This week in MathOnco 152

tumor forecasting, plasticity, PKPD competition models, MathOnco treatment decision-making, and more

“This week in Mathematical Oncology” — Newsletter

Mar. 4, 2021
>jeffrey.west@moffitt.org

From the editor:


Summary of contents:

• Prostate cancer model of vasculature

• Plasticity in cancer treatment

• Robustness of adaptive therapy to stochasticity

• Decision making using Math oncology

• PKPD combined w/ Lotka-Volterra competition models

• Tumor forecasting

• A new Phd job post

Enjoy,
-Jeffrey West

1. Relating prostate‐specific antigen leakage with vascular tumor growth in a mathematical model of prostate cancer response to androgen deprivation
   Johnna P. Barnaby, Inmaculada C. Sorribes, Harsh Vardhan Jain

2. Impact of Cancer Evolution on Immune Surveillance and Checkpoint Inhibitor Response
   Yin Wu, Dhruva Biswas, Charles Swanton

3. The impact of phenotypic heterogeneity of tumour cells on treatment and relapse dynamics
   Michael Raatz, Saumil Shah, Guranda Chitadze, Monika Brüggemann, Arne Traulsen

4. Experimental and mathematical modelling of magnetically labelled mesenchymal stromal cell delivery
   E. F. Yeo, H. Markides, A. T. Schade, A. J. Studd, J. M. Oliver, S. L. Waters and A. J. El Haj

5. A Quantitative Paradigm for Decision-Making in Precision Oncology
   Dalit Engelhardt, Franziska Michor

6. Dosage strategies for delaying resistance emergence in heterogeneous tumors
   Vahideh Vakil, Wade Trappe

1. Are adaptive chemotherapy schedules robust? A three-strategy stochastic evolutionary game theory model
   Rajvir Dua, Yongqian Ma, Paul K. Newton

2. Spatial patterns of tumour growth impact clonal diversification: computational modelling and evidence in the TRACERx Renal study
   Xiao Fu, Yue Zhao, Jose Lopez, Andrew Rowan, …, Erik Sahai, Kevin Litchfield, Samra Turajlic, Paul Bates

3. Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
   Guillermo Lorenzo, David A. Hormuth II, Angela M. Jarrett, Ernesto A. B. F. Lima, Shashank Subramanian, George Biros, J. Tinsley Oden, Thomas J. R. Hughes, Thomas E. Yankeelov

4. Prediction Models of Tumor Growth Trajectories Based on Pretreatment CT Images of TKI-Treated Lung Cancer Patients
   Huy Gia Truong, Hidetaka Arimura, Kentaro Tanaka, Kenta Ninomiya, Quoc Cuong Le

1. Traveling Wave Analysis: Behind the Paper
The Mathematical Oncology Blog

Gregory Kimmel: “The evolutionary public goods game (PGG) is used to address open questions that arise from facultative contributions of benefits into common spaces, for example in economics, behavior, the evolution of cooperation and more recently, it has been used in the context of cancer to explain the emergence and maintenance of heterogeneity. … Understanding the biological system that governs the speed at which cells move into unoccupied space is warranted. From a simplified view, the effect of cancer spreading outward takes the form of a traveling wave. A classic tool for understanding these waves is using the Fisher-Kolmogorov-Petrovsky-Piskunov (F-KPP) equation.

2. Adaptive Cancer Therapy: tackling cancer drug resistance by capitalising on competition

University of Oxford: “How to deal with resistance? This is the headline question these days with regards to COVID vaccines. But it is an important question also in cancer therapy. Over the past century, oncology has come a long way, but all too often cancers still recur due to the emergence of drug-resistant tumour cells. How to tackle these cells is one of the key questions in cancer research. The main strategy so far has been the development of new drugs to which the resistant cells are still sensitive. While this approach has been successful, it often doesn’t take too long for further mutants to arise, requiring yet another set of new treatments.”

Atomic Habits:
An Easy & Proven Way to Build Good Habits & Break Bad Ones

James Clear: "If you're having trouble changing your habits, the problem isn't you. The problem is your system. Bad habits repeat themselves again and again not because you don't want to change, but because you have the wrong system for change. You do not rise to the level of your goals. You fall to the level of your systems. Here, you'll get a proven system that can take you to new heights."

• 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: 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

• Postdoc in Statistics & Mathematics for Personalized Breast Cancer Therapy (Alvaro Köhn-Luque)

• Mathematical Modeling Expert in Oncology Translational Science (Boehringer Ingelheim)

• Research Associate - Biostatistician (University of Manchester)

• Postdoctoral Fellow in Cancer Resistance Modeling, Pfizer (Blerta Shtylla)

• Director Quantitative Clinical Pharmacology, Oncology

• Principal Scientist – Oncology PK/PD Modelling (Boehringer Ingelheim)

• Biosimulation Scientist (Physiomics)

• Postdoctoral Research Position in Computational Immunology (Sylvain Cussat-Blanc)

• 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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