Migration rather than proliferation transcriptomic signatures are strongly associated with breast cancer patient survival.

Autor:	Nair NU; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA.; Cancer Data Science Lab, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA., Das A; Department of Biostatistics and Computational Biology, Harvard School of Public Health, Boston, USA.; Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, USA., Rogkoti VM; Division of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands., Fokkelman M; Division of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands., Marcotte R; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, M5G 1L7, Canada.; National Research Council Canada, Montreal, Canada., de Jong CG; Division of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands., Koedoot E; Division of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands., Lee JS; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA.; Cancer Data Science Lab, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA., Meilijson I; Department of Statistics and Operations Research, School of Mathematical Sciences, Tel Aviv University, Tel Aviv, 69978, Israel., Hannenhalli S; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA., Neel BG; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, M5G 1L7, Canada.; Laura and Isaac Perlmutter Cancer Centre, NYU-Langone Medical Center, New York City, NY, 10016, USA.; Alexandria Center for Life Science, New York, NY, 10016, USA., de Water BV; Division of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands., Le Dévédec SE; Division of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands., Ruppin E; Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA. eytan.ruppin@nih.gov.; Cancer Data Science Lab, National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA. eytan.ruppin@nih.gov.; The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, 69978, Israel. eytan.ruppin@nih.gov.
Jazyk:	angličtina
Zdroj:	Scientific reports [Sci Rep] 2019 Jul 29; Vol. 9 (1), pp. 10989. Date of Electronic Publication: 2019 Jul 29.
DOI:	10.1038/s41598-019-47440-w
Abstrakt:	The efficacy of prospective cancer treatments is routinely estimated by in vitro cell-line proliferation screens. However, it is unclear whether tumor aggressiveness and patient survival are influenced more by the proliferative or the migratory properties of cancer cells. To address this question, we experimentally measured proliferation and migration phenotypes across more than 40 breast cancer cell-lines. Based on the latter, we built and validated individual predictors of breast cancer proliferation and migration levels from the cells' transcriptomics. We then apply these predictors to estimate the proliferation and migration levels of more than 1000 TCGA breast cancer tumors. Reassuringly, both estimates increase with tumor's aggressiveness, as qualified by its stage, grade, and subtype. However, predicted tumor migration levels are significantly more strongly associated with patient survival than the proliferation levels. We confirmed these findings by conducting siRNA knock-down experiments on the highly migratory MDA-MB-231 cell lines and deriving gene knock-down based proliferation and migration signatures. We show that cytoskeletal drugs might be more beneficial in patients with high predicted migration levels. Taken together, these results testify to the importance of migration levels in determining patient survival.
Databáze:	MEDLINE
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