This week in Mathematical Oncology

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This week in MathOnco 210

Cancer origins, lineage tracing, agent-based spatial models, reciprocal cell-cell interactions

Jeffrey West
,
Maximilian Strobl
, and
Sandy Anderson
May 19
1
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“This week in Mathematical Oncology” — May 19, 2022
> mathematical-oncology.org
From the editor:

Welcome to another edition of the Mathematical Oncology newsletter. Today we feature articles on cancer origins, lineage tracing, agent-based spatial models, reciprocal cell-cell interactions, and more. Enjoy,

Jeffrey West
jeffrey.west@moffitt.org


"There is an infinite number of incorrect theories correctly explaining the finite number of experimental data."
-Niels Bohr


  1. Attribution of cancer origins to endogenous, exogenous, and preventable mutational processes
    Vincent L. Cannataro, Jeffrey D. Mandell, Jeffrey P. Townsend

  2. Dynamic patterns of microRNA expression during acute myeloid leukemia state-transition
    David E. Frankhouser, Denis O’Meally, Sergio Branciamore, Lisa Uechi, …, Nadia Carlesso, Guido Marcucci, Russell C. Rockne, Ya-Huei Kuo

  3. Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution
    Dian Yang, Matthew G. Jones, Santiago Naranjo, William M. Rideout III, …, Michelle M. Chan, Nir Yosef, Tyler Jacks, Jonathan S. Weissman

  4. Interrogating and Quantifying In Vitro Cancer Drug Pharmacodynamics via Agent-Based and Bayesian Monte Carlo Modelling
    Marios Demetriades, Marko Zivanovic, Myrianthi Hadjicharalambous, Eleftherios Ioannou, …, Nevena Milivojevic, Odysseas Kokkinos, Roman Bauer, Vasileios Vavourakis

  5. Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models

    Jeon-Young Kang, Jared Aldstadt

  6. Agent-based Modeling of Tumor and Immune System Interactions in Combinational Therapy with Low-dose 5-fluorouracil and Dendritic Cell Vaccine in Melanoma B16F10
    Sarah Rahbar, Sajad Shafiekhani, Armin Allahverdy, Arezoo Jamali, … Sima Habibi, Bahador Makkiabadi, Jamshid Hadjati, Amir Homayoun Jafari

  7. Tumor cell malignancy: A complex trait built through reciprocal interactions between tumors and tissue-body system
    Jean Feunteun, Pauline Ostyn, Suzette Delaloge

  8. Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology
    Chengyue Wu, Guillermo Lorenzo, David A. Hormuth II, Ernesto A. B. F. Lima, Kalina P. Slavkova, Julie C. DiCarlo, John Virostko, Caleb M. Phillips, Debra Patt, Caroline Chung, Thomas E. Yankeelov

  9. Quantitative System Pharmacology as a Legitimate Approach to Examine Extrapolation Strategies used to Support Pediatric Drug Development
    Karim Azer, Jeffrey S. Barrett

  1. On tumoural growth and treatment under cellular dedifferentiation
    Matthias M. Fischer, Nils Blüthgen

  2. Tethering distinct molecular profiles of single cells by their lineage histories to investigate sources of cell state heterogeneity
    Anna Minkina, Junyue Cao, Jay Shendure

  3. Clonally heritable gene expression imparts a layer of diversity within cell types
    Jeff E. Mold, Martin H. Weissman, Michael Ratz, Michael Hagemann-Jensen, …, Joakim Lundeberg, Rickard Sandberg, Jakob Michaëlsson, Jonas Frisén

  4. Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems
    Sara Hamis, Panu Somervuo, J. Arvid Ågren, Dagim Shiferaw Tadele, Juha Kesseli, Jacob G. Scott, Matti Nykter, Philip Gerlee, Dmitri Finkelshtein, Otso Ovaskainen

  5. Picking winners in cell-cell collisions: wetting, speed, and contact
    Pedrom Zadeh, Brian A. Camley

  1. ABM Digest
    Newsletter on agent-based modeling, edited by Bill Jeffries (@billjeffries93). Subscribe here, or view the past issues of this newsletter, here.

The newsletter now has a dedicated homepage where we post the cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group.

(GIF may take a second to load)

Caption: “Tumor sequencing data reveal variants that have suffused throughout cancer genomes in tell-tale patterns. However, these mutational signatures do not directly represent the contribution of mutagenic processes to tumor formation, as the vast majority of variants have no role in tumorigenesis. To tie mutagenic processes to the tumor phenotype, one must determine the contribution of each variant in a tumor to increases in cellular growth and survival, and then link this quantification of cancer effect size to the likelihood each variant was fueled by each detected mutagenic process in the tumor. In a recent paper published in Molecular Biology and Evolution, Cannataro et al. made this connection in thousands of tumors of 24 cancer types. In a given tumor, the processes fueling mutation and selection are often very different. Each row in this cover image represents a different tumor type, and the different colors represent different mutational processes. The image, based off Fig. 4 in the manuscript, transitions from representing the sum of processes fueling mutation in each tumor type and the sum of the contribution of the processes to tumor phenotype, with the “phenotype” bars represented in the thumbnail.“

Created by: Vincent L. Cannataro (@VinCannataro), Jeff Townsend (@JeffTownsend)

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

2. Conferences / Meetings

3. Special issues

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