Evidence map›Paper›PMID 35139863›Full record

ArticleCancer cell international2022

CPNE1 is a potential prognostic biomarker, associated with immune infiltrates and promotes progression of hepatocellular carcinoma.

Jinfang Su, Yongbiao Huang, Yali Wang, Rui Li, Wanjun Deng, Hao Zhang, Huihua Xiong

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Materials today. Bio · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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 1 institution in 1 country.

Jinfang Su *Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yongbiao Huang *Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yali WangDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Rui LiDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Wanjun DengDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hao ZhangDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Huihua XiongDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China. lizaabear@tjh.tjmu.edu.cn.ORCID http://orcid.org/0000-0001-8981-1165
Tongji Hospital · CN

Funding

Chinese Society of Clinical Oncology 2019075
6 · The paper itself

Abstract

backgroundCopine1 (CPNE1), the first discovered CPNE1 family member, participates in the process of carcinogenesis and development of diverse tumors. Our study aimed to investigate the expression and prognostic value of CPNE1 gene in hepatocellular carcinoma (HCC), to explore its functional network in HCC and its effects on biological behaviors.

methodsHCCDB, CCLE, HPA and LinkedOmics online databases were used to explore the expression of CPNE1 gene and analyze the co-expression network of CPNE1 in hepatocellular carcinoma. Gene set enrichment analysis (GSEA) was used for GO functional annotation, KEGG pathway enrichment analysis and regulators of CPNE1 networks in LIHC. HepG2 and MHCC-97H cells were selected to construct CPNE1 knockdown cell lines by transfection with siRNA, and Hep3B cell was selected to construct CPNE1 overexpression cell line by transfection with plasmid. The effect of CPNE1 on the proliferation of hepatocellular carcinoma cells was examined by CCK8 assay and clone formation assay; the effect of CPNE1 on the migration ability of hepatocellular carcinoma cells was assessed by cell scratch assay and Transwell cell migration assay; finally, the expression of related signaling pathway proteins was examined by Western Blot. The correlation of CPNE1 expression with immune infiltration and immune checkpoint molecules in HCC tissues was analyzed using TIMER online database and GSEA.

resultsCPNE1 was highly expressed in HCC tissues and significantly correlated with sex, age, cancer stage and tumor grade. Overall survival (OS) was significantly lower in patients with high CPNE1 expression than in patients with low CPNE1 expression, and CPNE1 could be used as an independent prognostic indicator for HCC. Knockdown of CPNE1 gene inhibited the AKT/P53 pathway, resulting in decreased proliferation, migration and invasion of HCC cells. Overexpression of CPNE1 gene showed the opposite results. The level of CPNE1 expression in HCC was significantly and positively correlated with the level of infiltration of B cells, CD8

conclusionsOur study firstly found the expression of CPNE1 was significantly higher in LIHC tissues than in normal liver tissues, and high CPNE1 expression was associated with poor prognosis. In addition, we identified the possible mechanism by which CPNE1 functioned in LIHC. CPNE1 influenced AKT/P53 pathway activation and LIHC cell proliferation and migration. There was a significant correlation between CPNE1 expression and tumor immune infiltration in LIHC.

Indexed as

AKT/P53CPNE1Hepatocellular carcinomaImmune infiltrationPrognosis

Identifiers

PMID35139863
PMCPMC8826718
OpenAlexW4210832856

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.