Evidence map›Paper›PMID 39227683›Full record

ArticleScientific reports2024

Apelin (APLN) is a biomarker contributing to the diagnosis and prognosis of hepatocellular carcinoma.

Xi Mao, Xiaoya Zhu, Tong Pan, Zehui Liu, Pingping Shangguan, Yi Zhang, Yingle Liu, Xiwen Jiang, Qi Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

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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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Apelin/APJ: Another Player in the Cancer Biology Network.International journal of molecular sciences · 2025
    Review
  5. 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

9 authors.

Xi Mao *State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China.
Xiaoya Zhu *State Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China.
Tong PanState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China.
Zehui LiuState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China.
Pingping ShangguanState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China.
Yi ZhangState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China.
Yingle LiuState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China. mvlwu@whu.edu.cn.
Xiwen JiangSchool of Life Sciences and Biopharmaceuticals, Guangdong Pharmaceutical University, Guangzhou, China. yuanyecat@vip.sina.com.
Qi ZhangState Key Laboratory of Virology, College of Life Sciences, Wuhan University, Wuhan, China. gracetey@whu.edu.cn.

Funding

National Key Research and Development Program of China 2018YFE0204503
6 · The paper itself

Abstract

Liver cancer, classified as a malignant hepatic tumor, can be divided into two categories: primary, originating within the liver, and secondary, resulting from metastasis to the liver from other organs. Hepatocellular carcinoma (HCC) is the main form of primary liver cancer and the third leading cause of cancer-related deaths. The diagnosis and prognosis of HCC using current methods still face numerous challenges. This study aims to develop novel diagnostic and prognostic models while identifying new biomarkers for improved HCC treatment. Diagnostic and prognostic models for HCC were constructed using traditional binary classification methods and machine learning algorithms based on the TCGA database (Downloaded in August 2023). The mechanisms by which APLN (Apelin) affects HCC were investigated using single-cell sequencing data sourced from the GEO database (GSE149614). The diagnostic models yielded by various algorithms could effectively distinguished HCC samples from normal ones. The prognostic model, composed of four genes, was constructed using LASSO and Cox regression algorithms, demonstrating good performance in predicting the three-year survival rate of HCC patients. The HCC biomarker Apelin (APLN) was identified in this study. APLN in liver cancer tissues mainly comes from endothelial cells and is associated with the carcinogenesis of these cells. APLN expression is significantly upregulated in liver cancer tissues, marking it as a viable indicator of endothelial cell malignancy in HCC. Furthermore, APLN expression was determined to be an independent predictor of tumor endothelial cell carcinogenesis, unaffected by its modifications such as single nucleotide variation, copy number variation, and methylation. Additionally, liver cancers characterized by high APLN expression are likely to progress rapidly after T2 stage. Our study presents diagnostic and prognostic models for HCC with appreciably improved accuracy and reliability compared to previous reports. APLN is a reliable HCC biomarker and contributes to the establishment of our models.

Indexed as

ApelinBiomarkers, TumorCarcinoma, HepatocellularLiver NeoplasmsFemaleGene Expression Regulation, NeoplasticHumansMalePrognosisApelinAPLN protein, humanBiomarkers, TumorBiomarkerDiagnosisHepatocellular carcinomaPrognosis

Identifiers

PMID39227683
PMCPMC11371925

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