Disulfidptosis: disulfide stress-induced cell death

Prediction of clinical prognosis and drug sensitivity in hepatocellular carcinoma through the combination of multiple cell death pathways

Hepatocellular carcinoma (HCC) is the sixth most common malignant tumor, highlighting a significant need for reliable predictive models to assess clinical prognosis, disease progression, and drug sensitivity. Recent studies have highlighted the critical role of various programmed cell death pathways, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, NETotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, in tumor development. Therefore, by investigating these pathways, we aimed to develop a predictive model for HCC prognosis and drug sensitivity. We analyzed transcriptome, single-cell transcriptome, genomic, and clinical information using data from the TCGA-LIHC, GSE14520, GSE45436, and GSE166635 datasets. Machine learning algorithms were used to establish a cell death index (CDI) with seven gene signatures, which was validated across three independent datasets, showing that high CDI correlates with poorer prognosis. Unsupervised clustering revealed three molecular subtypes of HCC with distinct biological processes. Furthermore, a nomogram integrating CDI and clinical information demonstrated good predictive performance. CDI was associated with immune checkpoint genes and tumor microenvironment components using single-cell transcriptome analysis. Drug sensitivity analysis indicated that patients with high CDI may be resistant to oxaliplatin and cisplatin but sensitive to axitinib and sorafenib. In summary, our model offers a precise prediction of clinical outcomes and drug sensitivity for patients with HCC, providing valuable insights for personalized treatment strategies.

Targeting NQO1 induces ferroptosis and triggers anti-tumor immunity in immunotherapy-resistant KEAP1-deficient cancers

Immunotherapy has revolutionized cancer treatment, yet the efficacy of immunotherapeutic approaches remains limited. Resistance to ferroptosis is one of the reasons for the poor therapeutic outcomes in tumors with Kelch-like ECH-associated protein 1 (KEAP1) mutations. However, the specific mechanisms by which KEAP1-mutant tumors resist immunotherapy are not fully understood. In this study, we showed that the loss of function in KEAP1 results in resistance to ferroptosis. We identified NAD(P)H Quinone Dehydrogenase 1 (NQO1) as a transcriptional target of nuclear factor erythroid 2-related factor 2 (NRF2) and revealed that inducing NQO1-mediated ferroptosis in KEAP1-deficient tumors triggers an antitumor immune cascade. Additionally, it was found that NQO1 protein levels could serve as a candidate biomarker for predicting sensitivity to immunotherapy in clinical tumor patients. We validated these findings in several preclinical tumor models. Overall, KEAP1 mutations define a unique disease phenotype, and targeting its key downstream molecule NQO1 offers new hope for patients with resistance to immunotherapy.

Therapeutic Potential of lncRNAs in Regulating Disulfidptosis for Cancer Treatment

Non-coding RNAs (lncRNAs) play critical roles in various cellular processes, including a novel form of regulated cell death known as disulfidptosis, characterized by accumulating protein disulfide bonds and severe endoplasmic reticulum stress. This review highlights the therapeutic potential of lncRNAs in regulating disulfidptosis for cancer treatment, emphasizing their influence on key pathway components such as GPX4, SLC7A11, and PDIA family members. Recent studies have demonstrated that targeting specific lncRNAs can sensitize cancer cells to disulfidptosis, offering a promising approach to cancer therapy. The regulation of disulfidptosis by lncRNAs involves various signaling pathways, including oxidative stress, ER stress, and calcium signaling. This review also discusses the molecular mechanisms underlying lncRNA regulation of disulfidptosis, the challenges of developing lncRNA-based therapies, and the future potential of this rapidly advancing field in cancer research.

Investigating the role of disulfidptosis related genes in radiotherapy resistance of lung adenocarcinoma

Background

Radiotherapy resistance is an important reason for high mortality in lung cancer patients, but the mechanism is still unclear. Dysregulation of cell proliferation and death plays a crucial role in the onset and progression of lung adenocarcinoma (LUAD). In recent times, a novel form of cellular demise called disulfidptosis, has attracted increasing attention. However, it is unclear whether the radiation-related disulfidptosis genes have prognostic role in LUAD.

Methods

A complete suite of bioinformatics tools was used to analyze the expression and prognostic significance of radiation-related disulfidptosis genes. Afterward, we investigated the predictive significance of the risk signature in tumor microenvironments (TME), somatic mutations, and immunotherapies. In addition, we conducted a series of experiments to verify the expression of differentially expressed radiotherapy related disulfidptosis genes (DERRDGs) in vitro.

Results

A total of 88 DERRDGs were found. We constructed and validated a novel prognostic model based on PRELP, FGFBP1, CIITA and COL5A1. The enrichment analysis showed the DERRDG affected tumor prognosis by influencing tumor microenvironments (TME) and immunotherapy. And we constructed nomogram to promote clinical application. In addition, q-PCR confirmed the significant differences in the expression of prognostic genes between A549 irradiation-resistance cell and A549. Finally, western-blot, IHC staining, and small interference experiment suggested that PRELP may be a potential biomarker for radiotherapy resistance, whose low expression was associated with poor outcomes in LUAD patients.

Conclusion

This study reveals the signature and possible underlying mechanisms of DERRDGs in LUAD and discovered the key gene PRELP, which helps to identify new prognostic biomarkers and provides a basis for future research.

Thioredoxin reductase inhibition and glutathione depletion mediated by glaucocalyxin A promote intracellular disulfide stress in gastric cancer cells

Thioredoxin reductase 1 (TXNRD1) has been identified as one of the promising chemotherapeutic targets in cancer cells. Therefore, a novel TXNRD1 inhibitor could accelerate chemotherapy in clinical anticancer research. In this study, glaucocalyxin A (GlauA), a natural diterpene extracted from Rabdosia japonica var. glaucocalyx, was identified as a novel inhibitor of TXNRD1. We found that GlauA effectively inhibited recombinant TXNRD1 and reduced its activity in gastric cancer cells without affecting the enzyme's expression level. Mechanistically, the selenocysteine residue (U498) of TXNRD1 was irreversibly modified by GlauA through a Michael addition. Additionally, GlauA formed a covalent adduct with glutathione (GSH) and disrupted cellular redox balance by depleting cellular GSH. The inhibition of TXNRD1 and depletion of GSH by GlauA conferred its cytotoxic effects in spheroid culture and Transwell assays in AGS cells. The disulfide stress induced cytotoxicity of GlauA could be mitigated by adding reducing agents, such as DTT and β-ME. Furthermore, the FDA-approval drug auranofin, a TXNRD1 inhibitor, triggered oligomerization of the cytoskeletal protein Talin-1 in AGS cells, indicating that inhibiting TXNRD1 triggered disulfide stress. In conclusion, this study uncovered GlauA as an efficient inhibitor of TXNRD1 and demonstrated the potential of TXNRD1 inhibition as an effective anticancer strategy by disrupting redox homeostasis and inducing disulfide stress.

Disulfidptosis: a novel cell death modality induced by actin cytoskeleton collapse and a promising target for cancer therapeutics

Disulfidptosis is a novel discovered form of programmed cell death (PCD) that diverges from apoptosis, necroptosis, ferroptosis, and cuproptosis, stemming from disulfide stress-induced cytoskeletal collapse. In cancer cells exhibiting heightened expression of the solute carrier family 7 member 11 (SLC7A11), excessive cystine importation and reduction will deplete nicotinamide adenine dinucleotide phosphate (NADPH) under glucose deprivation, followed by an increase in intracellular disulfide stress and aberrant disulfide bond formation within actin networks, ultimately culminating in cytoskeletal collapse and disulfidptosis. Disulfidptosis involves crucial physiological processes in eukaryotic cells, such as cystine and glucose uptake, NADPH metabolism, and actin dynamics. The Rac1-WRC pathway-mediated actin polymerization is also implicated in this cell death due to its contribution to disulfide bond formation. However, the precise mechanisms underlying disulfidptosis and its role in tumors are not well understood. This is probably due to the multifaceted functionalities of SLC7A11 within cells and the complexities of the downstream pathways driving disulfidptosis. This review describes the critical roles of SLC7A11 in cells and summarizes recent research advancements in the potential pathways of disulfidptosis. Moreover, the less-studied aspects of this newly discovered cell death process are highlighted to stimulate further investigations in this field.

Integrative analysis of multiple cell death model for precise prognosis and drug response prediction in gastric cancer

BACKGROUND

Gastric cancer (GC) is a common upper gastrointestinal tumor. However, the evaluation of prognosis and treatment response in patients with gastric cancer remains a challenge. Programmed cell death (PCD) is one of the important terminal paths for the cells of metazoans, and is involved in a variety of biological events that include morphogenesis, maintenance of tissue homeostasis, and elimination of harmful cells. The objective of this project is to investigate the predictive significance of cell death pathways and create prognostic signatures associated to cell death, with the purpose of forecasting prognosis and providing guidance for the treatment of gastric cancer.

METHODS

Gene transcription profiles and corresponding clinical data of gastric cancer patients were collected from The Cancer Genome Atlas (TCGA-STAD, n = 448) and the Gene Expression Comprehensive Database (GSE84437, n = 483). Thirteen types of cell death-related genes, including apoptosis, necroptosis, pyroptosis, ferroptosis, autophagy, cuprotosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, were analysed. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Patients were categorized into high and low-risk groups based on the median risk score for survival difference analysis. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Additionally, the response to immunotherapy in the high-risk and low-risk groups was calculated using the oncoPredict algorithm. Futhermore, the model genes were validated in the GEO validation set.

RESULTS

A total of 324 differential programmed cell death (PCD)-related genes were identified, and 65 were selected through single-factor Cox analysis. Six PCD-related genes were ultimately identified by Lasso regression to construct a prognostic risk score model. The log-rank test revealed that patients in the high-risk group had inferior survival time compared with those in the low-risk group. The area under the ROC curve (AUC) for the training group at years 1, 3, and 5 were 0.684, 0.713, 0.743, respectively, while the AUC for the validation cohort at years 1, 3, and 5 were 0.695, 0.704, and 0.707, respectively. Unsupervised clustering identified potential subtypes included in the model, and a survival difference was also observed between the two subgroups. Multifactor Cox results, combined with clinical information, demonstrated that the prognostic risk score can serve as an independent prognostic factor, irrespective of other clinical features.

CONCLUSION

By comprehensively analyzing multiple cell death patterns, we have established a novel model that accurately forecasts the clinical prognosis and drug sensitivity of gastric cancer. It was found that all 12 representative drugs may not be suitable for patients in high-risk groups.

Intermetallics triggering pyroptosis and disulfidptosis in cancer cells promote anti-tumor immunity

Pyroptosis, an immunogenic programmed cell death, could efficiently activate tumor immunogenicity and reprogram immunosuppressive microenvironment for boosting cancer immunotherapy. However, the overexpression of SLC7A11 promotes glutathione biosynthesis for maintaining redox balance and countering pyroptosis. Herein, we develop intermetallics modified with glucose oxidase (GOx) and soybean phospholipid (SP) as pyroptosis promoters (Pd2Sn@GOx-SP), that not only induce pyroptosis by cascade biocatalysis for remodeling tumor microenvironment and facilitating tumor cell immunogenicity, but also trigger disulfidptosis mediated by cystine accumulation to further promote tumor pyroptosis in female mice. Experiments and density functional theory calculations show that Pd2Sn nanorods with an intermediate size exhibit stronger photothermal and enzyme catalytic activity compared with the other three morphologies investigated. The peroxidase-mimic and oxidase-mimic activities of Pd2Sn cause potent reactive oxygen species (ROS) storms for triggering pyroptosis, which could be self-reinforced by photothermal effect, hydrogen peroxide supply accompanied by glycometabolism, and oxygen production from catalase-mimic activity of Pd2Sn. Moreover, the increase of NADP+/NADPH ratio induced by glucose starvation could pose excessive cystine accumulation and inhibit glutathione synthesis, which could cause disulfidptosis and further augment ROS-mediated pyroptosis, respectively. This two-pronged treatment strategy could represent an alternative therapeutic approach to expand anti-tumor immunotherapy.

A disulfidptosis-related lncRNA signature for analyzing tumor microenvironment and clinical prognosis in hepatocellular carcinoma

Introduction

Disulfidptosis is a recently identified form of non-apoptotic programmed cell death which distinguishes itself from classical cell death pathways. However, the prognostic implications of disulfidptosis-related long non-coding RNAs (DRLs) and their underlying mechanisms in hepatocellular carcinoma (HCC) remain largely unexplored.

Methods

In this study, we leveraged RNA-sequencing data and clinical information of HCC patients from the TCGA database. Through expression correlation and prognostic correlation analyses, we identified a set of top-performing long non-coding RNAs. Subsequently, a 5-DRLs predictive signature was established by conducting a Lasso regression analysis.

Results

This signature effectively stratified patients into high- and low-risk groups, revealing notable differences in survival outcomes. Further validation through univariate and multivariate Cox regression analyses confirmed that the risk score derived from our signature independently predicted the prognosis of HCC patients. Moreover, we observed significant disparities in immune cell infiltration and tumor mutation burden (TMB) between the two risk groups, shedding light on the potential connection between immune-related mechanisms and disulfidptosis. Notably, the signature also exhibited predictive value in the context of chemotherapeutic drug sensitivity and immunotherapy efficacy for HCC patients. Finally, we performed experimental validation at both cellular and patient levels and successfully induced a disulfidptosis phenotype in HCC cells.

Discussion

In general, this multifaceted approach provides a comprehensive overview of DRLs profiles in HCC, culminating in the establishment of a novel risk signature that holds promise for predicting prognosis and therapy outcomes of HCC patients.

Development of a disulfidptosis-related prognostic model for endometrial cancer with potential therapeutic target

Prognosis biomarkers for endometrial cancer (EC) are in need. Recent evidence demonstrated the critical role of disulfidptosis, a novel cell death modality, in cancer. However, limited studies have developed a disulfidptosis-related gene model for EC. Disulfidptosis prognosis score of EC (disulfidptosis-PSEC) were constructed using disulfidptosis-related differently expression genes with the RNA data of 544 EC patients from The Cancer Genome Atlas (TCGA) dataset. Model was evaluated using time-dependent receiver operating characteristic curve analysis for overall survival (OS) and disease-free survival (DFS), along with the hazard ratio (HR) between risk groups. Then, the cellular and molecular profile for different risk groups were performed, along with drug target inference. Disulfidptosis-PSEC demonstrated outstanding prognostic value for OS and DFS, with 5-year area under curve of 0.71 (95% CI, 0.58-0.75) and 0.69 (95% CI, 0.62-0.76), respectively. Low risk group demonstrated better survival with an HR of 0.38 (95% CI, 0.24-0.59) and 0.46 (95% CI, 0.32-0.66) for OS and DFS, respectively. The model was independent of TCGA subtype. Low risk group were featured with more immune cell infiltration and less gene mutation. Serval drug targets, and the therapeutic value of serotonin receptor among copy number (CN)-low subpopulation, were identified. Disulfidptosis-PSEC was a potential prognosis biomarker for EC with targetable biological process.

Mechanisms and therapeutic potential of disulphidptosis in cancer

SLC7A11 plays a pivotal role in tumour development by facilitating cystine import to enhance glutathione synthesis and counteract oxidative stress. Disulphidptosis, an emerging form of cell death observed in cells with high expression of SLC7A11 under glucose deprivation, is regulated through reduction-oxidation reactions and disulphide bond formation. This process leads to contraction and collapse of the F-actin cytoskeleton from the plasma membrane, ultimately resulting in cellular demise. Compared to other forms of cell death, disulphidptosis exhibits distinctive characteristics and regulatory mechanisms. This mechanism provides novel insights and innovative strategies for cancer treatment while also inspiring potential therapeutic approaches for other diseases. Our review focuses on elucidating the molecular mechanism underlying disulphidptosis and its connection with the actin cytoskeleton, identifying alternative metabolic forms of cell death, as well as offering insights into disulphidptosis-based cancer therapy. A comprehensive understanding of disulphidptosis will contribute to our knowledge about fundamental cellular homeostasis and facilitate the development of groundbreaking therapies for disease treatment.

Disulfidptosis: A new type of cell death

Disulfidptosis is a novel form of cell death that is distinguishable from established programmed cell death pathways such as apoptosis, pyroptosis, autophagy, ferroptosis, and oxeiptosis. This process is characterized by the rapid depletion of nicotinamide adenine dinucleotide phosphate (NADPH) in cells and high expression of solute carrier family 7 member 11 (SLC7A11) during glucose starvation, resulting in abnormal cystine accumulation, which subsequently induces andabnormal disulfide bond formation in actin cytoskeleton proteins, culminating in actin network collapse and disulfidptosis. This review aimed to summarize the underlying mechanisms, influencing factors, comparisons with traditional cell death pathways, associations with related diseases, application prospects, and future research directions related to disulfidptosis.

Significance of Programmed Cell Death Pathways in Neurodegenerative Diseases

Programmed cell death (PCD) is a form of cell death distinct from accidental cell death (ACD) and is also referred to as regulated cell death (RCD). Typically, PCD signaling events are precisely regulated by various biomolecules in both spatial and temporal contexts to promote neuronal development, establish neural architecture, and shape the central nervous system (CNS), although the role of PCD extends beyond the CNS. Abnormalities in PCD signaling cascades contribute to the irreversible loss of neuronal cells and function, leading to the onset and progression of neurodegenerative diseases. In this review, we summarize the molecular processes and features of different modalities of PCD, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, and other novel forms of PCD, and their effects on the pathogenesis of neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA), multiple sclerosis (MS), traumatic brain injury (TBI), and stroke. Additionally, we examine the key factors involved in these PCD signaling pathways and discuss the potential for their development as therapeutic targets and strategies. Therefore, therapeutic strategies targeting the inhibition or facilitation of PCD signaling pathways offer a promising approach for clinical applications in treating neurodegenerative diseases.

Digitonin-Loaded Nanoscale Metal-Organic Framework for Mitochondria-Targeted Radiotherapy-Radiodynamic Therapy and Disulfidptosis

The efficacy of radiotherapy (RT) is limited by inefficient X-ray absorption and reactive oxygen species generation, upregulation of immunosuppressive factors, and a reducing tumor microenvironment (TME). Here, the design of a mitochondria-targeted and digitonin (Dig)-loaded nanoscale metal-organic framework, Th-Ir-DBB/Dig, is reported to overcome these limitations and elicit strong antitumor effects upon low-dose X-ray irradiation. Built from Th6O4(OH)4 secondary building units (SBUs) and photosensitizing Ir(DBB)(ppy)2 2+ (Ir-DBB, DBB = 4,4'-di(4-benzoato)-2,2'-bipyridine; ppy = 2-phenylpyridine) ligands, Th-Ir-DBB exhibits strong RT-radiodynamic therapy (RDT) effects via potent radiosensitization with high-Z SBUs for hydroxyl radical generation and efficient excitation of Ir-DBB ligands for singlet oxygen production. Th-Ir-DBB/Dig releases digitonin in acidic TMEs to trigger disulfidptosis of cancer cells and sensitize cancer cells to RT-RDT through glucose and glutathione depletion. The released digitonin simultaneously downregulates multiple immune checkpoints in cancer cells and T cells through cholesterol depletion. As a result, Th-Ir-DBB/dig plus X-ray irradiation induces strong antitumor immunity to effectively inhibit tumor growth in mouse models of colon and breast cancer.

Disulfide stress and its role in cardiovascular diseases

Cardiovascular disease (CVD) is one of the leading causes of mortality in humans, and oxidative stress plays a pivotal role in disease progression. This phenomenon typically arises from weakening of the cellular antioxidant system or excessive accumulation of peroxides. This review focuses on a specialized form of oxidative stress-disulfide stress-which is triggered by an imbalance in the glutaredoxin and thioredoxin antioxidant systems within the cell, leading to the accumulation of disulfide bonds. The genesis of disulfide stress is usually induced by extrinsic pathological factors that disrupt the thiol-dependent antioxidant system, manifesting as sustained glutathionylation of proteins, formation of abnormal intermolecular disulfide bonds between cysteine-rich proteins, or irreversible oxidation of thiol groups to sulfenic and sulfonic acids. Disulfide stress not only precipitates the collapse of the antioxidant system and the accumulation of reactive oxygen species, exacerbating oxidative stress, but may also initiate cellular inflammation, autophagy, and apoptosis through a cascade of signaling pathways. Furthermore, this review explores the detrimental effects of disulfide stress on the progression of various CVDs including atherosclerosis, hypertension, myocardial ischemia-reperfusion injury, diabetic cardiomyopathy, cardiac hypertrophy, and heart failure. This review also proposes several potential therapeutic avenues to improve the future treatment of CVDs.

Metabolic cell death in cancer: ferroptosis, cuproptosis, disulfidptosis, and beyond

Cell death resistance represents a hallmark of cancer. Recent studies have identified metabolic cell death as unique forms of regulated cell death resulting from an imbalance in the cellular metabolism. This review discusses the mechanisms of metabolic cell death-ferroptosis, cuproptosis, disulfidptosis, lysozincrosis, and alkaliptosis-and explores their potential in cancer therapy. Our review underscores the complexity of the metabolic cell death pathways and offers insights into innovative therapeutic avenues for cancer treatment.

Interaction between the TBC1D24 TLDc domain and the KIBRA C2 domain is disrupted by two epilepsy-associated TBC1D24 missense variants

Mutations of human TBC1D24 are associated with deafness, epilepsy, or DOORS syndrome (deafness, onychodystrophy, osteodystrophy, cognitive disability, and seizures). The causal relationships between TBC1D24 variants and the different clinical phenotypes are not understood. Our hypothesis is that phenotypic heterogeneity of missense mutations of TBC1D24 results, in part, from perturbed binding of different protein partners. To discover novel protein partners of TBC1D24, we conducted yeast two-hybrid (Y2H) screen using mouse full-length TBC1D24 as bait. Kidney and brain protein (KIBRA), a scaffold protein encoded by Wwc1, was identified as a partner of TBC1D24. KIBRA functions in the Hippo signaling pathway and is important for human cognition and memory. The TBC1D24 TLDc domain binds to KIBRA full-length and to its C2 domain, confirmed by Y2H assays. No interaction was detected with Y2H assays between the KIBRA C2 domain and TLDc domains of NCOA7, MEAK7, and OXR1. Moreover, the C2 domains of other WWC family proteins do not interact with the TLDc domain of TBC1D24, demonstrating specificity. The mRNAs encoding TBC1D24 and KIBRA proteins in mouse are coexpressed at least in a subset of hippocampal cells indicating availability to interact in vivo. As two epilepsy-associated recessive variants (Gly511Arg and Ala515Val) in the TLDc domain of human TBC1D24 disrupt the interaction with the human KIBRA C2 domain, this study reveals a pathogenic mechanism of TBC1D24-associated epilepsy, linking the TBC1D24 and KIBRA pathways. The interaction of TBC1D24-KIBRA is physiologically meaningful and necessary to reduce the risk of epilepsy.

Construction of a prognostic model for disulfidptosis-related long noncoding RNAs in R0 resected hepatocellular carcinoma and analysis of their impact on malignant behavior

BACKGROUND

Disulfidptosis is an emerging form of cellular death resulting from the binding of intracellular disulfide bonds to actin cytoskeleton proteins. This study aimed to investigate the expression and prognostic significance of hub disulfidptosis-related lncRNAs (DRLRs) in R0 resected hepatocellular carcinoma (HCC) as well as their impact on the malignant behaviour of HCC cells.

METHODS

A robust signature for R0 resected HCC was constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and was validated in an independent internal validation cohort to predict the prognosis of R0 HCC patients. Comprehensive bioinformatics analysis was performed on the hub DRLRs (KDM4A-AS1, MKLN1-AS, and TMCC1-AS1), followed by experimental validation using quantitative real-time polymerase chain reaction (qRT‒PCR) and cellular functional assays.

RESULTS

The signature served as an independent prognostic factor applicable to R0 HCC patients across different age groups, tumour stages, and pathological characteristics. Gene Ontology (GO) and gene set enrichment analysis (GSEA) revealed hub pathways associated with this signature. The high-risk group presented an increased abundance of M0 macrophages and activated memory CD4 T cells as well as elevated macrophage and major histocompatibility complex (MHC) class I expression. High-risk R0 HCC patients also presented increased tumour immune dysfunction and exclusion scores (TIDEs), mutation frequencies, and tumour mutational burdens (TMBs). Drug sensitivity analysis revealed that high-risk patients were more responsive to drugs, including GDC0810 and osimertinib. High expression levels of the three hub DRLRs were detected in R0 HCC tissues and HCC cell lines. Functional assays revealed that the three hub DRLRs enhanced HCC cell proliferation, migration, and invasion.

CONCLUSIONS

A signature was constructed on the basis of three DRLRs, providing novel insights for personalized precision therapy in R0 HCC patients.

Identification and verification of disulfidptosis-related genes in sepsis-induced acute lung injury

Background

Sepsis-induced acute lung injury (ALI) is a common and serious complication of sepsis that eventually progresses to life-threatening hypoxemia. Disulfidptosis is a newly discovered type of cell death associated with the pathogenesis of different diseases. This study investigated the potential association between sepsis-induced acute lung injury and disulfidptosis by bioinformatics analysis.

Methods

In order to identify differentially expressed genes (DEGs) linked to sepsis, we screened appropriate data sets from the GEO database and carried out differential analysis. The key genes shared by DEGs and 39 disulfidptosis-related genes were identified: ACSL4 and MYL6 mRNA levels of key genes were detected in different datasets. We then used a series of bioinformatics analysis techniques, such as immune cell infiltration analysis, protein-protein interaction (PPI) network, genetic regulatory network, and receiver operating characteristic (ROC), to investigate the possible relationship between key genes and sepsis. Then, experimental verification was obtained for changes in key genes in sepsis-induced acute lung injury. Finally, to investigate the relationship between genetic variants of MYL6 or ACSL4 and sepsis, Mendelian randomization (MR) analysis was applied.

Results

Two key genes were found in this investigation: myosin light chain 6 (MYL6) and Acyl-CoA synthetase long-chain family member 4 (ACSL4). We verified increased mRNA levels of key genes in training datasets. Immune cell infiltration analysis showed that key genes were associated with multiple immune cell levels. Building the PPI network between MYL6 and ACSL4 allowed us to determine that their related genes had distinct biological functions. The co-expression genes of key genes were involved in different genetic regulatory networks. In addition, both the training and validation datasets confirmed the diagnostic capabilities of key genes by using ROC curves. Additionally, both in vivo and in vitro experiments confirmed that the mRNA levels of ACSL4 and MYL6 in sepsis-induced acute lung injury were consistent with the results of bioinformatics analysis. Finally, MR analysis revealed a causal relationship between MYL6 and sepsis.

Conclusion

We have discovered and confirmed that the key genes ACSL4 and MYL6, which are linked to disulfidptosis in sepsis-induced acute lung injury, may be useful in the diagnosis and management of septic acute lung injury.

Prognostic and immunological implications of heterogeneous cell death patterns in prostate cancer

BACKGROUND

Prostate cancer is one of the most common cancers in men with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. Programmed cell death (PCD) mechanisms are known to play critical roles in tumor progression and can potentially serve as prognostic and therapeutic biomarkers in PCa. This study aimed to develop a prognostic signature for BCR in PCa using PCD-related genes.

MATERIALS AND METHODS

We conducted an analysis of 19 different modes of PCD to develop a comprehensive model. Bulk transcriptomic, single-cell transcriptomic, genomic, and clinical data were collected from multiple cohorts, including TCGA-PRAD, GSE58812, METABRIC, GSE21653, and GSE193337. We analyzed the expression and mutations of the 19 PCD modes and constructed, evaluated, and validated the model.

RESULTS

Ten PCD modes were found to be associated with BCR in PCa, with specific PCD patterns exhibited by various cell components within the tumor microenvironment. Through Lasso Cox regression analysis, we established a Programmed Cell Death Index (PCDI) utilizing an 11-gene signature. High PCDI values were validated in five independent datasets and were found to be associated with an increased risk of BCR in PCa patients. Notably, older age and advanced T and N staging were associated with higher PCDI values. By combining PCDI with T staging, we constructed a nomogram with enhanced predictive performance. Additionally, high PCDI values were significantly correlated with decreased drug sensitivity, including drugs such as Docetaxel and Methotrexate. Patients with lower PCDI values demonstrated higher immunophenoscores (IPS), suggesting a potentially higher response rate to immune therapy. Furthermore, PCDI was associated with immune checkpoint genes and key components of the tumor microenvironment, including macrophages, T cells, and NK cells. Finally, clinical specimens validated the differential expression of PCDI-related PCDRGs at both the gene and protein levels.

CONCLUSION

In conclusion, we developed a novel PCD-based prognostic feature that successfully predicted BCR in PCa patients and provided insights into drug sensitivity and potential response to immune therapy. These findings have significant clinical implications for the treatment of PCa.

Integrated analysis of disulfidoptosis-related genes identifies NRP1 as a novel biomarker promoting proliferation of gastric cancer via glutamine mediated energy metabolism

The incidence and mortality of gastric cancer rank fifth and fourth worldwide among all malignancies, respectively. Additionally, disulfidoptosis, a recently identified form of cellular demise, is closely linked to the initiation and advancement of malignancies. This study aims to create a novel signature of disulfidptosis-related genes (DRGs) and to further explore its association with the tumor immune microenvironment. Based on our comprehensive study, a prognostic signature consisting of 31 DRGs in stomach adenocarcinoma (STAD) was identified and characterized. Through the integrative analyses involving gene expression profiling, machine learning algorithms, and Cox regression models, the prognostic significance of these DRGs was demonstrated. Our findings highlight their strong predictive power in assessing overall survival across diverse patient datasets, and their better performance than traditional clinicopathological factors. Moreover, the DRGs signature showed association with the characteristics of the tumor microenvironment, which has implications for the immune modulation and therapeutic strategies in STAD. Specifically, NRP1 emerged as a key DRG with elevated expression in STAD, showing correlation with the advanced stages of diseases and poorer outcomes. Functional studies further revealed the role of NRP1 in promoting STAD cell proliferation through the modulation of glutamine metabolism. Overall, our study underscores the clinical relevance of DRGs as biomarker and potential therapeutic targets in STAD management, providing insights into disease biology and personalized treatments.

Emerging mechanisms and promising approaches in pancreatic cancer metabolism

Pancreatic cancer is an aggressive cancer with a poor prognosis. Metabolic abnormalities are one of the hallmarks of pancreatic cancer, and pancreatic cancer cells can adapt to biosynthesis, energy intake, and redox needs through metabolic reprogramming to tolerate nutrient deficiency and hypoxic microenvironments. Pancreatic cancer cells can use glucose, amino acids, and lipids as energy to maintain malignant growth. Moreover, they also metabolically interact with cells in the tumour microenvironment to change cell fate, promote tumour progression, and even affect immune responses. Importantly, metabolic changes at the body level deserve more attention. Basic research and clinical trials based on targeted metabolic therapy or in combination with other treatments are in full swing. A more comprehensive and in-depth understanding of the metabolic regulation of pancreatic cancer cells will not only enrich the understanding of the mechanisms of disease progression but also provide inspiration for new diagnostic and therapeutic approaches.

A disulfidptosis-related glucose metabolism and immune response prognostic model revealing the immune microenvironment in lung adenocarcinoma

Background

Lung adenocarcinoma accounts for the majority of lung cancer cases and impact survival rate of patients severely. Immunotherapy is an effective treatment for lung adenocarcinoma but is restricted by many factors including immune checkpoint expression and the inhibitory immune microenvironment. This study aimed to explore the immune microenvironment in lung adenocarcinoma via disulfidptosis.

Methods

Public datasets of lung adenocarcinoma from the TCGA and GEO was adopted as the training and validation cohort. Based on the differences in the expression of disulfidptosis -related genes, a glucose metabolism and immune response prognostic model was constructed. The prognostic value and clinical relationship of the model were further explored. Immune-related analyses were performed according to CIBERSORT, ssGSEA, TIDE, IPS.

Results

We verified that the model could accurately predict the survival expectancy of lung adenocarcinoma patients. Patients with lung adenocarcinoma and a low-risk score had better survival outcomes according to the model. Moreover, the high-risk group tended to have an immunosuppressive effect, as reflected by the immune cell components, phenotypes and functions. We also found that the clinically relevant immune checkpoint CTLA-4 was significantly higher in low-risk group (P<0.05), indicating that the high-risk group may suffer worse tumor immunotherapy efficacy. Finally, we found that this model has accurate predictive value for the efficacy of immune checkpoint blockade in non-small cell lung cancer (P<0.05).

Conclusion

The prognostic model demonstrated the feasibility of predicting survival and immunotherapy efficacy via disulfidptosis-related genes and will facilitate the development of personalized anticancer therapy.

Cuproptosis and Cu: a new paradigm in cellular death and their role in non-cancerous diseases

Cuproptosis, a newly characterized form of regulated cell death driven by copper accumulation, has emerged as a significant mechanism underlying various non-cancerous diseases. This review delves into the complex interplay between copper metabolism and the pathogenesis of conditions such as Wilson's disease (WD), neurodegenerative disorders, and cardiovascular pathologies. We examine the molecular mechanisms by which copper dysregulation induces cuproptosis, highlighting the pivotal roles of key copper transporters and enzymes. Additionally, we evaluate the therapeutic potential of copper chelation strategies, which have shown promise in experimental models by mitigating copper-induced cellular damage and restoring physiological homeostasis. Through a comprehensive synthesis of recent advancements and current knowledge, this review underscores the necessity of further research to translate these findings into clinical applications. The ultimate goal is to harness the therapeutic potential of targeting cuproptosis, thereby improving disease management and patient outcomes in non-cancerous conditions associated with copper dysregulation.

A disulfidptosis-related lncRNAs cluster to forecast the prognosis and immune landscapes of ovarian cancer

Objective

Disulfidptosis is a newly recognized form of regulated cell death that has been linked to cancer progression and prognosis. Despite this association, the prognostic significance, immunological characteristics and treatment response of disulfidptosis-related lncRNAs (DRLs) in ovarian cancer have not yet been elucidated.

Methods

The lncRNA data and clinical information for ovarian cancer and normal samples were obtained from the UCSC XENA. Differential expression analysis and Pearson analysis were utilized to identify core DRLs, followed by LASSO algorithm. Random Survival Forest was used to construct a prognostic model. The relationships between risk scores, RNA methylation, immune cell infiltration, mutation, responses to immunotherapy and drug sensitivity analysis were further examined. Additionally, qRT-PCR experiments were conducted to validate the expression of the core DRLs in human ovarian cancer cells and normal ovarian cells and the scRNA-seq data of the core DRLs were obtained from the GEO dataset, available in the TISCH database.

Results

A total of 8 core DRLs were obtained to construct a prognostic model for ovarian cancer, categorizing all patients into low-risk and high-risk groups using an optimal cutoff value. The AUC values for 1-year, 3-year and 5-year OS in the TCGA cohort were 0.785, 0.810 and 0.863 respectively, proving a strong predictive capability of the model. The model revealed the high-risk group patients exhibited lower overall survival rates, higher TIDE scores and lower TMB levels compared to the low-risk group. Variations in immune cell infiltration and responses to therapeutic drugs were observed between the high-risk and low-risk groups. Besides, our study verified the correlations between the DRLs and RNA methylation. Additionally, qRT-PCR experiments and single-cell RNA sequencing data analysis were conducted to confirm the significance of the core DRLs at both cellular and scRNA-seq levels.

Conclusion

We constructed a reliable and novel prognostic model with a DRLs cluster for ovarian cancer, providing a foundation for further researches in the management of this disease.

Unveiling diabetic nephropathy: a novel diagnostic model through single-cell sequencing and co-expression analysis

BACKGROUND

Diabetic nephropathy (DN) is a severe complication of diabetes that affects the kidneys. Disulfidptosis, a newly defined type of programmed cell death, has emerged as a potential area of interest, yet its significance in DN remains unexplored.

METHODS

This study utilized single-cell sequencing data GSE131882 from GEO database combined with bulk transcriptome sequencing data GSE30122, GSE30528 and GSE30529 to investigate disulfidptosis in DN. Single-cell sequencing analysis was performed on samples from DN patients and healthy controls, focusing on cell heterogeneity and communication. Weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA) were employed to identify disulfidptosis-related gene sets and pathways. A diagnostic model was constructed using machine learning techniques based on identified genes, and immunocorrelation analysis was conducted to explore the relationship between key genes and immune cells. PCR validation was performed on blood samples from DN patients and healthy controls.

RESULTS

The study revealed significant disulfidptosis heterogeneity and cell communication differences in DN. Specific targets related to disulfidptosis were identified, providing insights into the pathogenesis of DN. The diagnostic model demonstrated high accuracy in distinguishing DN from healthy samples across multiple datasets. Immunocorrelation analysis highlighted the complex interactions between immune cells and key disulfidptosis-related genes. PCR validation supported the differential expression of model genes VEGFA, MAGI2, THSD7A and ANKRD28 in DN.

CONCLUSION

This research advances our understanding of DN by highlighting the role of disulfidptosis and identifying potential biomarkers for early detection and personalized treatment.

Non-Apoptotic Programmed Cell Death as Targets for Diabetic Retinal Neurodegeneration

Diabetic retinopathy (DR) remains the leading cause of blindness among the global working-age population. Emerging evidence underscores the significance of diabetic retinal neurodegeneration (DRN) as a pivotal biomarker in the progression of vasculopathy. Inflammation, oxidative stress, neural cell death, and the reduction in neurotrophic factors are the key determinants in the pathophysiology of DRN. Non-apoptotic programmed cell death (PCD) plays a crucial role in regulating stress response, inflammation, and disease management. Therapeutic modalities targeting PCD have shown promising potential for mitigating DRN. In this review, we highlight recent advances in identifying the role of various PCD types in DRN, with specific emphasis on necroptosis, pyroptosis, ferroptosis, parthanatos, and the more recently characterized PANoptosis. In addition, the therapeutic agents aimed at the regulation of PCD for addressing DRN are discussed.

Development and validation of a novel disulfidptosis-related lncRNAs signature in patients with HPV-negative oral squamous cell carcinoma

Disulfidptosis is a recently identified mode of regulated cell death. Regulating disulfidptosis in carcinoma is a promising therapeutic approach. Long non-coding RNAs (lncRNAs) have been reported to be related to the occurrence and development of many cancers. Disulfidptosis-related lncRNAs (DRLs) in HPV-negative oral squamous cell carcinoma (OSCC) have not been studied. Based on The Cancer Genome Atlas (TCGA) database, least absolute shrinkage selection operator (LASSO) analysis and Cox regression analysis were used to identify overall survival related DRLs and construct the signature. Kaplan-Meier, time-dependent receiver operating characteristics (ROC) and principal component analyses (PCA) were explored to demonstrate the prediction potential of the signature. Subgroup analysis stratified by different clinicopathological characteristics were conducted. Nomogram was established by DRLs signature and independent clinicopathological characteristics. The calibration plots were performed to reveal the accuracy of nomogram. Immune cell subset infiltration, immunotherapy response, drug sensitivity analysis, and tumor mutation burden (TMB) were conducted. Underlying functions and pathways were explored by Gene Set Enrichment Analysis (GSEA) analysis. Previous lncRNA signatures of OSCC were retrieved from PubMed for further validation. Gene expression omnibus (GEO) datasets (GSE41613 and GSE85446) were merged as an external validation for DRLs signature. Consensus clustering analysis of DRLs signature and experimental validation of DRLs were also explored. This research sheds light on the robust performance of DRLs signature in survival prediction, immune cell infiltration, immune escape, and immunotherapy of HPV-negative OSCC.

Developing a prognostic model using machine learning for disulfidptosis related lncRNA in lung adenocarcinoma

Disulfidptosis represents a novel cell death mechanism triggered by disulfide stress, with potential implications for advancements in cancer treatments. Although emerging evidence highlights the critical regulatory roles of long non-coding RNAs (lncRNAs) in the pathobiology of lung adenocarcinoma (LUAD), research into lncRNAs specifically associated with disulfidptosis in LUAD, termed disulfidptosis-related lncRNAs (DRLs), remains insufficiently explored. Using The Cancer Genome Atlas (TCGA)-LUAD dataset, we implemented ten machine learning techniques, resulting in 101 distinct model configurations. To assess the predictive accuracy of our model, we employed both the concordance index (C-index) and receiver operating characteristic (ROC) curve analyses. For a deeper understanding of the underlying biological pathways, we referred to the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) for functional enrichment analysis. Moreover, we explored differences in the tumor microenvironment between high-risk and low-risk patient cohorts. Additionally, we thoroughly assessed the prognostic value of the DRLs signatures in predicting treatment outcomes. The Kaplan-Meier (KM) survival analysis demonstrated a significant difference in overall survival (OS) between the high-risk and low-risk cohorts (p < 0.001). The prognostic model showed robust performance, with an area under the ROC curve exceeding 0.75 at one year and maintaining a value above 0.72 in the two and three-year follow-ups. Further research identified variations in tumor mutational burden (TMB) and differential responses to immunotherapies and chemotherapies. Our validation, using three GEO datasets (GSE31210, GSE30219, and GSE50081), revealed that the C-index exceeded 0.67 for GSE31210 and GSE30219. Significant differences in disease-free survival (DFS) and OS were observed across all validation cohorts among different risk groups. The prognostic model offers potential as a molecular biomarker for LUAD prognosis.

A disulfidptosis-related classification and risk signature identifies immunotherapy biomarkers and predicts prognosis in gastric cancer: An observational study

Gastric cancer (GC) is one of the most prevalent types of cancer globally, often detected at advanced stages. However, its prognosis remains poor, necessitating the exploration of new biomarkers. Disulfidptosis, a recently identified form of programmed cell death, has not yet been investigated in relation to GC and its associated mechanisms. We analyzed and identified potential associations between disulfidptosis genes and GC clinical risk using TCGA (The Cancer Genome Atlas)-STAD (stomach adenocarcinoma) as the training set and GSE84433 as the validation set. In addition, we explored the prognostic value and potential biological mechanisms of disulfide genes in GC by consensus clustering, enrichment analysis, mutation histology analysis and immune infiltration analysis. Finally, we constructed a disulfidptosis-related risk signature (DRRS) to assess the association between risk class, survival prognosis, and immune infiltration. By utilizing data from 19 disulfidptosis-related genes, we successfully identified subgroups of C1 and C2 patients through consensus clustering. Notably, the 2 groups exhibited significant variations in terms of survival rates, immune scores, and immune cell infiltration. Subsequently, we developed a DRRS via LASSO (least absolute shrinkage and selection operator) regression analysis, incorporating PRICKLE1, NRP1, APOD, MISP3, and SERPINE1. This scoring system effectively distinguished individuals with high and low risks, as verified with a validation set. These findings strongly indicate a close association between disulfidptosis and the immune microenvironment of GC tumors. Moreover, the DRRS demonstrated commendable predictive capabilities for the survival outcomes of GC patients. In this study, we have identified the association between different subtypes of disulfidptosis and alterations in the GC immunotumour microenvironment. Furthermore, we have developed and verified the accuracy of the DRRS, a valuable tool for predicting survival, biological function, and immune infiltration in patients with GC. These findings contribute to a better comprehension of disulfidptosis and offer potential opportunities for innovative approaches in GC treatment.

Constructing a disulfidptosis-related prognostic signature of hepatocellular carcinoma based on single-cell sequencing and weighted co-expression network analysis

Hepatocellular carcinoma (HCC) ranks as the second leading cause of cancer-related deaths globally. Disulfidptosis is a newly identified form of regulated cell death that is induced by glucose starvation. However, the clinical prognostic characteristics of disulfidptosis-associated genes in HCC remain poorly understood. We conducted an analysis of the single-cell datasets GSE149614 and performed weighted co-expression network analysis (WGCNA) on the Cancer Genome Atlas (TCGA) datasets to identify the genes related to disulfidptosis. A prognostic model was constructed using univariate COX and Lasso regression. Survival analysis, immune microenvironment analysis, and mutation analysis were performed. Additionally, a nomogram associated with disulfidptosis-related signature was constructed to identify the prognosis of HCC patients. Patients with HCC in the TCGA and GSE14520 datasets were categorized using a disulfidptosis-related model, revealing significant differences in survival times between the high- and low-disulfidptosis groups. High-disulfidptosis patients exhibited increased expression of immune checkpoint-related genes, implying that immunotherapy and certain chemotherapies may be beneficial for them. Meanwhile, the ROC and decision curves analysis (DCA) indicated that the nomogram has satisfying prognostic efficacy. Moreover, the experimental results of GATM in this prognostic model indicated that GATM is low expressed in HCC tissues, and GATM knockdown promotes the proliferation and migration of HCC cells. By analyzing single-cell and bulk multi-omics sequencing data, we developed a prognostic signature related to disulfidptosis and explored the relationship between high- and low-disulfidptosis groups in HCC. This study offers a novel reference for gaining a deeper understanding of the role of disulfidptosis in HCC.

Emerging role of immunogenic cell death in cancer immunotherapy

Cancer immunotherapy, such as immune checkpoint blockade (ICB), has emerged as a groundbreaking approach for effective cancer treatment. Despite its considerable potential, clinical studies have indicated that the current response rate to cancer immunotherapy is suboptimal, primarily attributed to low immunogenicity in certain types of malignant tumors. Immunogenic cell death (ICD) represents a form of regulated cell death (RCD) capable of enhancing tumor immunogenicity and activating tumor-specific innate and adaptive immune responses in immunocompetent hosts. Therefore, gaining a deeper understanding of ICD and its evolution is crucial for developing more effective cancer therapeutic strategies. This review focuses exclusively on both historical and recent discoveries related to ICD modes and their mechanistic insights, particularly within the context of cancer immunotherapy. Our recent findings are also highlighted, revealing a mode of ICD induction facilitated by atypical interferon (IFN)-stimulated genes (ISGs), including polo-like kinase 2 (PLK2), during hyperactive type I IFN signaling. The review concludes by discussing the therapeutic potential of ICD, with special attention to its relevance in both preclinical and clinical settings within the field of cancer immunotherapy.

Disulfidptosis-related lncRNA signature reveals immune microenvironment and novel molecular subtyping of stomach adenocarcinoma

The main challenge in treating stomach adenocarcinoma (STAD) is chemotherapy resistance, which is characterized by changes in the immune microenvironment. Disulfidptosis, a novel form of programmed cell death, is involved in STAD but its mechanism is not fully understood. Long non-coding RNAs (LncRNAs) may play a role in regulating disulfidptosis and influencing the immune microenvironment and chemotherapy resistance in STAD. This study aims to establish disulfidptosis-related lncRNA (DRL) features and explore their significance in the immune microenvironment and chemotherapy resistance in STAD patients. By analyzing RNA sequencing and clinical data from STAD patients and extracting disulfidptosis-related genes, we identified DRLs through co-expression, single-factor and multi-factor Cox regression, and Lasso regression analyses. We also investigated differences in the immune microenvironment, immune function, immune checkpoint gene expression, and chemotherapy resistance between different risk groups using various algorithms. A prognostic risk model consisting of 2 DRLs was constructed, with a strong predictive value for patient survival, outperforming other clinical-pathological factors in predicting 3-year and 5-year survival. Immune-related analysis revealed a strong positive correlation between T cell CD4+ cells and risk score across all algorithms, and higher expression of immune checkpoint genes in the high-risk group. In addition, high-risk patients showed better sensitivity to Erlotinib, Oxaliplatin, and Gefitinib. Furthermore, three novel molecular subtypes of STAD were identified based on the 2-DRLs features, with evaluation of the immune microenvironment and chemotherapy drug sensitivity for each subgroup, which holds significant implications for achieving precise treatment in STAD. Overall, our 2-DRLs prognostic model demonstrates high predictive value for patient survival in STAD, potentially providing new targets for individualized immune and chemical therapy.

Epigenetic regulation of diverse cell death modalities in cancer: a focus on pyroptosis, ferroptosis, cuproptosis, and disulfidptosis

Tumor is a local tissue hyperplasia resulted from cancerous transformation of normal cells under the action of various physical, chemical and biological factors. The exploration of tumorigenesis mechanism is crucial for early prevention and treatment of tumors. Epigenetic modification is a common and important modification in cells, including DNA methylation, histone modification, non-coding RNA modification and m6A modification. The normal mode of cell death is programmed by cell death-related genes; however, recent researches have revealed some new modes of cell death, including pyroptosis, ferroptosis, cuproptosis and disulfidptosis. Epigenetic regulation of various cell deaths is mainly involved in the regulation of key cell death proteins and affects cell death by up-regulating or down-regulating the expression levels of key proteins. This study aims to investigate the mechanism of epigenetic modifications regulating pyroptosis, ferroptosis, cuproptosis and disulfidptosis of tumor cells, explore possible triggering factors in tumor development from a microscopic point of view, and provide potential targets for tumor therapy and new perspective for the development of antitumor drugs or combination therapies.

Progress of medicinal plants and their active metabolites in ischemia-reperfusion injury of stroke: a novel therapeutic strategy based on regulation of crosstalk between mitophagy and ferroptosis

The death of cells can occur through various pathways, including apoptosis, necroptosis, mitophagy, pyroptosis, endoplasmic reticulum stress, oxidative stress, ferroptosis, cuproptosis, and disulfide-driven necrosis. Increasing evidence suggests that mitophagy and ferroptosis play crucial regulatory roles in the development of stroke. In recent years, the incidence of stroke has been gradually increasing, posing a significant threat to human health. Hemorrhagic stroke accounts for only 15% of all strokes, while ischemic stroke is the predominant type, representing 85% of all stroke cases. Ischemic stroke refers to a clinical syndrome characterized by local ischemic-hypoxic necrosis of brain tissue due to various cerebrovascular disorders, leading to rapid onset of corresponding neurological deficits. Currently, specific therapeutic approaches targeting the pathophysiological mechanisms of ischemic brain tissue injury mainly include intravenous thrombolysis and endovascular intervention. Despite some clinical efficacy, these approaches inevitably lead to ischemia-reperfusion injury. Therefore, exploration of treatment options for ischemic stroke remains a challenging task. In light of this background, advancements in targeted therapy for cerebrovascular diseases through mitophagy and ferroptosis offer a new direction for the treatment of such diseases. In this review, we summarize the progress of mitophagy and ferroptosis in regulating ischemia-reperfusion injury in stroke and emphasize their potential molecular mechanisms in the pathogenesis. Importantly, we systematically elucidate the role of medicinal plants and their active metabolites in targeting mitophagy and ferroptosis in ischemia-reperfusion injury in stroke, providing new insights and perspectives for the clinical development of therapeutic drugs for these diseases.

Prognostic Model Construction of Disulfidptosis-Related Genes and Targeted Anticancer Drug Research in Pancreatic Cancer

Pancreatic cancer stands as one of the most lethal malignancies, characterized by delayed diagnosis, high mortality rates, limited treatment efficacy, and poor prognosis. Disulfidptosis, a recently unveiled modality of cell demise induced by disulfide stress, has emerged as a critical player intricately associated with the onset and progression of various cancer types. It has emerged as a promising candidate biomarker for cancer diagnosis, prognosis assessment, and treatment strategies. In this study, we have effectively established a prognostic risk model for pancreatic cancer by incorporating multiple differentially expressed long non-coding RNAs (DElncRNAs) closely linked to disulfide-driven cell death. Our investigation delved into the nuanced relationship between the DElncRNA-based predictive model for disulfide-driven cell death and the therapeutic responses to anticancer agents. Our findings illuminate that the high-risk subgroup exhibits heightened susceptibility to the small molecule compound AZD1208, positioning it as a prospective therapeutic agent for pancreatic cancer. Finally, we have elucidated the underlying mechanistic potential of AZD1208 in ameliorating pancreatic cancer through its targeted inhibition of the peroxisome proliferator-activated receptor-γ (PPARG) protein, employing an array of comprehensive analytical methods, including molecular docking and molecular dynamics (MD) simulations. This study explores disulfidptosis-related genes, paving the way for the development of targeted therapies for pancreatic cancer and emphasizing their significance in the field of oncology. Furthermore, through computational biology approaches, the drug AZD1208 was identified as a potential treatment targeting the PPARG protein for pancreatic cancer. This discovery opens new avenues for exploring targets and screening drugs for pancreatic cancer.

Analysis of network expression and immune infiltration of disulfidptosis-related genes in chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a globally prevalent respiratory disease, and programmed cell death plays a pivotal role in the development of COPD. Disulfidptosis is a newly discovered type of cell death that may be associated with the progression of COPD. However, the expression and role of disulfidptosis-related genes (DRGs) in COPD remain unclear.

METHODS

The expression of DRGs was identified by analyzing RNA sequencing (RNA-seq) data in COPD. Further, COPD patients were classified into two subtypes by unsupervised cluster analysis to reveal their differences in gene expression and immune infiltration. Meanwhile, hub genes associated with disulfidptosis were screened by weighted gene co-expression network analysis. Subsequently, the hub genes were validated experimentally in cells and animals. In addition, we screened potential therapeutic drugs through the hub genes.

RESULTS

We identified two distinct molecular clusters and observed significant differences in immune cell populations between them. In addition, we screened nine hub genes, and experimental validation showed that CDC71, DOHH, PDAP1, and SLC25A39 were significantly upregulated in cigarette smoke-induced COPD mouse lung tissues and bronchial epithelial cells (BEAS-2B) treated with cigarette smoke extract. Finally, we predicted 10 potential small molecule drugs such as Atovaquone, Taurocholic acid, Latamoxef, and Methotrexate.

CONCLUSION

We highlighted the strong association between COPD and disulfidptosis, with DRGs demonstrating a discriminative capacity for COPD. Additionally, the expression of certain novel genes, including CDC71, DOHH, PDAP1, and SLC25A39, is linked to COPD and may aid in the diagnosis and assessment of this condition.

Pan-cancer and single-cell analysis of actin cytoskeleton genes related to disulfidptosis

Disulfidptosis was recently reported to be caused by abnormal disulfide accumulation in cells with high SLC7A11 levels subjected to glucose starvation, suggesting that targeting disulfidptosis was a potential strategy for cancer treatment. We analyzed the relationships between gene expression and mutations and prognoses of patients. In addition, the correlation between gene expression and immune cell infiltration was explored. The potential regulatory mechanisms of these genes were assessed by investigating their related signaling pathways involved in cancer, their expression patterns, and their cellular localization. Most cancer types showed a negative correlation between the gene-set variation analysis (GSVA) scores and infiltration of B cells and neutrophils, and a positive correlation between GSVA scores and infiltration of natural killer T and induced regulatory T cells. Single-cell analysis revealed that ACTB, DSTN, and MYL6 were highly expressed in different bladder urothelial carcinoma subtypes, but MYH10 showed a low expression. Immunofluorescence staining showed that actin cytoskeleton proteins were mainly localized in the actin filaments and plasma membrane. Notably, IQGAP1 was localized in the cell junctions. In conclusion, this study provided an overview of disulfidptosis-related actin cytoskeleton genes in pan-cancer. These genes were associated with the survival of patients and might be involved in cancer-related pathways.

Effect of disulfidptosis-related genes SLC3A2, SLC7A11 and FLNB polymorphisms on risk of autoimmune thyroiditis in a Chinese population

PURPOSE

This study aimed to evaluate the associations between disulfidptosis related genes-SLC3A2, SLC7A11 and FLNB polymorphisms and risk of autoimmune thyroiditis (AIT).

METHODS

Six SNPs in the SLC3A2, SLC7A11 and FLNB were genotyped in 650 AIT cases and 650 controls using a MassARRAY platform.

RESULTS

Minor alleles of SLC3A2-rs12794763, rs1059292 and FLNB-rs839240 might lead to a higher risk of AIT (p < 0.001), while SLC7A11-rs969319-C allele tends to decrease the risk of the disease (p = 0.006). Genetic model analysis showed that SLC3A2-rs12794763, SLC3A2-rs1059292 and FLNB-rs839240 polymorphisms were risk factors for AIT (p < 0.001); while SLC7A11-rs969319 showed a protective role for the disease in all genetic models (p < 0.005). Stratification analysis showed that SLC3A2-rs1059292 and rs12794763 were correlated with higher risk of AIT regardless of sex (p < 0.05). Moreover, FLNB-rs839240 exhibited higher risk of disease only in females (p < 0.05). By contrast, SLC7A11-rs969319 showed a protective role only in females (p < 0.05).

CONCLUSION

Our results shed new light on the association between disulfidptosis-related genes and AIT risk.

Merlin/NF2 regulates SLC7A11/xCT expression and cell viability under glucose deprivation at high cell density in glioblastoma cells

The cystine/glutamate transporter SLC7A11/xCT is highly expressed in many cancer cells and plays an important role in antioxidant activity by supplying cysteine for glutathione synthesis. Under glucose-depleted conditions, however, SLC7A11-mediated cystine uptake causes oxidative stress and cell death called disulfidptosis, a new form of cell death. We previously reported that high cell density (HD) promotes lysosomal degradation of SLC7A11 in glioblastoma cells, allowing them to survive under glucose-depleted conditions. In this study, we found that the neurofibromatosis type 2 gene, Merlin/NF2 is a key regulator of SLC7A11 in glioblastoma cells at HD. Deletion of Merlin increased SLC7A11 protein level and cystine uptake at HD, leading to promotion of cell death under glucose deprivation. Furthermore, HD significantly decreased SLC7A11 mRNA level, which was restored by Merlin deletion. This study suggests that Merlin suppresses glucose deprivation-induced cell death by downregulating SLC7A11 expression in glioblastoma cells at HD.

Integrated machine learning-driven disulfidptosis profiling: CYFIP1 and EMILIN1 as therapeutic nodes in neuroblastoma

BACKGROUND

Neuroblastoma (NB), a prevalent pediatric solid tumor, presents formidable challenges due to its high malignancy and intricate pathogenesis. The role of disulfidptosis, a novel form of programmed cell death, remains poorly understood in the context of NB.

METHODS

Gaussian mixture model (GMM)-identified disulfidptosis-related molecular subtypes in NB, differential gene analysis, survival analysis, and gene set variation analysis were conducted subsequently. Weighted gene co-expression network analysis (WGCNA) selected modular genes most relevant to the disulfidptosis core pathways. Integration of machine learning approaches revealed the combination of the Least absolute shrinkage and selection operator (LASSO) and Random Survival Forest (RSF) provided optimal dimensionality reduction of the modular genes. The resulting model was validated, and a nomogram assessed disulfidptosis characteristics in NB. Core genes were filtered and subjected to tumor phenotype and disulfidptosis-related experiments.

RESULTS

GMM clustering revealed three distinct subtypes with diverse prognoses, showing significant variations in glucose metabolism, cytoskeletal structure, and tumor-related pathways. WGCNA highlighted the red module of genes highly correlated with disulfide isomerase activity, cytoskeleton formation, and glucose metabolism. The LASSO and RSF combination yielded the most accurate and stable prognostic model, with a significantly worse prognosis for high-scoring patients. Cytological experiments targeting core genes (CYFIP1, EMILIN1) revealed decreased cell proliferation, migration, invasion abilities, and evident cytoskeletal deformation upon core gene knockdown.

CONCLUSIONS

This study showcases the utility of disulfidptosis-related gene scores for predicting prognosis and molecular subtypes of NB. The identified core genes, CYFIP1 and EMILIN1, hold promise as potential therapeutic targets and diagnostic markers for NB.

Reductive stress in cancer: coming out of the shadows

Redox imbalance is defined by disruption in oxidative and reductive pathways and has a central role in cancer initiation, development, and treatment. Although redox imbalance has traditionally been characterized by high levels of oxidative stress, emerging evidence suggests that an overly reductive environment is just as detrimental to cancer proliferation. Reductive stress is defined by heightened levels of antioxidants, including glutathione and elevated NADH, compared with oxidized NAD, which disrupts central biochemical pathways required for proliferation. With the advent of new technologies that measure and manipulate reductive stress, the sensors and drivers of this overlooked metabolic stress are beginning to be revealed. In certain genetically defined cancers, targeting reductive stress pathways may be an effective strategy. Redox-based pathways are gaining recognition as essential 'regulatory hubs,' and a broader understanding of reductive stress signaling promises not only to reveal new insights into metabolic homeostasis but also potentially to transform therapeutic options in cancer.

Development of a novel disulfidptosis-related lncRNA signature for prognostic and immune response prediction in clear cell renal cell carcinoma

Disulfidptosis, a novel form of regulated cell death, occurs due to the aberrant accumulation of intracellular cystine and other disulfides. Moreover, targeting disulfidptosis could identify promising approaches for cancer treatment. Long non-coding RNAs (lncRNAs) are known to be critically implicated in clear cell renal cell carcinoma (ccRCC) development. Currently, the involvement of disulfidptosis-related lncRNAs in ccRCC is yet to be elucidated. This study primarily dealt with identifying and validating a disulfidptosis-related lncRNAs-based signature for predicting the prognosis and immune landscape of individuals with ccRCC. Clinical and RNA sequencing data of ccRCC samples were accessed from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was conducted for the identification of the disulfidptosis-related lncRNAs. Additionally, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator Cox regression, and stepwise multivariate Cox analysis were executed to develop a novel risk prognostic model. The prognosis-predictive capacity of the model was then assessed using an integrated method. Variation in biological function was noted using GO, KEGG, and GSEA. Additionally, immune cell infiltration, the tumor mutational burden (TMB), and tumor immune dysfunction and exclusion (TIDE) scores were calculated to investigate differences in the immune landscape. Finally, the expression of hub disulfidptosis-related lncRNAs was validated using qPCR. We established a novel signature comprised of eight lncRNAs that were associated with disulfidptosis (SPINT1-AS1, AL121944.1, AC131009.3, AC104088.3, AL035071.1, LINC00886, AL035587.2, and AC007743.1). Kaplan-Meier and receiver operating characteristic curves demonstrated the acceptable predictive potency of the model. The nomogram and C-index confirmed the strong correlation between the risk signature and clinical decision-making. Furthermore, immune cell infiltration analysis and ssGSEA revealed significantly different immune statuses among risk groups. TMB analysis revealed the link between the high-risk group and high TMB. It is worth noting that the cumulative effect of the patients belonging to the high-risk group and having elevated TMB led to decreased patient survival times. The high-risk group depicted greater TIDE scores in contrast with the low-risk group, indicating greater potential for immune escape. Finally, qPCR validated the hub disulfidptosis-related lncRNAs in cell lines. The established novel signature holds potential regarding the prognosis prediction of individuals with ccRCC as well as predicting their responses to immunotherapy.

Mitochondrial dysfunction and disulfidptosis co-regulate neuronal cell in neuropathic pain based on bioinformatics analysis

Neuropathic pain (NP) affects approximately 6.9-10% of the world's population and necessitates the development of novel treatments. Mitochondria are essential in the regulation of cell death. Neuroimmune mechanisms are implicated in various forms of cell death associated with NP. However, the specific involvement of mitochondrial dysfunction and disulfidptosis in NP remains uncertain. Further research is required to gain a better understanding of their combined contribution. Our comprehensive study employs a variety of bioinformatic analysis methods, including differential gene analysis, weighted gene co-expression network analysis, machine learning, functional enrichment analysis, immune infiltration, sub-cluster analysis, single-cell dimensionality reduction and cell-cell communication to gain insight into the molecular mechanisms behind these processes. Our study rationally defines a list of key gene sets for mitochondrial dysfunction and disulfidptosis. 6 hub mitochondrial genes and 3 disulfidptosis-related genes (DRGs) were found to be associated with NP. The key genes were predominantly expressed in neurons and were lowly expressed in the NP group compared to SHAM. In addition, our macrophages used the APP (Amyloid precursor protein)-CD74 (MHC class II invariant chain) pathway to interact with neurons. These results suggest that NP is interconnected with the mechanistic processes of mitochondrial dysfunction and disulfidptosis, which may contribute to clinically targeted therapies.

Molecular landmarks of tumor disulfidptosis across cancer types to promote disulfidptosis-target therapy

The mystery about the mechanistic basis of disulfidptosis has recently been unraveled and shows promise as an effective treatment modality for triggering cancer cell death. However, the limited understanding of the role of disulfidptosis in tumor progression and drug sensitivity has hindered the development of disulfidptosis-targeted therapy and combinations with other therapeutic strategies. Here, we established a disulfidptosis signature model to estimate tumor disulfidptosis status in approximately 10,000 tumor samples across 33 cancer types and revealed its prognostic value. Then, we characterized disulfidptosis-associated molecular features and identified various types of molecular alterations that correlate with both drug-resistant and drug-sensitive responses to anti-tumor drugs. We further showed the vast heterogeneity in disulfidptosis status among 760 cancer cell lines across 25 cancer types. We experimentally validated that disulfidptosis score-high cell lines are more susceptible to glucose starvation-induced disulfidptosis compared to their counterparts with low scores. Finally, we investigated the impact of disulfidptosis status on drug response and revealed that disulfidptosis induction may enhance sensitivity to anti-cancer drugs, but in some cases, it could also lead to drug resistance in cultured cells. Overall, our multi-omics analysis firstly elucidates a comprehensive profile of disulfidptosis-related molecular alterations, prognosis, and potential therapeutic therapies at a pan-cancer level. These findings may uncover opportunities to utilize multiple drug sensitivities induced by disulfidptosis, thereby offering practical implications for clinical cancer therapy.

Development of the RF-GSEA Method for Identifying Disulfidptosis-Related Genes and Application in Hepatocellular Carcinoma

Disulfidptosis is a newly discovered cellular programmed cell death mode. Presently, a considerable number of genes related to disulfidptosis remain undiscovered, and its significance in hepatocellular carcinoma remains unrevealed. We have developed a powerful analytical method called RF-GSEA for identifying potential genes associated with disulfidptosis. This method draws inspiration from gene regulation networks and graph theory, and it is implemented through a combination of random forest regression model and Gene Set Enrichment Analysis. Subsequently, to validate the practical application value of this method, we applied it to hepatocellular carcinoma. Based on the RF-GSEA method, we developed a disulfidptosis-related signature. Lastly, we looked into how the disulfidptosis-related signature is connected to HCC prognosis, the tumor microenvironment, the effectiveness of immunotherapy, and the sensitivity of chemotherapy drugs. The RF-GSEA method identified a total of 220 disulfidptosis-related genes, from which 7 were selected to construct the disulfidptosis-related signature. The high-disulfidptosis-related score group had a worse prognosis compared to the low-disulfidptosis-related score group and showed lower infiltration levels of immune-promoting cells. The high-disulfidptosis-related score group had a higher likelihood of benefiting from immunotherapy compared to the low-disulfidptosis-related score group. The RF-GSEA method is a powerful tool for identifying disulfidptosis-related genes. The disulfidptosis-related signature effectively predicts HCC prognosis, immunotherapy response, and drug sensitivity.

A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer

Colorectal cancer (CRC) is a common and deadly cancer worldwide with a high lethality rate. Disulfidptosis has been found to be an emerging mode of death in cancer, and the purpose of this study was to explore the relationship between disulfidptosis-related lncRNAs (DRLs) and CRC and to develop a prognostic model for CRC and DRLs. The gene expression data and clinicopathologic information of colorectal cancer patients were obtained from The Cancer Genome Atlas (TCGA) and screened for DRLs based on correlation analysis. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to construct the prognostic model, and its validation was carried out by PCA and receiver operating characteristic (ROC) curves. We constructed nomograms combined with the model. Finally, the possible mechanisms by which lncRNAs affect CRC were explored by functional enrichment analysis, immune infiltration and immune escape analysis. In summary, we developed a prognostic marker consisting of lncRNAs associated with disulfidptosis to help clinicians predict the survival of different CRC patients and use different targeted therapies and immunotherapies depending on the condition.