Construction of a prognostic model for HCC based on ferroptosis-related lncRNAs expression and its potential to predict the response and irAEs of immunotherapy

Dong, Lemeng; Zhou, Shengnan; Bai, Xuesong; He, Xiaodong

doi:10.3389/fphar.2023.1090895

Cited by 4 publications

(3 citation statements)

References 52 publications

(54 reference statements)

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“…Studies have revealed that plasma level of HULC and NEAT1 are markedly elevated in HCC patients [ 144 , 145 ], serving as significant predictors of HCC tumor growth and metastasis, which hold promise as non-invasive biomarkers for diagnosing hepatoma, and their diagnostic accuracy may be enhanced when combined with AFP [ 145 – 147 ]. Moreover, several studies have developed HCC prognostic models based on ferroptosis-related lncRNA signatures, aiming to enhance survival prognostication in HCC through tumor classification [ 127 , 148 ]. These ferroptosis-related lncRNAs significantly contribute to the immunosuppressive tumor microenvironment and clinically therapeutic response in HCC, potentially aiding in individualized prognosis determination and treatment planning for HCC patients [ 127 , 148 ].…”

Section: Ferroptosis-related Lncrnas In Hcc Progression and Prognosismentioning

confidence: 99%

“…Moreover, several studies have developed HCC prognostic models based on ferroptosis-related lncRNA signatures, aiming to enhance survival prognostication in HCC through tumor classification [ 127 , 148 ]. These ferroptosis-related lncRNAs significantly contribute to the immunosuppressive tumor microenvironment and clinically therapeutic response in HCC, potentially aiding in individualized prognosis determination and treatment planning for HCC patients [ 127 , 148 ]. For example, Wang and his colleagues have established a model based on ferroptosis-related lncRNAs that could accurately predict HCC prognosis, with associations to tumor grade, macrophage and fibroblast infiltration [ 149 ].…”

Section: Ferroptosis-related Lncrnas In Hcc Progression and Prognosismentioning

confidence: 99%

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The multifaceted perspectives on the regulation of lncRNAs in hepatocellular carcinoma ferroptosis: from bench-to-bedside

Jin,

Huang,

Tian

2024

Clin Exp Med

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Despite being characterized by high malignancy, high morbidity, and low survival rates, the underlying mechanism of hepatocellular carcinoma (HCC) has not been fully elucidated. Ferroptosis, a non-apoptotic form of regulated cell death, possesses distinct morphological, biochemical, and genetic characteristics compared to other types of cell death. Dysregulated actions within the molecular network that regulates ferroptosis have been identified as significant contributors to the progression of HCC. Long non-coding RNAs (lncRNAs) have emerged as influential contributors to diverse cellular processes, regulating gene function and expression through multiple mechanistic pathways. An increasing body of evidence indicates that deregulated lncRNAs are implicated in regulating malignant events such as cell proliferation, growth, invasion, and metabolism by influencing ferroptosis in HCC. Therefore, elucidating the inherent role of ferroptosis and the modulatory functions of lncRNAs on ferroptosis in HCC might promote the development of novel therapeutic interventions for this disease. This review provides a succinct overview of the roles of ferroptosis and ferroptosis-related lncRNAs in HCC progression and treatment, aiming to drive the development of promising therapeutic targets and biomarkers for HCC patients.

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Section: Ferroptosis-related Lncrnas In Hcc Progression and Prognosismentioning

confidence: 99%

Section: Ferroptosis-related Lncrnas In Hcc Progression and Prognosismentioning

confidence: 99%

The multifaceted perspectives on the regulation of lncRNAs in hepatocellular carcinoma ferroptosis: from bench-to-bedside

Jin,

Huang,

Tian

2024

Clin Exp Med

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“…With the advancements in bioinformatics technology, several prognostic gene characteristics have been developed (16,17). In the case of HCC, numerous multi-gene signature characteristics, such as the well-known ferroptosis signature (18), m6A signature (19), and others (20), have been discovered to assess patient risk.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based integration develops a neutrophil-derived signature for improving outcomes in hepatocellular carcinoma

et al. 2023

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IntroductionThe heterogeneity of tumor immune microenvironments is a major factor in poor prognosis among hepatocellular carcinoma (HCC) patients. Neutrophils have been identified as playing a critical role in the immune microenvironment of HCC based on recent single-cell studies. However, there is still a need to stratify HCC patients based on neutrophil heterogeneity. Therefore, developing an approach that efficiently describes "neutrophil characteristics" in HCC patients is crucial to guide clinical decision-making.MethodsWe stratified two cohorts of HCC patients into molecular subtypes associated with neutrophils using bulk-sequencing and single-cell sequencing data. Additionally, we constructed a new risk model by integrating machine learning analysis from 101 prediction models. We compared the biological and molecular features among patient subgroups to assess the model's effectiveness. Furthermore, an essential gene identified in this study was validated through molecular biology experiments.ResultsWe stratified patients with HCC into subtypes that exhibited significant differences in prognosis, clinical pathological characteristics, inflammation-related pathways, levels of immune infiltration, and expression levels of immune genes. Furthermore, A risk model called the "neutrophil-derived signature" (NDS) was constructed using machine learning, consisting of 10 essential genes. The NDS's RiskScore demonstrated superior accuracy to clinical variables and correlated with higher malignancy degrees. RiskScore was an independent prognostic factor for overall survival and showed predictive value for HCC patient prognosis. Additionally, we observed associations between RiskScore and the efficacy of immune therapy and chemotherapy drugs.DiscussionOur study highlights the critical role of neutrophils in the tumor microenvironment of HCC. The developed NDS is a powerful tool for assessing the risk and clinical treatment of HCC. Furthermore, we identified and analyzed the feasibility of the critical gene RTN3 in NDS as a molecular marker for HCC.

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Autophagy-based therapy for hepatocellular carcinoma: from standard treatments to combination therapy, oncolytic virotherapy, and targeted nanomedicines

Rahdan,

Abedi,

Dianat-Moghadam

et al. 2024

Clin Exp Med

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Human hepatocellular carcinoma (HCC) has been identified as a significant cause of mortality worldwide. In recent years, extensive research has been conducted to understand the underlying mechanisms of autophagy in the pathogenesis of the disease, with the aim of developing novel therapeutic agents. Targeting autophagy with conventional therapies in invasive HCC has opened up new opportunities for treatment. However, the emergence of resistance and the immunosuppressive tumor environment highlight the need for combination therapy or specific targeting, as well as an efficient drug delivery system to ensure targeted tumor areas receive sufficient doses without affecting normal cells or tissues. In this review, we discuss the findings of several studies that have explored autophagy as a potential therapeutic approach in HCC. We also outline the potential and limitations of standard therapies for autophagy modulation in HCC treatment. Additionally, we discuss how different combination therapies, nano-targeted strategies, and oncolytic virotherapy could enhance autophagy-based HCC treatment in future research.

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Construction of a prognostic model for HCC based on ferroptosis-related lncRNAs expression and its potential to predict the response and irAEs of immunotherapy

Cited by 4 publications

References 52 publications

The multifaceted perspectives on the regulation of lncRNAs in hepatocellular carcinoma ferroptosis: from bench-to-bedside

The multifaceted perspectives on the regulation of lncRNAs in hepatocellular carcinoma ferroptosis: from bench-to-bedside

Machine learning-based integration develops a neutrophil-derived signature for improving outcomes in hepatocellular carcinoma

Autophagy-based therapy for hepatocellular carcinoma: from standard treatments to combination therapy, oncolytic virotherapy, and targeted nanomedicines

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