Evidence map›Paper›PMID 34049287›Full record

ArticleAging2021

Comprehensive analysis of the competing endogenous circRNA-lncRNA-miRNA-mRNA network and identification of a novel potential biomarker for hepatocellular carcinoma.

Lu Zhang, Haisu Tao, Jiang Li, Erlei Zhang, Huifang Liang, Bixiang Zhang

Open access · hybridAbstract read
In one paragraph

Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

31 citing papers in PubMed, 61 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

6 authors at 2 institutions in 1 country.

Lu ZhangHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China.
Haisu TaoHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China.
Jiang LiHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China.
Erlei ZhangHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China.
Huifang LiangHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China.
Bixiang ZhangHepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China.
Huazhong University of Science and Technology · CNTongji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe competing endogenous RNAs (ceRNAs) hypothesis has received increasing attention as a novel explanation for tumorigenesis and cancer progression. However, there is still a lack of comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in hepatocellular carcinoma (HCC).

methodsRNA sequencing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were employed to identify Differentially Expressed mRNAs (DEmRNAs), DElncRNAs, and DEcircRNAs between HCC and normal tissues. Candidates were identified to construct networks through a comprehensive bioinformatics strategy. A prognostic mRNA signature was established based on data from TCGA database and validated using data from the GEO database. Then, the HCC prognostic circRNA-lncRNA-miRNA-mRNA ceRNA network was established. Finally, the expression and function of an unexplored hub gene, deoxythymidylate kinase (DTYMK), was explored through data mining. The results were examined using clinical samples and

resultsWe constructed a prognostic signature with seven target mRNAs by univariate, lasso and multivariate Cox regression analyses, which yielded 1, 3 and 5-year AUC values of 0.797, 0.733 and 0.721, respectively, indicating its sensitivity and specificity in the prognosis of HCC. Moreover, the prognostic signature could be validated in GSE14520. The prognostic ceRNA network of 21 circRNAs, 15 lncRNAs, 5 miRNAs, and 7 mRNAs was established according to the targeting relationship between 7 hub mRNAs and other RNAs. Our experiment results indicated that the depletion of DTYMK inhibited liver cancer cell proliferation and invasion.

conclusionsThe network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving HCC, and provide novel candidate biomarkers for evaluating the prognosis of HCC.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksCarcinoma, HepatocellularCell Line, TumorCell MovementGene Expression ProfilingHumansLiver NeoplasmsMicroRNAsModels, BiologicalNeoplasm InvasivenessNucleoside-Phosphate KinasePrognosisReproducibility of ResultsRisk FactorsRNA, CirculardTMP kinaseMicroRNAsNucleoside-Phosphate KinaseRNA, CircularRNA, Long NoncodingRNA, MessengerceRNA networkDTYMKHCCprognostic signature

Identifiers

PMID34049287
PMCPMC8266324
OpenAlexW3164167256

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.