A six lipid metabolism related gene signature for predicting the prognosis of hepatocellular carcinoma

Xu, Kequan; Xia, Peng; Liu, Pan; Zhang, Xiao

doi:10.1038/s41598-022-25356-2

Cited by 14 publications

(10 citation statements)

References 16 publications

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“…Consequently, some researchers have examined the relationship between metabolism-related genes, lipid metabolism-related genes, and CYP2C subfamily genes and the prognosis of liver cancer patients. These studies have confirmed that CYP2C9 is an independent prognostic factor with high diagnostic value (Wang et al 2018 ; Huo et al 2021 ; Xu et al 2022 ). These studies have performed differential gene analysis on liver cancer data from multiple datasets of the TCGA database and GEO.…”

Section: Discussionmentioning

confidence: 71%

Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma

et al. 2023

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Hepatocellular carcinoma (HCC) is a challenging disease to evaluate in terms of prognosis, requiring close attention to the prognosis of HCC patients. Exosomes have been shown to play an important role in HCC development and have significant potential in managing HCC patient prognosis, as they are detectable in patients’ blood. By using small extracellular vesicular RNA, liquid biopsies can reflect the underlying physiological and pathological status of the originating cells, providing a valuable assessment of human health. No study has explored the diagnostic value of mRNA expression changes in exosomes for liver cancer. The present study investigated establishing a risk prognosis model based on mRNA expression levels in exosomes from blood samples of liver cancer patients and evaluated its diagnostic and prognostic value, providing new targets for liver cancer detection. We obtained mRNA data from HCC patients and normal controls from the TCGA and exoRBase 2.0 databases and established a risk prognostic assessment model using exosomes-related risk genes selected through prognostic analysis and Lasso Cox analysis. The patients were divided into high-risk and low-risk groups based on median risk score values to validate the independence and evaluability of the risk score. The clinical value of the model was further analyzed using a nomograph model, and the efficacy of immunotherapy and cell-origin types of prognostic risk genes were further assessed in the high- and low-risk groups by immune checkpoint and single-cell sequencing. A total of 44 genes were found to be significantly associated with the prognosis of HCC patients. From this group, we selected six genes (CLEC3B, CYP2C9, GNA14, NQO1, NT5DC2, and S100A9) as exosomal risk genes and used them as a basis for the risk prognosis model. The clinical information of HCC patients from the TCGA and ICGC databases demonstrated that the risk prognostic score of the model established in this study was an independent prognostic factor with good robustness. When pathological stage and risk prognostic score were incorporated into the model to predict clinical outcomes, the nomograph model had the best clinical benefit. Furthermore, immune checkpoint assays and single-cell sequencing analysis suggested that exosomal risk genes were derived from different cell types and that immunotherapy in the high-risk groups could be beneficial. Our study demonstrated that the prognostic scoring model based on exosomal mRNA was highly effective. The six genes selected using the scoring model have been previously reported to be associated with the occurrence and development of liver cancer. However, this study is the first to confirm that these related genes existed in the blood exosomes, which could be used for liquid biopsy of patients with liver cancer, thereby avoiding the need for puncture diagnosis. This approach has a high value in clinical application. Through single-cell sequencing, we found that the six genes in the risk model originate from multiple cell types. This finding suggests that the exosomal characteristic molecules secreted by different types of cells in the microenvironment of liver cancer may serve as diagnostic markers.

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Section: Discussionmentioning

confidence: 71%

Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma

et al. 2023

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“…Out of these patients, 371 samples possess complete survival information for subsequent survival and clinical analysis. The transcriptomic data underwent log2 transformation in order to standardize the gene expression data within each sample [ 13 ]. By utilizing Ensembl's annotation file, we successfully extracted the expression levels of both mRNA and lncRNA genes.…”

Section: Methodsmentioning

confidence: 99%

“…The analysis of differentially expressed DRLs between gastric cancer and its corresponding normal tissues (n = 32) was carried out utilizing the limma package [ 13 ]. DRLs that exhibited a notable distinction in expression levels within gastric cancer were identified employing a cutoff of |logFC| ≥ 1 and false discovery rate (FDR) adjusted p-value <0.05.…”

Section: Methodsmentioning

confidence: 99%

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Disulfidptosis-related lncRNA signature reveals immune microenvironment and novel molecular subtyping of stomach adenocarcinoma

Li,

Xia,

Song

et al. 2024

Heliyon

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“…According to recent research, metabolic reprogramming is crucial to cancer progression. Particularly, the Warburg effect, wherein cancer cells are dependent on glucose as a substrate under aerobic conditions, is important to the pathogenesis of HCC [ 7 – 10 ]. The Warburg effect regulates HCC proliferation, immune escape, invasion, metastasis, angiogenesis, and drug resistance.…”

Section: Introductionmentioning

confidence: 99%

LncRNA RP11-620J15.3 promotes HCC cell proliferation and metastasis by targeting miR-326/GPI to enhance glycolysis

Liu

et al. 2023

Biol Direct

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Background Accumulating studies have demonstrated that the Warburg effect plays a central role in the occurrence and development of hepatocellular carcinoma (HCC), albeit the role of non-coding RNA (lncRNA) in its association remains unclear. Methods The Zhengzhou University People’s Hospital kindly provided 80 pairs of HCC tissues and their matched paracancerous tissues for this study. Bioinformatics analysis, real-time quantitative polymerase chain reaction, Western blotting, and oncology functional assays were performed to determine the contribution of RP11-620J15.3 to the development of HCC. The mechanism of co-immunoprecipitation and a luciferase reporter gene was employed to ascertain how RP11-620J15.3 interacts with important molecular targets. Results Our results revealed that a lncRNA termed RP11-620J15.3 was overexpressed in HCC and was substantially associated with the tumor size. A high expression of RP11-620J15.3 mRNA was found to be significantly associated with worsening prognosis in HCC patients. We discovered that RP11-620J15.3 stimulated the glycolytic pathway in HCC cells by RNA-sequencing (RNA-seq) and metabolomics analyses. Mechanistically, RP11-620J15.3 acted as a competitive endogenous RNA to regulate the GPI expression by sponging miR-326 in HCC. In addition, TBP acted as a transcription factor for RP11-620J15.3, which contributed to the high expression of RP11-620J15.3 in HCC cells. Conclusion Based on our findings, lncRNA RP11-620J15.3 is a novel LncRNA that positively regulates tumor progression. Specifically, RP11-620J15.3/miR-326/GPI pathway promotes HCC malignant progression by regulating glycolysis, thereby providing novel targets for HCC treatment and drug development.

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A six lipid metabolism related gene signature for predicting the prognosis of hepatocellular carcinoma

Cited by 14 publications

References 16 publications

Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma

Establishment and Evaluation of Exosomes-Related Gene Risk Model in Hepatocellular Carcinoma

Disulfidptosis-related lncRNA signature reveals immune microenvironment and novel molecular subtyping of stomach adenocarcinoma

LncRNA RP11-620J15.3 promotes HCC cell proliferation and metastasis by targeting miR-326/GPI to enhance glycolysis

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