Evidence map›Paper›PMID 29631214›Full record

ArticleTranslational oncology2018

Identification of Prognostic Biomarkers by Combined mRNA and miRNA Expression Microarray Analysis in Pancreatic Cancer.

Bin Liu, Hai Yang, Leila Taher, Axel Denz, Robert Grützmann, Christian Pilarsky, Georg F Weber

Open access · goldAbstract read
In one paragraph

Article in Translational oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
3.1field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 51 citations in OpenAlex.

  1. Advancements in Cancer Survival Prediction: A Systematic Review of Classical and Modern Approaches.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2025
    Review
  2. TheJournal of gastrointestinal oncology · 2024
    Article
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  16. Hypoxia: a barricade to conquer the pancreatic cancer.Cellular and molecular life sciences : CMLS · 2020
    Review
  17. An Integrated Microarray Analysis Reveals Significant Diagnostic and Prognostic Biomarkers in Pancreatic Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
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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

7 authors at 2 institutions in 1 country.

Bin LiuDepartment of Surgery, Universitätsklinikum Erlangen, Krankenhausstraße 12, Erlangen, Germany.
Hai YangDepartment of Surgery, Universitätsklinikum Erlangen, Krankenhausstraße 12, Erlangen, Germany.
Leila TaherDivision of Bioinformatics, Department of Biology, Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany.
Axel DenzDepartment of Surgery, Universitätsklinikum Erlangen, Krankenhausstraße 12, Erlangen, Germany.
Robert GrützmannDepartment of Surgery, Universitätsklinikum Erlangen, Krankenhausstraße 12, Erlangen, Germany.
Christian PilarskyDepartment of Surgery, Universitätsklinikum Erlangen, Krankenhausstraße 12, Erlangen, Germany. Electronic address: christian.pilarsky@uk-erlangen.de.
Georg F WeberDepartment of Surgery, Universitätsklinikum Erlangen, Krankenhausstraße 12, Erlangen, Germany.
Universitätsklinikum Erlangen · DEFriedrich-Alexander-Universität Erlangen-Nürnberg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is the fourth leading cause for cancer-related death, and early diagnosis is one key to improve the survival rate of this disease. Molecular biomarkers are an important method for diagnostic use in pancreatic cancer. We used data from three mRNA microarray datasets and a microRNA dataset (GSE16515, GSE15471, GSE28735, and GSE41372) to identify potential key genes. Differentially expressed genes (DEGs) and microRNAs (DEMs) were identified. Functional, pathway enrichment, and protein-protein interaction analyses were performed on common DEGs across all datasets. The target genes of the DEMs were identified. DEMs targets that were also DEGs were further scrutinized using overall survival analysis. A total of 236 DEGs and 21 DEMs were identified. There were a total of four DEGs (ECT2, NR5A2, NRP2, and TGFBI), which were also predicted target genes of DEMs. Overall survival analysis showed that high expression levels of three of these genes (ECT2, NRP2, and TGFBI) were associated with poor overall survival for pancreatic cancer patients. The basic expression of DEGs in pancreas stood lower level in various organ tissues. The expression of ECT2 and NRP2 was higher in different pancreatic cancer cell lines than normal pancreas cell line. Knockout of ECT2 by Crispr Cas9 gene editing system decreased proliferation and migration ability in pancreatic cancer cell line MiaPaCa2. In conclusion, we think that data mining method can do well in biomarker screening, and ECT2 and NRP2 can play as potential biomarker or therapy target by Crispr Cas9 in pancreatic cancer.

Identifiers

PMID29631214
PMCPMC6154866
OpenAlexW2795400743

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.