Evidence map›Paper›PMID 27150055›Full record

ArticleOncotarget2016

Identification of breast cancer candidate genes using gene co-expression and protein-protein interaction information.

Zhenyu Yue, Hai-Tao Li, Yabing Yang, Sajid Hussain, Chun-Hou Zheng, Junfeng Xia, Yan Chen

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Role of tRNAs in Breast Cancer Regulation.Advances in experimental medicine and biology · 2021
    Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. An In Vitro Assay to Detect tRNA-Isopentenyl Transferase Activity.Journal of visualized experiments : JoVE · 2018
    Article
  12. Article
  13. Article
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

7 authors.

Zhenyu YueSchool of Life Sciences, Anhui University, Hefei, Anhui 230601, China.
Hai-Tao LiCollege of Electrical Engineering and Automation, Anhui University, Hefei, Anhui 230601, China.
Yabing YangSchool of Life Sciences, Anhui University, Hefei, Anhui 230601, China.
Sajid HussainSchool of Life Sciences, Anhui University, Hefei, Anhui 230601, China.
Chun-Hou ZhengCollege of Electrical Engineering and Automation, Anhui University, Hefei, Anhui 230601, China.
Junfeng XiaInstitute of Health Sciences, Anhui University, Hefei, Anhui 230601, China.
Yan ChenSchool of Life Sciences, Anhui University, Hefei, Anhui 230601, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) is one of the most common malignancies that could threaten female health. As the molecular mechanism of BC has not yet been completely discovered, identification of related genes of this disease is an important area of research that could provide new insights into gene function as well as potential treatment targets. Here we used subnetwork extraction algorithms to identify novel BC related genes based on the known BC genes (seed genes), gene co-expression profiles and protein-protein interaction network. We computationally predicted seven key genes (EPHX2, GHRH, PPYR1, ALPP, KNG1, GSK3A and TRIT1) as putative genes of BC. Further analysis shows that six of these have been reported as breast cancer associated genes, and one (PPYR1) as cancer associated gene. Lastly, we developed an expression signature using these seven key genes which significantly stratified 1660 BC patients according to relapse free survival (hazard ratio [HR], 0.55; 95% confidence interval [CI], 0.46-0.65; Logrank p = 5.5e-13). The 7-genes signature could be established as a useful predictor of disease prognosis in BC patients. Overall, the identified seven genes might be useful prognostic and predictive molecular markers to predict the clinical outcome of BC patients.

Indexed as

Gene Expression Regulation, NeoplasticBiomarkers, TumorBreast NeoplasmsFemaleGene Expression ProfilingGene Regulatory NetworksGenetic Predisposition to DiseaseHumansKaplan-Meier EstimatePrognosisProportional Hazards ModelsProtein Interaction MapsBiomarkers, Tumorbreast cancercandidate genegene co-expressionprotein-protein interactionsubnetwork extraction algorithm

Identifiers

PMID27150055
PMCPMC5094985

What OpenQuestion holds

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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.