#MathOnco Issue 99: phenotypic coexistence & switching, evolutionary trajectories & algorithms, CAR-T-cells & single cells, and more.
This week in
Math Oncology
Jan. 23, 2019 ~ Issue 99
From the editor
Hello!
Today's issue contains models on phenotypic coexistence & switching, evolutionary trajectories & algorithms, CAR-T-cells & single cells, and more.
A few months ago, I wrote a blog post on the concept known as 'antifragility,' and how it may be relevant to cancer modeling. This month I'll be linking to the book which coined the term. While not directly math oncology, it does have an interesting discourse on the antifragility of evolutionary processes. I've personally found it an intriguing read.
Please enjoy!
-Jeffrey West
#MathOnco Publications
Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data
Authors: Prativa Sahoo, Xin Yang, Daniel Abler, Davide Maestrini, ..., Margarita Gutova, Sergio Branciamore, Christine E. Brown, Russell C. Rockne
Mix and Match: Phenotypic Coexistence as a Key Facilitator of Cancer Invasion
Authors: Maximilian A. R. Strobl, Andrew L. Krause, Mehdi Damaghi, Robert Gillies, Alexander R. A. Anderson & Philip K. Maini
Extreme intratumour heterogeneity and driver evolution in mismatch repair deficient gastro-oesophageal cancer
Authors: Katharina von Loga, Andrew Woolston, Marco Punta, Louise J. Barber, ..., Guido Sauter, Stefano Lise, Nik Matthews & Marco Gerlinger
Understanding the role of phenotypic switching in cancer drug resistance
Authors: Einar Gunnarsson, Subhajyoti De, Kevin Leder, Jasmine Foo
Cancer Genome Evolutionary Trajectories in Metastasis
Authors: Nicolai J. Birkbak, Nicholas McGranahan
Intratumor heterogeneity reflects clinical disease course
Authors: Christine A. Iacobuzio-Donahue, Kevin Litchfield & Charles Swanton
#MathOnco Preprints
Longitudinal cancer evolution from single cells
Authors: Daniele Ramazzotti, Fabrizio Angaroni, Davide Maspero, Gianluca Ascolani, Isabella Castiglioni, Rocco Piazza, Marco Antoniotti, Alex Graudenzi
Predictable Properties of Fitness Landscapes Induced by Adaptational Tradeoffs
Authors: Suman Gaurab Das, Susana O. L. Direito, Bartlomiej Waclaw, Rosalind J. Allen, Joachim Krug
Evolutionary algorithms: Bridging the gap between machine learning and mechanistic approaches in mathematical oncology
The Mathematical Oncology Blog
David Basanta: "Machine learning (ML) approaches are proving themselves invaluable in using the increasingly abundant longitudinal clinical data to find patterns to help make predictions and suggest treatment schedules. The one critique that has been consistently leveled on ML-based approaches is that it is a black box approach where the resulting algorithm capable of, potentially, outstanding predictions is inscrutable. Various efforts are being carried out to make that black box more translucent and I would like to share one based on my experience.."
#MathOnco - Book of the month
Antifragile: Things That Gain from Disorder
Nassim Nicholas Taleb: "Just as human bones get stronger when subjected to stress and tension, and rumors or riots intensify when someone tries to repress them, many things in life benefit from stress, disorder, volatility, and turmoil. What Taleb has identified and calls “antifragile” is that category of things that not only gain from chaos but need it in order to survive and flourish. The antifragile is beyond the resilient or robust. The resilient resists shocks and stays the same; the antifragile gets better and better. Furthermore, the antifragile is immune to prediction errors and protected from adverse events."
Most clicked links of December
Tumor diversity and the trade-off between universal cancer tasks
Opportunities for improving cancer treatment using systems biology
Inferring growth and genetic evolution of tumors from genome sequences
Jobs
Postdoctoral Fellow in Mathematical Oncology (Russell Rockne)
PhD in Dynamic interplay of cell shape and tumour evolution (Fabian Spill)
PhD in Dynamics of Mitochondria in Health and Disease (Fabian Spill)
PhD in Mathematical Modelling of Cancer-Cell Transmigration Through Blood Vessels (Fabian Spill)
Postdoc: University of Birmingham - Institute of Metabolism and Systems Research
Pre-leukemic Dynamics – MSc or PhD Studentship (Morgan Craig)
Quantitative Systems Pharmacology (QSP) Modeler - Cell Therapy (Dean Bottino)
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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