This week in MathOnco 158

Tumor containment, cancer cachexia, glioma microenvironment, multi-region sequencing

“This week in Mathematical Oncology” — Newsletter

Apr. 15, 2021
>jeffrey.west@moffitt.org

From the editor:


Summary of contents:

• An extensive analysis of tumor containment

• Cancer cachexia

• Topology & oncology

• Microenvironment & gliomas

• Multiregion sequencing

Enjoy,
-Jeffrey West

1. A theoretical analysis of tumour containment
   Yannick Viossat, Robert Noble

2. Radiomics predicts risk of cachexia in advanced NSCLC patients treated with immune checkpoint inhibitors
   Wei Mu, Evangelia Katsoulakis, Christopher J. Whelan, Kenneth L. Gage, Matthew B. Schabath, Robert J. Gillies

3. Identifying “more equal than others” edges in diverse biochemical networks
   Kishore Hari, Uday Ram, Mohit Kumar Jolly

4. Applications of Topological Data Analysis in Oncology
   Anuraag Bukkuri, Noemi Andor, Isabel K. Darcy

5. The many faces of cancer evolution
   Giovanni Ciriello, Luca Magnani

6. Budget Impact of Adaptive Abiraterone Therapy for Castration-Resistant Prostate Cancer
   Neil T. Mason, Jason M. Burkett, Ryan S. Nelson, Julio M. Pow-Sang, Robert A. Gatenby, Timothy Kubal, John W. Peabody, G. Douglas Letson, Howard L. McLeod, Jingsong Zhang

7. Multiscale modeling of glioma pseudopalisades: contributions from the tumor microenvironment
   Pawan Kumar, Jing Li, Christina Surulescu

1. Tracing the evolution of aneuploid cancers by multiregional sequencing with CRUST
   View ORCID ProfileSubhayan Chattopadhyay, View ORCID ProfileJenny Karlsson, View ORCID ProfileAnders Valind, View ORCID ProfileNatalie Andersson, View ORCID ProfileDavid Gisselsson
   

1. Quantifying intratumor heterogeneity in cancer

Jeff Wintersinger: “Once you can measure heterogeneity numerically, you can conduct statistical hypothesis tests and start to formulate conclusions. There are, however, many ways in which you can go about quantifying heterogeneity, with two of the most prominent methods being regrettably misleading. In the sections that follow, I will show why those methods are wrong, how we can correct the most promising definition, and how we can extend the corrected definitions to incorporate additional information about cancer evolution.”

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

• 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

The newsletter now has a dedicated homepage. Click here, then click “let me read it first” to see past covers. If you’d like to submit a cover for consideration please reply to this email. We encourage submissions that coincide with the release of a recent paper from your group. Today’s submission (created by yours truly) is below:

• Research Fellow in Computational Systems Biology Cancer Research (Simon Mitchell)

• PhD student - Measuring cancer evolution in a changing tumour microenvironment (Xiaowei Jiang)

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

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

• 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

• 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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