Expression and prognostic signatures of m6A-related lncRNAs in hepatocellular carcinoma

Hao, Kenan; Li, Jincheng; Zhang, Youao; Zhao, Wei; Chen, Xiaojing; Xu, Jiabin; Tian, Ye; Li, Xinmin; Fen, Jianyu; He, Xiaofeng

doi:10.1007/s00432-022-04338-x

Cited by 4 publications

(2 citation statements)

References 28 publications

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“…Currently, the clinical treatment methods include surgery, interventional therapy, local ablation [2], and targeted drugs [3]. Despite recent breakthroughs in treatment strategies, the prognosis of patients remains notably poor, with a high likelihood of recurrence and significant accompanying complications causing considerable distress to patients [4,5]. Therefore, it is imperative to conduct accurate prognostic screenings to identify risk factors tailored to the specific conditions of patients with liver cancer.…”

Section: Introductionmentioning

confidence: 99%

A prognostic aging-related lncRNA risk model correlates with the immune microenvironment in HCC

Mei,

Chen,

Wang

et al. 2024

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Background: Hepatocellular carcinoma (HCC) stands out as one of the most lethal cancers globally, given its complexity, recurrence following surgical resection, metastatic potential, and inherent heterogeneity. In recent years, researchers have systematically elucidated the significance of long non-coding RNA (lncRNA) in the initiation and progression of HCC. The introduction of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases has significantly enhanced the prognostic assessment of HCC. However, the association between HCC and cell senescence has been infrequently explored in the literature. Method: We downloaded liver hepatocellular carcinoma (LIHC)-related messenger RNA and lncRNA expression levels from TCGA. Correlation analysis, Cox regression, and least absolute shrinkage and selection operator (LASSO) regression analysis were employed to validate the lncRNA risk model associated with cellular aging. Comparing the infiltration of diverse immune cells enabled the identification of distinct differences in the immunological microenvironments of the two risk groups. Subsequently, we conducted a real-time polymerase chain reaction (qPCR) experiment to confirm the accuracy of the selected lncRNAs. Results: A predictive framework for HCC was constructed based on the expression levels of five lncRNAs. Multivariate and univariate Cox regression analyses revealed that lncRNA signatures associated with senescence were independently correlated with an increased risk of HCC. Additionally, the nomogram also provides a more refined and sensitive model. Further investigation into the variations in immune cells and functions between the high-risk and low-risk groups was conducted. Subsequently, a qPCR experiment results revealed underexpression of AC068756.1, AC090578.1, AC145343.1, and LINC0022 in Huh7 and LM3 cells. In contrast, AP003392.4 did not exhibit a significant difference between Huh7 and control cells. Conclusion: The prognostic features and nomogram, consisting of five aging-related lncRNAs (AC068756.1, AC090578.1, AC145343.1, AP003392.4, and LINC00221), may be useful in predicting the overall survival of HCC.

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Section: Introductionmentioning

confidence: 99%

A prognostic aging-related lncRNA risk model correlates with the immune microenvironment in HCC

Mei,

Chen,

Wang

et al. 2024

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“…The study found T significant differences in progression-free survival (PFS), expression of three tumor microenvironment (TME)-related scores, 15 immune-related gene sets, and two immune checkpoints between the two subtypes [ 27 ]. Another study by Hao et al highlighted the potential prognostic value of m6A-associated lncRNAs in HCC by reporting the significant differences in the expression levels of m6A-lncRNAs in HCC [ 28 ]. However, more precise prognostic models are necessary for the precise treatment of HCC.…”

Section: Introductionmentioning

confidence: 99%

Cuproptosis- and m6A-Related lncRNAs for Prognosis of Hepatocellular Carcinoma

Zhu

Tan

Goon

2023

Biology

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Cuproptosis and N6-methyladenosine (m6A) have potential as prognostic predictors in cancer patients, but their roles in hepatocellular carcinoma (HCC) are unclear. This study aimed to screen a total of 375 HCC samples were retrieved from the TCGA database, and lncRNAs related to cuproptosis and m6A were obtained through correlation analysis. To construct a risk assessment model, univariate Cox regression analysis and LASSO Cox regression were employed. Analyze the regulatory effect of relevant risk assessment models on tumor mutation load (TMB) and immune microenvironment. A total of five lncRNAs (AC007405.3, AL031985.3, TMCC1-AS1, MIR210HG, TMEM220-AS1) with independent overall survival-related risk models were obtained by LASSO survival regression. TP53 and CTNNB1 were the three genes found to have the most mutations in high-risk group patients. The high-risk group with low TMB had the worst survival, whereas the low-risk group with high TMB had the best survival. KEGG pathway analysis revealed that the high-risk group was enriched with cell cycle, oocyte meiosis, cell senescence, and glycolysis/glucose production pathways. We constructed a reliable cuproptosis- and m6A-related lncRNA model for the prognosis of HCC. The model may provide new insights into managing HCC patients, but further research is needed to validate it.

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