Identification of the prognostic value of ferroptosis-related gene signature in breast cancer patients

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.

Emerging role of necroptosis, pyroptosis, and ferroptosis in breast cancer: New dawn for overcoming therapy resistance

Breast cancer (BC) is one of the primary causes of death in women worldwide. The challenges associated with adverse outcomes have increased significantly, and the identification of novel therapeutic targets has become increasingly urgent. Regulated cell death (RCD) refers to a type of cell death that can be regulated by several different biomacromolecules, which is distinctive from accidental cell death (ACD). In recent years, apoptosis, a representative RCD pathway, has gained significance as a target for BC medications. However, tumor cells exhibit avoidance of apoptosis and result in treatment resistance, which emphasizes further studies devoted to alternative cell death processes, namely necroptosis, pyroptosis, and ferroptosis. Here, in this review, we focus on summarizing the crucial signaling pathways of these RCD in BC. We further discuss the molecular mechanism and potentiality in clinical application of several prospective drugs, nanoparticles, and other small compounds targeting different RCD subroutines of BC. We also discuss the benefits of modulating RCD processes on drug resistance and the advantages of combining RCD modulators with conventional treatments in BC. This review will deepen our understanding of the relationship between RCD and BC, and shed new light on future directions to attack cancer vulnerabilities with RCD modulators for therapeutic purposes.

Design, synthesis, and biological evaluation of novel halogenated chlorido[N,N'-bis(salicylidene)-1,2-bis(3-methoxyphenyl)ethylenediamine]iron(III) complexes as anticancer agents

Iron(III) complexes based on N,N´-bis(salicylidene)ethylenediamine (salene) scaffolds have demonstrated promising anticancer features like induction of ferroptosis, an iron dependent cell death. Since poor cellular uptake limits their therapeutical potential, this study aimed to enhance the lipophilic character of chlorido[N,N'-bis(salicylidene)-1,2-bis(3-methoxyphenyl)ethylenediamine]iron(III) complexes by introducing lipophilicity improving ligands such as fluorine (X1), chlorine (X2) and bromine (X3) in 5-position in the salicylidene moieties. After detailed characterization the binding to nucleophiles, logP values and cellular uptake were determined. The complexes were further evaluated regarding their biological activity on MDA-MB 231 mammary carcinoma, the non-tumorous SV-80 fibroblast, HS-5 stroma and MCF-10A mammary gland cell lines. Stability of the complexes in aqueous and biological environments was proven by the lack of interactions with amino acids and glutathione. Cellular uptake was positively correlated with the logP values, indicating that higher lipophilicity enhanced cellular uptake. The complexes induced strong antiproliferative and antimetabolic effects on MDA-MB 231 cells, but were inactive on all non-malignant cells tested. Generation of mitochondrial reactive oxygen species, increase of lipid peroxidation and induction of both ferroptosis and necroptosis were identified as mechanisms of action. In conclusion, halogenation of chlorido[N,N'-bis(salicylidene)-1,2-bis(3-methoxyphenyl)ethylenediamine]iron(III) complexes raises their lipophilic character resulting in improved cellular uptake.

A novel model based on lipid metabolism-related genes associated with immune microenvironment predicts metastasis of breast cancer

BACKGROUND

Breast cancer (BC) is the most prevalent malignant tumor among women worldwide and a significant cause of cancer-related deaths in females. Recent studies have shown that lipid metabolism-related genes (LMRGs) exhibit prognostic potential in various types of tumors, including BC. Our study aimed to establish a novel model to predict the metastasis of BC.

METHODS

Clinical information and corresponding RNA data of patients with BC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering was performed to identify novel molecular subgroups. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression, microenvironment cell populations counter, microenvironment cell populations counter, and single-sample gene set enrichment analyses were employed to determine the tumor immune microenvironment and immune status of the identified subgroups. Functional analyses, including Gene Ontology and gene set enrichment analyses, were conducted to elucidate the underlying mechanisms. A prognostic risk model was constructed using the Least Absolute Shrinkage and Selection Operator algorithm and multivariate Cox regression analysis.

RESULTS

This study identified differential gene expression between patients with BC exhibiting metastasis and those without metastasis using public databases. Using the obtained data, we established predictive models based on six LMRGs. Furthermore, consensus clustering and prognostic score grouping analysis revealed that differentially expressed LMRGs influence tumor prognosis by regulating tumor immunity. To facilitate clinical application, we developed a nomogram integrating the risk model and clinical characteristics to accurately predict the prognosis of patients with BC.

CONCLUSION

We developed and validated a novel signature associated with LMRGs for predicting disease-free survival in patients with BC. The expression of LMRGs correlates with the immune microenvironment of patients with BC, providing new insights and improved strategies for the diagnosis and treatment of BC.

The regulation and function of Nrf2 signaling in ferroptosis-activated cancer therapy

Ferroptosis is an iron-dependent programmed cell death process that involves lipid oxidation via the Fenton reaction to produce lipid peroxides, causing disruption of the lipid bilayer, which is essential for cellular survival. Ferroptosis has been implicated in the occurrence and treatment response of various types of cancer, and targeting ferroptosis has emerged as a promising strategy for cancer therapy. However, cancer cells can escape cellular ferroptosis by activating or remodeling various signaling pathways, including oxidative stress pathways, thereby limiting the efficacy of ferroptosis-activating targeted therapy. The key anti-oxidative transcription factor, nuclear factor E2 related factor 2 (Nrf2 or NFE2L2), plays a dominant role in defense machinery by reprogramming the iron, intermediate, and glutathione peroxidase 4 (GPX4)-related network and the antioxidant system to attenuate ferroptosis. In this review, we summarize the recent advances in the regulation and function of Nrf2 signaling in ferroptosis-activated cancer therapy and explore the prospect of combining Nrf2 inhibitors and ferroptosis inducers as a promising cancer treatment strategy.

Construction of the circRNA-miRNA-mRNA axis based on ferroptosis-related gene AKR1C1 to explore the potential pathogenesis of abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a cardiovascular disease that seriously threatens human health and brings huge economic burden. At present, its pathogenesis remains unclear and its treatment is limited to surgical treatment. With the deepening and analysis of studies on the mechanism of ferroptosis, a new idea has been provided for the clinical management of AAA patients, including diagnosis, treatment and prevention. Therefore, this paper aims to construct a competitive endogenous RNA (ceRNA) regulatory axis based on ferroptosis to preliminarily explore the pathogenesis and potential therapeutic targets of AAA. We obtained upregulated and downregulated ferroptosis-related DEGs (FRGs) from GSE144431 dataset and 60 known ferroptosis-related genes. Pearson correlation analysis was used to find aldoketone reductase 1C (AKR1C1) in AAA samples. Enrichment analysis of these genes was performed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Correlation test between immune cells and AKR1C1 was investigated through single-sample gene set enrichment analysis (ssGSEA). The AKR1C1-miRNA pairs were predicted by the TargetScan database and miRWalk database. Circular RNA (CircRNA)-miRNA pairs were selected by the CircInteractome database. Overlapping miRNA between circRNA-miRNA and AKR1C1-miRNA pairs was visualized by Venn diagram. Finally, the circRNA-miRNA-mRNA axis was constructed by searching for upstream circRNA and downstream mRNA of overlapping miRNA. Only one downregulated AKR1C1 gene was found in GSE144431 and 60 ferroptosis-related genes. Functional Enrichment and Pathway Analysis of AKR1C1-related genes were further explored, and it was observed that they were mainly enriched in "response to oxidative stress," "glutathione biosynthetic process" and "nonribosomal peptide biosynthetic process," "Ferroptosis," "Glutathione metabolism" and "Chemical carcinogenesis-reactive oxygen species." They were also found to be significantly associated with most immune cells, including Activated Dendritic cells, CD56dim Natural killer cells, Gamma Delta T cells, Immature B cells, Plasmacytoid dendritic cell, Type 2 T helper cell, Activated CD4 T cell and Type 1 T helper cell. Has_circ_0005073-miRNA-543 and AKR1C1-miRNA-543 were identified by Online Database analysis. Therefore, we have established the has_circ_0005073/miRNA-543/AKR1C1 axis in AAA. We found AKR1C1 was differentially expressed between normal and AAA groups. Based on AKR1C1, we constructed the has_circ_0005073/miRNA-543/AKR1C1 axis to analyze AAA.

Ferroptosis defense mechanisms: The future and hope for treating osteosarcoma

Currently, challenges such as chemotherapy resistance, resulting from preoperative and postoperative chemotherapy, postoperative recurrence, and poor bone regeneration quality, are becoming increasingly prominent in osteosarcoma (OS) treatment. There is an urgent need to find more effective ways to address these issues. Ferroptosis is a novel form of iron-dependent programmed cell death, distinct from other forms of cell death. In this paper, we summarize how, through the three major defense systems of ferroptosis, not only can substances from traditional Chinese medicine, antitumor drugs, and nano-drug carriers induce ferroptosis in OS cells, but they can also be combined with immunotherapy, differentiation therapy, and other treatment modalities to significantly enhance chemotherapy sensitivity and inhibit tumor growth. Thus, ferroptosis holds great potential in treating OS, offering more choices and possibilities for future clinical interventions.

Angelica sinensis polysaccharide combined with cisplatin reverses cisplatin resistance of ovarian cancer by inducing ferroptosis via regulating GPX4

Cisplatin (DDP) resistance poses a significant challenge in the treatment of ovarian cancer. Studies have shown that the combination of certain polysaccharides derived from plants with DDP is an effective approach to overcoming drug resistance in some cancers. Angelica sinensis (Oliv.) Diels has been used for centuries in China to treat gynecological ailments. Numerous studies indicate that Angelica sinensis polysaccharide (ASP), an extract from Angelica sinensis, can inhibit various forms of cancer. However, the impact of ASP on ovarian cancer remains unexplored. Through both in vitro and in vivo experiments, our study revealed the capability of ASP to effectively reversing DDP resistance in cisplatin-resistant ovarian cancer cells, while exhibiting acceptable safety profiles in vivo. To elucidate the mechanism underlying drug resistance reversal, we employed RNA-seq analysis and identified GPX4 as a key gene. Considering the role of GPX4 in ferroptosis, we conducted additional research to explore the effects of combining ASP with DDP on SKOV3/DDP cells. In summary, our findings demonstrate that the combination of ASP and DDP effectively suppresses GPX4 expression in SKOV3/DDP cells, thereby reversing their resistance to DDP.

Inhibition of circRNA NGFR promotes ferroptosis in gallbladder carcinoma cells

Background

Gallbladder carcinoma (GBC) is a formidably aggressive malignancy. Circular RNAs (circRNAs) play crucial regulatory roles in cancer. NGFR is a novel circRNA implicated in various types of cancers. The primary goal of this study was to elucidate the role of NGFR in GBC.

Methods

NGFR variants exhibiting discernible discrepancies were identified using RNA sequencing and validated using real-time PCR. Cell proliferation was assessed using 5-ethynyl-2'-deoxyuridine and Cell Counting Kit-8 assays. The ferroptotic phenotype was characterized by assessing the reactive oxygen species and Fe2+ levels. Western blotting was used to analyze ferroptosis-associated proteins. Superoxide dismutase, malondialdehyde, and glutathione levels were measured using commercially available reagent kits. The severity of mitochondrial damage was evaluated by assessing JC-1, MitoSOX, and ATP activities.

Results

NGFR was upregulated, and its suppression inhibited cell proliferation and increased Fe2+ levels in GBC cells. Furthermore, NGFR downregulation disrupted mitochondrial function.

Conclusion

Circular RNA NGFR can impede the advancement of GBC by modulating the ferroptotic phenotype, thereby potentially offering a novel avenue for the clinical diagnosis and treatment strategies of GBC.

PESSA: A web tool for pathway enrichment score-based survival analysis in cancer

The activation levels of biologically significant gene sets are emerging tumor molecular markers and play an irreplaceable role in the tumor research field; however, web-based tools for prognostic analyses using it as a tumor molecular marker remain scarce. We developed a web-based tool PESSA for survival analysis using gene set activation levels. All data analyses were implemented via R. Activation levels of The Molecular Signatures Database (MSigDB) gene sets were assessed using the single sample gene set enrichment analysis (ssGSEA) method based on data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The European Genome-phenome Archive (EGA) and supplementary tables of articles. PESSA was used to perform median and optimal cut-off dichotomous grouping of ssGSEA scores for each dataset, relying on the survival and survminer packages for survival analysis and visualisation. PESSA is an open-access web tool for visualizing the results of tumor prognostic analyses using gene set activation levels. A total of 238 datasets from the GEO, TCGA, EGA, and supplementary tables of articles; covering 51 cancer types and 13 survival outcome types; and 13,434 tumor-related gene sets are obtained from MSigDB for pre-grouping. Users can obtain the results, including Kaplan-Meier analyses based on the median and optimal cut-off values and accompanying visualization plots and the Cox regression analyses of dichotomous and continuous variables, by selecting the gene set markers of interest. PESSA (https://smuonco.shinyapps.io/PESSA/ OR http://robinl-lab.com/PESSA) is a large-scale web-based tumor survival analysis tool covering a large amount of data that creatively uses predefined gene set activation levels as molecular markers of tumors.

Targeting Group 3 Medulloblastoma by the Anti-PRUNE-1 and Anti-LSD1/KDM1A Epigenetic Molecules

Medulloblastoma (MB) is a highly malignant childhood brain tumor. Group 3 MB (Gr3 MB) is considered to have the most metastatic potential, and tailored therapies for Gr3 MB are currently lacking. Gr3 MB is driven by PRUNE-1 amplification or overexpression. In this paper, we found that PRUNE-1 was transcriptionally regulated by lysine demethylase LSD1/KDM1A. This study aimed to investigate the therapeutic potential of inhibiting both PRUNE-1 and LSD1/KDM1A with the selective inhibitors AA7.1 and SP-2577, respectively. We found that the pharmacological inhibition had a substantial efficacy on targeting the metastatic axis driven by PRUNE-1 (PRUNE-1-OTX2-TGFβ-PTEN) in Gr3 MB. Using RNA seq transcriptomic feature data in Gr3 MB primary cells, we provide evidence that the combination of AA7.1 and SP-2577 positively affects neuronal commitment, confirmed by glial fibrillary acidic protein (GFAP)-positive differentiation and the inhibition of the cytotoxic components of the tumor microenvironment and the epithelial-mesenchymal transition (EMT) by the down-regulation of N-Cadherin protein expression. We also identified an impairing action on the mitochondrial metabolism and, consequently, oxidative phosphorylation, thus depriving tumors cells of an important source of energy. Furthermore, by overlapping the genomic mutational signatures through WES sequence analyses with RNA seq transcriptomic feature data, we propose in this paper that the combination of these two small molecules can be used in a second-line treatment in advanced therapeutics against Gr3 MB. Our study demonstrates that the usage of PRUNE-1 and LSD1/KDM1A inhibitors in combination represents a novel therapeutic approach for these highly aggressive metastatic MB tumors.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer

BACKGROUND

Ferroptosis has recently been associated with multiple degenerative diseases. Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases. However, the association of iron proliferation-related genes with prognosis in HER2+ breast cancer (BC) patients is unclear.

AIM

To identify and evaluate fresh ferroptosis-related biomarkers for HER2+ BC.

METHODS

First, we obtained the mRNA expression profiles and clinical information of HER2+ BC patients from the TCGA and METABRIC public databases. A four-gene prediction model comprising PROM2, SLC7A11, FANCD2, and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort. Patients were stratified into high-risk and low-risk groups based on their median risk score, an independent predictor of overall survival (OS). Based on these findings, immune infiltration, mutations, and medication sensitivity were analyzed in various risk groupings. Additionally, we assessed patient prognosis by combining the tumor mutation burden (TMB) with risk score. Finally, we evaluated the expression of critical genes by analyzing single-cell RNA sequencing (scRNA-seq) data from malignant vs normal epithelial cells.

RESULTS

We found that the higher the risk score was, the worse the prognosis was (P < 0.05). We also found that the immune cell infiltration, mutation, and drug sensitivity were different between the different risk groups. The high-risk subgroup was associated with lower immune scores and high TMB. Moreover, we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses. HRisk-HTMB patients had the worst prognosis, whereas LRisk-LTMB patients had the best prognosis (P < 0.0001). Analysis of the scRNA-seq data showed that PROM2, SLC7A11, and FANCD2 were significantly differentially expressed, whereas FH was not, suggesting that these genes are expressed mainly in cancer epithelial cells (P < 0.01).

CONCLUSION

Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

Background

Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer.

Methods

The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool.

Results

BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans.

Conclusion

The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Metabolism-regulated ferroptosis in cancer progression and therapy

Cancer metabolism mainly includes carbohydrate, amino acid and lipid metabolism, each of which can be reprogrammed. These processes interact with each other to adapt to the complicated microenvironment. Ferroptosis is a regulated cell death induced by iron-dependent lipid peroxidation, which is morphologically different from apoptosis, necrosis, necroptosis, pyroptosis, autophagy-dependent cell death and cuprotosis. Cancer metabolism plays opposite roles in ferroptosis. On the one hand, carbohydrate metabolism can produce NADPH to maintain GPX4 and FSP1 function, and amino acid metabolism can provide substrates for synthesizing GPX4; on the other hand, lipid metabolism might synthesize PUFAs to trigger ferroptosis. The mechanisms through which cancer metabolism affects ferroptosis have been investigated extensively for a long time; however, some mechanisms have not yet been elucidated. In this review, we summarize the interaction between cancer metabolism and ferroptosis. Importantly, we were most concerned with how these targets can be utilized in cancer therapy.

Endoplasmic reticulum stress in breast cancer: a predictive model for prognosis and therapy selection

Background

Breast cancer (BC) is a leading cause of mortality among women, underscoring the urgent need for improved therapeutic predictio. Developing a precise prognostic model is crucial. The role of Endoplasmic Reticulum Stress (ERS) in cancer suggests its potential as a critical factor in BC development and progression, highlighting the importance of precise prognostic models for tailored treatment strategies.

Methods

Through comprehensive analysis of ERS-related gene expression in BC, utilizing both single-cell and bulk sequencing data from varied BC subtypes, we identified eight key ERS-related genes. LASSO regression and machine learning techniques were employed to construct a prognostic model, validated across multiple datasets and compared with existing models for its predictive accuracy.

Results

The developed ERS-model categorizes BC patients into distinct risk groups with significant differences in clinical prognosis, confirmed by robust ROC, DCA, and KM analyses. The model forecasts survival rates with high precision, revealing distinct immune infiltration patterns and treatment responsiveness between risk groups. Notably, we discovered six druggable targets and validated Methotrexate and Gemcitabine as effective agents for high-risk BC treatment, based on their sensitivity profiles and potential for addressing the lack of active targets in BC.

Conclusion

Our study advances BC research by establishing a significant link between ERS and BC prognosis at both the molecular and cellular levels. By stratifying patients into risk-defined groups, we unveil disparities in immune cell infiltration and drug response, guiding personalized treatment. The identification of potential drug targets and therapeutic agents opens new avenues for targeted interventions, promising to enhance outcomes for high-risk BC patients and paving the way for personalized cancer therapy.

GPX4 is a potential diagnostic and therapeutic biomarker associated with diffuse large B lymphoma cell proliferation and B cell immune infiltration

At present, GPX4's role in the occurrence and development of diffuse large B lymphoma (DLBCL) is rarely reported. This study's purpose is to explore GPX4's significance in the diagnosis, treatment, and pathological mechanisms of DLBCL. The TIMER 2.0, GEPIA, and GEO databases were used to analyze GPX4's expression levels in DLBCL tissue, peripheral blood, and single cells, and evaluate its potential performance as a therapeutic and diagnostic marker. Cell experiments validate GPX4's role in DLBCL cells. And revealed the potential mechanism of GPX4's action from three aspects: immunity, pathogenic gene expression, and protein interaction. The results indicate that GPX4 can be used as a biomarker for treatment and diagnosis (FC > 1.5, P < 0.05, AUC>0.8, KM-P value < 0.05). In single cell data, GPX4 also showed high expression in immune cells. Besides, cell experiments have confirmed that GPX4's high expression can inhibit DLBCL cells' proliferation. Meanwhile, we found a negative correlation between GPX4 and the 16 core DLBCL's pathogenic genes, and a significant negative correlation with immune B cell infiltration. In summary, GPX4 can serve as a potential therapeutic and diagnostic marker for DLBCL. GPX4's high expression can lead to a good prognosis in DLBCL patients, which may be related to its inhibition of cancer cell proliferation, high expression of key pathogenic genes, and infiltration of immune B cells.

Butyrate ameliorated ferroptosis in ulcerative colitis through modulating Nrf2/GPX4 signal pathway and improving intestinal barrier

Oxidative stress and intestinal inflammation are main pathological features of ulcerative colitis (UC). Ferroptosis, characterized by iron accumulation and lipid peroxidation, is closely related to the pathologic process of UC. 16S rRNA sequencing for intestinal microbiota analysis and gas chromatography-mass spectrometry (GC-MS) for short-chain fatty acid (SCFA) contents clearly demonstrated lower amounts of butyrate-producing bacteria and butyrate in colitis mice. However, the precise mechanisms of sodium butyrate (NaB) in treating UC remain largely unclear. We found that ferroptosis occurred in colitis models, as evidenced by the inflammatory response, intracellular iron level, mitochondria ultrastructural observations and associated protein expression. NaB inhibited ferroptosis in colitis, significantly rescued weight loss and colon shortening in mice and reduced inflammatory lesions and mitochondrial damage. Furthermore, NaB improved intestinal barrier integrity and markedly suppressed the expression of pro-ferroptosis proteins. Conversely, the protein expression of anti-ferroptosis markers including nuclear factor erythroid-related Factor 2 (Nrf2) and glutathione peroxidase 4 (GPX4), was significantly upregulated with NaB treatment. Moreover, the knockdown of Nrf2 reversed the anti-colitis effect of NaB. Taken together, NaB exhibited a protective effect by ameliorating ferroptosis in experimental colitis through Nrf2/GPX4 signaling and improving intestinal barrier integrity, which provides a novel mechanism for NaB prevention of UC.

POU2F2-mediated upregulation of lncRNA PTPRG-AS1 inhibits ferroptosis in breast cancer via miR-376c-3p/SLC7A11 axis

Background: Triple-negative breast cancer (TNBC) is a subtype of BC with high rates of mortality. The mechanism of PTPRG-AS1 in ferroptosis of TNBC was investigated. Methods: Chromatin immunoprecipitation and dual-luciferase reporter assays were used to measure intermolecular relationships. MTT and colony formation assays detected cell viability and proliferation. Kits detected Fe2+ and reactive oxygen species levels. The role of PTPRG-AS1 in tumor growth was analyzed in vivo. Results: PTPRG-AS1 was increased in TNBC tissues and cells. PTPRG-AS1 silencing increased the reduction of glutathione and GPX4, increased Fe2+ and reactive oxygen species in erastin-treated cells and inhibited proliferation. POU2F2 transcriptionally upregulated PTPRG-AS1. PTPRG-AS1 targeted miR-376c-3p to upregulate SLC7A11. PTPRG-AS1 knockdown suppressed tumor growth in vivo. Conclusion: POU2F2 transcriptionally activates PTPRG-AS1 to modulate ferroptosis and proliferation by miR-376c-3p/SLC7A11, promoting TNBC.

The integration of multidisciplinary approaches revealed PTGES3 as a novel drug target for breast cancer treatment

BACKGROUND

The main challenge in personalized treatment of breast cancer (BC) is how to integrate massive amounts of computing resources and data. This study aimed to identify a novel molecular target that might be effective for BC prognosis and for targeted therapy by using network-based multidisciplinary approaches.

METHODS

Differentially expressed genes (DEGs) were first identified based on ESTIMATE analysis. A risk model in the TCGA-BRCA cohort was constructed using the risk score of six DEGs and validated in external and clinical in-house cohorts. Subsequently, independent prognostic factors in the internal and external cohorts were evaluated. Cell viability CCK-8 and wound healing assays were performed after PTGES3 siRNA was transiently transfected into the BC cell lines. Drug prediction and molecular docking between PTGES3 and drugs were further analyzed. Cell viability and PTGES3 expression in two BC cell lines after drug treatment were also investigated.

RESULTS

A novel six-gene signature (including APOOL, BNIP3, F2RL2, HINT3, PTGES3 and RTN3) was used to establish a prognostic risk stratification model. The risk score was an independent prognostic factor that was more accurate than clinicopathological risk factors alone in predicting overall survival (OS) in BC patients. A high risk score favored tumor stage/grade but not OS. PTGES3 had the highest hazard ratio among the six genes in the signature, and its mRNA and protein levels significantly increased in BC cell lines. PTGES3 knockdown significantly inhibited BC cell proliferation and migration. Three drugs (gedunin, genistein and diethylstilbestrol) were confirmed to target PTGES3, and genistein and diethylstilbestrol demonstrated stronger binding affinities than did gedunin. Genistein and diethylstilbestrol significantly inhibited BC cell proliferation and reduced the protein and mRNA levels of PTGES3.

CONCLUSIONS

PTGES3 was found to be a novel drug target in a robust six-gene prognostic signature that may serve as a potential therapeutic strategy for BC.

Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia

BACKGROUND

Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this study was to analyze the expression of ferroptosis-related genes (FRGs) in GIM tissues and to explore the relationship between ferroptosis and GIM.

METHOD

The results of GIM tissue full transcriptome sequencing were downloaded from Gene Expression Omnibus(GEO) database. R software (V4.2.0) and R packages were used for screening and enrichment analysis of differentially expressed genes(DEGs). The key genes were screened by least absolute shrinkage and selection operator(LASSO) and support vector machine-recursive feature elimination(SVM-RFE) algorithm. Receiver operating characteristic(ROC) curve was used to evaluate the diagnostic efficacy of key genes in GIM. Clinical samples were used to further validate hub genes.

RESULTS

A total of 12 differentially expressed ferroptosis-related genes (DEFRGs) were identified. Using two machine learning algorithms, GOT1, ALDH3A2, ACSF2 and SESN2 were identified as key genes. The area under ROC curve (AUC) of GOT1, ALDH3A2, ACSF2 and SESN2 in the training set were 0.906, 0.955, 0.899 and 0.962 respectively, and the AUC in the verification set were 0.776, 0.676, 0.773 and 0.880, respectively. Clinical samples verified the differential expression of GOT1, ACSF2, and SESN2 in GIM.

CONCLUSION

We found that there was a significant correlation between ferroptosis and GIM. GOT1, ACSF2 and SESN2 can be used as diagnostic markers to effectively identify GIM.

The Emerging Roles of the Metabolic Regulator G6PD in Human Cancers

Metabolic reprogramming, especially reprogrammed glucose metabolism, is a well-known cancer hallmark related to various characteristics of tumor cells, including proliferation, survival, metastasis, and drug resistance. Glucose-6-phosphate dehydrogenase (G6PD) is the first and rate-limiting enzyme of the pentose phosphate pathway (PPP), a branch of glycolysis, that converts glucose-6-phosphate (G6P) into 6-phosphogluconolactone (6PGL). Furthermore, PPP produces ribose-5-phosphate (R5P), which provides sugar-phosphate backbones for nucleotide synthesis as well as nicotinamide adenine dinucleotide phosphate (NADPH), an important cellular reductant. Several studies have shown enhanced G6PD expression and PPP flux in various tumor cells, as well as their correlation with tumor progression through cancer hallmark regulation, especially reprogramming cellular metabolism, sustaining proliferative signaling, resisting cell death, and activating invasion and metastasis. Inhibiting G6PD could suppress tumor cell proliferation, promote cell death, reverse chemoresistance, and inhibit metastasis, suggesting the potential of G6PD as a target for anti-tumor therapeutic strategies. Indeed, while challenges-including side effects-still remain, small-molecule G6PD inhibitors showing potential anti-tumor effect either when used alone or in combination with other anti-tumor drugs have been developed. This review provides an overview of the structural significance of G6PD, its role in and regulation of tumor development and progression, and the strategies explored in relation to G6PD-targeted therapy.

SNORA56-mediated pseudouridylation of 28 S rRNA inhibits ferroptosis and promotes colorectal cancer proliferation by enhancing GCLC translation

BACKGROUND

Colorectal cancer (CRC) is one of the most common malignancies and is characterized by reprogrammed metabolism. Ferroptosis, a programmed cell death dependent on iron, has emerged as a promising strategy for CRC treatment. Although small nucleolar RNAs are extensively involved in carcinogenesis, it is unclear if they regulate ferroptosis during CRC pathogenesis.

METHODS

The dysregulated snoRNAs were identified using published sequencing data of CRC tissues. The expression of the candidate snoRNAs, host gene and target gene were assessed by real-time quantitative PCR (RT-qPCR), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC) and western blots. The biological function of critical molecules was investigated using in vitro and in vivo strategies including Cell Counting Kit-8 (CCK8), colony formation assay, flow cytometry, Fe2+/Fe3+, GSH/GSSG and the xenograft mice models. The ribosomal activities were determined by polysome profiling and O-propargyl-puromycin (OP-Puro) assay. The proteomics was conducted to clarify the downstream targets and the underlying mechanisms were validated by IHC, Pearson correlation analysis, protein stability and rescue assays. The clinical significance of the snoRNA was explored using the Cox proportional hazard model, receiver operating characteristic (ROC) and survival analysis.

RESULTS

Here, we investigated the SNORA56, which was elevated in CRC tissues and plasma, and correlated with CRC prognosis. SNORA56 deficiency in CRC impaired proliferation and triggered ferroptosis, resulting in reduced tumorigenesis. Mechanistically, SNORA56 mediated the pseudouridylation of 28 S rRNA at the U1664 site and promoted the translation of the catalytic subunit of glutamate cysteine ligase (GCLC), an indispensable rate-limiting enzyme in the biosynthesis of glutathione, which can inhibit ferroptosis by suppressing lipid peroxidation.

CONCLUSIONS

Therefore, the SNORA56/28S rRNA/GCLC axis stimulates CRC progression by inhibiting the accumulation of cellular peroxides, and it may provide biomarker and therapeutic applications in CRC.

Development and validation of stable ferroptosis- and pyroptosis-related signatures in predicting prognosis and immune status in breast cancer

To develop and validate the predictive effects of stable ferroptosis- and pyroptosis-related features on the prognosis and immune status of breast cancer (BC). We retrieved as well as downloaded ferroptosis- and pyroptosis-related genes from the FerrDb and GeneCards databases. The minimum absolute contraction and selection operator (LASSO) algorithm in The Cancer Genome Atlas (TCGA) was used to construct a prognostic classifier combining the above two types of prognostic genes with differential expression, and the Integrated Gene Expression (GEO) dataset was used for validation. Seventeen genes presented a close association with BC prognosis. Thirteen key prognostic genes with prognostic value were considered to construct a new expression signature for classifying patients with BC into high- and low-risk groups. Kaplan-Meier analysis revealed a worse prognosis in the high-risk group. The receiver operating characteristic (ROC) curve and multivariate Cox regression analysis identified its predictive and independent features. Immune profile analysis showed that immunosuppressive cells were upregulated in the high-risk group, and this risk model was related to immunosuppressive molecules. We successfully constructed combined features of ferroptosis and pyroptosis in BC that are closely related to prognosis, clinicopathological and immune features, chemotherapy efficacy and immunosuppressive molecules. However, further experimental studies are required to verify these findings.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

Tamoxifen induces ferroptosis in MCF-7 organoid

BACKGROUND

Breast cancer is the most common female malignant tumor type globally. The occurrence and development of breast cancer involve ferroptosis, which is closely related to its treatment. The development of breast cancer organoids facilitates the analysis of breast cancer molecular background and tumor biological behavior, including clinical pathological characteristics, drug response, or drug resistance relationship, and promotes the advancement of precision treatment for breast cancer. The three-dimensional (3D) cell culture of breast cancer MCF-7 organoid is more similar to the in vivo environment and thus obtains more realistic results than 2D cell culture. Our study examined the new mechanism of tamoxifen in treating breast cancer through breast cancer MCF-7 organoids.

METHODS

We used 3D cells to culture breast cancer MCF-7 organoid, as well as tamoxifen-treated MCF-7 and tamoxifen-resistant MCF-7 (MCF-7 TAMR) cells. We used transcriptome sequencing. We detected GPX4 and SLC7A11 protein levels using Western blotting and the content of ATP, glutathione, and ferrous ions using the Cell Counting Lite 3D Kit. We assessed cell viability using the Cell Counting Kit-8 (CCK-8) assay.

RESULTS

Tamoxifen significantly inhibited the growth of MCF-7 organoids and significantly induced ferroptosis in MCF-7 organoids. The ferroptosis inhibitor reversed the significant tamoxifen-induced MCF-7 organoid inhibition activity. Moreover, the ferroptosis activator enhanced the tamoxifen-induced MCF-7 TAMR cell activity inhibition.

CONCLUSION

Our study revealed that ferroptosis plays an important role in tamoxifen-induced MCF-7 organoid cell death and provides a new research idea for precise treatment of breast cancer through an organoid model.

Identification of a novel five ferroptosis-related gene signature as a promising prognostic model for breast cancer

BACKGROUND

Breast cancer (BCa) is a major challenge for women's health worldwide. Ferroptosis is closely related to tumorigenesis and cancer progression. However, the prognostic value of ferroptosis-related genes in BCa remains unclear, and more accurate prognostic models are urgently needed.

METHODS

Gene expression profiles and clinical information of BCa patients were collected from public databases. LASSO and multivariate Cox regression analysis were utilized to construct the prognostic gene signature. Kaplan-Meier plotter, receiver operating characteristic (ROC) curves, and nomogram were used to validate the prognostic value of the gene signature. Gene set enrichment analysis was performed to explore the molecular functions and signaling pathways.

RESULTS

Differentially expressed ferroptosis-related genes between BCa samples and normal tissues were obtained. A novel five-gene signature including BCL2, SLC40A1, TFF1, APOOL, and PRAME was established for prognosis prediction. Patients stratified into high-risk or low-risk group displayed significantly different survival. Kaplan-Meier and ROC curves showed a good performance for survival prediction in different cohorts. Biological function analysis revealed that the five-gene signature was associated with cancer progression, immune infiltration, immune response, and drug resistance. Nomogram including the five-gene signature was established.

CONCLUSION

A novel five ferroptosis-related gene signature and nomogram could be used for prognostic prediction in BCa.

Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in breast cancer

Introduction

Breast cancer (BC) is now the most common type of cancer in women. Disulfidptosis is a new regulation of cell death (RCD). RCD dysregulation is causally linked to cancer. However, the comprehensive relationship between disulfidptosis and BC remains unknown. This study aimed to explore the predictive value of disulfidptosis-related genes (DRGs) in BC and their relationship with the TME.

Methods

This study obtained 11 disulfidptosis genes (DGs) from previous research by Gan et al. RNA sequencing data of BC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO) databases. First, we examined the effect of DG gene mutations and copy number changes on the overall survival of breast cancer samples. We then used the expression profile data of 11 DGs and survival data for consensus clustering, and BC patients were divided into two clusters. Survival analysis, gene set variation analysis (GSVA) and ss GSEA were used to compare the differences between them. Subsequently, DRGs were identified between the clusters used to perform Cox regression and least absolute shrinkage and selection operator regression (LASSO) analyses to construct a prognosis model. Finally, the immune cell infiltration pattern, immunotherapy response, and drug sensitivity of the two subtypes were analyzed. CCK-8 and a colony assay obtained by knocking down genes and gene sequencing were used to validate the model.

Result

Two DG clusters were identified based on the expression of 11DGs. Then, 225 DRGs were identified between them. RS, composed of six genes, showed a significant relationship with survival, immune cell infiltration, clinical characteristics, immune checkpoints, immunotherapy response, and drug sensitivity. Low-RS shows a better prognosis and higher immunotherapy response than high-RS. A nomogram with perfect stability constructed using signature and clinical characteristics can predict the survival of each patient. CCK-8 and colony assay obtained by knocking down genes have demonstrated that the knockdown of high-risk genes in the RS model significantly inhibited cell proliferation.

Discussion

This study elucidates the potential relationship between disulfidptosis-related genes and breast cancer and provides new guidance for treating breast cancer.

Analysis of a new therapeutic target and construction of a prognostic model for breast cancer based on ferroptosis genes

Breast cancer, which is the most common malignant tumor among women worldwide and an important cause of death in women. The existing prognostic model for patients with breast cancer is not accurate as breast cancer is resistant to commonly used antitumor drugs. Ferroptosis is a novel mechanism of programmed cell death that depends on iron accumulation and lipid peroxidation. Various studies have confirmed the role of ferroptosis in tumor regulation and ferroptosis is now considered to play an important role in breast cancer development. At present, the association between breast cancer prognosis and ferroptosis-related gene expression remains unclear. Further exploration of this research area may optimize the evaluation and prediction of prognosis of patients with breast cancer and finding of new therapeutic targets. In this study, clinical factors and the expression of multiple genes were evaluated in breast cancer samples from the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database database. Eleven prognostication-related genes (TP63, IFNG, MT3, ANO6, FLT3, PTGS2, SLC1A4, JUN, SLC7A5, CHAC1, and TF) were identified from differentially expressed genes to construct a survival prediction model, which showed a good prediction ability. KEGG pathway analysis revealed that immune-related pathways were the primary pathways. ssGSEA analysis showed significant differences in the distribution of certain immune-related cell subsets, such as CD8+T cells and B cells, and in the expression of multiple immune genes, including type II IFN response and APC coinhibition. In addition, 10 immune targets related to ferroptosis in breast cancer were found: CD276, CD80, HHLA2, LILRA2, NCR3LG1, NECTIN3, PVR, SLAMF9,TNFSF4, and BTN1A1. Using TCGA, new ferroptosis genes related to breast cancer prognosis were identified, a new reliable and accurate prognosis model was developed, and 10 new potential therapeutic targets different from the traditional targeted drugs were identified to provide a reference for improving the poor prognosis of patients with breast cancer.

A prognostic model related to necrotizing apoptosis of breast cancer based on biorthogonal constrained depth semi-supervised nonnegative matrix decomposition and single-cell sequencing analysis

Breast cancer (BC) is one of the most common malignant tumours in women, and its prognosis is poor. The prognosis of BC patients can be improved by immunotherapy. However, due to the heterogeneity of BC, the identification of new biomarkers is urgently needed to improve the prognosis of BC patients. Necrotic apoptosis has been shown to play an essential role in many cancers. First, this study proposed a novel clustering algorithm called biorthogonal constrained depth semisupervised nonnegative matrix factorization (DO-DSNMF). The DO-DSNMF algorithm added multilayer nonlinear transformation to the coefficient matrix obtained after decomposition, which was used to mine the nonlinear relationship between samples. In addition, we also added orthogonal constraints on the basis matrix and coefficient matrix to reduce the influence of redundant features and samples on the results. We applied the DO-DSNMF algorithm and analysed the differences in survival and immunity between the subtypes. Then, we used prognosis analysis to construct the prognosis model. Finally, we analysed single cells using single-cell sequencing (scRNA-seq) data from the GSE75688 dataset in the GEO database. We identified two BC subtypes based on the BC transcriptome data in the TCGA database. Immune infiltration analysis showed that the necrotizing apoptosis-related genes of BC were related to various immune cells and immune functions. Necrotizing apoptosis was found to play a role in BC progression and immunity. The role of prognosis-related NRGs in BC was also verified by cell experiments. This study proposed a novel clustering algorithm to analyse BC subtypes and constructed an NRG prognostic model for BC. The prognosis and immune landscape of BC patients were evaluated by this model. The cell experiment supported its role in BC, which provides a potential therapeutic target for the treatment of BC.

Differences of ferroptosis-related genes between White and Asian patients with liver cancer

Ferroptosis results from metabolic dysregulation and is closely linked to liver cancer. Although a ferroptosis-related gene signature in liver cancer has been established, the precise regulatory mechanism is still unclear. To identify shared pathogenic genes linked to ferroptosis across liver cancer patients from diverse racial backgrounds, we evaluated various ferroptosis-related genes, constructing a signature for both Asian and White patients using The Cancer Genome Atlas (TCGA) database. Based on the differential expression and functionality of ferroptosis-associated genes, we selected Farnesyl diphosphate farnesyl transferase 1 (FDFT1), Acyl-CoA synthetase long-chain 4 (ACSL4) and Endoplasmic reticulum membrane protein complex 2 (EMC2) for further study in liver cancer cells. FDFT1, ACSL4 and EMC2 induced ferroptosis of liver cancer cells though upregulation of reactive oxygen species (ROS) levels and downregulation of glutathione peroxidase (GPX4). Current data indicate no notable influence of racial differences on the functionality of ferroptosis-related genes. Our data suggests potential novel therapeutic avenues for liver cancer treatment.

A novel disulfidptosis-associated expression pattern in breast cancer based on machine learning

Background: Breast cancer (BC), the leading cause of cancer-related deaths among women, remains a serious threat to human health worldwide. The biological function and prognostic value of disulfidptosis as a novel strategy for BC treatment via induction of cell death remain unknown. Methods: Gene mutations and copy number variations (CNVs) in 10 disulfidptosis genes were evaluated. Differential expression, prognostic, and univariate Cox analyses were then performed for 10 genes, and BC-specific disulfidptosis-related genes (DRGs) were screened. Unsupervised consensus clustering was used to identify different expression clusters. In addition, we screened the differentially expressed genes (DEGs) among different expression clusters and identified hub genes. Moreover, the expression level of DEGs was detected by RT-qPCR in cellular level. Finally, we used the least absolute shrinkage and selection operator (LASSO) regression algorithm to establish a prognostic feature based on DEGs, and verified the accuracy and sensitivity of its prediction through prognostic analysis and subject operating characteristic curve analysis. The correlation of the signature with the tumor immune microenvironment and tumor stemness was analyzed. Results: Disulfidptosis genes showed significant CNVs. Two clusters were identified based on three DRGs (DNUFS1, LRPPRC, SLC7A11). Cluster A was found to be associated with better survival outcomes(p < 0.05) and higher levels of immune cell infiltration(p < 0.05). A prognostic signature of four disulfidptosis-related DEGs (KIF21A, APOD, ALOX15B, ELOVL2) was developed by LASSO regression analysis. The signature showed a good prediction ability. In addition, the prognostic signature in this study were strongly related to the tumor microenvironment (TME), tumor immune cell infiltration, tumor mutation burden (TMB), tumor stemness, and drug sensitivity. Conclusion: The prognostic signature we constructed based on disulfidptosis-DEGs is a good predictor of prognosis in patients with BC. This prognostic signature is closely related to TME, and its potential correlation provides clues for further studies.

MFAP2 enhances cisplatin resistance in gastric cancer cells by regulating autophagy

Background

Cisplatin (CDDP) is of importance in cancer treatment and widely used in advanced gastric cancer (GC). However, its clinical usage is limited due to its resistance, and the regulatory mechanism of CDDP resistance in GC has not yet been fully elucidated. In this study, we first conducted a comprehensive study to investigate the role of MFAP2 through bioinformatics analysis.

Methods

The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were applied to downloadgene expression data and clinicopathologic data, and the differentially expressed genes (DEGs) were further analyzed. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and survival analysis were conducted. Furthermore, according to the clinicopathological characteristics of TCGA, clinical correlation analysis was conducted, and a receiver operating characteristic curve (ROC) was plotted.

Results

We revealed that FAP, INHBA and MFAP2 were good diagnostic factors of GC. However, the mechanism of MFAP2 in GC remains elusive, especially in the aspect of chemotherapy resistance. We developed the CDDP-resistant cell line, and found that MFAP2 was upregulated in CDDP-resistant cells, and MFAP2-knockdown improved CDDP sensitivity. Finally, we found that MFAP2 enhanced CDDP resistance by inducing autophagy in drug-resistant cell lines.

Conclusions

The above results suggested that MFAP2 could affect the chemotherapy resistance by altering the level of autophagy in GC patients as a potential therapeutic target.

Bioinformatics identification and validation of aging‑related molecular subtype and prognostic signature in breast cancer

Patients with metastatic breast cancer have a poor clinical outcome, accounting for more than 90 percent of breast cancer-related deaths. Aging could regulate many biological processes in malignancies by regulating cell senescence. The role of aging has not been fully clarified. Consensus cluster analysis was performed to differentiate The Cancer Genome Atlas (TCGA) breast cancer cases. Least absolute shrinkage and selection operator (LASSO) cox regression analysis was performed to construct an aging-related prognostic signature. A total of 118 differentially expressed aging-related genes (ARGs) was obtained in breast cancer. Consensus clustering analysis identified 3 categories of TCGA-breast cancer with significant difference in prognosis and immune infiltration. We also constructed an aging-related prognostic signature for breast cancer, which had a good performance in predicting the 1-year, 3-year and 5-year OS and disease specific survival (DSS) of breast cancer patients. Further single gene analysis revealed that the expression of PIK3R1 was significantly different in different pT and pN stages of breast cancer. Moreover, low expression of PIK3R1 showed resistance to many drugs based on the data of Genomics of Drug Sensitivity in Cancer (GDSC) and Genomics of Therapeutics Response Portal (CTRP). PIK3R1 played a vital role in many well-known cancer-related pathways. The current study identified 3 clusters of TCGA-breast cancer cases with significant differences in prognosis and immune infiltration. We also constructed an aging-related prognostic signature for breast cancer. However, further in vivo and in vitro studies should be conducted to verify these results.

A novel PD-1/PD-L1 pathway molecular typing-related signature for predicting prognosis and the tumor microenvironment in breast cancer

BACKGROUND

Currently, the development of breast cancer immunotherapy based on the PD-1/PD-L1 pathway is relatively slow, and the specific mechanism affecting the immunotherapy efficacy in breast cancer is still unclear.

METHODS

Weighted correlation network analysis (WGCNA) and the negative matrix factorization (NMF) were used to distinguish subtypes related to the PD-1/PD-L1 pathway in breast cancer. Then univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were used to construct the prognostic signature. A nomogram was established based on the signature. The relationship between the signature gene IFNG and breast cancer tumor microenvironment was analyzed.

RESULTS

Four PD-1/PD-L1 pathway-related subtypes were distinguished. A prognostic signature related to PD-1/PD-L1 pathway typing was constructed to evaluate breast cancer's clinical characteristics and tumor microenvironment. The nomogram based on the RiskScore could be used to accurately predict breast cancer patients' 1-year, 3-year, and 5-year survival probability. The expression of IFNG was positively correlated with CD8+ T cell infiltration in the breast cancer tumor microenvironment.

CONCLUSION

A prognostic signature is constructed based on the PD-1/PD-L1 pathway typing in breast cancer, which can guide the precise treatment of breast cancer. The signature gene IFNG is positively related to CD8+ T cell infiltration in breast cancer.

Role of Escin in breast cancer therapy: potential mechanism for inducing ferroptosis and synergistic antitumor activity with cisplatin

Breast cancer (BC) has threatened women worldwide for a long time, and novel treatments are needed. Ferroptosis is a new form of regulated cell death that is a potential therapeutic target for BC. In this study, we identified Escin, a traditional Chinese medicine, as a possible supplement for existing chemotherapy strategies. Escin inhibited BC cell growth in vitro and in vivo, and ferroptosis is probable to be the main cause for Escin-induced cell death. Mechanistically, Escin significantly downregulated the protein level of GPX4, while overexpression of GPX4 could reverse the ferroptosis triggered by Escin. Further study revealed that Escin could promote G6PD ubiquitination and degradation, thus inhibiting the expression of GPX4 and contributing to the ferroptosis. Moreover, proteasome inhibitor MG132 or G6PD overexpression could partially reverse Escin-induced ferroptosis, when G6PD knockdown aggravated that. In vivo study also supported that downregulation of G6PD exacerbated tumor growth inhibition by Escin. Finally, our data showed that cell apoptosis was dramatically elevated by Escin combined with cisplatin in BC cells. Taken together, these results suggest that Escin inhibits tumor growth in vivo and in vitro via regulating the ferroptosis mediated by G6PD/GPX4 axis. Our findings provide a promising therapeutic strategy for BC.

An immune-related prognostic model predicts neoplasm-immunity interactions for metastatic nasopharyngeal carcinoma

Background

The prognosis of nasopharyngeal carcinoma (NPC) has been recognized to improve immensely owing to radiotherapy combined with chemotherapy. However, patients with metastatic NPC have a poor prognosis. Immunotherapy has dramatically prolonged the survival of patients with NPC. Hence, further research on immune-related biomarkers is imperative to establish the prognosis of metastatic NPC.

Methods

10 NPC RNA expression profiles were generated from patients with or without distant metastasis after chemoradiotherapy from the Fujian Cancer Hospital. The differential immune-related genes were identified and validated by immunohistochemistry analysis. The method of least absolute shrinkage and selection operator (LASSO)was used to further establish the immune-related prognostic model in an external GEO database (GSE102349, n=88). The immune microenvironment and signal pathways were evaluated in multiple dimensions at the transcriptome and single-cell levels.

Results

1328 differential genes were identified, out of which 520 were upregulated and 808 were downregulated. Notably, most of the immune genes and pathways were down-regulated in the metastasis group. A prognostic immune model involving nine hub genes. Patients in low-risk group were characterized by survival advantage, hot immune phenotype and benefit from immunotherapy. Compared with immune cells, malignant cell exhibited the most active levels of risk score by ssGSEA. Accordingly, intercellular communications including LT, CD70, CD40 and SPP1, and the like, between high-risk and low-risk were explored by the R package “Cellchat”.

Conclusion

We have constructed a model based on immunity of metastatic NPC and determined its prognostic value. The model identified the level of immune cell infiltration, cell-cell communication, along with potential immunotherapy for metastatic NPC.

Upregulation of the ferroptosis-related STEAP3 gene is a specific predictor of poor triple-negative breast cancer patient outcomes

Objective

This study was designed to assess ferroptosis regulator gene (FRG) expression patterns in patients with TNBC based on data derived from The Cancer Genome Atlas (TCGA). Further, it was utilized to establish a TNBC FRG signature, after which the association between this signature and the tumor immune microenvironment (TIME) composition was assessed, and relevant prognostic factors were explored.

Methods

The TCGA database was used to obtain RNA expression datasets and clinical information about 190 TNBC patients, after which a prognostic TNBC-related FRG signature was established using a least absolute shrinkage and selection operator (LASSO) Cox regression approach. These results were validated with separate data from the Gene Expression Omnibus (GEO). The TNBC-specific prognostic gene was identified via this method. The STEAP3 was then validated through Western immunoblotting, immunohistochemical staining, and quantitative real‐time polymerase chain reaction (RT-qPCR) analyses of clinical tissue samples and TNBC cell lines. Chemotherapy interactions and predicted drug sensitivity studies were investigated to learn more about the potential clinical relevance of these observations.

Results

These data revealed that 87 FRGs were differentially expressed when comparing TNBC tumors and healthy tissue samples (87/259, 33.59%). Seven of these genes (CA9, CISD1, STEAP3, HMOX1, DUSP1, TAZ, HBA1) are significantly related to the overall survival of TNBC patients. Kaplan-Meier analyses and established FRG signatures and nomograms identified CISD1 and STEAP3 genes of prognostic relevance. Prognostic Risk Score values were positively correlated with the infiltration of CD4+ T cells (p = 0.001) and myeloid dendritic cells (p =0.004). Further evidence showed that STEAP3 was strongly and specifically associated with TNBC patient OS (P&lt;0.05). The results above were confirmed by additional examinations of STEAP3 expression changes in TNBC patient samples and cell lines. High STEAP3 levels were negatively correlated with half-maximal inhibitory concentration (IC50) values for GSK1904529A (IGF1R inhibitor), AS601245 (JNK inhibitor), XMD8−85 (Erk5 inhibitor), Gefitinib, Sorafenib, and 5-Fluorouracil (P &lt; 0.05) in patients with TNBC based on information derived from the TCGA-TNBC dataset.

Conclusion

In the present study, a novel FRG model was developed and used to forecast the prognosis of TNBC patients accurately. Furthermore, it was discovered that STEAP3 was highly overexpressed in people with TNBC and associated with overall survival rates, laying the groundwork for the eventually targeted therapy of individuals with this form of cancer.

Integrated analysis of ferroptosis-related gene signature for overall survival prediction in Asian patients with hepatocellular carcinoma

PURPOSE

Hepatocellular carcinoma (HCC) is one of the most prevalent types of cancers in Asia. Accumulating evidence suggests that ferroptosis is a non-apoptotic form of cell death, and has played an important role in cancer biology.

METHODS

Based on the manually curated ferroptosis-related gene set and TCGA-LIHC dataset of Asian patients, we used DESeq2, Kaplan-Meier analysis, and univariate Cox regression to identify differentially expressed ferroptosis-related genes with significantly prognostic capacity. A risk signature was constructed based on the selected genes for predicting the survival of HCC patients in Asia. The survival prediction accuracy was confirmed by the time-dependent receiver operating characteristic (ROC) curve analysis. Gene set variation analysis (GSVA) was used to explore the functional associations of the signature. Ferroptosis potential index (FPI) and xCell algorithm was applied to quantify ferroptosis and immune cell infiltration, respectively. Two independent datasets from the GEO and the ICGC database were used for external validation.

RESULTS

The ferroptosis-related signature could accurately predict the survival outcomes of HCC patients in Asian (p value < 0.0001). We showed that the signature was an independent factor and was beneficial in elevating risk stratification of current clinicopathologic features, such as the amount of alpha-fetoprotein (AFP) and residual tumor classification. Functional characterization showed that critical processes in tumorigenesis belonged to the high-risk groups, for example inflammatory response, which may be the main driver of HCC. The high-risk group had higher FPIs and infiltrations of macrophages and T-helper cells than the low-risk group. Furthermore, two independent cohorts confirmed the prognostic value of our signature.

CONCLUSION

Overall, our results demonstrated potential application of ferroptosis-related genes as independent biomarkers in Asian HCC patients. Targeting ferroptosis may be clinically useful beyond known clinicopathological factors and provide benefit in immunotherapy.

Ferroptosis-related genes are involved in asthma and regulate the immune microenvironment

Background: Asthma was a chronic inflammatory illness driven by complicated genetic regulation and environmental exposure. The complex pathophysiology of asthma has not been fully understood. Ferroptosis was involved in inflammation and infection. However, the effect of ferroptosis on asthma was still unclear. The study was designed to identify ferroptosis-related genes in asthma, providing potential therapeutic targets. Methods: We conducted a comprehensive analysis combined with WGCNA, PPI, GO, KEGG, and CIBERSORT methods to identify ferroptosis-related genes that were associated with asthma and regulated the immune microenvironment in GSE147878 from the GEO. The results of this study were validated in GSE143303 and GSE27066, and the hub genes related to ferroptosis were further verified by immunofluorescence and RT-qPCR in the OVA asthma model. Results: 60 asthmatics and 13 healthy controls were extracted for WGCNA. We found that genes in the black module (r = -0.47, p < 0.05) and magenta module (r = 0.51, p < 0.05) were associated with asthma. CAMKK2 and CISD1 were discovered to be ferroptosis-related hub genes in the black and magenta module, separately. We found that CAMKK2 and CISD1 were mainly involved in the CAMKK-AMPK signaling cascade, the adipocytokine signaling pathway, the metal cluster binding, iron-sulfur cluster binding, and 2 iron, 2 sulfur cluster binding in the enrichment analysis, which was strongly correlated with the development of ferroptosis. We found more infiltration of M2 macrophages and less Tregs infiltration in the asthma group compared to healthy controls. In addition, the expression levels of CISD1 and Tregs were negatively correlated. Through validation, we found that CAMKK2 and CISD1 expression were upregulated in the asthma group compared to the control group and would inhibit the occurrence of ferroptosis. Conclusion: CAMKK2 and CISD1 might inhibit ferroptosis and specifically regulate asthma. Moreover, CISD1 might be tied to the immunological microenvironment. Our results could be useful to provide potential immunotherapy targets and prognostic markers for asthma.

Identification and validation of a five-gene prognostic signature based on bioinformatics analyses in breast cancer

Background

This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data.

Methods

The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma". Secondly, the DEGs were used to construct a polygenic risk scoring model by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator Cox regression (Lasso-cox) analysis method. Thirdly, survival analysis was performed to investigate the risk score values in the TCGA cohort. And the enrichment analysis, immune cell infiltration levels analysis, and protein-protein internet (PPI) analysis were performed. Simultaneously, the GEO cohort was used to validate the model. Lastly, we constructed a nomogram to explore the influence of polygenic risk score and other clinical factors on the survival probability of patients with BRCA.

Results

A total of 1000 DEGs including 396 upregulated genes and 604 downregulated genes were identified from the TCGA-BRCA dataset. We obtained 5 prognosis-related genes, as the key biomarkers by Lasso-cox analysis (FBXL19, HAGHL, PHKG2, PKMYT1, and TXNDC17), all of which were significantly upregulated in breast tumors. The prognostic prediction of the 5 genes model was great in training and validation cohorts. Moreover, the high-risk group had a poorer prognosis. The Cox regression analysis showed that the comprehensive risk score for 5 genes was an independent prognosis factor.

Conclusion

The 5 genes risk model constructed in this study had an independent predictive ability to distinguish patients with a high risk of death from those with a low-risk score, and it can be used as a practical and reliable prognostic tool for BRCA.

ACSF2-mediated ferroptosis is involved in ulcerative colitis

AIMS

To investigate the role of ferroptosis-related genes in the induction into ulcerative colitis (UC) and provide new strategies for the prevention and treatment of UC.

MATERIALS AND METHODS

We screened the UC dataset from the GEO database and obtained ferroptosis-related genes from FerrDB and GeneCards. The R package "CancerSubtypes" was performed to identify the UC subtypes, followed by Short Time-series Expression Miner (STEM) analysis. The key genes were further screened by machine learning algorithms (LASSO and SVM-RFE). WB and IHC verified the changes in the expression content of ACSF2 in vivo and in vitro models. The changes in intracellular ROS and Fe^{2 +} levels were detected.

KEY FINDINGS

Through bioinformatics analysis, we selected the ferroptosis-related gene ACSF2 (acyl CoA synthetase family member 2), which is significantly associated with immune-related pathways "Toll-like receptor signaling pathway", "NF-kappa B signaling pathway" and "NOD-like receptor signaling pathway". The expression of ACSF2 was significantly down-regulated in UC animals, Salmonella typhimurium colitis models and cell models, while the ferroptosis inhibitor Fer-1 reversed the expression of ACSF2 in LPS-induced cell models, indicating that the ferroptosis-related gene ACSF2 plays an important role in mediating ferroptosis and inflammation, and is expected to become a new target for further research.

SIGNIFICANCE

Ferroptosis is closely associated with the development of UC, and the ferroptosis-related gene ACSF2 can be used as a potential biomarker for the diagnosis and treatment of UC.

Identification of a Novel Gene Signature with DDR and EMT Difunctionalities for Predicting Prognosis, Immune Activity, and Drug Response in Breast Cancer

Breast cancer, with an overall poor clinical prognosis, is one of the most heterogeneous cancers. DNA damage repair (DDR) and epithelial-mesenchymal transition (EMT) have been identified to be associated with cancer's progression. Our study aimed to explore whether genes with both functions play a more crucial role in the prognosis, immune, and therapy response of breast cancer patients. Based on the Cancer Genome Atlas (TCGA) cancer database, we used LASSO regression analysis to identify the six prognostic-related genes with both DDR and EMT functions, including TP63, YWHAZ, BRCA1, CCND2, YWHAG, and HIPK2. Based on the six genes, we defined the risk scores of the patients and reasonably analyzed the overall survival rate between the patients with the different risk scores. We found that overall survival in higher-risk-score patients was lower than in lower-risk-score patients. Subsequently, further GO and KEGG analyses for patients revealed that the levels of immune infiltration varied for patients with high and low risk scores, and the high-risk-score patients had lower immune infiltration's levels and were insensitive to treatment with chemotherapeutic agents. Furthermore, the Gene Expression Omnibus (GEO) database validated our findings. Our data suggest that TP63, YWHAZ, BRCA1, CCND2, YWHAG, and HIPK2 can be potential genetic markers of prognostic assessment, immune infiltration and chemotherapeutic drug sensitivity in breast cancer patients.

A novel ferroptosis‑related gene signature for overall survival prediction and immune infiltration in patients with breast cancer

Breast cancer is the most prevalent type of cancer among women worldwide. The heterogeneous nature of breast cancer poses a serious challenge for prognostic prediction and individualized therapies. Recently, ferroptosis, an iron‑dependent form of programmed cell death, has been reported to serve a significant role in the regulation of the biological behavior of tumors. Several studies have revealed the prognostic significance of the ferroptosis‑related gene (FRG) model; however, additional efforts are required to elucidate the details. Moreover, genes that modulate ferroptosis may be promising candidate bioindicators in cancer therapy. The present study systematically assessed the expression profiles of FRGs to reveal the relationship between FRGs and the prognostic features of patients with breast cancer based on data obtained from the Gene Expression Omnibus and Molecular Taxonomy of Breast Cancer International Consortium. Using a non‑negative matrix factorization clustering method, patients with breast cancer were classified into two sub‑groups (cluster 1 and cluster 2) based on the expression of FRGs. Furthermore, Cox regression, and least absolute shrinkage and selection operator methods were used to construct a risk score formula comprised of nine genes, which stratified patients with breast cancer into two risk groups. Patients belonging to the high‑risk group exhibited significantly shorter overall survival (OS) time compared with patients in the low‑risk group. The prognostic value of this signature was further verified in the training and validation cohorts. The results for univariate and multivariate Cox regression analyses indicated that risk score acted as an independent predictor for OS. Subsequently, a nomogram was constructed. Receiver operating characteristic analysis further confirmed that the resulting nomogram exhibited powerful discriminatory ability. Functional analysis revealed that the immune environment differed notably between the two groups and indicated an association between ferroptosis and breast cancer proliferation, migration and drug resistance. Taken together, the present study demonstrated that FRGs were significantly associated with breast cancer progression, and thus could be used as novel biomarkers for prognostic prediction and individualized treatment of patients with breast cancer.

Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model

Breast cancer (BRCA) is the most prevalent malignancy and the leading cause of death in women. Interleukin (IL) genes are critical in tumor initiation and control. Nevertheless, the prognosis value of the IL in BRCA remains unclear. We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard. Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature. GSE22219, GSE25065, and GSE21653 were derived as validation sets. The expression differences in the tumor microenvironment (TME), immunotherapy, and chemosensitivity of BRCA between the high- and low-risk groups were evaluated. Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA. IL score could distinguish BRCA patients with inferior outcomes, and AUC of it was 0.70, 0.76, and 0.72 for 1-,3- and 5- years, respectively, which was also verified in GSE22219, GSE25065, and GSE21653 cohorts. Meanwhile, compared to luminal A and luminal B, HER2-positive and TNBC had significantly higher IL score. Besides, the high-risk group had a significantly higher prevalence of TP53 and TTN but a lower prevalence of PIK3CA, as well as higher tumor mutation burden (TMB) and neoantigen level. High- and low-risk groups exhibited notable differences in immunomodulators and tumor infiltrates immune cells (TIICs), and the high-risk group had significantly lower Tumor Immune Dysfunction and Exclusion (TIDE) score. Additionally, the high-risk group has more responders to immune or anti-HER2 combination therapy, whereas the low-risk group has higher sensitivity to docetaxel and paclitaxel. Consequently, we constructed a reliable risk model based on the IL genes, which can provide more information on both the risk stratification and personalizing management strategies for BRCA.

Ferroptosis and its role in skeletal muscle diseases

Ferroptosis is characterized by the accumulation of iron and lipid peroxidation products, which regulates physiological and pathological processes in numerous organs and tissues. A growing body of research suggests that ferroptosis is a key causative factor in a variety of skeletal muscle diseases, including sarcopenia, rhabdomyolysis, rhabdomyosarcoma, and exhaustive exercise-induced fatigue. However, the relationship between ferroptosis and various skeletal muscle diseases has not been investigated systematically. This review’s objective is to provide a comprehensive summary of the mechanisms and signaling factors that regulate ferroptosis, including lipid peroxidation, iron/heme, amino acid metabolism, and autophagy. In addition, we tease out the role of ferroptosis in the progression of different skeletal muscle diseases and ferroptosis as a potential target for the treatment of multiple skeletal muscle diseases. This review can provide valuable reference for the research on the pathogenesis of skeletal muscle diseases, as well as for clinical prevention and treatment.

High co-expression of SLC7A11 and GPX4 as a predictor of platinum resistance and poor prognosis in patients with epithelial ovarian cancer

OBJECTIVE

The aim was to assess the expression levels of SLC7A11 and GPX4 in relation to platinum resistance and prognosis in patients with epithelial ovarian cancer (EOC).

DESIGN

A retrospective cohort study.

SETTING

Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.

POPULATION OR SAMPLE

We included 192 eligible patients from hospital between January 2002 and December 2018.

METHODS

We retrospectively analysed the medical records of patients with EOC. Surgical specimens of EOC were stained for SLC7A11 and GPX4. Survival analysis was performed using the Kaplan-Meier and Cox regression methods.

MAIN OUTCOME MEASURES

Clinical end points include platinum-free interval (PFI), progression-free survival (PFS) and overall survival (OS).

RESULTS

Patients with high co-expression levels of SLC7A11 and GPX4 had a 60-fold higher risk of platinum resistance compared with those with low co-expression (risk ratio, 60.46; 95% confidence interval [CI] 22.76-160.58; p < 0.001). Moreover, high co-expression level of SLC7A11 and GPX4 was an independent prognostic factor for poor OS (p < 0.001, hazard ratio [HR] 4.44, 95% CI, 2.77-7.14) and poor PFS (p < 0.001, HR = 5.73, 95% CI, 3.86-8.73). For in vitro experiments, SLC7A11 and GPX4 expression were both upregulated in platinum-resistant cells compared with their parental ovarian cancer cells, and siRNA-induced SLC7A11 and GPX4 inhibition decreased platinum resistance.

CONCLUSIONS

High expression levels of SLC7A11 and GPX4 are associated with platinum resistance in EOC patients. High co-expression of SLC7A11 and GPX4 may be a significant independent prognostic factor and a potential therapeutic target for platinum resistance in EOC patients.

Regulation mechanism of ferroptosis and its research progress in tumor immunotherapy

Ferroptosis is a novel regulatory cell death, which is characterized by iron dependency and mainly caused by accumulation of intracellular lipid peroxides and reactive oxygen species. Ferroptosis plays an important role in the occurrence and development of a variety of malignant tumors, especially in anti-tumor treatment. As an emerging treatment method, the immunotherapy has been widely applied in the clinical practice, and the role of ferroptosis in tumor immunotherapy has been gradually explored. This study aims to illustrate the features of ferroptosis, and its role in anti-tumor immunotherapy and potential clinical application.

Identification of a novel ferroptosis-related gene signature associated with prognosis, the immune landscape, and biomarkers for immunotherapy in ovarian cancer

Ferroptosis has been implicated in tumor progression and immunoregulation. Identification of ferroptosis-related prognostic gene is important for immunotherapy and prognosis in ovarian cancer (OV). We assessed the potential predictive power of a novel ferroptosis-related gene (FRG) signature for prognosis and immunotherapy in Asian and Caucasian OV populations. We collected gene expression profiles and clinicopathological data from public databases. The least absolute shrinkage and selection operator Cox regression algorithm was used to construct the FRG signature. Receiver operating characteristic (ROC) curve, Kaplan-Meier method, Cox regression model were used to evaluate the clinical benefits of FRG signature. Gene functional and gene set enrichment analyses were used for functional annotation and immune landscape analysis. A 15-FRG signature was constructed and used to stratify patients into two risk groups. Patients in the high-risk group had significantly worse survival. The risk score was a significant independent risk factor for OS. The area under the ROC curve indicated the good prediction performance of the FRG signature. Notably, the low-risk group showed a significant enrichment in immune-related pathways and a “hot” immune status. The risk score was found to be an efficient and robust predictor of response to immunotherapy. In conclusion, our study identified a novel 15-FRG prognostic signature that can be used for prognostic prediction and precision immunotherapy in Asian and Caucasian OV populations.

A novel 10-gene ferroptosis-related prognostic signature in acute myeloid leukemia

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies and exhibits a high rate of relapse and unfavorable outcomes. Ferroptosis, a relatively recently described type of cell death, has been reported to be involved in cancer development. However, the prognostic value of ferroptosis-related genes (FRGs) in AML remains unclear. In this study, we found 54 differentially expressed ferroptosis-related genes (DEFRGs) between AML and normal marrow tissues. 18 of 54 DEFRGs were correlated with overall survival (OS) (P<0.05). Using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we selected 10 DEFRGs that were associated with OS to build a prognostic signature. Data from AML patients from the International Cancer Genome Consortium (ICGC) cohort as well as the First Affiliated Hospital of Wenzhou Medical University (FAHWMU) cohort were used for validation. Notably, the prognostic survival analyses of this signature passed with a significant margin, and the riskscore was identified as an independent prognostic marker using Cox regression analyses. Then we used a machine learning method (SHAP) to judge the importance of each feature in this 10-gene signature. Riskscore was shown to have the highest correlation with this 10-gene signature compared with each gene in this signature. Further studies showed that AML was significantly associated with immune cell infiltration. In addition, drug-sensitive analysis showed that 8 drugs may be beneficial for treatment of AML. Finally, the expressions of 10 genes in this signature were verified by real-time quantitative polymerase chain reaction. In conclusion, our study establishes a novel 10-gene prognostic risk signature based on ferroptosis-related genes for AML patients and FRGs may be novel therapeutic targets for AML.