Prognostic value of ferroptosis-related genes in patients with lung adenocarcinoma

Cephaeline promotes ferroptosis by targeting NRF2 to exert anti-lung cancer efficacy

CONTEXT

Cephaeline is a natural product isolated from ipecac (Cephaelis ipecacuanha [Brot.] A. Rich. [Rubiaceae]). It exhibits promising anti-lung cancer activity and ferroptosis induction may be a key mechanism for its anti-lung cancer effect.

OBJECTIVES

This study investigates the anti-lung cancer activity and mechanisms of cephaeline both in vitro and in vivo.

MATERIALS AND METHODS

H460 and A549 lung cancer cells were used. The cephaeline inhibition rate on lung cancer cells was detected via a Cell Counting Kit-8 assay after treatment with cephaeline for 24 h. Subsequently, the concentrations of 25, 50 and 100 nM were used for in vitro experiments. In addition, the antitumour effects of cephaeline (5, 10 mg/kg) in vivo were evaluated after 12 d of cephaeline treatment.

RESULTS

Cephaeline showed significant inhibitory effects on lung cancer cells, and the IC50 of cephaeline on H460 and A549 at 24, 48 and 72 h were 88, 58 and 35 nM, respectively, for H460 cells and 89, 65 and 43 nM, respectively, for A549 cells. Meanwhile, we demonstrated that ferroptosis is the key mechanism of cephaeline against lung cancer. Finally, we found that cephaeline induced ferroptosis in lung cancer cells by targeting NRF2.

DISCUSSION AND CONCLUSION

We demonstrated for the first time that cephaeline inhibits NRF2, leading to ferroptosis in lung cancer cells. These findings may contribute to the development of innovative therapeutics for lung cancer.

Targeting Nrf2/PHKG2 axis to enhance radiosensitivity in NSCLC

While ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis. Clinical samples were analyzed to confirm PHKG2 expression changes before and after radiotherapy. The study further examined ferritinophagy-related factors, intracellular iron levels, mitochondrial function, and ferroptosis in NSCLC cells undergoing radiation exposure to explore the effect of PHKG2 on radiosensitivity or radioresistance. The research also demonstrated the transcriptional inhibition of PHKG2 by NRF2 and created in situ transplantation tumor models of NSCLC to examine the role of NRF2/PHKG2 axis in NSCLC radiosensitivity and resistance in vivo. The Lasso risk regression model that incorporated ferroptosis-associated genes effectively predicted the prognosis of patients with NSCLC. Radiotherapy-sensitive tissues exhibited an increased expression of PHKG2. Overexpression of PHKG2 led to elevated intracellular iron levels by promoting ferritinophagy and increased mitochondrial stress-dependent ferroptosis induced by radiotherapy. PHKG2 transcription repression was achieved through NRF2. The FAGs-Lasso risk regression model can accurately predict the prognosis of NSCLC patients. Targeting Nrf2 upregulates the expression of PHKG2 and reverses radiotherapy resistance in NSCLC by promoting iron autophagy and inducing mitochondrial dysfunction, thereby increasing radiotherapy sensitivity.

Ferroptosis-related genes DUOX1 and HSD17B11 affect tumor microenvironment and predict overall survival of lung adenocarcinoma patients

BACKGROUND

Recent studies have found that ferroptosis-related genes (FRGs) have broad applications in tumor therapy. However, the predictive potential of these genes in lung adenocarcinoma (LUAD) remains to be fully characterized. We aimed to investigate the FRGs that might be potential targets for LUAD.

METHODS

We screened the RNA sequencing samples from LUAD patients from the GEO database and analyzed the ferroptosis-related differentially expressed genes (DEGs). A functional analysis of DEGs was performed. The risk model was constructed to evaluation and validation FRGs. We explored the immune landscape of LUAD and controls. The value of FRGs in diagnosing LUAD was tested in the GSE30219, GSE37745, GSE0081 datasets, and qPCR was used to verify their diagnostic value in LUAD patients in our hospital.

RESULTS

A total of 1327 DEGs in quantitative proteomics were obtained, of which ferroptosis-related DEGs were 259. Enrichment analysis showed significant enrichment in the absorption and metabolism of fatty acids and arachidonic acid. The upregulated genes (GCLC, RRM2, AURKA, SLC7A5, and SLC2A1) and downregulated genes (ANGPTL7, ALOX15, ALOX15B, HSD17B11, IL33, TSC22D3, and DUOX1) were selected as core genes in tissue samples from 62 patients by qPCR. DUOX1 and HSD17B11 were obtained by bioinformatics analysis, both of which showed similar expression trends at the RNA and protein levels. The Kaplan-Meier method showed that DUOX1 and HSD17B11 were closely related to the overall survival (OS) of LUAD patients.

CONCLUSION SUBSECTIONS

Ferroptosis-related genes DUOX1 and HSD17B11 are of considerable value in the diagnosis of LUAD patients. Their low expression suggests an increased recurrence rate and leads to a decrease in the patient quality of life.

Cuproptosis-related lncRNAs predict the prognosis and immune response in hepatocellular carcinoma

Cuproptosis has been recently used to indicate unique biological processes triggered by Cu action as a new term. This study aimed to explore the relationship between cuproptosis-related lncRNA and hepatocellular carcinoma (HCC) with regard to immunity and prognosis. RNA sequencing and the clinical data were downloaded from the TCGA database. The cuproptosis-related genes were sorted out through literature study. The cuproptosis-related IncRNA signature was identified by Cox regression analysis and the least absolute shrinkage and selection operator analysis. The K-M survival analysis, receiver operating characteristic analysis, and C-index analysis were adopted to evaluate the prognostic prediction performance of the signature. The functional enrichment, immune infiltration and tumor mutation analysis were further analyzed. Subsequently, we predicted the differences in chemosensitivity from tumor gene expression levels for some chemotherapy drugs. The prognostic signature consisting of 5 overall survival-related CUPlncRNAs. It showed an extraordinary ability to predict the prognoses of patients with HCC. The signature can predict the abundance of immune cell infiltration, immune functions, expression of immune checkpoint inhibitors, m6A genes, which was supported by the GO biological process and KEGG analysis. And it may also have a guiding effect in the sensitivity of different chemotherapeutic drugs and tumor mutation burden. We constructed a new cuproptosis-related lncRNA signature for HCC patients. The model can be used for prognostic prediction and immune evaluation, providing a reference for immunotherapies and targeted therapies.

Regulation of Ferroptosis in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common lung cancer, which accounts for about 35-40% of all lung cancer patients. Despite therapeutic advancements in recent years, the overall survival time of LUAD patients still remains poor, especially KRAS mutant LUAD. Therefore, it is necessary to further explore novel targets and drugs to improve the prognos is for LUAD. Ferroptosis, an iron-dependent regulated cell death (RCD) caused by lipid peroxidation, has attracted much attention recently as an alternative target for apoptosis in LUAD therapy. Ferroptosis has been found to be closely related to LUAD at every stage, including initiation, proliferation, and progression. In this review, we will provide a comprehensive overview of ferroptosis mechanisms, its regulation in LUAD, and the application of targeting ferroptosis for LUAD therapy.

Construction of a Novel Ferroptosis-Related Gene Signature for Predicting Survival of Patients With Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most diagnosed subtype of lung cancer; ferroptosis is widely involved in the pathological cell death associated with various cancers, including lung cancer. However, the comprehensive relationship between ferroptosis and LUAD is little known in molecular levels until now. In the present study, 513 LUAD patients could be aggregated into three clusters by consensus clustering based on RNA sequencing data of 291 ferroptosis-related genes (FRGs) in The Cancer Genome Atlas (TCGA) database; cluster2 had significant survival advantage compared to the other two clusters. A novel prognostic model of 8 differential FRGs was constructed to effectively divide LUAD patients into high- or low-risk group according to the risk scores by the Cox and LASSO regression analyses. The overall survival of LUAD patients in the high-risk group was significantly worse in the TCGA and GEO cohorts. Moreover, patients with radiation therapy or high clinical stage had obviously higher risk scores. We validated the differential mRNA and protein expression of four FRGs in paired tumor and normal samples from our clinical cohort. Our study constructed a novel FRG signature to predict the prognosis of LUAD patients, which might provide a new prognostic tool and potential therapeutic targets for LUAD.

Risk stratification of lung adenocarcinoma using a nomogram combined with ferroptosis-related LncRNAs and subgroup analysis with immune and N6-methyladenosine modification

Background

Determining the prognosis of lung adenocarcinoma (LUAD) is challenging. The present study aimed to identify prognostic ferroptosis-related long noncoding RNAs (FRLs) and construct a prognostic model. Moreover, differential analysis of immune and N6-methyladenosine (m6A)-related genes was systematically conducted.

Methods

A total of 504 patients selected from a dataset from The Cancer Genome Atlas were included. The patients with LUAD were randomly divided into a training group and a test group at a ratio of 1:1. Pearson correlation analysis and univariate Cox regression analysis were used to identify the prognostic FRLs. Then, a prognostic model was constructed from the optimized subset of prognostic FRLs based on the least absolute shrinkage and selection operator (LASSO) algorithm. Subsequently, the receiver operating characteristic (ROC) curve and survival analysis were used to evaluate the performance of the model. The risk score based on the prognostic model was analyzed using Cox regression analysis. Moreover, gene set enrichment analysis and differential analysis of immune- and m6A-related genes were conducted.

Results

After univariate Cox regression analysis and LASSO algorithm analysis, a total of 19 prognostic FRLs were selected to construct the final model to obtain the risk score. The area under the ROC curve of the prognostic model for 1-year, 3-year, and 5-year overall survival (OS) was 0.763, 0.745, and 0.778 in the training set and 0.716, 0.724, and 0.736 in the validation set, respectively. Moreover, the OS of the high-risk group was significantly worse than that of the low-risk group in the training group (P < 0.001) and in the test group (P < 0.001). After univariate and multivariate Cox regression analysis, the risk score [hazard ratio (HR) = 1.734; P < 0.001] and stage (HR = 1.557; P < 0.001) were both considered significant prognostic factors for LUAD. A nomogram was constructed based on clinical features and risk score. The expression of 34 checkpoint genes and 13 m6A-related genes varied significantly between the two risk groups.

Conclusion

This study constructed a prognostic model to effectively predict the OS of patients with LUAD, and these OS-related FRLs might serve as potential therapeutic targets of LUAD.

Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma

Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature on the basis of long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of patients with LUAD. We selected ARlncRNAs associated with prognosis to construct a model and divided each sample into different groups on the basis of risk score. The ARlncRNA signature could be recognized as an independent prognostic factor for patients with LUAD, and patients in the low-risk group had a greater survival advantage. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden. Low-risk patients had a higher PD-1, CTLA-4, and HAVCR2 expression and had a better efficacy of immune checkpoint inhibitors, including PD-1/CTLA-4 inhibitor. A reliable signature on the basis of ARlncRNAs was constructed to explore the TIME and prognosis of patients with LUAD, which could provide valuable information for individualized LUAD treatment.

Ferroptosis in Lung Cancer: From Molecular Mechanisms to Prognostic and Therapeutic Opportunities

Lung cancer is the second commonly diagnosed malignancy worldwide and has the highest mortality rate among all cancers. Tremendous efforts have been made to develop novel strategies against lung cancer; however, the overall survival of patients still is low. Uncovering underlying molecular mechanisms of this disease can open up new horizons for its treatment. Ferroptosis is a newly discovered type of programmed cell death that, in an iron-dependent manner, peroxidizes unsaturated phospholipids and results in the accumulation of radical oxygen species. Subsequent oxidative damage caused by ferroptosis contributes to cell death in tumor cells. Therefore, understanding its molecular mechanisms in lung cancer appears as a promising strategy to induce ferroptosis selectively. According to evidence published up to now, significant numbers of research have been done to identify ferroptosis regulators in lung cancer. Therefore, this review aims to provide a comprehensive standpoint of molecular mechanisms of ferroptosis in lung cancer and address these molecules’ prognostic and therapeutic values, hoping that the road for future studies in this field will be paved more efficiently.

Construction of a Ferroptosis-Related Long Non-coding RNA Prognostic Signature and Competing Endogenous RNA Network in Lung Adenocarcinoma

Ferroptosis-related genes play an important role in the progression of lung adenocarcinoma (LUAD). However, the potential function of ferroptosis-related lncRNAs in LUAD has not been fully elucidated. Thus, to explore the potential role of ferroptosis-related lncRNAs in LUAD, the transcriptome RNA-seq data and corresponding clinical data of LUAD were downloaded from the TCGA dataset. Pearson correlation was used to mine ferroptosis-related lncRNAs. Differential expression and univariate Cox analysis were performed to screen prognosis related lncRNAs. A ferroptosis-related lncRNA prognostic signature (FLPS), which included six ferroptosis-related lncRNAs, was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were divided into a high risk-score group and low risk-score group by the median risk score. Receiver operating characteristic (ROC) curves, principal component analysis (PCA), and univariate and multivariate Cox regression were performed to confirm the validity of FLPS. Enrichment analysis showed that the biological processes, pathways and markers associated with malignant tumors were more common in high-risk subgroups. There were significant differences in immune microenvironment and immune cells between high- and low-risk groups. Then, a nomogram was constructed. We further investigated the relationship between six ferroptosis-related lncRNAs and tumor microenvironment and tumor stemness. A competing endogenous RNA (ceRNA) network was established based on the six ferroptosis-related lncRNAs. Finally, we detected the expression levels of ferroptosis-related lncRNAs in clinical samples through quantitative real-time polymerase chain reaction assay (qRT-PCR). In conclusion, we identified the prognostic ferroptosis-related lncRNAs in LUAD and constructed a prognostic signature which provided a new strategy for the evaluation and prediction of prognosis in LUAD.

Targeting Ferroptosis for Lung Diseases: Exploring Novel Strategies in Ferroptosis-Associated Mechanisms

Ferroptosis is an iron-dependent regulated necrosis characterized by the peroxidation damage of lipid molecular containing unsaturated fatty acid long chain on the cell membrane or organelle membrane after cellular deactivation restitution system, resulting in the cell membrane rupture. Ferroptosis is biochemically and morphologically distinct and disparate from other forms of regulated cell death. Recently, mounting studies have investigated the mechanism of ferroptosis, and numerous proteins play vital roles in regulating ferroptosis. With detailed studies, emerging evidence indicates that ferroptosis is found in multiple lung diseases, demonstrating that ferroptosis appears to be particularly important for lung diseases. The mounting interest in ferroptosis drugs specifically targeting the ferroptosis mechanism holds substantial therapeutic promise in lung diseases. The present review emphatically summarizes the functions and integrated molecular mechanisms of ferroptosis in various lung diseases, proposing that multiangle regulation of ferroptosis might be a promising strategy for the clinical treatment of lung diseases.

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.

Prognostic value of ferroptosis-related genes in patients with lung adenocarcinoma

Background

The prevalence of lung adenocarcinomas (LUADs) has dramatically increased in recent decades. Ferroptosis is a process of iron‐dependent regulatory cell death. It is still unclear whether the expression of ferroptosis‐related genes (FRGs) is involved in the pathogenesis and survival of patients with LUAD.

Methods

We retrieved LUAD data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and used LASSO Cox regression analysis to select the gene signature suitable for modeling. The risk score was calculated according to the model, and the patients were divided into high‐ and low‐risk groups according to the median risk score. Functional enrichment analysis was carried out by this group, and a model for predicting clinical prognosis was established by combining this group with clinical factors.

Results

Gene set enrichment analysis (GSEA) and single‐sample gene set enrichment analysis (ssGSEA) analysis showed that there were several immune‐related pathways and immune infiltration differences between high‐ and low‐risk groups. A prognostic model integrating 10 ferroptosis‐related genes (FR‐DEGs), and clinical factors were constructed and validated in an external cohort.

Conclusions

The FR‐DEGs signature was related to immune infiltration, and a model based on FR‐DEGs and clinical factors was established to predict the prognosis of patients with LUAD.