Evidence map›Paper›PMID 31746439›Full record

ArticleOncology reports2020

Integrative analysis of mRNA and miRNA expression profiles reveals seven potential diagnostic biomarkers for non‑small cell lung cancer.

Jie Zhang, Dong Li, Yueming Zhang, Zongli Ding, Yulong Zheng, Song Chen, Yufeng Wan

Open access · hybridAbstract read
In one paragraph

Article in Oncology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

17 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
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  8. Hallmarks of exosomes.Future science OA · 2022
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  11. Circulating microRNAs as molecular biomarkers for lung adenocarcinoma.Cancer biomarkers : section A of Disease markers · 2022
    Article
  12. Article
  13. Cell Behavior of Non-Small Cell Lung Cancer Is at EGFR and MicroRNAs Hands.International journal of molecular sciences · 2021
    Review
  14. Review
  15. Article
  16. Review
  17. 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 at 3 institutions in 1 country.

Jie Zhang *Department of Respiratory Diseases, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, Jiangsu 223002, P.R. China.
Dong Li *Department of Ear‑Nose‑Throat, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, Jiangsu 223002, P.R. China.
Yueming ZhangDepartment of Respiratory Diseases, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, Jiangsu 223002, P.R. China.
Zongli DingDepartment of Respiratory Diseases, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, Jiangsu 223002, P.R. China.
Yulong ZhengDepartment of Respiratory Diseases, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, Jiangsu 223002, P.R. China.
Song ChenInstitute of Medicinal Biotechnology, Jiangsu College of Nursing, Huai'an, Jiangsu 223300, P.R. China.
Yufeng WanDepartment of Respiratory Diseases, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, Jiangsu 223002, P.R. China.
Xuzhou Medical College · CNSecond People’s Hospital of Huai’an · CNJiangsu Vocational College of Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to explore specific molecular targets for the diagnosis and treatment of non‑small cell lung cancer (NSCLC). The expression profiles of microRNAs (miRNAs) and mRNAs were downloaded from the GEO (GSE102286 and GSE101929) and TCGA databases. After data preprocessing, differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) in cancer and normal tissues were selected and used to construct a DEM‑DEG regulatory network and a protein‑protein interaction (PPI) network. The genes and miRNAs in these networks were subjected to functional enrichment and survival analyses. Several key DEMs and DEGs were verified using RT‑qPCR, and the results were statistically interpreted using a multivariate logistic regression analysis. In this study, 25 DEMs and 789 DEGs common to all datasets were identified, which were then used for the construction of a DEM‑DEG regulatory network and a PPI network module. Survival analyses of 19 DEMs in the DEM‑DEG regulatory network and 36 DEGs in the PPI network module revealed that 34 DEGs (including TOP2A, CCNB1, BIRC5, and TTK) and two miRNAs (miR‑21‑5p and miR‑31‑5p) were significantly associated with NSCLC prognosis. Moreover, RT‑qPCR analysis identified three DEGs and five DEMs that had changes in expression consistent with those observed in the bioinformatic analysis. Finally, a multivariate logistic regression analysis of the data showed that TOP2A, CCNB1, BIRC5, miR‑21‑5p, miR‑193b‑3p, miR‑210‑3p and miR‑31‑5p could be combined for the diagnosis of NSCLC. In conclusion, TOP2A, CCNB1, BIRC5, miR‑21‑5p, miR‑193b‑3p, miR‑210‑3p and miR‑31‑5p may therefore serve as important biomarkers and diagnostic targets for NSCLC.

Indexed as

Gene Regulatory NetworksA549 CellsAdultAgedBiomarkers, TumorCarcinoma, Non-Small-Cell LungCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansLung NeoplasmsMaleMicroRNAsMiddle AgedPrognosisBiomarkers, TumorMicroRNAsmicroRNAmRNAmultivariate logistic regression analysisnetworknon‑small cell lung cancer

Identifiers

PMID31746439
PMCPMC6908938
OpenAlexW2989474954

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.