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Rethinking Causation in Cancer through Modularity

Liu, Katherine E (2017) Rethinking Causation in Cancer through Modularity. [Preprint]

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Abstract

Despite the productivity of basic cancer research, cancer continues to be a health burden to society because this research has not yielded corresponding clinical applications. Many proposed solutions to this dilemma have revolved around implementing organizational and policy changes related to cancer research. Here I argue for a different solution: a new conceptualization of causation in cancer. Neither the standard molecular biomarker approaches nor evolutionary medicine approaches to cancer fully capture its complex causal dynamics, even when considered jointly. These approaches map on to Ernst Mayr’s proximate-ultimate distinction, which is an inadequate conceptualization of causation in biological systems and makes it difficult to connect developmental and evolutionary viewpoints. I conceptualize causation in cancer through the notion of modularity as a bridge between molecular biomarker approaches and evolution medicine approaches. A modularity-based approach requires the consideration of relationships between multiple levels of organization and the incorporation of different time scales, thereby overcoming the proximate-ultimate divide. The proposed perspective on causation in cancer is better suited to integrating the complexity of current empirical results and can facilitate novel developments in the investigation and clinical treatment of cancer.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Liu, Katherine Eliuxx971@umn.edu0000-0001-8965-4163
Keywords: cancer, causation, evolutionary medicine, modularity, proximate-ultimate, biomarker
Subjects: Specific Sciences > Biology
Specific Sciences > Biology > Evolutionary Theory
Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Causation
Specific Sciences > Medicine
Depositing User: Katherine Liu
Date Deposited: 16 Sep 2017 13:43
Last Modified: 16 Sep 2017 13:43
Item ID: 13440
Subjects: Specific Sciences > Biology
Specific Sciences > Biology > Evolutionary Theory
Specific Sciences > Biology > Molecular Biology/Genetics
General Issues > Causation
Specific Sciences > Medicine
Date: 2017
URI: http://philsci-archive.pitt.edu/id/eprint/13440

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