as an Optimal Hedging Strategy
Alexander P. Browning, Jesse A. Sharp, Tarunendu Mapder, Christopher M. Baker, Kevin Burrage, Matthew J. SimpsonDevelopment and Validation of a Prediction Model of Overall Survival in High-Risk Neuroblastoma Using Mechanistic Modeling of Metastasis
Sébastien Benzekry, Coline Sentis, Carole Coze, Laëtitia Tessonnier, Nicolas AndréMaximizing cooperation in the prisoner's dilemma evolutionary game via optimal control
Paul K. Newton, Yonqian MaImpact of tumor-parenchyma biomechanics on liver metastatic progression: a multi-model approach
Yafei Wang, Erik Brodin, Kenichiro Nishii, Hermann B. Frieboes, Shannon M. Mumenthaler, Jessica L. Sparks & Paul MacklinOn the reporting and analysis of a cancer evolutionary adaptive dosing trial
Hitesh B. MistryResponse to Mistry
Jingsong Zhang, Jessica J. Cunningham, Joel S. Brown, Robert A. Gatenby
Intermittent radiotherapy as alternative treatment for recurrent high grade glioma: A modelling study based on longitudinal tumor measurements
Sarah C. Brueningk, Jeffrey Peacock, Christopher J. Whelan, Hsiang-Hsuan M. Yu, Solmaz Sahebjam, Heiko EnderlingAsymptotic analysis of a biphase tumor fluid flow. The weak coupling case
Cristina Vaghi, Sébastien Benzekry, Clair PoignardIn situ characterization of the 3D microanatomy of the pancreas and pancreatic cancer at single cell resolution
Ashley Kiemen, Alicia M. Braxton, Mia P. Grahn, Kyu Sang Han, …, Laura D. Wood, Ralph H. Hruban, Pei-Hsun Wu, Denis Wirtz
Cosmos Magazine: “Before 2020, the phrase ‘mathematical modelling’ may have made your eyes glaze over. But as COVID-19 escalated across the globe, we’ve watched mathematics combine with epidemiology to make predictions, guide government decisions, and inform the public about the state of the pandemic. … But the usefulness of tackling biological problems with the framework of maths extends far beyond viruses – as Matthew Simpson, a mathematician at Queensland University of Technology (QUT), knows well.”
2. Peer Review: Implementing a "publish, then review" model of publishing
eLife: From July 2021 eLife will only review manuscripts already published as preprints, and will focus its editorial process on producing public reviews to be posted alongside the preprints.
Korryn Bodner, et. al: “Here, we present 10 simple rules for tackling your first mathematical models. While many of these rules are applicable to basic scientific research, our discussion relates explicitly to the process of model-building within ecological and epidemiological contexts using dynamical models. … As graduate students ourselves, we have created rules we wish we had internalized before beginning our model-building journey—a guide by graduate students, for graduate students—and we hope they prove insightful for anyone seeking to begin their own adventures in mathematical modelling.”
Apollo's Arrow:
The Profound and Enduring Impact of Coronavirus on the Way We Live
N. Christakis: "Apollo's Arrow offers a riveting account of the impact of the coronavirus pandemic as it swept through American society in 2020, and of how the recovery will unfold in the coming years. Drawing on momentous (yet dimly remembered) historical epidemics, contemporary analyses, and cutting-edge research from a range of scientific disciplines, bestselling author, physician, sociologist, and public health expert Nicholas A. Christakis explores what it means to live in a time of plague — an experience that is paradoxically uncommon to the vast majority of humans who are alive, yet deeply fundamental to our species."
Understanding the Evolutionary Dynamics and Ecology of Cancer in Treatment Resistance
Guest Editor: David BasantaMathematical Models of Cellular Immunotherapies in Cancer
Guest Editors: V. Pérez-García, L. de Pillis, P. Altrock, R. RockneFrom Ecology to Cancer Biology and Back Again
Guest Editors: Fred Adler, Sarah Amend, Chris WhelanFrontiers in quantitative cancer modeling
Guest Editors: Mohit Kumar Jolly, Heiko Enderling
NEW: Early Stage Researcher: Evolutionary therapy in ovarian cancer (Ben Werner)
Postdoc in Statistics & Mathematics for Personalized Breast Cancer Therapy (Alvaro Köhn-Luque)
PhD on Modelling Cell Life and Death (Dan Tennant/Fabian Spill)
Mathematical Modeling Expert in Oncology Translational Science (Boehringer Ingelheim)
Research Associate - Biostatistician (University of Manchester)
Research Fellow in Computational Systems Biology Cancer Research (Simon Mitchell)
Research Fellow in Laboratory and Computational Systems Biology Cancer Research (Simon Mitchell)
Postdoctoral Fellow in Cancer Resistance Modeling, Pfizer (Blerta Shtylla)
Principal Scientist – Oncology PK/PD Modelling (Boehringer Ingelheim)
Postdoctoral Research Position in Computational Immunology (Sylvain Cussat-Blanc)
Postdoc Position - TKI treatments in lung cancer (David Basanta)
Systems Biology Modeler Positions in Biopharma Consulting Company (Helen Moore)
Computational Approaches to Breast Cancer Evolution - Postdoc (Marc Ryser)
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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