Uncovering the Subtype-Specific Temporal Order of Cancer Pathway Dysregulation

Resource type
Date created
2019-11-11
Authors/Contributors
Abstract
Cancer is driven by genetic mutations that dysregulate pathways important for proper cell function. Therefore, discovering these cancer pathways and their dysregulation order is key to understanding and treating cancer. However, the heterogeneity of mutations between different individuals makes this challenging and requires that cancer progression is studied in a subtype-specific way. To address this challenge, we provide a mathematical model, called Subtype-specific Pathway Linear Progression Model (SPM), that simultaneously captures cancer subtypes and pathways and order of dysregulation of the pathways within each subtype. Experiments with synthetic data indicate the robustness of SPM to problem specifics including noise compared to an existing method. Moreover, experimental results on glioblastoma multiforme and colorectal adenocarcinoma show the consistency of SPM’s results with the existing knowledge and its superiority to an existing method in certain cases. The implementation of our method is available at https://github.com/Dalton386/SPM.
Document
Published as
Khakabimamaghani S, Ding D, Snow O, Ester M (2019) Uncovering the subtype-specific temporal order of cancer pathway dysregulation. PLoS Comput Biol 15(11): e1007451. DOI: 10.1371/journal.pcbi.1007451.
Publication title
PLoS Comput Biol
Document title
Uncovering the Subtype-Specific Temporal Order of Cancer Pathway Dysregulation
Date
2019
Volume
15
Issue
11
Publisher DOI
10.1371/journal.pcbi.1007451
Copyright statement
Copyright is held by the author(s).
Scholarly level
Peer reviewed?
Yes
Language
Member of collection
Attachment Size
journal.pcbi_.1007451.pdf 2.53 MB