This week in MathOnco 154

Genetic/non-genetic diversity, models of hypoxia, clonal dominance, and heterogeneity

“This week in Mathematical Oncology” — Newsletter

Mar. 18, 2021
>jeffrey.west@moffitt.org

From the editor:


Today’s edition contains a review on genetic/non-genetic diversity, models of hypoxia, clonal dominance, and heterogeneity, as well asa nice blog post on in silico trials.

Enjoy!
-Jeffrey West

1. Genetic and non-genetic clonal diversity in cancer evolution
   James R. M. Black, Nicholas McGranahan

2. Cycling hypoxia selects for constitutive HIF stabilization
   Mariyah Pressley, Jill A. Gallaher, Joel S. Brown, Michal R. Tomaszewski, Punit Borad, Mehdi Damaghi, Robert J. Gillies & Christopher J. Whelan

3. Mathematical modelling of the hematopoietic stem cell-niche system: Clonal dominance based on stem cell fitness
   Rasmus Kristoffer Pedersen, MortenAndersen, Thomas Stiehl, Johnny T. Ottesen

4. A novel mathematical model of heterogeneous cell proliferation
   Sean T. Vittadello, Scott W. McCue, Gency Gunasingh, Nikolas K. Haass, Matthew J. Simpson

5. Novel evolutionary dynamics of small populations in breast cancer adjuvant and neoadjuvant therapy
   Yael Artzy-Randrup, Tamir Epstein, Joel S. Brown, Ricardo L. B. Costa, Brian J. Czerniecki & Robert A. Gatenby

6. Assessing the contribution of tumor mutational phenotypes to cancer progression risk
   Yifeng Tao, Ashok Rajaraman, Xiaoyue Cui, Ziyi Cui, Haoran Chen, Yuanqi Zhao, Jesse Eaton, Hannah Kim, Jian Ma, Russell Schwartz

1. Re-polarisation of macrophages within a multi-scale moving boundary tumour invasion model
   Szabolcs Suveges, Raluca Eftimie, Dumitru Trucu

2. Universal absorption-time distributions in birth-death Markov processes
   David Hathcock, Steven H. Strogatz

3. Reconstruction of Contemporary Human Stem Cell Dynamics with Oscillatory Molecular Clocks
   Calum Gabbutt, Ryan O Schenck, Daniel Weisenberger, Christopher Kimberley, …, Simon J Leedham, Alexander RA Anderson, Trevor A Graham, Darryl Shibata
   

1. In silico clinical trials: Improving the discovery to approved pipeline
The Mathematical Oncology Blog

Adrianne Jenner: “While mathematical modelling has provided significant advancements in cancer treatment, the speed at which we are moving towards effective all-encompassing treatments is slow in comparison to the growth of this disease. Fortunately, virtual or in silico clinical trials are ideally situated to respond to the needs of the oncology industry and assist in more rapid translation of treatments from discovery to approved.”

2. Let’s chat
Nature Methods Editorial Board

“At Nature Methods we are happy to engage with prospective authors and readers. Here we go through the why, what, who, when and how of talking to journal editors.”

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• Networks in Cancer: From Symmetry Breaking to Targeted Therapy
  Guest Editor: Cristian Axenie, Roman Bauer, María Rodríguez Martínez

• Understanding the Evolutionary Dynamics and Ecology of Cancer in Treatment Resistance
  Guest Editor: David Basanta

• Mathematical Models of Cellular Immunotherapies in Cancer
  Guest Editors: V. Pérez-García, L. de Pillis, P. Altrock, R. Rockne

• From Ecology to Cancer Biology and Back Again
  Guest Editors: Fred Adler, Sarah Amend, Chris Whelan

• Frontiers in quantitative cancer modeling
  Guest Editors: Mohit Kumar Jolly, Heiko Enderling

• NEW: Postdoctoral Scholar - Genetics and Genome Sciences (Christopher McFarland)

• PhD Position - Simulation of Tissue (Jakob Rosenbauer)

• Postdoc on colorectal cancer evolution or cancer immunotherapy (Ivana Bozic)

• PhD student in modeling evolution and ecology of cancer (Rob Noble)

• Postdoc on cancer/immune modeling and machine learning (Eduardo Sontag)

• PhD candidate/Early Career Researcher: Theory of Stackelberg evolutionary games for cancer treatment (Katerina Stankova)

• Early Stage Researcher: Impact of different resistance mechanisms on the outcomes of cancer treatment game (Weini Huang)

• Early Stage Researcher: Evolutionary therapy in ovarian cancer (Ben Werner)

• CDC Steven M. Teutsch Prevention Effectiveness Fellowship

• Research Associate - Biostatistician (University of Manchester)

• 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)

• Machine Learning / Math Modeling Postdoc (Noemi Andor)

• Cancer immunotherapy / systems bio postdoc (Elana J Fertig)

• Integrated Math Oncology Ph.D. (Moffitt)

• Integrated Math Oncology Postdoc (Sandy Anderson)

• Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)

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