Evidence map›Paper›PMID 34336642›Full record

ArticleFrontiers in oncology2021

Construction of Novel lncRNA-miRNA-mRNA Network Associated With Recurrence and Identification of Immune-Related Potential Regulatory Axis in Hepatocellular Carcinoma.

Tian Zhan, Xiang Gao, Guoguang Wang, Fan Li, Jian Shen, Chen Lu, Lei Xu, Yuan Li, Jianping Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.9field-weighted citation impact, top 7% 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

28 citing papers in PubMed, 40 citations in OpenAlex.

  1. Review
  2. LncRNA SNHG3: a potential biomarker for human diseases.Frontiers in cell and developmental biology · 2026
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  15. The role of LncRNAs in tumor immunotherapy.Cancer cell international · 2023
    Review
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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

9 authors at 2 institutions in 1 country.

Tian ZhanDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Xiang GaoDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Guoguang WangDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Fan LiDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Jian ShenDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Chen LuDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Lei XuDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Yuan LiThe Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China.
Jianping ZhangDepartment of General Surgery, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Nanjing Medical University · CNSecond Affiliated Hospital of Nanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is one of the most common malignant diseases globally. Despite continuous improvement of treatment methods, high postoperative recurrence rate remains an urgent problem. In order to determine the mechanism underlying recurrence of liver cancer and identify prognostic genes, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were integrated and analyzed. Differentially expressed genes (DEGs) between HCC tissue and normal liver tissue were identified, and a protein-protein interaction network was constructed to find hub genes. Clinical correlation analysis and disease-free survival (DFS) analysis were performed using the R language and GEPIA to identify relapse-related genes. Correlation analysis was used to identify a potential regulatory axis. Dual-luciferase reporter gene assay was used to confirm the reliability of the long non-coding RNA (lncRNA)-microRNA (miRNA)-mRNA regulatory axis. Immune infiltration analysis was performed using the TIMER database. Correlations between immune gene markers and ASF1B were verified using quantitative real-time polymerase chain reaction (RT-qPCR). In this work, we found that nine lncRNAs and five mRNAs were significantly overexpressed in HCC tissues from patients with recurrence.

Indexed as

ASF1BHCCimmune infiltrationlncRNA-miRNA-mRNA networkrecurrence

Identifiers

PMID34336642
PMCPMC8320021
OpenAlexW3185196559

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.