Evidence map›Paper›PMID 31796663›Full record

ArticleCancer biomarkers : section A of Disease markers2020

MicroRNA-105 plays an independent prognostic role in esophageal cancer and acts as an oncogene.

Ruixiang Gao, Zhen Wang, Qiang Liu, Chunmei Yang

Abstract read
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

12 citing papers in PubMed.

  1. Article
  2. ESOMIR: a curated database of biomarker genes and miRNAs associated with esophageal cancer.Database : the journal of biological databases and curation · 2023
    Article
  3. Article
  4. Review
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  7. Article
  8. Regulation of miRNAs Expression by Mutant p53 Gain of Function in Cancer.Frontiers in cell and developmental biology · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. 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

4 authors.

Ruixiang GaoDepartment of Oncology, Dongying People's Hospital of Shandong Province, Dongying, Shandong, China.
Zhen WangDepartment of Thoracic Surgery, 970 Hospital of the PLA Joint Logistic Support Force, Yantai, Shandong, China.
Qiang LiuDepartment of Oncology, Dongying People's Hospital of Shandong Province, Dongying, Shandong, China.
Chunmei YangDepartment of Oncology, Dongying People's Hospital of Shandong Province, Dongying, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEsophageal cancer is a common tumor with high mortality worldwide. In the present study, we aimed to investigate the prognostic significance and regulatory effects of miR-105 on cellular functions of esophageal cancer cells.

methodsThe expression level of miR-105 was analyzed in esophageal cancer tissues and cell lines by qRT-PCR. Survival analysis was carried out using the Kaplan-Meier and the prognostic significance of miR-105 was analyzed with Cox regression analysis. The effects of miR-105 on cell proliferation, migration, and invasion abilities were detected with cellular experiments.

resultsWe found that miR-105 was significantly upregulated in esophageal cancer tissues and cell lines, compared with the control group, respectively. Moreover, overexpression of miR-105 was significantly associated with positive lymph node metastasis, advanced TNM stage, and poor overall survival. In addition, overexpression of miR-105 promoted cell proliferation, migration, and invasion in esophageal cancer cells, while downregulation of miR-105 suppressed these cellular behaviors.

conclusionOur findings indicate that a higher level of miR-105 predicts poorer prognosis in esophageal cancer patients, and miR-105 can promote esophageal cancer cell proliferation, migration, and invasion.

Indexed as

Case-Control StudiesCell MovementCell ProliferationEsophageal NeoplasmsFemaleHumansLymphatic MetastasisMaleMicroRNAsMiddle AgedNeoplasm InvasivenessPrognosisSurvival RateTumor Cells, CulturedMicroRNAsMIRN105 microRNA, humanesophageal cancerinvasionMicroRNA-105migrationprognosisproliferation

Identifiers

PMID31796663
PMCPMC12662286

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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.