#MathOnco Issue 133: cancer evolution, Allee effects, invasion, immunology, chromosomal instability and more.
This week in
Math Oncology
Oct. 1, 2020 ~ Issue 133
From the editor
Dear readers,
Today's issue contains articles on topics like cancer evolution, Allee effects, invasion, immunology, chromosomal instability and more. There is an interesting article via The Scientist on virtual conferences. It also highlights the fact that so much science is communicated via Twitter these days. Perhaps this article may persuade you to dive deeper into science twitter, especially the #MathOnco hashtag.
Enjoy,
-Jeffrey West
#MathOnco Publications
Discovering functional evolutionary dependencies in human cancers
Authors: Marco Mina, Arvind Iyer, Daniele Tavernari, Franck Raynaud, Giovanni Ciriello
The science and medicine of human immunology
Authors: Bali Pulendran, Mark M. Davis
Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
Authors: Kaustav Bera, Kurt A. Schalper, David L. Rimm, Vamsidhar Velcheti, Anant Madabhushi
Is the Allee effect relevant in cancer evolution and therapy?
Authors: Marcello Delitala, Mario Ferraro
Population mutation properties of tumor evolution
Authors: LeeYoung Park
Multi-parametric evolution of conditions leading to cancer invasion in biological systems
Authors: Larysa Dzyubak, Oleksandr Dzyubak, Jan Awrejcewicz
Use of Wearable Activity Tracker in Patients With Cancer Undergoing Chemotherapy: Toward Evaluating Risk of Unplanned Health Care Encounters
Authors: Tanachat Nilanon, Luciano P. Nocera, Alexander S. Martin, Anand Kolatkar, ..., Joan Broderick, Cyrus Shahabi, Peter Kuhn, Jorge J. Nieva
#MathOnco Preprints
Chromosomal instability accelerates the evolution of resistance to anti-cancer therapies
Authors: Devon A. Lukow, Erin L. Sausville, Pavit Suri, Narendra Kumar Chunduri, Justin Leu, Jude Kendall, Zihua Wang, Zuzana Storchova, Jason M. Sheltzer
An Advanced Framework for Time-lapse Microscopy Image Analysis
Authors: Qibing Jiang, Praneeth Sudalagunta, Mark B. Meads, Khandakar Tanvir Ahmed, Tara Rutkowski, Ken Shain, Ariosto S. Silva, Wei Zhang
Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways
Authors: Juho A. J. Kontio, Tanja Pyhäjärvi, Mikko J. Sillanpää
The adaptive cancer cell: How metastases evolve to resist treatment
Dr Sarah Amend: "Species adapt to survive in a changing environment through the process of evolution. Evolutionary processes can also take place at the cellular level. Dr Sarah Amend of Johns Hopkins University, Baltimore, USA, is investigating poly-aneuploid cancer cells (PACCs). These large, DNA-laden cells, which are more common in metastatic cancer, develop evolvability: the capacity to evolve. Dr Amend believes that targeting the evolvability of PACCs and exploiting cancer ecology could offer new potential treatment routes for patients with metastatic cancer."
COVID-19 Ushers in the Future of Conferences
Abby Olena: "The Society for Mathematical Biology and the European Society for Mathematical and Theoretical Biology had planned to hold a joint conference this August in Heidelberg, Germany. But by the time spring rolled around, and the pandemic took firm hold of global travel, that was looking less and less likely. On May 9, the organizers postponed the in-person meeting until 2021. Amber Smith, a mathematical biologist at the University of Tennessee Health Science Center, and her fellow conference organizers stepped in to put together a virtual conference to give researchers a chance to share the research still advancing worldwide."
Special Issue:
Latest Developments in Mathematical Oncology and Cancer Systems Biology
Guest Editors: M. Kumar Jolly, H. Enderling
Announcement: Here, we invite investigators in the interdisciplinary field of mathematical oncology and cancer systems biology to contribute their latest research articles and/or review articles and perspectives on applying the different kinds of computational, mathematical, and statistical tools and techniques to applicable biological or clinical data to train such models to better elucidate the dynamics of tumor progression, to identify novel therapeutic schemas or targets, and to design more effective therapies.
Special Issue:
"Mathematical Models of Cellular Immunotherapies in Cancer"
Guest Editors: V. Pérez-García, L. de Pillis, P. Altrock, R. Rockne
Announcement: In this Special Issue, we plan to address cellular therapies from a mathematical and computational modeling perspective. Mathematical modeling has the potential to help in finding optimal administration protocols, provide a deeper understanding of the mechanisms and dynamics, help in the design of new clinical trials, and more. Despite the immense potential of these treatments, applied mathematicians and computational modelers have started to study these processes only very recently.
#MathOnco Virtual Seminars
Moffitt's Integrated Mathematical Oncology Dept. Series
Mathematical Oncology Series
1. Dr. Stacey Finley
"In silico control and optimization of Natural Killer Cell activation"
Oct 8, 2020 12:00 PM US Eastern
2. Dr. Arturo Aarujo
"Modelling cell division to understand clinical outcomes: Investigations in Oesophageal, Colon and Prostate to Bone Metastasis"
Oct 15, 2020 12:00pm US Eastern
#MathOnco - Featured Book
Rebel Cell: Cancer, Evolution, and the New Science of Life's Oldest Betrayal
Kat Arney: "Cancer exists in nearly every animal and has afflicted humans as long as our species has walked the earth. In Rebel Cell: Cancer, Evolution, and the New Science of Life's Oldest Betrayal, Kat Arney reveals the secrets of our most formidable medical enemy, most notably the fact that it isn’t so much a foreign invader as a double agent: cancer is hardwired into the fundamental processes of life. New evidence shows that this disease is the result of the same evolutionary changes that allowed us to thrive. Evolution helped us outsmart our environment, and it helps cancer outsmart its environment as well—alas, that environment is us."
Jobs
Research Fellow in Systems Biology Cancer Research (Simon Mitchell)
Principal Scientist – Oncology PK/PD Modelling (Boehringer Ingelheim)
Postdoctoral Research Position in Computational Immunology (Sylvain Cussat-Blanc)
Postdoc Position - TKI treatments in lung cancer (David Basanta)
Research Associate, Postdoc, and Research Faculty positions – Mathematical Oncology (Russ Rockne)
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)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
Do you see something we missed? Reply to this email to send us an idea for next week's issue.
The #MathOnco newsletter is maintained by Jeffrey West.
If you were forwarded this email, subscribe for free here to get it delivered every week.