Evidence map›Paper›PMID 28789354›Full record

ArticleOncology letters2017

Analysis of salivary microRNA expression profiles and identification of novel biomarkers in esophageal cancer.

Jiang Du, Lin Zhang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

19 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. A bioinformatics analysis for diagnostic roles of theJournal of gastrointestinal oncology · 2022
    Article
  6. Saliva Diagnostics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2022
    Review
  7. Article
  8. Observational
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Sample-to-answer salivary miRNA testing: New frontiers in point-of-care diagnostic technologies.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
    Review
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

2 authors at 1 institution in 1 country.

Jiang DuDepartment of Thoracic Surgery, Chinese Medical University Affiliated No. 1 Hospital, Shenyang, Liaoning 110001, P.R. China.
Lin ZhangDepartment of Thoracic Surgery, Chinese Medical University Affiliated No. 1 Hospital, Shenyang, Liaoning 110001, P.R. China.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs/miRs) regulate the expression of target genes and are considered to be associated with human cancer. The aim of the present study was to screen novel miRNA biomarkers in esophageal cancer (EC). The miRNA expression profile GSE41268 was extracted from Gene Expression Omnibus database, and differentially expressed miRNAs between whole saliva samples from patients with EC and healthy controls were identified using the Linear Models for Microarray Data package. Then, the targets of these miRNAs were screened using the miRecords database and used to construct the regulatory network. Gene ontology and pathway enrichment analyses were performed for the target genes of differentially expressed miRNAs to predict their potential functions. A total of 18 differentially expressed miRNAs were identified in saliva samples from patients with EC, and 43 validated target genes corresponding to 7 upregulated miRNAs were identified. Then, 6 miRNAs (miR-144, miR-451, miR-98, miR-10b, miR-486-5p and miR-363) and their target genes were used to construct a regulatory network. Within the network, miR-144 may target Notch homolog 1, fibrinogen α chain and fibrinogen β chain; miR-451 may regulate murine thymoma viral oncogene homolog 1, matrix metalloproteinase (

Indexed as

differentially expressedesophageal cancermicroRNAnetworktarget gene

Identifiers

PMID28789354
PMCPMC5529882
OpenAlexW2624629200

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.