Evidence map›Paper›PMID 28325915›Full record

ArticleScientific reports2017

Prognostic value of CA20, a score based on centrosome amplification-associated genes, in breast tumors.

Angela Ogden, Padmashree C G Rida, Ritu Aneja

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
1.3field-weighted citation impact, top 22% of its field
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

36 citing papers in PubMed, 49 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Angela OgdenDepartment of Biology, Georgia State University, Atlanta, GA, USA.
Padmashree C G RidaDepartment of Biology, Georgia State University, Atlanta, GA, USA.
Ritu AnejaDepartment of Biology, Georgia State University, Atlanta, GA, USA. raneja@gsu.edu.
Georgia State University · US

Funding

Evaluation of centrosome amplification as a risk-predictor for breast cancer aggrU01CA179671 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ANEJA, RITU · 2014 to 2018
$1.6M
NCI NIH HHS U01 CA179671
6 · The paper itself

Abstract

Centrosome amplification (CA) is a hallmark of cancer, observable in ≥75% of breast tumors. CA drives aggressive cellular phenotypes such as chromosomal instability (CIN) and invasiveness. Thus, assessment of CA may offer insights into the prognosis of breast cancer and identify patients who might benefit from centrosome declustering agents. However, it remains unclear whether CA is correlated with clinical outcomes after adjusting for confounding factors. To gain insights, we developed a signature, "CA20", comprising centrosome structural genes and genes whose dysregulation is implicated in inducing CA. We found that CA20 was a significant independent predictor of worse survival in two large independent datasets after adjusting for potentially confounding factors. In multivariable analyses including both CA20 and CIN25 (a gene expression-based score that correlates with aneuploidy and has prognostic value in many types of cancer), only CA20 was significant, suggesting CA20 captures the risk-predictive information of CIN25 and offers information beyond it. CA20 correlated strongly with CIN25, so a high CA20 score may reflect tumors with high CIN and potentially other aggressive features that may require more aggressive treatment. Finally, we identified processes and pathways differing between CA20-low and high groups that may be valuable therapeutic targets.

Indexed as

CentrosomeGene DosageBreast NeoplasmsFemaleHumansNeoplasm GradingPathology, MolecularPrognosisSurvival Analysis

Identifiers

PMID28325915
PMCPMC5428291
OpenAlexW2709293732

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.