Evidence map›Paper›PMID 31358840›Full record

ArticleScientific reports2019

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

Nishanth Ulhas Nair, Avinash Das, Vasiliki-Maria Rogkoti, Michiel Fokkelman, Richard Marcotte, Chiaro G de Jong, Esmee Koedoot, Joo Sang Lee, Isaac Meilijson, Sridhar Hannenhalli and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

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  16. A comparative assessment ofRSC advances · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Nishanth Ulhas NairCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA.
Avinash DasDepartment of Biostatistics and Computational Biology, Harvard School of Public Health, Boston, USA.
Vasiliki-Maria RogkotiDivision of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands.
Michiel FokkelmanDivision of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands.ORCID http://orcid.org/0000-0002-6937-9384
Richard MarcottePrincess Margaret Cancer Centre, University Health Network, Toronto, ON, M5G 1L7, Canada.
Chiaro G de JongDivision of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands.
Esmee KoedootDivision of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands.
Joo Sang LeeCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA.
Isaac MeilijsonDepartment of Statistics and Operations Research, School of Mathematical Sciences, Tel Aviv University, Tel Aviv, 69978, Israel.
Sridhar HannenhalliCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA.
Benjamin G NeelPrincess Margaret Cancer Centre, University Health Network, Toronto, ON, M5G 1L7, Canada.
Bob van de WaterDivision of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands.
Sylvia E Le DévédecDivision of Drug Discovery and Safety, LACDR, Leiden University, Leiden, The Netherlands.ORCID http://orcid.org/0000-0002-0615-9616
Eytan RuppinCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, 20742, USA. eytan.ruppin@nih.gov.

Funding

Discovery of genetic interactions in cancerZIABC011802 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI RUPPIN, EYTAN · 2018 to 2025
$19.6M
6 · The paper itself

Abstract

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.

Indexed as

Cell MovementCell ProliferationTranscriptomeBreast NeoplasmsCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansNeoplasm InvasivenessPrognosisSurvival Analysis

Identifiers

PMID31358840
PMCPMC6662662

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.