SPREAD OF PREMALIGNANT MUTANT CLONES AND CANCER INITIATION IN MULTILAYERED TISSUE

Jasmine Foo; Einar Bjarki Gunnarsson; Kevin Leder; Kathleen Storey

doi:10.1214/22-AAP1816

SPREAD OF PREMALIGNANT MUTANT CLONES AND CANCER INITIATION IN MULTILAYERED TISSUE

Jasmine Foo
, Einar Bjarki Gunnarsson
, Kevin Leder
, Kathleen Storey

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Over 80% of human cancers originate from the epithelium, which covers the outer and inner surfaces of organs and blood vessels. In stratified epithelium, the bottom layers are occupied by stem and stem-like cells that continually divide and replenish the upper layers. In this work, we study the spread of premalignant mutant clones and cancer initiation in stratified epithelium, using the biased voter model on stacked two-dimensional lattices. Our main result is an estimate of the propagation speed of a premalignant mutant clone, which is asymptotically precise in the cancer-relevant weak-selection limit. We use our main result to study cancer initiation under a two-step mutational model of cancer, which includes computing the distributions of the time of cancer initiation and the size of the premalignant clone giving rise to cancer. Our work quantifies the effect of epithelial tissue thickness on the process of carcinogenesis, thereby contributing to an emerging understanding of the spatial evolutionary dynamics of cancer.

Original language	English (US)
Pages (from-to)	299-343
Number of pages	45
Journal	Annals of Applied Probability
Volume	33
Issue number	1
DOIs	https://doi.org/10.1214/22-AAP1816
State	Published - Feb 2023

Bibliographical note

Funding Information:
Funding. EBG and KL were supported in part by NSF Grant CMMI-1552764. EBG, JF and KS were supported in part by NSF Grants DMS-1349724 and DMS-2052465. KL and JF were supported in part by the U.S.–Norway Fulbright Foundation and the Research Council of Norway R&D Grant 309273. EBG was supported in part by the Norwegian Centennial Chair grant.

Publisher Copyright:
© Institute of Mathematical Statistics, 2023.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Spatial cancer models
biased voter model
branching coalescing random walks
evolutionary dynamics
field cancerization

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abstract = "Over 80\% of human cancers originate from the epithelium, which covers the outer and inner surfaces of organs and blood vessels. In stratified epithelium, the bottom layers are occupied by stem and stem-like cells that continually divide and replenish the upper layers. In this work, we study the spread of premalignant mutant clones and cancer initiation in stratified epithelium, using the biased voter model on stacked two-dimensional lattices. Our main result is an estimate of the propagation speed of a premalignant mutant clone, which is asymptotically precise in the cancer-relevant weak-selection limit. We use our main result to study cancer initiation under a two-step mutational model of cancer, which includes computing the distributions of the time of cancer initiation and the size of the premalignant clone giving rise to cancer. Our work quantifies the effect of epithelial tissue thickness on the process of carcinogenesis, thereby contributing to an emerging understanding of the spatial evolutionary dynamics of cancer.",

keywords = "Spatial cancer models, biased voter model, branching coalescing random walks, evolutionary dynamics, field cancerization",

author = "Jasmine Foo and Gunnarsson, \{Einar Bjarki\} and Kevin Leder and Kathleen Storey",

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language = "English (US)",

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AU - Storey, Kathleen

N1 - Funding Information: Funding. EBG and KL were supported in part by NSF Grant CMMI-1552764. EBG, JF and KS were supported in part by NSF Grants DMS-1349724 and DMS-2052465. KL and JF were supported in part by the U.S.–Norway Fulbright Foundation and the Research Council of Norway R&D Grant 309273. EBG was supported in part by the Norwegian Centennial Chair grant. Publisher Copyright: © Institute of Mathematical Statistics, 2023.

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N2 - Over 80% of human cancers originate from the epithelium, which covers the outer and inner surfaces of organs and blood vessels. In stratified epithelium, the bottom layers are occupied by stem and stem-like cells that continually divide and replenish the upper layers. In this work, we study the spread of premalignant mutant clones and cancer initiation in stratified epithelium, using the biased voter model on stacked two-dimensional lattices. Our main result is an estimate of the propagation speed of a premalignant mutant clone, which is asymptotically precise in the cancer-relevant weak-selection limit. We use our main result to study cancer initiation under a two-step mutational model of cancer, which includes computing the distributions of the time of cancer initiation and the size of the premalignant clone giving rise to cancer. Our work quantifies the effect of epithelial tissue thickness on the process of carcinogenesis, thereby contributing to an emerging understanding of the spatial evolutionary dynamics of cancer.

AB - Over 80% of human cancers originate from the epithelium, which covers the outer and inner surfaces of organs and blood vessels. In stratified epithelium, the bottom layers are occupied by stem and stem-like cells that continually divide and replenish the upper layers. In this work, we study the spread of premalignant mutant clones and cancer initiation in stratified epithelium, using the biased voter model on stacked two-dimensional lattices. Our main result is an estimate of the propagation speed of a premalignant mutant clone, which is asymptotically precise in the cancer-relevant weak-selection limit. We use our main result to study cancer initiation under a two-step mutational model of cancer, which includes computing the distributions of the time of cancer initiation and the size of the premalignant clone giving rise to cancer. Our work quantifies the effect of epithelial tissue thickness on the process of carcinogenesis, thereby contributing to an emerging understanding of the spatial evolutionary dynamics of cancer.

KW - Spatial cancer models

KW - biased voter model

KW - branching coalescing random walks

KW - evolutionary dynamics

KW - field cancerization

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SPREAD OF PREMALIGNANT MUTANT CLONES AND CANCER INITIATION IN MULTILAYERED TISSUE

Abstract

Bibliographical note

UN SDGs

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