This week in MathOnco 172

Microvesicle transfer, adaptive prostate cancer therapy, mechanisms in modeling, drug discovery, and modular systems biology modeling

“This week in Mathematical Oncology” — Newsletter
> mathematical-oncology.org

July 29, 2021

From the editor:
> jeffrey.west@moffitt.org


Dear readers,

Today’s issue contains articles on microvesicle transfer (with neat artwork!), adaptive prostate cancer therapy, mechanisms in modeling, drug discovery, and modular systems biology modeling. Enjoy,

- Jeffrey West

1. Global analysis of a cancer model with drug resistance due to Lamarckian induction and microvesicle transfer
   Attila Dénes, Sadegh Marzban, Gergely Röst

2. Do mechanisms matter? Comparing cancer treatment strategies across mathematical models and outcome objectives
   Cassidy K. Buhler, Rebecca S. Terry, Kathryn G. Link, Frederick R. Adler

3. Beyond the single average tumor: Understanding IO combinations using a clinical QSP model that incorporates heterogeneity in patient response
   Rukmini Kumar, Kannan Thiagarajan, Lakshmanan Jagannathan, Liming Liu, Kapil Mayawala, Dinesh de Alwis, Brian Topp

4. Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility
   Flora T. Musuamba, Ine Skottheim Rusten, Raphaëlle Lesage, Giulia Russo, …, Enrico Dall’ara, Blanca Rodriguez, Francesco Pappalardo, Liesbet Geris

5. Biomarker-Guided Individualization of Antibiotic Therapy
   Linda B.S. Aulin, Dylan W. de Lange, Mohammed A.A. Saleh, Piet H. van der Graaf, Swantje Völler, J.G. Coen van Hasselt

6. Model Development of CDK4/6 Predicted Efficacy in Patients With Hormone Receptor–Positive, Human Epidermal Growth Factor Receptor 2–Negative Advanced or Metastatic Breast Cancer
   Jeremy Mason, Yutao Gong, Laleh Amiri-Kordestani, Suparna Wedam, …, Richard Pazdur, Peter Kuhn, Gideon M. Blumenthal, Julia A. Beaver

7. Bispecific antibodies: A guide to model informed drug discovery and development
   Irina Kareva, Anup Zutshi, Pawan Gupta, Senthil Kabilan
   

1. A community-based approach to image analysis of cells, tissues and tumors
   CSBC/PS-ON Image Analysis Working Group, Juan Carlos Vizcarra, Erik A. Burlingame, Clemens B. Hug, Yury Goltsev, Brian S. White, Darren R. Tyson, Artem Sokolov

2. Modular assembly of dynamic models in systems biology
   Michael Pan, Peter J. Gawthrop, Joseph Cursons, Edmund J. Crampin

1. Cancer Corruption
   The Mathematical Oncology Blog
   Anuraag Bukkuri, Fred Adler: “Our paper begins by outlining the five main mechanisms that prevent deceptive signaling in nature: (1) eliminating conflicts of interest, such as through the high relatedness of sterile worker ants in a colony, (2) making signal cost quality-dependent, such as the energetically expensive and time consuming songs of territorial birds, (3) making signal cost need-dependent, such as begging by nestlings, (4) enforcement, such as through individually directed skepticism in squirrel alarm calls, and (5) physical constraints, such as those that body size puts on vocalization frequency. We show how cancers evolve ways to escape each of these controls through uncontrolled growth, oncogene expression, loss of tumor suppressors, T cell exhaustion, and immune evasion, respectively.”

The newsletter now has a dedicated homepage (thisweekmathonco.substack.com), which allows us to post cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group.

Caption: “A recent discovery is that the phenotype conversion of cancer cells from sensitive to resistant can occur through the transfer of microvesicles from resistant cells to sensitive cells, in a way similar to the spread of an infectious agent. We constructed two mathematical models to understand the possible effect of this phenonemon on the outcome of chemotherapy: an ODE model to perform a comprehensive analyis, and an ABM to reveal the spatiotemporal dynamics. The figure shows the bifurcation chart of possible outcomes with respect to drug concentration and the fitness of the resistant cells: tumour eradication, partial response to therapy, or treatment failure. Blue cells are sensitive, and green ones are resistant. Our results suggest that the presence of microvesicle transfer cannot ruin a therapy that otherwise leads to complete remission of the tumour, however it may doom a partially successful therapy to failure. Read the full paper here.”

Created by: Attila Dénes, Sadegh Marzban (@S_Marzban), Gergely Röst (@gergely_rost)

Non-Local Cell Adhesion Models
Symmetries and Bifurcations in 1-D

Authors: Buttenschoen, Andreas, Hillen, Thomas: “While deeply grounded in the biological application of cell adhesion and tissue formation, this monograph focuses on the mathematical analysis of non-local adhesion models. The novel aspect is the non-local term (an integral operator), which accounts for forces generated by long ranged cell interactions. The analysis of non-local models has started only recently, and it has become a vibrant area of applied mathematics.”

Visit the mathematical oncology page to view jobs, meetings, and special issues. We will post new additions here, but the full list can found at mathematical-oncology.org.

1. Jobs

• NEW: Research Fellow in Biomedical Mathematics (Institute for Basic Science, Daejeon South Korea) - Due: 8th August

2. Conferences / Meetings

3. Special issues

Current subscriber count: >1k