A novel ferroptosis phenotype-related clinical-molecular prognostic signature for hepatocellular carcinoma

Ferroptosis in hepatocellular carcinoma: Mechanisms and therapeutic implications

Ferroptosis is a novel form of oxidative cell death, in which highly expressed unsaturated fatty acids on the cell membrane are catalyzed by divalent iron or ester oxygenase to promote liposome peroxidation. This process reduces cellular antioxidant capacity, increases lipid reactive oxygen species, and leads to the accumulation of intracellular ferrous ions, which disrupts intracellular redox homeostasis and ultimately causes oxidative cell death. Studies have shown that ferroptosis induces an immune response that has a dual role in liver disease, ferroptosis also offers a promising strategy for precise cancer therapy. Ferroptosis regulators are beneficial in maintaining cellular homeostasis and tissue health, have shown efficacy in treating diseases of the hepatic system. However, the mechanisms of action and molecular regulatory pathways of ferroptosis in hepatocellular carcinoma (HCC) have not been fully elucidated. Therefore, deciphering the role of ferroptosis and its mechanisms in HCC progression is crucial for treating the disease. In this review, we introduce the morphological features and biochemical functions of ferroptosis, outline the molecular regulatory pathways of ferroptosis, and highlights the therapeutic potential of ferroptosis inhibitors and modulators to target it in HCC.

The Role of Methylation in Ferroptosis

Methylation modification is a crucial epigenetic alteration encompassing RNA methylation, DNA methylation, and histone methylation. Ferroptosis represents a newly discovered form of programmed cell death (PCD) in 2012, which is characterized by iron-dependent lipid peroxidation. The comprehensive investigation of ferroptosis is therefore imperative for a more profound comprehension of the pathological and pathophysiological mechanisms implicated in a wide array of diseases. Researches show that methylation modifications can exert either promotive or inhibitory effects on cell ferroptosis. Consequently, this review offers a comprehensive overview of the pivotal role played by methylation in ferroptosis, elucidating its associated factors and underlying mechanisms.

Identification and verification of novel ferroptosis biomarkers predicts the prognosis of hepatocellular carcinoma

BACKGROUND

Big data mining and experiments are widely used to mine new prognostic markers.

METHODS

Candidate genes were identified from CROEMINE and FerrDb. Kaplan-Meier survival and Cox regression analysis were applied to assess the association of genes with Overall survival time (OS) and Disease-free survival time (DFS) in two HCC cohorts. Real-time quantitative polymerase chain reaction (RT-qPCR) and Immunohistochemistry were performed in HCC samples.

RESULTS

21 and 15 genes that can predict OS and DFS, which had not been reported before, were identified from 719 genes, respectively. Survival analysis showed elevated mRNA expression of GLMP, SLC38A6, and WDR76 were associated with poor prognosis, and three genes combination signature was an independent prognostic factor in HCC. RT-qPCR and Immunohistochemistry confirmed the results.

CONCLUSIONS

We established a novel computational process, which identified the expression levels of GLMP, SLC38A6, and WDR76 as potential ferroptosis-related biomarkers indicating the prognosis of HCC.

Ferroptosis regulation by methylation in cancer

Epigenetic regulation plays a critical role in cancer development and progression. Methylation is an important epigenetic modification that influences gene expression by adding a methyl group to nucleic acids and proteins. Ferroptosis is a new form of regulated cell death triggered by the accumulation of iron and lipid peroxidation. Emerging evidence have shown that methylation regulation plays a significant role in the regulation of ferroptosis in cancer. This review aims to explore the methylation regulation of ferroptosis in cancer, including reactive oxygen species and iron bio-logical activity, amino acid and lipid metabolism, and drugs interaction. The findings of this review may provide new insights and strategies for the prevention and treatment of cancer.

Identification and verification of novel immune-related ferroptosis signature with excellent prognostic predictive and clinical guidance value in hepatocellular carcinoma

Background: Immunity and ferroptosis often play a synergistic role in the progression and treatment of hepatocellular carcinoma (HCC). However, few studies have focused on identifying immune-related ferroptosis gene biomarkers. Methods: We performed weighted gene co-expression network analysis (WGCNA) and random forest to identify prognostic differentially expressed immune-related genes (PR-DE-IRGs) highly related to HCC and characteristic prognostic differentially expressed ferroptosis-related genes (PR-DE-FRGs) respectively to run co-expression analysis for prognostic differentially expressed immune-related ferroptosis characteristic genes (PR-DE-IRFeCGs). Lasso regression finally identified 3 PR-DE-IRFeCGs for us to construct a prognostic predictive model. Differential expression and prognostic analysis based on shared data from multiple sources and experimental means were performed to further verify the 3 modeled genes' biological value in HCC. We ran various performance testing methods to test the model's performance and compare it with other similar signatures. Finally, we integrated composite factors to construct a comprehensive quantitative nomogram for accurate prognostic prediction and evaluated its performance. Results: 17 PR-DE-IRFeCGs were identified based on co-expression analysis between the screened 17 PR-DE-FRGs and 34 PR-DE-IRGs. Multi-source sequencing data, QRT-PCR, immunohistochemical staining and testing methods fully confirmed the upregulation and significant prognostic influence of the three PR-DE-IRFeCGs in HCC. The model performed well in the performance tests of multiple methods based on the 5 cohorts. Furthermore, our model outperformed other related models in various performance tests. The immunotherapy and chemotherapy guiding value of our signature and the comprehensive nomogram's excellent performance have also stood the test. Conclusion: We identified a novel PR-DE-IRFeCGs signature with excellent prognostic prediction and clinical guidance value in HCC.

Life span-associated ferroptosis-related genes identification and validation for hepatocellular carcinoma patients as hepatitis B virus carriers

BACKGROUND

Hepatitis B virus (HBV)-infected population accounts for approximately 50% of all hepatocellular carcinoma (HCC) cases and has a relatively poor prognosis. Although the significant role of ferroptosis in the development and therapeutic response of various cancers has been validated, the key ferroptosis-related genes (FRGs) on the stratification of HBV-associated HCC are still unclear.

METHODS

Through the random forest, GSVA and Cox regression analyses, we established a comprehensive prognostic system covering multiple FRGs to elevate the predictive accuracy for the survival rate of HBV-related HCC using information obtained from public databases. The association between key FRGs and the immune microenvironment was evaluated, and the molecular mechanism was identified by GSEA and SNV analyses. Finally, the differential expression of key FRGs was validated by immunohistochemistry staining of patient tissue microarrays.

RESULTS

Within the top 10 key FRGs, EPAS1 and GABARAPL1 were taken as protective factors, and SQLE, RAD51AP1, RPL8, CAPG, RRM2, SLC1A5, SLC38A1, and SRC were the other eight dangerous markers. Cox regression analysis combined with clinicopathological features indicated the independent prognostic efficacy of GSVA complex score based on these FRGs. In addition, key FRGs were related to immune and metabolic-related functions. Especially, the immunohistochemical analysis of SQLE in 50 clinical samples showed significantly higher expression in HBV+ HCC tissues.

CONCLUSIONS

These results indicate that 10 FRGs may be potential biomarkers and therapeutic targets for long-term survival in HBV-related HCC.

Disulfidptosis classification of hepatocellular carcinoma reveals correlation with clinical prognosis and immune profile

A new mode of cell death, disulfidptosis, has been discovered. Clinical prognostic significance of disulfidptosis related pattern in hepatocellular carcinoma(HCC). In this study, a risk score model was established based on disulfidptosis model to analyze the role of risk score in clinical prognosis, immune cell infiltration, drug sensitivity and immunotherapy response. Disulfidptosis subtype were constructed based on the transcriptional profiles of 15 disulfidptosis-related genes(DRGs). All 601 samples were defined as high risk group(HRG) and low risk group(LRG) based on the disulfidptosis risk score. Drug sensitivity and response to immunotherapy were calculated by immunophenotypic score(IPS), tumor prediction, tumor immune dysfunction and rejection(TIDE). RT-qPCR was used to determine the mRNA level of disulfidptosis prognostic gene. Risk groups was identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. HRG may benefit from immunotherapy. Classification is very effective in predicting the prognosis and therapeutic effect of patients, and provides a reference for accurate individualized treatment. This study suggests that new biomarkers related to Disulfidptosis can be used in clinical diagnosis of liver cancer to predict prognosis and treatment targets.

A macropinocytosis-related gene signature predicts the prognosis and immune microenvironment in hepatocellular carcinoma

Background

Available treatments for hepatocellular carcinoma (HCC), a common human malignancy with a low survival rate, remain unsatisfactory. Macropinocytosis (MPC), a type of endocytosis that involves the non-specific uptake of dissolved molecules, has been shown to contribute to HCC pathology; however, its biological mechanism remains unknown.

Methods

The current study identified 27 macropinocytosis-related genes (MRGs) from 71 candidate genes using bioinformatics. The R software was used to create a prognostic signature model by filtering standardized mRNA expression data from HCC patients and using various methods to verify the reliability of the model and indicate immune activity.

Results

The prognostic signature was constructed using seven MPC-related differentially expressed genes, GSK3B, AXIN1, RAC1, KEAP1, EHD1, GRB2, and SNX5, through LASSO Cox regression. The risk score was acquired from the expression of these genes and their corresponding coefficients. HCC patients in the discovery and validation cohorts were stratified, and the survival of low-risk score patients was improved in both cohorts. Time-dependent ROC analysis indicated that the model's prediction reliability was the highest in the short term. Subsequent immunologic analysis, including KEGG, located the immune action pathway of the differentially expressed genes in the direction of the cancer pathway, etc. Immune infiltration and immune checkpoint tests provided valuable guidance for future follow-up experiments.

Conclusion

A risk model with MRGs was constructed to effectively predict HCC patient prognoses and suggest changes in the immune microenvironment during the disease process. The findings should benefit the development of a prognostic stratification and treatment strategy for HCC.

Biomarker discovery and application-An opportunity to resolve the challenge of liver cancer diagnosis and treatment

Liver cancer is one of the most common malignancies, with severe morbidity and mortality. While considerable progress has been made in liver cancer treatment, the 5-year overall survival (OS) of patients has not improved significantly. Reasons include the inadequate capability of early screening and diagnosis, a high incidence of recurrence and metastasis, a high degree of tumor heterogeneity, and an immunosuppressive tumor microenvironment. Therefore, the identification and validation of specific and robust liver cancer biomarkers are of major importance for early screening, timely diagnosis, accurate prognosis, and the prevention of tumor progression. In this review, we highlight some of the latest research progress and potential applications of liver cancer biomarkers, describing hotspots and prospective directions in biomarker discovery.

Ferroptosis in hepatocellular carcinoma: mechanisms and targeted therapy

Hepatocellular carcinoma is the most prevalent form of primary liver cancer with a multifactorial aetiology comprising genetic, environmental, and behavioural factors. Evading cell death is a defining hallmark of hepatocellular carcinoma, underpinning tumour growth, progression, and therapy resistance. Ferroptosis is a form of nonapoptotic cell death driven by an array of cellular events, including intracellular iron overload, free radical production, lipid peroxidation and activation of various cell death effectors, ultimately leading to rupture of the plasma membrane. Although induction of ferroptosis is an emerging strategy to suppress hepatocellular carcinoma, malignant cells manage to develop adaptive mechanisms, conferring resistance to ferroptosis and ferroptosis-inducing drugs. Herein, we aim at elucidating molecular mechanisms and signalling pathways involved in ferroptosis and offer our opinions on druggable targets and new therapeutic strategy in an attempt to restrain the growth and progression of hepatocellular carcinoma through induction of ferroptotic cell death.

Role of ferroptosis and its non-coding RNA regulation in hepatocellular carcinoma

Ferroptosis is a newly discovered form of programmed cell death that involves the accumulation of iron-dependent lipid peroxides and plays a vital role in the tumorigenesis, development, and drug resistance of various tumors such as hepatocellular carcinoma (HCC). As a hotspot in molecular biology, non-coding RNAs (ncRNAs) participate in the initiation and progression of HCC, either act as oncogenes or tumor suppressors. Recent studies have shown that ncRNAs can regulate ferroptosis in HCC cells, which would affect the tumor progression and drug resistance. Therefore, clarifying the underlying role of ferroptosis and the regulatory role of ncRNA on ferroptosis in HCC could develop new treatment interventions for this disease. This review briefly summarizes the role of ferroptosis and ferroptosis-related ncRNAs in HCC tumorigenesis, progression, treatment, drug resistance and prognosis, for the development of potential therapeutic strategies and prognostic markers in HCC patients.

Systematical analysis of ferroptosis regulators and identification of GCLM as a tumor promotor and immunological biomarker in bladder cancer

Bladder cancer (BCa) is a life-threaten disease with an increasing incidence with age, and immunotherapy has become an important treatment for BCa, while the efficiency of the immune system declines with age. It is vital to reveal the mechanisms of tumor immune microenvironment (TIME) and identify novel immunotherapy targets for BCa. Through analyzing the RNA-seq of TCGA-BLCA cohort, we distinguished two ferroptosis-related BCa clusters, and we discovered that in comparation with cluster 2, the cluster 1 BCa patients showed higher PD-L1 expression, more unfavorable overall survival and higher tumor stage and grade. XCELL analyses showed that higher level of Th2 cell and Myeloid dendritic cell were enriched in cluster 1, while NK T cell was enriched in cluster 2, and TIDE analysis revealed that cluster 2 was more sensitive to immunotherapy than cluster 1. GSEA analysis implied that Toll-like signaling pathway and JAK_STAT signaling pathway were significantly enriched in cluster 1. Subsequently, through performing bioinformatic analysis and cell experiments, we demonstrated that GCLM is overexpressed in BCa and indicates dismal prognosis, and knockdown of GCLM can significantly suppress the colony formation ability of BCa cells. Furthermore, we also found that GCLM might be correlated with immune infiltration in BCa, and can serve as a tumor promotor and immunological biomarker in BCa, our research showed the vital roles of ferroptosis regulators in TIME of BCa, and GCLM is a latent therapeutic target for cancer immunotherapy.

Identification and validation of a tyrosine metabolism-related prognostic prediction model and characterization of the tumor microenvironment infiltration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive and heterogeneous disease characterized by high morbidity and mortality. The liver is the vital organ that participates in tyrosine catabolism, and abnormal tyrosine metabolism could cause various diseases, including HCC. Besides, the tumor immune microenvironment is involved in carcinogenesis and can influence the patients' clinical outcomes. However, the potential role of tyrosine metabolism pattern and immune molecular signature is poorly understood in HCC.

METHODS

Gene expression, somatic mutations, copy number variation data, and clinicopathological information of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. GSE14520 from the Gene Expression Omnibus (GEO) databases was used as a validation dataset. We performed unsupervised consensus clustering of tyrosine metabolism-related genes (TRGs) and classified patients into distinct molecular subtypes. We used ESTIMATE algorithms to evaluate the immune infiltration. We then applied LASSO Cox regression to establish the TRGs risk model and validated its predictive performance.

RESULTS

In this study, we first described the alterations of 42 TRGs in HCC cohorts and characterized the clinicopathological characteristics and tumor microenvironmental landscape of the two distinct subtypes. We then established a tyrosine metabolism-related scoring system and identified five TRGs, which were highly correlated with prognosis and representative of this gene set, namely METTL6, GSTZ1, ADH4, ADH1A, and LCMT1. Patients in the high-risk group had an inferior prognosis. Univariate and multivariate Cox proportional hazards regression analysis also showed that the tyrosine metabolism-related signature was an independent prognostic indicator. Besides, receiver operating characteristic curve (ROC) analysis demonstrated the predictive accuracy of the TRGs signature that could reliably predict 1-, 3-, and 5-year survival in both TCGA and GEO cohorts. We also got consistent results by performing clone formation and invasion analysis, and immunohistochemical (IHC) assays. Moreover, we also discovered that the TRGs signature was significantly associated with the different immune landscapes and therapeutic drug sensitivity.

CONCLUSION

Our comprehensive analysis revealed the potential molecular signature and clinical utilities of TRGs in HCC. The model based on five TRGs can accurately predict the survival outcomes of HCC, improving our knowledge of TRGs in HCC and paving a new path for guiding risk stratification and treatment strategy development for HCC patients.

Machine learning-based transcriptome analysis of lipid metabolism biomarkers for the survival prediction in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the liver with a very high fatality rate. Our goal in this study is to find a reliable lipid metabolism-related signature associated with prognostic significance for HCC. In this study, HCC lipid metabolism-related molecular subtype analysis was conducted based on the 243 lipid metabolism genes collected from the Molecular Signatures Database. Several significant disparities in prognosis, clinicopathological characteristics, and immune and ferroptosis-related status were found across the three subtypes, especially between C1 and C3 subgroups. Differential expression analysis yielded 57 differentially expressed genes (DEGs) between C1 and C3 subtypes. GO and KEGG analysis was employed for functional annotation. Three of 21 prognostic DEGs (CXCL8, SLC10A1, and ADH4) were finally selected through machine-learning-based discovery and validation strategy. The risk score = (0.103) × expression value of CXCL8 + (−0.0333) × expression value of SLC10A1 + (−0.0812) × expression value of ADH4. We used these three to construct a HCC prognostic risk model, which stratified the patients of the validation cohort into two risk subtypes with significantly different overall survival. Our work provides possible significance of the lipid metabolism-associated model in stratifying patient prognosis and its feasibility to guide therapeutic selection.

A Novel Ferroptosis-Related Long Non-Coding RNA Prognostic Signature Correlates With Genomic Heterogeneity, Immunosuppressive Phenotype, and Drug Sensitivity in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) with high heterogeneity is a common malignancy worldwide, but effective treatments are limited. Ferroptosis plays a critical role in tumors as a novel iron-dependent and reactive oxygen species-reliant type of cell death. Several studies have shown that long non-coding RNAs (lncRNAs) can drive HCC initiation and progression. However, the prognostic value of ferroptosis-related lncRNAs in patients with HCC has not been explored comprehensively. Gene set variation analysis (GSVA) based on gene set and RNA-seq profiles obtained from public databases indicated that ferroptosis is suppressed in HCC patients. Ferroptosis-related differentially expressed lncRNAs were screened by Pearson’s test. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression were performed to establish a novel five ferroptosis-related lncRNA signature in the training cohort with 60% patients, which was further verified in the testing cohort with 40% patients. Dimensionality reduction analysis, Kaplan–Meier curve, receiver operating characteristic (ROC) curve, independent prognostic analysis, and stratification analysis confirmed that our signature had a high clinical application value in predicting the overall survival of HCC patients. Compared to the clinicopathological factors and the other four published HCC prognostic signatures, the current risk model had a better predictive value. The comparison results of functional enrichment, tumor immune microenvironment, genomic heterogeneity, and drug sensitivity between the high- and low-risk groups showed that the risk score is associated with extensive genomic alterations, immunosuppressive tumor microenvironment, and clinical treatment response. Finally, cell experiments showed that silencing LNCSRLR expression inhibited the growth, proliferation, migration, and invasion of the HCC cell line. Thus, the model can function as an efficient indicator for predicting clinical prognosis and treatment of anticancer drugs in HCC patients.

A novel epithelial-mesenchymal transition gene signature for the immune status and prognosis of hepatocellular carcinoma

Background

This study clarified whether EMT-related genes can predict immunotherapy efficacy and overall survival in patients with HCC.

Methods

The RNA-sequencing profiles and patient information of 370 samples were derived from the Cancer Genome Atlas (TCGA) dataset, and EMT-related genes were obtained from the Molecular Signatures database. The signature model was constructed using the least absolute shrinkage and selection operator Cox regression analysis in TCGA cohort. Validation data were obtained from the International Cancer Genome Consortium (ICGC) dataset of patients with HCC. Kaplan–Meier analysis and multivariate Cox analyses were employed to estimate the prognostic value. Immune status and tumor microenvironment were estimated using a single-sample gene set enrichment analysis (ssGSEA). The expression of prognostic genes was verified using qRT-PCR analysis of HCC cell lines.

Results

A signature model was constructed using EMT-related genes to determine HCC prognosis, based on which patients were divided into high-risk and low-risk groups. The risk score, as an independent factor, was related to tumor stage, grade, and immune cells infiltration. The results indicated that the most prognostic genes were highly expressed in the HCC cell lines, but GADD45B was down-regulated. Enrichment analysis suggested that immunoglobulin receptor binding and material metabolism were essential in the prognostic signature.

Conclusion

Our novel prognostic signature model has a vital impact on immune status and prognosis, significantly helping the decision-making related to the diagnosis and treatment of patients with HCC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12072-022-10354-3.

Integrated Analysis Reveals Critical Ferroptosis Regulators and FTL Contribute to Cancer Progression in Hepatocellular Carcinoma

Background: The carcinogenesis and prognosis of hepatocellular carcinoma (HCC) involve complex molecular mechanisms, and ferroptosis is related to the development and therapeutic efficacy of HCC, but the specific mechanism and prognostic role of ferroptosis-related genes in HCC have not been elucidated. Methods: Differentially expressed gene analysis, Cox regression, and unsupervised consensus clustering were applied to identify crucial ferroptosis regulators and establish ferroptosis-related subtypes in HCC. Random forest analysis and survival analysis were adopted to confirm FTL as the hub prognostic and diagnostic ferroptosis regulator in HCC. Results: The ferroptosis-related subtypes based on the crucial prognostic ferroptosis regulators showed that patients in fescluster A had a higher survival probability (p < 0.001) and better clinical characteristics than patients in fescluster B in the TCGA-LIHC cohort. Patients with a high tumor mutation burden (TMB) in fescluster B presented a significantly poorer prognosis. FTL was the core ferroptosis regulator, and its low expression revealed a significant survival advantage compared with its high expression (p = 0.03). The expression and predictive value of FTL were both closely related to the clinical features (p < 0.05). Expression of FTL accurately distinguished HCC from normal tissues in the TCGA-LIHC cohort, ICGC cohort, and GSE14520 dataset. In addition, higher infiltrating fractions of immune cells, such as activated CD8⁺ T cells and Gamma delta T cells, mainly enriched immune-related signaling pathways, including the IL2-STAT3 signaling pathway and interferon-gamma response signaling pathway, and higher expression of immune checkpoints, including PDCD1, CTLA4, TIGIT, and CD83, were presented in patients with high FTL expression (p < 0.05). Patients with high FTL were more sensitive to some targeted drugs, such as cisplatin, dasatinib, and sorafenib, than those with low FTL (p < 0.05). A nomogram based on FTL accurately predicted the prognosis of HCC. Further knockdown of FTL was determined to significantly inhibit cell proliferation and migration in HCC. Conclusion: Our study validated ferroptosis-related subtypes and FTL with effective prognostic value in HCC and was beneficial for identifying candidates suitable for targeted drug therapy and immunotherapy, thereby offering further insight into individual treatment strategies to improve disease outcomes in HCC patients.

Ferroptosis in Hepatocellular Carcinoma: Mechanisms, Drug Targets and Approaches to Clinical Translation

Simple Summary

In recent decades, scientific discoveries brought up several new treatments and improvements for patients suffering from hepatocellular carcinoma (HCC). However, increasing resistance to current therapies, such as sorafenib, worsen the outcome of HCC patients, leading to a search for alternative therapeutic strategies. The term ferroptosis describes a novel form of regulated cell death, which is different from apoptosis and necroptosis in a mechanistical and morphological manner. The main mechanism, which leads to cell death, is lipid peroxidation, caused by iron overload and the accumulation of polyunsaturated fatty acids. Recent studies demonstrate that ferroptosis can hamper the carcinogenesis in several tumor entities and in HCC. Therefore, a better understanding and a deeper insight in the processes of ferroptosis in HCC and the possible application of it in the clinical practice are of extreme importance.

Abstract

Ferroptosis, an iron and reactive oxygen species (ROS)-dependent non-apoptotic type of regulated cell death, is characterized by a massive iron overload and peroxidation of polyunsaturated fatty acids (PUFAs), which finally results in cell death. Recent studies suggest that ferroptosis can influence carcinogenesis negatively and therefore may be used as a novel anti-cancer strategy. Hepatocellular carcinoma (HCC) is a deadly malignancy with poor chances of survival and is the second leading cause of cancer deaths worldwide. Diagnosis at an already late stage and general resistance to current therapies may be responsible for the dismal outcome. As the liver acts as a key factor in iron metabolism, ferroptosis is shown to play an important role in HCC carcinogenesis and, more importantly, may hold the potential to eradicate HCC. In this review, we summarize the current knowledge we have of the role of ferroptosis in HCC and the application of ferroptosis as a therapy option and provide an overview of the potential translation of ferroptosis in the clinical practice of HCC.

NF-κB-Related Metabolic Gene Signature Predicts the Prognosis and Immunotherapy Response in Gastric Cancer

Background

Sufficient evidence indicated the crucial role of NF-κB family played in gastric cancer (GC). The novel discovery that NF-κB could regulate cancer metabolism and immune evasion greatly increased its attraction in cancer research. However, the correlation among NF-κB, metabolism, and cancer immunity in GC still requires further improvement.

Methods

TCGA, hTFtarget, and MSigDB databases were employed to identify NF-κB-related metabolic genes (NFMGs). Based on NFMGs, we used consensus clustering to divide GC patients into two subtypes. GSVA was employed to analyze the enriched pathway. ESTIMATE, CIBERSORT, ssGSEA, and MCPcounter algorithms were applied to evaluate immune infiltration in GC. The tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict patients' response to immunotherapy. We also established a NFMG-related risk score by using the LASSO regression model and assessed its efficacy in TCGA and GSE62254 datasets.

Results

We used 27 NFMGs to conduct an unsupervised clustering on GC samples and classified them into two clusters. Cluster 1 was characterized by high active metabolism, tumor mutant burden, and microsatellite instability, while cluster 2 was featured with high immune infiltration. Compared to cluster 2, cluster 1 had a better prognosis and higher response to immunotherapy. In addition, we constructed a 12-NFMG (ADCY3, AHCY, CHDH, GUCY1A2, ITPA, MTHFD2, NRP1, POLA1, POLR1A, POLR3A, POLR3K, and SRM) risk score. Followed analysis indicated that this risk score acted as an effectively prognostic factor in GC.

Conclusion

Our data suggested that GC subtypes classified by NFMGs may effectively guide prognosis and immunotherapy. Further study of these NFMGs will deepen our understanding of NF-κB-mediated cancer metabolism and immunity.

The Prognostic Significance and Potential Mechanism of Ferroptosis-Related Genes in Hepatocellular Carcinoma

Ferroptosis exerts a pivotal role in the formation and dissemination processes of hepatocellular carcinoma (HCC). The heterogeneity of ferroptosis and the link between ferroptosis and immune responses have remained elusive. Based on ferroptosis-related genes (FRGs) and HCC patients from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) cohorts, we comprehensively explored the heterogeneous ferroptosis subtypes. The genetic alterations, consensus clustering and survival analysis, immune infiltration, pathway enrichment analysis, integrated signature development, and nomogram building were further investigated. Kaplan-Meier plotter confirmed statistically differential probabilities of survival among the three subclusters. Immune infiltration analysis showed there were clear differences among the types of immune cell infiltration, the expression of PD-L1, and the distribution of TP53 mutations among the three clusters. Univariate Cox regression analysis, random survival forest, and multivariate Cox analysis were used to identify the prognostic integrated signature, including MED8, PIGU, PPM1G, RAN, and SNRPB. Kaplan-Meier analysis and time-dependent receiver operating characteristic (ROC) curves revealed the satisfactory predictive potential of the five-gene model. Subsequently, a nomogram was established, which combined the signature with clinical factors. The nomogram including the ferroptosis-based signature was conducted and showed some clinical net benefits. These results facilitated an understanding of ferroptosis and immune responses for HCC.

A narrative review of mechanisms of ferroptosis in cancer: new challenges and opportunities

Objective

This article reviews the specific mechanism of ferroptosis in cancer and introduces in detail the opportunities and challenges of ferroptosis-based cancer therapy, aiming to provide a new research direction for tumor therapy.

Background

Ferroptosis is a newly discovered programmed non-apoptotic form of cell death. Involving changes in metabolic processes and the accumulation of peroxidation caused by factors such as drugs or genes which destruct the cell membrane structure, this kind of cell death has been linked with the pathological process of diseases such as tumors, neurological diseases, ischemia-reperfusion injury, kidney injury, and hemopathy. This kind of cell death can play a vital role in inhibiting tumorigenesis by eliminating the adaptive characteristics of malignant cells and removing cells that are unable to obtain key nutritional factors or are infected and damaged by environmental changes. The present focus of research on the regulation of ferroptosis-related diseases involves the use of small molecule compounds.

Methods

We described the mechanism of ferroptosis and its related small molecules compounds, which involved in the regulatory mechanism, and analyzed the role and regulatory mechanism of ferroptosis in different tumors.

Conclusions

This article reviewed the mechanism of ferroptosis and its role and mechanism in different tumors, and showed it can inhibit the occurrence and development of different tumors and may reduce the adverse effects of current treatment methods.

The Prognostic Model Based on Tumor Cell Evolution Trajectory Reveals a Different Risk Group of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, and heterogeneity of HCC is the major barrier in improving patient outcome. To stratify HCC patients with different degrees of malignancy and provide precise treatment strategies, we reconstructed the tumor evolution trajectory with the help of scRNA-seq data and established a 30-gene prognostic model to identify the malignant state in HCC. Patients were divided into high-risk and low-risk groups. C-index and receiver operating characteristic (ROC) curve confirmed the excellent predictive value of this model. Downstream analysis revealed the underlying molecular and functional characteristics of this model, including significantly higher genomic instability and stronger proliferation/progression potential in the high-risk group. In summary, we established a novel prognostic model to overcome the barriers caused by HCC heterogeneity and provide the possibility of better clinical management for HCC patients to improve their survival outcomes.

Identification of a Ferroptosis-Related Signature Model Including mRNAs and lncRNAs for Predicting Prognosis and Immune Activity in Hepatocellular Carcinoma

Background

Ferroptosis is a novel form of regulated cell death involved in tumor progression. The role of ferroptosis-related lncRNAs in hepatocellular carcinoma (HCC) remains unclear.

Methods

RNA-seq and clinical data for HCC patients were downloaded from The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC) portal. Bioinformatics methods, including weighted gene coexpression network analysis (WGCNA), Cox regression, and least absolute shrinkage and selection operator (LASSO) analysis, were used to identify signature markers for diagnosis/prognosis. The tumor microenvironment, immune infiltration and functional enrichment were compared between the low-risk and high-risk groups. Subsequently, small molecule drugs targeting ferroptosis-related signature components were predicted via the L1000FWD and PubChem databases.

Results

The prognostic model consisted of 2 ferroptosis-related mRNAs (SLC1A5 and SLC7A11) and 8 ferroptosis-related lncRNAs (AC245297.3, MYLK-AS1, NRAV, SREBF2-AS1, AL031985.3, ZFPM2-AS1, AC015908.3, MSC-AS1). The areas under the curves (AUCs) were 0.830 and 0.806 in the training and test groups, respectively. Decision curve analysis (DCA) revealed that the ferroptosis-related signature performed better than all pathological characteristics. Multivariate Cox regression analysis showed that the risk score was an independent prognostic factor. The survival probability of low- and high-risk patients could be clearly distinguished by the principal component analysis (PCA) plot. The risk score divided HCC patients into two distinct groups in terms of immune status, especially checkpoint gene expression, which was further supported by the Gene Ontology (GO) biological process, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, several small molecule drugs (SIB-1893, geldanamycin and PD-184352, etc) targeting ferroptosis-related signature components were identified for future reference.

Conclusion

We constructed a new ferroptosis-related mRNA/lncRNA signature for HCC patients. The model can be used for prognostic prediction and immune evaluation, providing a reference for immunotherapies and targeted therapies.

A novel ferroptosis phenotype-related clinical-molecular prognostic signature for hepatocellular carcinoma

Ferroptosis is a newly identified cell death mechanism and potential biomarker for hepatocellular carcinoma (HCC) therapy; however, its clinical relevance and underlying mechanism remain unclear. In this study, transcriptome and methylome data from 374 HCC cases were investigated for 41 ferroptosis-related genes to identify ferroptosis activity-associated subtypes. These subtypes were further investigated for associations with clinical and pathological variables, gene mutation landscapes, deregulated pathways and tumour microenvironmental immunity. A gene expression signature and predictive model were developed and validated using an additional 232 HCC cases from another independent cohort. Two distinct ferroptosis phenotypes (Ferroptosis-H and Ferroptosis-L) were identified according to ferroptosis gene expression and methylation in the patients with HCC. Patients with the Ferroptosis-H had worse overall and disease-specific survival, and the molecular subtypes were significantly associated with different clinical characteristics, mRNA expression patterns, tumour mutation profiles and microenvironmental immune status. Furthermore, a 15-gene ferroptosis-related prognostic model (FPM) for HCC was developed and validated which demonstrated accurate risk stratification ability. A nomogram included the FPM risk score, ECOG PS and hepatitis B status was developed for eventual clinical translation. Our results suggest that HCC subtypes defined by ferroptosis gene expression and methylation may be used to stratify patients for clinical decision-making.