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

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.

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Publication Details

Journal
Scientific Reports
Published
2024-09-03
DOI
https://doi.org/10.1038/s41598-024-71495-z
Citations
8
Primary Topic
Apelin-related biomedical research
Type
article
Field-Weighted Citation Impact
3.58

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article

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

Yingle Liu, Xiwen Jiang, Pingping Shangguan, Yi Zhang et al.
8 citations
Scientific Reports
Apelin-related biomedical research
3.58
article

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

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

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.

Scientific ReportsVol. 14(1)
Guangdong Pharmaceutical University (CN), Wuhan University (CN)
National Key Research and Development Program of China
Good health and well-being
Openalex Percentile: Top 7%
Apelin-related biomedical research
3.58
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