Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

Malta, T. M., Sokolov, A., Gentles, A. J., Burzykowski, T., Poisson, L., Weinstein, J. N., Kaminska, B., Huelsken, J., Omberg, L., Gevaert, O., Colaprico, A., Czerwinska, P., Mazurek, S., Mishra, L., Heyn, H., Krasnitz, A., Godwin, A. K., Lazar, A. J., Stuart, J. M., Hoadley, K. A., Laird, P. W., Noushmehr, H., Wiznerowicz, M. (April 2018) Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation. Cell, 173 (2). 338-354.e15. ISSN 0092-8674

URL: https://www.ncbi.nlm.nih.gov/pubmed/29625051
DOI: 10.1016/j.cell.2018.03.034

Abstract

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.

Item Type: Paper
Uncontrolled Keywords: The Cancer Genome Atlas cancer stem cells dedifferentiation epigenomic genomic machine learning pan-cancer stemness
Subjects: diseases & disorders > cancer
bioinformatics > computational biology > algorithms > machine learning
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > stem cells
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > stem cells
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > stem cells
CSHL Authors:
Communities: CSHL labs > Krasnitz lab
Depositing User: Matt Covey
Date: 5 April 2018
Date Deposited: 24 Apr 2018 20:29
Last Modified: 15 Feb 2019 19:12
PMCID: PMC5902191
Related URLs:
URI: http://repository.cshl.edu/id/eprint/36512

Actions (login required)

Administrator's edit/view item Administrator's edit/view item
CSHL HomeAbout CSHLResearchEducationNews & FeaturesCampus & Public EventsCareersGiving