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Development and validation of ferroptosis-related lncRNAs signature for hepatocellular carcinoma.

作者信息

Liang Jiaying, Zhi Yaofeng, Deng Wenhui, Zhou Weige, Li Xuejun, Cai Zheyou, Zhu Zhijian, Zeng Jinxiang, Wu Wanlan, Dong Ying, Huang Jin, Zhang Yuzhuo, Xu Shichao, Feng Yixin, Ding Fuping, Zhang Jin

机构信息

Guangzhou University of Chinese Medicine, School of Basic Medical Sciences, Guangzhou, China.

Guangzhou University of Chinese Medicine, Research Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou, China.

出版信息

PeerJ. 2021 Jun 11;9:e11627. doi: 10.7717/peerj.11627. eCollection 2021.


DOI:10.7717/peerj.11627
PMID:34178478
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8202323/
Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors throughout the world. However, there is no research to establish a ferroptosis-related lncRNAs (FRlncRNAs) signature for the patients with HCC. Therefore, this study was designed to establish a novel FRlncRNAs signature to predict the survival of patients with HCC. METHOD: The expression profiles of lncRNAs were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. FRlncRNAs co-expressed with ferroptosis-related genes were utilized to establish a signature. Cox regression was used to construct a novel three FRlncRNAs signature in the TCGA cohort, which was verified in the GEO validation cohort. RESULTS: Three differently expressed FRlncRNAs significantly associated with prognosis of HCC were identified, which composed a novel FRlncRNAs signature. According to the FRlncRNAs signature, the patients with HCC could be divided into low- and high-risk groups. Patients with HCC in the high-risk group displayed shorter overall survival (OS) contrasted with those in the low-risk group ( < 0.001 in TCGA cohort and = 0.045 in GEO cohort). This signature could serve as a significantly independent predictor in Cox regression (multivariate HR > 1, < 0.001), which was verified to a certain extent in the GEO cohort (univariate HR > 1, < 0.05). Meanwhile, it was also a useful tool in predicting survival among each stratum of gender, age, grade, stage, and etiology,etc. This signature was connected with immune cell infiltration (i.e., Macrophage, Myeloid dendritic cell, and Neutrophil cell, etc.) and immune checkpoint blockade targets (PD-1, CTLA-4, and TIM-3). CONCLUSION: The three FRlncRNAs might be potential therapeutic targets for patients, and their signature could be utilized for prognostic prediction in HCC.

摘要

相似文献

[1]
Development and validation of ferroptosis-related lncRNAs signature for hepatocellular carcinoma.

PeerJ. 2021-6-11

[2]
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[6]
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[7]
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[8]
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引用本文的文献

[1]
Long non-coding rnas as key modulators of the immune microenvironment in hepatocellular carcinoma: implications for Immunotherapy.

Front Immunol. 2025-4-25

[2]
Ferroptosis and its relationship with cancer.

Front Cell Dev Biol. 2025-1-14

[3]
Single-cell and bulk RNAseq unveils the immune infiltration landscape and targeted therapeutic biomarkers of psoriasis.

Front Genet. 2024-4-18

[4]
Machine learning-based disulfidptosis-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity in hepatocellular carcinoma.

Sci Rep. 2024-2-22

[5]
Bioinformatics identification of a T-cell-related signature for predicting prognosis and drug sensitivity in hepatocellular carcinoma.

IET Syst Biol. 2023-12

[6]
EXOSC10 is a novel hepatocellular carcinoma prognostic biomarker: a comprehensive bioinformatics analysis and experiment verification.

PeerJ. 2023

[7]
Combining bulk and single-cell RNA-sequencing data to develop an NK cell-related prognostic signature for hepatocellular carcinoma based on an integrated machine learning framework.

Eur J Med Res. 2023-8-30

[8]
Bioinformatics prediction and experimental verification identify cuproptosis-related lncRNA as prognosis biomarkers of hepatocellular carcinoma.

Biochem Biophys Rep. 2023-6-21

[9]
Machine learning-based prognostic modeling of lysosome-related genes for predicting prognosis and immune status of patients with hepatocellular carcinoma.

Front Immunol. 2023

[10]
A T-cell-related signature for prognostic stratification and immunotherapy response in hepatocellular carcinoma based on transcriptomics and single-cell sequencing.

BMC Bioinformatics. 2023-5-25

本文引用的文献

[1]
Advances in immunotherapy for hepatocellular carcinoma.

Nat Rev Gastroenterol Hepatol. 2021-8

[2]
Mechanistic Rationales Guiding Combination Hepatocellular Carcinoma Therapies Involving Immune Checkpoint Inhibitors.

Hepatology. 2021-10

[3]
Ferroptosis-Related Long Non-Coding RNA signature predicts the prognosis of Head and neck squamous cell carcinoma.

Int J Biol Sci. 2021

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Long non-coding RNA MAPKAPK5-AS1/PLAGL2/HIF-1α signaling loop promotes hepatocellular carcinoma progression.

J Exp Clin Cancer Res. 2021-2-17

[5]
LncRNA PART1 promotes cell proliferation and progression in non-small-cell lung cancer cells via sponging miR-17-5p.

J Cell Biochem. 2021-4

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IncRNA MAPKAPK5-AS1 promotes proliferation and migration of thyroid cancer cell lines by targeting miR-519e-5p/YWHAH.

Eur J Histochem. 2020-12-3

[7]
A Nuclear Long Non-Coding RNA LINC00618 Accelerates Ferroptosis in a Manner Dependent upon Apoptosis.

Mol Ther. 2021-1-6

[8]
Long Noncoding RNA Promotes Hepatocellular Carcinoma Progression via Targeting miR-590-3p/ Axis.

Onco Targets Ther. 2020-9-16

[9]
LncRNA RHPN1-AS1 Promotes Cell Proliferation, Migration and Invasion Through Targeting miR-7-5p and Activating PI3K/AKT/mTOR Pathway in Hepatocellular Carcinoma.

Technol Cancer Res Treat. 2020

[10]
LncRNA PVT1 regulates ferroptosis through miR-214-mediated TFR1 and p53.

Life Sci. 2020-8-20

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