Disulfidptosis: a new form of programmed cell death

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.

Inducing disulfidptosis in tumors:potential pathways and significance

Regulated cell death (RCD) is crucial for the elimination of abnormal cells. In recent years, strategies aimed at inducing RCD, particularly apoptosis, have become increasingly important in cancer therapy. However, the ability of tumor cells to evade apoptosis has led to treatment resistance and relapse, prompting extensive research into alternative death processes in cancer cells. A recent study identified a novel form of RCD known as disulfidptosis, which is linked to disulfide stress. Cancer cells import cystine from the extracellular environment via solute carrier family 7 member 11 (SLC7A11) and convert it to cysteine using nicotinamide adenine dinucleotide phosphate (NADPH). When NADPH is deficient or its utilization is impaired, cystine accumulates, leading to the formation of disulfide bonds in the actin cytoskeleton, triggering disulfidptosis. Disulfidptosis reveals a metabolic vulnerability in tumors, offering new insights into cancer therapy strategies. This review provides a detailed overview of the mechanisms underlying disulfidptosis, the current research progress, and limitations. It also highlights innovative strategies for inducing disulfidptosis and explores the potential of combining these approaches with traditional cancer therapies, particularly immunotherapy, to expedite clinical translation.

Disulfidptosis-related gene expression reflects the prognosis of drug-resistant cancer patients and inhibition of MYH9 reverses sorafenib resistance

The onset of drug resistance in advanced cancer patients markedly diminishes their prognosis. Recently, disulfidptosis, a novel form of cell death, has been identified, triggered by excessive disulfide formation leading to cell shrinkage and F-actin contraction. Previous studies have identified 15 essential genes (FLNA, FLNB, MYH9, TLN1, ACTB, MYL6, MYH10, CAPZB, DSTN, IQGAP1, ACTN4, PDLIM1, CD2AP, INF2, SLC7A11) associated with disulfidptosis. This study sourced pan-cancer mRNA expression data from Xena to thoroughly evaluate the molecular and clinical characteristics of disulfidptosis-related genes. Through unsupervised clustering, mRNA expression data identified the expression levels of disulfidptosis-related genes and potential clusters related to this form of cell death. Kaplan-Meier survival curves illustrated the correlation between different clusters and overall survival. The findings reveal that high expression of disulfidptosis-related genes is linked to poor survival in liver cancer. The GDSC database was utilized to analyze the relationship between disulfidptosis-related genes and the AUC of 198 drugs. The results demonstrate that 12 disulfidptosis-related genes influence sorafenib resistance, as revealed by the intersection of differential genes related to sorafenib resistance from the GSE109211 dataset. Among them, the MYH9 gene was found to play a crucial role in both. Finally, experimental evidence confirmed that MYH9 mitigates sorafenib resistance in hepatocellular carcinoma through disulfidptosis-like changes. This study identifies disulfidptosis as a promising avenue for enhancing the sensitivity of tumor cells to drugs, offering new therapeutic perspectives for future research on disulfidptosis and drug resistance in cancer patients.

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.

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.

Disulfidptosis-related gene SLC7A11 predicts prognosis and indicates tumor immune infiltration in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is closely associated with factors such as smoking and metabolic disorders. A unique form of cell death known as disulfidptosis, which is regulated by genes like SLC7A11, has emerged as an area of interest; however, its effect on the immune microenvironment in the context of cancer remains largely unexplored. The aim of this study was to analyze the immunoregulatory role of disulfidptosis-related genes in LUAD to unveil and underscore their significance in the process of immune regulation.

Methods

This study examined the role of disulfidptosis-related genes in LUAD using data from The Cancer Genome Atlas (TCGA) with a particular focus on immune infiltration and the function of SLC7A11. The research employed a clustering analysis, survival analysis, and immune function assessment, integrating both bulk and single-cell RNA sequencing data, to gain a comprehensive understanding of disulfidptosis in LUAD.

Results

The analysis revealed three distinct LUAD clusters, each characterized by different survival rates and patterns of immune cell infiltration. Notably, high expression levels of SLC7A11 were associated with a poor prognosis and mechanisms of immune evasion. High SLC7A11 expression is correlated with a poor prognosis and immune evasion in LUAD. These results underscore the significant role of SLC7A11 in the progression of disulfidptosis and LUAD.

Conclusions

This study sheds new light on the role of disulfidptosis in LUAD, particularly highlighting the immunoregulatory effects of SLC7A11. The findings suggest that targeting SLC7A11 could lead to the development of novel therapeutic strategies aimed at enhancing the response to immunotherapy in LUAD patients. To substantiate these results, further experimental validation is needed.

Predictive value of cuproptosis and disulfidptosis-related lncRNA in head and neck squamous cell carcinoma prognosis and treatment

Objective

Head and neck squamous cell carcinoma (HNSCC) is a highly lethal and prevalent malignant tumor with a poor prognosis due to its high recurrence rate, This study aims to develop a prognostic index for HNSCC patients based on Cuproptosis and Disulfidptosis-related long noncoding RNA.

Methods

Gene expression and clinical data for HNSCC were obtained from The Cancer Genome Atlas (TCGA). Using Lasso regression and multivariate Cox regression, we established a risk scoring model. The predictive ability of the nomogram, based on clinical features and risk scores, was verified using receiver operating characteristics and calibration curves. We compared independent prognostic parameters, risk score distribution, and survival between high-risk and low-risk groups, followed by preliminary validity evaluations of the model.

Results

Our systematic evaluation of prognostic risk provides a new direction for improving the survival prognosis of HNSCC patients in clinical practice, The model effectively categorized patients into high- and low-risk groups with distinct outcomes, identifying numerous gene mutations in these groups, A low-risk score was associated with a better prognosis and higher survival rates.

Conclusion

The risk score prognostic prediction system developed in this study shows potential efficacy in predicting the prognosis of HNSCC patients and has practical applications in clinical settings.

Disulfidptosis: A New Target for Parkinson's Disease and Cancer

Recent studies have uncovered intriguing connections between Parkinson's disease (PD) and cancer, two seemingly distinct disease categories. Disulfidptosis has garnered attention as a novel form of regulated cell death that is implicated in various pathological conditions, including neurodegenerative disorders and cancer. Disulfidptosis involves the dysregulation of intracellular redox homeostasis, leading to the accumulation of disulfide bonds and subsequent cell demise. This has sparked our interest in exploring common molecular mechanisms and genetic factors that may be involved in the relationship between neurodegenerative diseases and tumorigenesis. The Gene4PD database was used to retrieve PD differentially expressed genes (DEGs), the biological functions of differential expression disulfidptosis-related genes (DEDRGs) were analyzed, the ROCs of DEDRGs were analyzed using the GEO database, and the expression of DEDRGs was verified by an MPTP-induced PD mouse model in vivo. Then, the DEDRGs in more than 9000 samples of more than 30 cancers were comprehensively and systematically characterized by using multi-omics analysis data. In PD, we obtained a total of four DEDRGs, including ACTB, ACTN4, INF2, and MYL6. The enriched biological functions include the regulation of the NF-κB signaling pathway, mitochondrial function, apoptosis, and tumor necrosis factor, and these genes are rich in different brain regions. In the MPTP-induced PD mouse model, the expression of ACTB was decreased, while the expression of ACTN4, INF2, and MYL6 was increased. In pan-cancer, the high expression of ACTB, ACTN4, and MYL6 in GBMLGG, LGG, MESO, and LAML had a poor prognosis, and the high expression of INF2 in LIHC, LUAD, UVM, HNSC, GBM, LAML, and KIPAN had a poor prognosis. Our study showed that these genes were more highly infiltrated in Macrophages, NK cells, Neutrophils, Eosinophils, CD8 T cells, T cells, T helper cells, B cells, dendritic cells, and mast cells in pan-cancer patients. Most substitution mutations were G-to-A transitions and C-to-T transitions. We also found that miR-4298, miR-296-3p, miR-150-3p, miR-493-5p, and miR-6742-5p play important roles in cancer and PD. Cyclophosphamide and ethinyl estradiol may be potential drugs affected by DEDRGs for future research. This study found that ACTB, ACTN4, INF2, and MYL6 are closely related to PD and pan-cancer and can be used as candidate genes for the diagnosis, prognosis, and therapeutic biomarkers of neurodegenerative diseases and cancers.

Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research

Spatial transcriptomics (ST) examines gene expression within its spatial context on tissue, linking morphology and function. Advances in ST resolution and throughput have led to an increase in scientific interest, notably in cancer research. This scoping study reviews the challenges and practical applications of ST, summarizing current methods, trends, and data analysis techniques for ST in neoplasm research. We analyzed 41 articles published by the end of 2023 alongside public data repositories. The findings indicate cancer biology is an important focus of ST research, with a rising number of studies each year. Visium (10x Genomics, Pleasanton, CA, USA) is the leading ST platform, and SCTransform from Seurat R library is the preferred method for data normalization and integration. Many studies incorporate additional data types like single-cell sequencing and immunohistochemistry. Common ST applications include discovering the composition and function of tumor tissues in the context of their heterogeneity, characterizing the tumor microenvironment, or identifying interactions between cells, including spatial patterns of expression and co-occurrence. However, nearly half of the studies lacked comprehensive data processing protocols, hindering their reproducibility. By recommending greater transparency in sharing analysis methods and adapting single-cell analysis techniques with caution, this review aims to improve the reproducibility and reliability of future studies in cancer research.

Bioactive Nanoliposomes for Enhanced Sonodynamic-Triggered Disulfidptosis-Like Cancer Cell Death via Lipid Peroxidation

Introduction

Cell death regulation holds a unique value in the field of cancer therapy. Recently, disulfidptosis has garnered substantial scientific attention. Previous studies have reported that sonodynamic therapy (SDT) based on reactive oxygen species (ROS) can regulate cancer cell death, achieving an limited anti-cancer effect. However, the integration of SDT with disulfidptosis as an anti-cancer strategy has not been extensively developed. In this study, we constructed an artificial membrane disulfidptosis sonosensitizer, specifically, a nanoliposome (SC@lip) coated with a combination of the chemotherapy medicine Sorafenib (Sora) and sonosensitizer Chlorin e6 (Ce6), to realize a one-stop enhanced SDT effect that induces disulfidptosis-like cancer cell death.

Methods

Sorafenib and Ce6 were co-encapsulated into PEG-modified liposomes, and SC@Lip was constructed using a simple rotary evaporation phacoemulsification method. The cell phagocytosis, ROS generation ability, glutathione (GSH) depletion ability, lipid peroxidation (LPO), and disulfidptosis-like death mediated by SC@Lip under ultrasound (US) irradiation were evaluated. Based on a 4T1 subcutaneous tumor model, both the in vivo biological safety assessment and the efficacy of SDT were assessed.

Results

SC@Lip exhibits high efficiency in cellular phagocytosis. After being endocytosed by 4T1 cells, abundant ROS were produced under SDT activation, and the cell survival rates were below 5%. When applied to a 4T1 subcutaneous tumor model, the enhanced SDT mediated by SC@Lip inhibited tumor growth and prolonged the survival time of mice. In vitro and in vivo experiments show that SC@Lip can enhance the SDT effect and trigger disulfidptosis-like cancer cell death, thus achieving anti-tumor efficacy both in vitro and in vivo.

Conclusion

SC@Lip is a multifunctional nanoplatform with an artificial membrane, which can integrate the functions of sonosensitization and GSH depletion into a biocompatible nanoplatform, and can be used to enhance the SDT effect and promote disulfidptosis-like cancer cell death.

Role of N6-methyladenosine RNA modification in cancer

N6-methyladenosine (m6A) is the most abundant modification of RNA in eukaryotic cells. Previous studies have shown that m6A is pivotal in diverse diseases especially cancer. m6A corelates with the initiation, progression, resistance, invasion, and metastasis of cancer. However, despite these insights, a comprehensive understanding of its specific roles and mechanisms within the complex landscape of cancer is still elusive. This review begins by outlining the key regulatory proteins of m6A modification and their posttranslational modifications (PTMs), as well as the role in chromatin accessibility and transcriptional activity within cancer cells. Additionally, it highlights that m6A modifications impact cancer progression by modulating programmed cell death mechanisms and affecting the tumor microenvironment through various cancer-associated immune cells. Furthermore, the review discusses how microorganisms can induce enduring epigenetic changes and oncogenic effect in microorganism-associated cancers by altering m6A modifications. Last, it delves into the role of m6A modification in cancer immunotherapy, encompassing RNA therapy, immune checkpoint blockade, cytokine therapy, adoptive cell transfer therapy, and direct targeting of m6A regulators. Overall, this review clarifies the multifaceted role of m6A modification in cancer and explores targeted therapies aimed at manipulating m6A modification, aiming to advance cancer research and improve patient outcomes.

Unveiling disulfidptosis-related biomarkers and predicting drugs in Alzheimer's disease

Alzheimer's disease is the predominant form of dementia, and disulfidptosis is the latest reported mode of cell death that impacts various disease processes. This study used bioinformatics to analyze genes associated with disulfidptosis in Alzheimer's disease comprehensively. Based on the public datasets, the differentially expressed genes associated with disulfidptosis were identified, and immune cell infiltration was investigated through correlation analysis. Subsequently, hub genes were determined by a randomforest model. A prediction model was constructed using logistic regression. In addition, the drug-target affinity was predicted by a graph neural network model, and the results were validated by molecular docking. Five hub genes (PPEF1, NEUROD6, VIP, NUPR1, and GEM) were identified. The gene set showed significant enrichment for AD-related pathways. The logistic regression model demonstrated an AUC of 0.952, with AUC values of 0.916 and 0.864 in validated datasets. The immune infiltration analysis revealed significant heterogeneity between the Alzheimer's disease and control groups. High-affinity drugs for hub genes were identified. Through our study, a disease prediction model was constructed using potential biomarkers, and drugs targeting the genes were predicted. These results contribute to further understanding of the molecular mechanisms underlying Alzheimer's disease.

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.

Disulfidoptosis as a Novel Mechanism of Neuronal Death: Insights from Creutzfeldt-Jakob Disease

BACKGROUND

Sporadic Creutzfeldt-Jakob Disease (SCJD) is a severe neurodegenerative disorder characterized by rapid progression and extensive neuronal loss. Disulfidptosis is an innovative type of programmed cell demise characterized by an accumulation of disulfide bonds within the cellular cytoplasm, subsequently triggering functional disruption and cell demise.

METHODS

Through literature review and analysis, we identified 18 candidate disulfidptosis-related genes (DRGs) involved in cellular processes. The dataset used for analysis, GSE124571, was obtained from the Gene Expression Omnibus database. Gene-gene and protein-protein interactions were analyzed using the GeneMANIA and STRING databases, respectively. We also performed enrichment analysis, differential expressed genes analysis, weighted gene correlation network analysis analysis, immune infiltration, consensus clustering, and matrix correlation.

RESULTS

The analysis showed that 12 out of 18 DRGs were significantly changed between SCJD and control groups. The DRGs had strong interactions such as physical interactions, co-expression and genetic interactions, and were enriched in biological processes and pathways related to actin cytoskeletal regulation. The study most notably identified 3 hub genes (WASF2, TLN1 and G6PD) important for SCJD and emphasized the functional significance of the identified hub genes. The role of the immune system in the pathogenesis of SCJD. The study found that the composition of immune cells in SCJD brain tissue is altered. Consensus clustering provided insights into immune infiltration and hub gene expression in SCJD subgroup.

CONCLUSIONS

Our study reveals the possible involvement of disulfidptosis in SCJD and highlights the significance of identified hub genes as potential biomarkers and therapeutic targets for SCJD.

Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation

BACKGROUND

Endometriosis (EMs) is an enigmatic disease of yet-unknown pathogenesis. Disulfidptosis, a novel identified form of programmed cell death resulting from disulfide stress, stands a chance of treating diverse ailments. However, the potential roles of disulfidptosis-related genes (DRGs) in EMs remain elusive. This study aims to thoroughly explore the key disulfidptosis genes involved in EMs, and probe novel diagnostic markers and candidate therapeutic compounds from the aspect of disulfidptosis based on bioinformatics analysis, machine learning, and animal experiments.

RESULTS

Enrichment analysis on key module genes and differentially expressed genes (DEGs) of eutopic and ectopic endometrial tissues in EMs suggested that EMs was closely related to disulfidptosis. And then, we obtained 20 and 16 disulfidptosis-related DEGs in eutopic and ectopic endometrial tissue, respectively. The protein-protein interaction (PPI) network revealed complex interactions between genes, and screened nine and ten hub genes in eutopic and ectopic endometrial tissue, respectively. Furthermore, immune infiltration analysis uncovered distinct differences in the immunocyte, human leukocyte antigen (HLA) gene set, and immune checkpoints in the eutopic and ectopic endometrial tissues when compared with health control. Besides, the hub genes mentioned above showed a close correlation with the immune microenvironment of EMs. Furthermore, four machine learning algorithms were applied to screen signature genes in eutopic and ectopic endometrial tissue, including the binary logistic regression (BLR), the least absolute shrinkage and selection operator (LASSO), the support vector machine-recursive feature elimination (SVM-RFE), and the extreme gradient boosting (XGBoost). Model training and hyperparameter tuning were implemented on 80% of the data using a ten-fold cross-validation method, and tested in the testing sets which determined the excellent diagnostic performance of these models by six indicators (Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value, Accuracy, and Area Under Curve). And seven eutopic signature genes (ACTB, GYS1, IQGAP1, MYH10, NUBPL, SLC7A11, TLN1) and five ectopic signature genes (CAPZB, CD2AP, MYH10, OXSM, PDLIM1) were finally identified based on machine learning. The independent validation dataset also showed high accuracy of the signature genes (IQGAP1, SLC7A11, CD2AP, MYH10, PDLIM1) in predicting EMs. Moreover, we screened 12 specific compounds for EMs based on ectopic signature genes and the pharmacological impact of tretinoin on signature genes was further verified in the ectopic lesion in the EMs murine model.

CONCLUSION

This study verified a close association between disulfidptosis and EMs based on bioinformatics analysis, machine learning, and animal experiments. Further investigation on the biological mechanism of disulfidptosis in EMs is anticipated to yield novel advancements for searching for potential diagnostic biomarkers and revolutionary therapeutic approaches in EMs.

SLC7A11: the Achilles heel of tumor?

The non-natriuretic-dependent glutamate/cystine inverse transporter-system Xc- is composed of two protein subunits, SLC7A11 and SLC3A2, with SLC7A11 serving as the primary functional component responsible for cystine uptake and glutathione biosynthesis. SLC7A11 is implicated in tumor development through its regulation of redox homeostasis, amino acid metabolism, modulation of immune function, and induction of programmed cell death, among other processes relevant to tumorigenesis. In this paper, we summarize the structure and biological functions of SLC7A11, and discuss its potential role in tumor therapy, which provides a new direction for precision and personalized treatment of tumors.

Construction and validation of a prognostic model for bladder cancer based on disulfidptosis-related lncRNAs

BACKGROUND

Bladder cancer (BLCA) is a prevalent and aggressive cancer associated with high mortality and poor prognosis. Currently, studies on the role of disulfidptosis-related long non-coding RNAs (DRLs) in BLCA are limited. This study aims to construct a prognostic model based on DRLs to improve the accuracy of survival predictions for patients and identify novel targets for therapeutic intervention in BLCA management.

METHODS

Transcriptomic and clinical datasets for patients with BLCA were obtained from The Cancer Genome Atlas. Using multivariate Cox regression and least absolute shrinkage and selection operator techniques, a risk prognostic signature defined by DRLs was developed. The model's accuracy and prognostic relevance were assessed through Kaplan-Meier survival plots, receiver operating characteristic curves, concordance index, and principal component analysis. Functional and pathway enrichment analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis, were conducted to elucidate the underlying biological processes. Immune cell infiltration was quantified using the CIBERSORT algorithm. Differences and functions of immune cells in different risk groups were evaluated through single-sample Gene Set Enrichment Analysis. The Tumor Immune Dysfunction and Exclusion predictor and tumor mutational burden (TMB) assessments were utilized to gauge the likelihood of response to immunotherapy. Drug sensitivity predictions were made using the Genomics of Drug Sensitivity in Cancer database.

RESULTS

A robust 8-DRL risk prognostic model, comprising LINC00513, SMARCA5-AS1, MIR4435-2HG, MIR4713HG, AL122035.1, AL359762.3, AC006160.1, and AL590428.1, was identified as an independent prognostic indicator. This model demonstrated strong predictive power for overall survival in patients with BLCA, revealing significant disparities between high- and low-risk groups regarding tumor microenvironment, immune infiltration, immune functions, TMB, Tumor Immune Dysfunction and Exclusion scores, and drug susceptibility.

CONCLUSION

This study introduces an innovative prognostic signature of 8 DRLs, offering a valuable prognostic tool and potential therapeutic targets for bladder carcinoma. The findings have significant implications for TMB, the immune landscape, and patient responsiveness to immunotherapy and targeted treatments.

Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients

BACKGROUND

Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present.

METHODS

The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance.

RESULTS

A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses.

CONCLUSION

We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.

Therapeutic strategies of targeting non-apoptotic regulated cell death (RCD) with small-molecule compounds in cancer

Regulated cell death (RCD) is a controlled form of cell death orchestrated by one or more cascading signaling pathways, making it amenable to pharmacological intervention. RCD subroutines can be categorized as apoptotic or non-apoptotic and play essential roles in maintaining homeostasis, facilitating development, and modulating immunity. Accumulating evidence has recently revealed that RCD evasion is frequently the primary cause of tumor survival. Several non-apoptotic RCD subroutines have garnered attention as promising cancer therapies due to their ability to induce tumor regression and prevent relapse, comparable to apoptosis. Moreover, they offer potential solutions for overcoming the acquired resistance of tumors toward apoptotic drugs. With an increasing understanding of the underlying mechanisms governing these non-apoptotic RCD subroutines, a growing number of small-molecule compounds targeting single or multiple pathways have been discovered, providing novel strategies for current cancer therapy. In this review, we comprehensively summarized the current regulatory mechanisms of the emerging non-apoptotic RCD subroutines, mainly including autophagy-dependent cell death, ferroptosis, cuproptosis, disulfidptosis, necroptosis, pyroptosis, alkaliptosis, oxeiptosis, parthanatos, mitochondrial permeability transition (MPT)-driven necrosis, entotic cell death, NETotic cell death, lysosome-dependent cell death, and immunogenic cell death (ICD). Furthermore, we focused on discussing the pharmacological regulatory mechanisms of related small-molecule compounds. In brief, these insightful findings may provide valuable guidance for investigating individual or collaborative targeting approaches towards different RCD subroutines, ultimately driving the discovery of novel small-molecule compounds that target RCD and significantly enhance future cancer therapeutics.

Disulfidptosis: A Novel Prognostic Criterion and Potential Treatment Strategy for Diffuse Large B-Cell Lymphoma (DLBCL)

Diffuse Large B-cell Lymphoma (DLBCL), with its intrinsic genetic and epigenetic heterogeneity, exhibits significantly variable clinical outcomes among patients treated with the current standard regimen. Disulfidptosis, a novel form of regulatory cell death triggered by disulfide stress, is characterized by the collapse of cytoskeleton proteins and F-actin due to intracellular accumulation of disulfides. We investigated the expression variations of disulfidptosis-related genes (DRGs) in DLBCL using two publicly available gene expression datasets. The initial analysis of DRGs in DLBCL (GSE12453) revealed differences in gene expression patterns between various normal B cells and DLBCL. Subsequent analysis (GSE31312) identified DRGs strongly associated with prognostic outcomes, revealing eight characteristic DRGs (CAPZB, DSTN, GYS1, IQGAP1, MYH9, NDUFA11, NDUFS1, OXSM). Based on these DRGs, DLBCL patients were stratified into three groups, indicating that (1) DRGs can predict prognosis, and (2) DRGs can help identify novel therapeutic candidates. This study underscores the significant role of DRGs in various biological processes within DLBCL. Assessing the risk scores of individual DRGs allows for more precise stratification of prognosis and treatment strategies for DLBCL patients, thereby enhancing the effectiveness of clinical practice.

Pan-cancer analysis of the disulfidptosis-related gene RPN1 and its potential biological function and prognostic significance in gliomas

Background

Numerous studies have shown a strong correlation between disulfidptosis and various cancers. However, the expression and function of RPN1, a crucial gene in disulfidptosis, remain unclear in the context of cancer.

Methods

Gene expression and clinical information on lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. RPN1 expression was analyzed using the Timer2.0 and the Human Protein Atlas (HPA) databases. Prognostic significance was assessed using Cox regression analysis and Kaplan-Meier curves. Genetic mutations and methylation levels were examined using the cBioPortal and UALCAN platforms, respectively. The relationship between RPN1 and tumor mutation burden (TMB) and microsatellite instability (MSI) across different cancer types was analyzed using the Spearman correlation coefficient. The relationship between RPN1 and immune cell infiltration was analyzed using the Timer2.0 database, whereas variations in drug sensitivity were explored using the CellMiner database. Receiver operating characteristic curves validated RPN1's diagnostic potential in glioma, and its correlation with immune checkpoint inhibitors (ICIs) was assessed using Spearman's correlation coefficient. Single-sample gene set enrichment analysis elucidated a link between RPN1 and immune cells and pathways. In addition, a nomogram based on RPN1 was developed to predict patient prognosis. The functional impact of RPN1 on glioma cells was confirmed using scratch and Transwell assays.

Result

RPN1 was aberrantly expressed in various cancers and affected patient prognosis. The main mutation type of RPN1 in the cancer was amplified. RPN1 exhibited a positive correlation with myeloid-derived suppressor cells, neutrophils, and macrophages, and a negative correlation with CD8+ T cells and hematopoietic stem cells. RPN1 expression was associated with TMB and MSI in various cancers. The expression of RPN1 affected drug sensitivity in cancer cells. RPN1 was positively correlated with multiple ICIs in gliomas. RPN1 also affected immune cell infiltration into the tumor microenvironment. RPN1 was an independent prognostic factor for gliomas, and the nomogram demonstrated excellent predictive performance. Interference with RPN1 expression reduces the migratory and invasive ability of glioma cells.

Conclusion

RPN1 exerts multifaceted effects on different stages of cancer, including immune infiltration, prognosis, and treatment outcomes. RPN1 expression affects the prognosis and immune microenvironment infiltration in patients with glioma, making RPN1 a potential target for the treatment of glioma.

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.

Disulfidptosis, A Novel Cell Death Pathway: Molecular Landscape and Therapeutic Implications

Programmed cell death is pivotal for several physiological processes, including immune defense. Further, it has been implicated in the pathogenesis of developmental disorders and the onset of numerous diseases. Multiple modes of programmed cell death, including apoptosis, pyroptosis, necroptosis, and ferroptosis, have been identified, each with their own unique characteristics and biological implications. In February 2023, Liu Xiaoguang and his team discovered "disulfidptosis," a novel pathway of programmed cell death. Their findings demonstrated that disulfidptosis is triggered in glucose-starved cells exhibiting high expression of a protein called SLC7A11. Furthermore, disulfidptosis is marked by a drastic imbalance in the NADPH/NADP+ ratio and the abnormal accumulation of disulfides like cystine. These changes ultimately lead to the destabilization of the F-actin network, causing cell death. Given that high SLC7A11 expression is a key feature of certain cancers, these findings indicate that disulfidptosis could serve as the basis of innovative anti-cancer therapies. Hence, this review delves into the discovery of disulfidptosis, its underlying molecular mechanisms and metabolic regulation, and its prospective applications in disease treatment.

Disulfidptosis decoded: a journey through cell death mysteries, regulatory networks, disease paradigms and future directions

Cell death is an important part of the life cycle, serving as a foundation for both the orderly development and the maintenance of physiological equilibrium within organisms. This process is fundamental, as it eliminates senescent, impaired, or aberrant cells while also promoting tissue regeneration and immunological responses. A novel paradigm of programmed cell death, known as disulfidptosis, has recently emerged in the scientific circle. Disulfidptosis is defined as the accumulation of cystine by cancer cells with high expression of the solute carrier family 7 member 11 (SLC7A11) during glucose starvation. This accumulation causes extensive disulfide linkages between F-actins, resulting in their contraction and subsequent detachment from the cellular membrane, triggering cellular death. The RAC1-WRC axis is involved in this phenomenon. Disulfidptosis sparked growing interest due to its potential applications in a variety of pathologies, particularly oncology, neurodegenerative disorders, and metabolic anomalies. Nonetheless, the complexities of its regulatory pathways remain elusive, and its precise molecular targets have yet to be definitively identified. This manuscript aims to meticulously dissect the historical evolution, molecular underpinnings, regulatory frameworks, and potential implications of disulfidptosis in various disease contexts, illuminating its promise as a groundbreaking therapeutic pathway and target.

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.

Unlocking the future of hepatocellular carcinoma treatment: A comprehensive analysis of disulfidptosis-related lncRNAs for prognosis and drug screening

Background

The disulfide stress-induced cell death known as disulfidptosis is characterized by the disintegration of cytoskeletal proteins and F-actin as a result of an excessive buildup of disulfides within the cell. The relationship between disulfidptosis-associated long non-coding RNA (lncRNA) in hepatocellular carcinoma (HCC) progression is still not clearly understood. In this article, we aim to explore the crucial role of lncRNA in HCC.

Methods

We initially obtained lncRNA related to HCC and clinical data from TCGA. The genes associated with disulfidptosis were identified through co-expression analysis, Cox regression, and Lasso regression. Additionally, we established a prognostic model for verification.

Results

The risk model constructed with disulfidptosis-related lncRNA has been confirmed to be a good predictor of high and low-risk groups of HCC patients through survival curves, independent prognostic analysis, concordance index (C-index), ROC curves, and Kaplan-Meier plots. We also discovered differences in the response to immune targets and anticancer drugs between the two groups of patients, with GDC0810, Osimertinib, Paclitaxel, and YK-4-279 being more effective for patients in the high-risk group.

Conclusion

In conclusion, we have developed a risk model that can guide future efforts to diagnose and treat HCC.

Prognosis and chemotherapy drug sensitivity in liver hepatocellular carcinoma through a disulfidptosis-related lncRNA signature

Disulfidptosis, a new type of regulated cell death associated with the actin cytoskeleton, provides a new therapeutic tool for cancers. The direct relationship between disulfidptosis-related lncRNAs(DRLs) in liver hepatocellular carcinoma(HCC) remains unclear. We acquired transcriptomic data, corresponding clinical data, and tumor mutation data of HCC from the TCGA database. First of all, DRLs were determined through correlation analysis. Then, a prognostic model containing six DRLs was created by adopting univariate Cox regression, LASSO algorithm and multivariate Cox regression analysis. Based on the model, 424 HCC patients were divided into high- and low-risk groups. Next, we structured ROC curves and PCA through combining the model and clinical data. Enrichment analysis and immune infiltration analysis were adopted to further explore the relationship between the model and prognosis. In addition, we explored the relationship between the model and tumor mutation burden (TMB). There were significant differences between high- and low- risk groups, and patients in the high-risk group showed poor prognosis. Enrichment analysis suggested that metabolic progress was obviously different between the two groups. According to the analysis of immune infiltration, there were several differences in immune cells, function, and checkpoints. Patients with high-risk and high TMB demonstrated the least favorable prognosis. The two risk groups both manifested visiblly in chemotherapy drug sensitivity. To sum up, we set up a DRL-based signature and that may provide a predictable value for the prognosis and use of chemotherapy drugs for HCC patients.

Design, synthesis and anti-necroptosis activity of fused heterocyclic MLKL inhibitors

Necroptosis is an important form of programmed cell death (PCD), which is mediated by a death receptor and independent of the caspase proteolytic enzyme. Mixed lineage kinase domain-like (MLKL) is the final effector of necroptosis, playing an irreplaceable role in the execution of necroptosis. However, the studies on MLKL inhibitors are in their infancy. Necrosulfonamide (NSA) is an early-discovered covalent MLKL inhibitor, possessing medium anti-necroptosis activity and a structure-activity relationship (SAR) not widely disclosed. In this study, with the covalent motif maintained, we aim to improve the activity by introducing the terminal fused heterocycles and meanwhile revealing the SAR on the part. As a result, compounds 9 and 14 showed the best activity (EC50 = 148.4 and 595.9 nM) against necroptosis among the analogues by covalently binding to MLKL. The SAR was also concluded to guide further structural optimization in this field.

Identification of a disulfidptosis-related lncRNA signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma

PURPOSE

Disulfidptosis, a newly identified form of cell death, is triggered by disulfide stress. Herein, a unique signature was developed based on disulfidptosis-related lncRNAs (DRlncRNAs) for the prognostic and immune landscape prediction of head and neck squamous cell carcinoma (HNSCC).

METHODS

Transcriptome, somatic mutation, and clinical data were acquired at The Cancer Genome Atlas database. Individuals were partitioned into training and test cohorts at a 1:1 ratio to facilitate the development of a DRlncRNA signature using the least absolute shrinkage and selection operation method. Based on the median risk score, all HNSCC individuals were stratified into the high-risk group (HRG) and low-risk group (LRG). Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were used to estimate the prognostic value, and a nomogram was generated for survival prediction. To provide a more comprehensive assessment, the tumor microenvironment, functional enrichment, immune cell infiltration, and immunotherapeutic sensitivity were explored between LRG and HRG.

RESULTS

A DRlncRNA signature was established with 10 DRlncRNAs. The corresponding values of areas under the ROC curves for 1-, 3-, and 5-year overall survival were 0.710, 0.692, and 0.640. A more favorable prognosis was noted in the patients with lower risk, along with higher immune scores, increased immune-related functions, and immune cell infiltration, as well as improved response to the immunotherapeutic intervention in comparison with individuals at higher risk.

CONCLUSION

These findings demonstrate that the developed DRlncRNA signature holds promise as a reliable prognostic marker and predictor of immunotherapy response in HNSCC patients.

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.

Creation of signatures and identification of molecular subtypes based on disulfidptosis-related genes for glioblastoma patients' prognosis and immunological activity

BACKGROUND

In recent times, disulfidptosis, an intricate form of cellular demise, has garnered attention due to its impact on prognosis, tumor progression and treatment response. Nevertheless, the exact significance of disulfidptosis-related genes (DisRGs) in glioblastoma (GBM) remains enigmatic.

METHODS

The GEO and TCGA databases provided transcriptional and clinically relevant data on tumor samples, while the GTEx database provided data on healthy tissues. Disulfidptosis-related genes (DisRGs) were procured from previous scholarly investigations. The expression profile of DisRGs was initially scrutinized among patients diagnosed with GBM, subsequent to which their prognostic value was explored. Through consensus clustering, we constructed DisRGs-related clusters and gene subtypes. Our results established that the DisRG-related clusters had differentially expressed genes, resulting in a DisulfidptosisScore model, which had a positive prognostic value.

RESULTS

The differential expression profile of 24 DisRGs between GBM samples and healthy samples was acquired. Through consensus cluster analysis, two distinct disulfidptosis subtypes, namely DisRGcluster A and DisRGcluster B, were identified. Then, the DisulfidptosisScore model including 4 characteristic genes was constructed.Notably, patients with GBM assigned with lower score demonstrated a considerably longer overall survival (OS) compared to those with higher score.

CONCLUSION

We have effectively devised a prognostic model associated with disulfidptosis, presenting autonomous prognostic predictions for patients with GBM. These findings serve as a valuable addition to the current comprehension of disulfidptosis and offer fresh theoretical substantiation for the development of enhanced treatment strategies.

CA9, CYFIP2 and LGALS3BP-A Novel Biomarker Panel to Aid Prognostication in Glioma

Brain cancer is a devastating and life-changing disease. Biomarkers are becoming increasingly important in addressing clinical issues, including in monitoring tumour progression and assessing survival and treatment response. The goal of this study was to identify prognostic biomarkers associated with glioma progression. Discovery proteomic analysis was performed on a small cohort of astrocytomas that were diagnosed as low-grade and recurred at a higher grade. Six proteins were chosen to be validated further in a larger cohort. Three proteins, CA9, CYFIP2, and LGALS3BP, were found to be associated with glioma progression and, in univariate analysis, could be used as prognostic markers. However, according to the results of multivariate analysis, these did not remain significant. These three proteins were then combined into a three-protein panel. This panel had a specificity and sensitivity of 0.7459 for distinguishing between long and short survival. In silico data confirmed the prognostic significance of this panel.

Multi-omics analysis of disulfidptosis regulators and therapeutic potential reveals glycogen synthase 1 as a disulfidptosis triggering target for triple-negative breast cancer

Disruption of disulfide homeostasis during biological processes can have fatal consequences. Excess disulfides induce cell death in a novel manner, termed as "disulfidptosis." However, the specific mechanism of disulfidptosis has not yet been elucidated. To determine the cancer types sensitive to disulfidptosis and outline the corresponding treatment strategies, we firstly investigated the crucial functions of disulfidptosis regulators pan-cancer at multi-omics levels. We found that different tumor types expressed dysregulated levels of disulfidptosis regulators, most of which had an impact on tumor prognosis. Moreover, we calculated the disulfidptosis activity score in tumors and validated it using multiple independent datasets. Additionally, we found that disulfidptosis activity was correlated with classic biological processes and pathways in various cancers. Disulfidptosis activity was also associated with tumor immune characteristics and could predict immunotherapy outcomes. Notably, the disulfidptosis regulator, glycogen synthase 1 (GYS1), was identified as a promising target for triple-negative breast cancer and validated via in vitro and in vivo experiments. In conclusion, our study elucidated the complex molecular phenotypes and clinicopathological correlations of disulfidptosis regulators in tumors, laying a solid foundation for the development of disulfidptosis-targeting strategies for cancer treatment.

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.

Identifying molecular subtypes and tumor microenvironment infiltration signatures in kidney renal clear cell carcinoma based on stemness-associated disulfidptosis genes by integrating machine learning, single-cell analyses and experimental validation

Clear cell renal cell carcinoma (ccRCC) is an aggressive malignant tumor. Disulfidptosis is a new programmed cell death mechanism, which is characterized by the abnormal accumulation of intracellular disulfides that are highly toxic to cells. However, the contribution of disulfidptosis to ccRCC progression has not been fully clarified. In this study, two different molecular subtypes related to disulfidptosis were identified in ccRCC patients by the non-negative matrix factorization (NMF) algorithm. The cluster 1 was characterized by a worse prognosis and higher mRNAsi levels. Then, difference analysis and weighted gene co-expression network analysis (WGCNA) were conducted to search modular genes that are highly associated with tumor stemness and tumor microenvironment. Subsequently, a SADG signature containing nine genes was constructed stepwise by WGCNA and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The high-risk score group had a worse outcome, and immune regulation and metabolic signatures might be responsible for cancer progression in the high-risk group. After that, a predictive nomogram was constructed, and the predicting power of the risk model was verified using inter and three independent external validation datasets. Nine SADGs were shown to significantly correlate with immune infiltration, tumor mutation burden (TMB), microsatellite instability (MSI) and immune checkpoint. In addition, based on the single-cell RNA sequencing dataset (GSE139555), the distribution and expression of nine hub genes in various types of immune cells were analyzed. Finally, the expression level of the nine genes was verified in clinical samples by qRT-PCR.

The development of prognostic gene markers associated with disulfidptosis in gastric cancer and their application in predicting drug response

Background

Gastric cancer (GC) is a malignancy known for its high fatality rate. Disulfidptosis, a potentially innovative therapeutic strategy for cancer treatment, has been proposed. Nevertheless, the specific involvement of disulfidptosis in the context of GC remains uncertain.

Methods

The mRNA expression profiles were obtained from the TCGA and GEO databases. Univariate and LASSO Cox regression analyses were employed to identify differentially expressed genes and develop a risk model for disulfidptosis-related genes. The performance of the model was evaluated using Kaplan-Meier curve, ROC curve, and nomogram. Univariate and multivariate Cox regression analyses were conducted to determine if the risk model could serve as an independent prognostic factor. The biological function of the identified genes was assessed through GO, KEGG, and GSEA analyses. The prediction of drug response was conducted employing the package "pRRophetic". Furthermore, gene expression was determined using qRT-PCR.

Results

An eight-gene signature were identified and utilized to categorize patients into low- and high-risk groups. Survival, receiver operating characteristic (ROC) curve, and Cox analyses provided clarification that these eight hub genes served as a favorable independent prognostic factor for patients with GC. A nomogram was constructed by integrating clinical parameters with the risk signatures, demonstrating high precision in predicting 1-, 3-, and 5-year survival rates. Additionally, drug sensitivity was different in the high-risk and low-risk groups, and the expression of three genes was verified by qRT-PCR.

Conclusion

The prognostic risk model developed in this study demonstrates the potential to accurately forecast the prognosis of patients with GC.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment for LUAD patients.

Disulfidptosis characterizes the tumor microenvironment and predicts immunotherapy sensitivity and prognosis in bladder cancer

Background

Bladder cancer (BLCA) is prone to metastasis and has poor prognosis with unsatisfactory treatment responsiveness. Disulfidptosis is a recently discovered, novel mode of cell death that is closely associated with human cancers. However, a comprehensive analysis of the relationship between disulfidptosis and BLCA is lacking. Therefore, this study aimed to explore the potential effect of disulfidptosis on BLCA and identify a biomarker for evaluating the prognosis and immunotherapy of patients with BLCA.

Material and methods

We acquired BLCA RNA sequencing data from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) cohort (containing 19 normal samples and 409 tumor samples) and the GES39281 cohort (containing 94 tumor samples) which were used for external validation of the signature. Initially, we performed unsupervised consensus clustering to explore disulfidptosis-related subgroups. We then conducted functional enrichment analysis on these subgroups to gain insights into their biological significance and evaluate their immunotherapy response and chemotherapy sensitivity. Next, we conducted Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression to construct a prognostic signature in the TCGA training set for prognosis-related differentially expressed genes (DEGs) in the disulfidptosis-related subgroups. Subsequently, we used a receiver operating characteristic (ROC) curve and independent prognostic analysis to validate the predictive performance of the signature in the TCGA testing and the GES39281 cohorts. Finally, we explored the therapeutic value of this signature in patients with BLCA, in terms of immunotherapy and chemotherapy.

Result

In this study, we obtained two subgroups: DRG-high (238 samples) and DRG-low (160 samples). The DRG-high group exhibited a poor survival rate compared to the DRG-low group and had a significant association with tumor grade, stage, and metastasis. Additionally, several pathways related to cancer and the immune system were enriched in the high-DRG group. Moreover, the DRG-high group exhibited higher expression of PD1 and CTLA4 and had a better response to immunotherapy in patients with both PD1 and CTLA4 positivity. Conversely, the DRG-high group was more sensitive to common chemotherapeutic agents. A prognostic signature was created, consisting of COL5A1, DIRAS3, NKG7, and POLR3G and validated as having a robust predictive capability. Patients in the low-risk-score group had more immune cells associated with tumor suppression and better immunotherapy outcomes.

Conclusion

This study contributes to our understanding of the characteristics of disulfidptosis-related subgroups in BLCA. Disulfidptosis-related signatures can be used to assess the prognosis and immunotherapy of patients with BLCA.

Identification and analysis of diverse cell death patterns in diabetic kidney disease using microarray-based transcriptome profiling and single-nucleus RNA sequencing

BACKGROUND

Diabetic kidney disease (DKD) is the most lethal complication of diabetes. Diverse programmed cell death (PCD) has emerged as a crucial disease phenotype that has the potential to serve as an indicator of renal function decline and can be used as a target for researching drugs for DKD.

METHODS

Microarray-based transcriptome profiling and single-nucleus transcriptome sequencing (snRNA-seq) related to DKD were retrieved from the Gene Expression Omnibus (GEO) database. 13 PCD-related genes (including alkaliptosis, apoptosis, autophagy-dependent cell death, cuproptosis, disulfidptosis, entotic cell death, ferroptosis, lysosome-dependent cell death, necroptosis, netotic cell death, oxeiptosis, parthanatos, and pyroptosis) were obtained from various public databases and reviews. The gene set variation analysis (GSVA) analysis was used to explore the pathway activity of these 13 PCDs in DKD, and the pathway activity of these PCDs in different renal cells was studied based on DKD-related snRNA-seq data. To identify the core PCDs that play a significant role in DKD, we analyzed the relationships between different types of PCD and immune infiltration, fibrosis-related gene expression levels, glomerular filtration rate (GFR), and diagnostic efficiency in DKD. Using the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm, we screened for core death genes among the core PCDs and constructed a cell death-related signature (CDS) risk score based on the Least Absolute Shrinkage and Selection Operator (LASSO). Finally, we validated the predictive performance of the CDS risk score in an independent validation set.

RESULTS

We identified 4 core PCD pathways, namely entotic cell death, apoptosis, necroptosis, and pyroptosis in DKD, and further applied the WGCNA algorithm to screen 4 core death genes (CASP1, CYBB, PLA2G4A, and CTSS) and constructed a CDS risk score based on these genes. The CDS risk score demonstrated high diagnostic efficiency for DKD patients, and those with higher scores had higher levels of immune cell infiltration and poorer GFR.

CONCLUSION

Our study sheds light on the fact that multiple PCDs contribute to the progression of DKD, highlighting potential therapeutic targets for treating this disease.

Disulfidptosis status influences prognosis and therapeutic response in clear cell renal cell carcinoma

Disulfidptosis is a recently identified type of programmed cell death. It is characterized by aberrant accumulation of intracellular disulfides. The clinical implications of disulfidptosis in clear cell renal cell carcinoma (ccRCC) remain unclear. A series of bioinformatics approaches were employed to analyze ten disulfidptosis-related molecules. Firstly, the expression patterns of the disulfidptosis-related molecules were different between normal and ccRCC tissues. A comprehensive cohort of patients with ccRCC was then assembled from three public databases and subjected to cluster analysis based on disulfidptosis-related molecules. Consensus cluster analysis revealed three distinct disulfidptosis clusters. We then conducted weighted gene co-expression network analysis (WGCNA) to identify highly correlated genes. 267 hub genes were screened out through WGCNA, and three gene clusters were then determined. Finally, we identified 87 genes with prognostic value and then used them to develop a disulfidptosis scoring (DSscore) system, which was proven to independently predict survival in ccRCC. Patients in the high-DSscore group exhibited a significant survival advantage and better immunotherapeutic responses compared with those in the low-DSscore group. However, the patients in the low-DSscore group exhibited a greater degree of chemotherapeutic response. In addition, the expression of disulfidptosis-related molecules was validated by qRT-PCR, and the potential of disulfidptosis-related molecules to indicate distinct cell subtypes were validated by single-cell RNA-sequencing. In conclusion, DSscore is a promising index for predicting the prognosis and efficacy of immunotherapy in patients with ccRCC and may provide a basis for novel strategies for future studies.

A disulfidptosis-related lncRNAs signature in hepatocellular carcinoma: prognostic prediction, tumor immune microenvironment and drug susceptibility

Disulfidptosis, a novel type of programmed cell death, has attracted researchers' attention worldwide. However, the role of disulfidptosis-related lncRNAs (DRLs) in liver hepatocellular carcinoma (LIHC) not yet been studied. We aimed to establish and validate a prognostic signature of DRLs and analyze tumor microenvironment (TME) and drug susceptibility in LIHC patients. RNA sequencing data, mutation data, and clinical data were obtained from the Cancer Genome Atlas Database (TCGA). Lasso algorithm and cox regression analysis were performed to identify a prognostic DRLs signature. Kaplan-Meier curves, principal component analysis (PCA), nomogram and calibration curve, function enrichment, TME, immune dysfunction and exclusion (TIDE), tumor mutation burden (TMB), and drug sensitivity analyses were analyzed. External datasets were used to validate the predictive value of DRLs. qRT-PCR was also used to validate the differential expression of the target lncRNAs in tissue samples and cell lines. We established a prognostic signature for the DRLs (MKLN1-AS and TMCC1-AS1) in LIHC. The signature could divide the LIHC patients into low- and high-risk groups, with the high-risk subgroup associated with a worse prognosis. We observed discrepancies in tumor-infiltrating immune cells, immune function, function enrichment, and TIDE between two risk groups. LIHC patients in the high-risk group were more sensitive to several chemotherapeutic drugs. External datasets, clinical tissue, and cell lines confirmed the expression of MKLN1-AS and TMCC1-AS1 were upregulated in LIHC and associated with a worse prognosis. The novel signature based on the two DRLs provide new insight into LIHC prognostic prediction, TME, and potential therapeutic strategies.

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.

Prognostic and immune infiltration features of disulfidptosis-related subtypes in breast cancer

Breast cancer (BC) is a prominent cause of cancer incidence and mortality around the world. Disulfidptosis, a type of cell death, can induce tumor cell death. The purpose of this study was to analyze the potential impact of disulfidptosis-related genes (DRGs) on the prognosis and immune infiltration features of BC. Based on DRGs, we conducted an unsupervised clustering analysis on gene expression data of BC in TCGA-BRCA dataset and identified two BC subtypes, cluster1 and cluster2, with cluster1 showing a higher likelihood of favorable survival. Through immune analysis, we found that cluster1 had lower proportions of infiltration in immune-related cells, including aDCs, DCs, NK_cells, Th2_cells, and Treg. Based on the immunophenoscore (IPS) results, we inferred that cluster1 might benefit more from immune checkpoint inhibitors targeting CTLA-4 and PD1. Targeted small molecule prediction results showed that patients with cluster2 BC might respond better to antagonistic small molecule compounds, including clofazimine, lenalidomide, and epigallocatechin. Differentially expressed genes between the two subtypes were found to be enriched in signaling pathways related to steroid hormone biosynthesis, ovarian steroidogenesis, and neutrophil extracellular trap formation, according to enrichment analyses. In conclusion, this study identified BC subtypes based on DRGs so as to help predict patient prognosis and provide valuable tools for guiding clinical management and precise treatment of BC patients.

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.

Disulfidptosis-Associated lncRNAs are Potential Biomarkers for Predicting Immune Response and Prognosis Within Individuals Diagnosed with Hepatocellular Carcinoma

Purpose

Hepatocellular carcinoma (HCC) is a prevalent form of cancer that is distributed globally. Disulfidptosis, characterized by the fragility of the actin cytoskeleton, represents a distinct type of cell death and holds promise for novel cancer therapies. Nevertheless, the connection among disulfidptosis-associated long non-coding RNAs (lncRNAs) and HCC is still unexplored. This study uses an in silico approach to provide the novel biomarkers of disulfidptosis-associated lncRNAs for predicting the immune response and prognosis with HCC.

Methods

In order to address this gap, we integrated transcriptomic data of HCC from The Cancer Genome Atlas (TCGA) and identified genes that exhibit differential expression with disulfidptosis and lncRNAs. Through co-expression analysis, we identified disulfidptosis-related lncRNAs. Afterwards, by employing univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO), a model for disulfidptosis-associated lncRNA was constructed. The risk model underwent assessment through the utilization of diverse analytical methodologies, including functional enrichment annotation, Kaplan-Meier analysis, principal component analysis (PCA), immune infiltration and immune status analysis, as well as tumor mutation analysis. Furthermore, we discussed the implications of the model in predicting drug sensitivity.

Results

Our study culminated in the construction of a disulfidptosis-related lncRNA model comprising four prognostic disulfidptosis-related lncRNAs (ACYTOR, NRAV, AL080248.1, and AC069307.1). This model demonstrates exceptional diagnostic value for HCC patients and holds practical implications for guiding clinicians in personalizing immunotherapy and drug selection based on individual variations.

Conclusion

In summary, our research introduces a novel predictive tool utilizing disulfidptosis-related lncRNAs, offering potential guidance for the therapeutic management of HCC.

Constructed Risk Prognosis Model Associated with Disulfidptosis lncRNAs in HCC

Disulfidptosis is a novel cell death mode in which the accumulation of disulfide bonds in tumor cells leads to cell disintegration and death. Long-stranded noncoding RNAs (LncRNAs) are aberrantly expressed in hepatocellular carcinoma (HCC) and have been reported to carry significant potential as a biomarker for HCC prognosis. However, lncRNA studies with disulfidptosis in hepatocellular carcinoma have rarely been reported. Therefore, this study aimed to construct a risk prognostic model based on the disulfidptosis-related lncRNA and investigate the mechanisms associated with disulfidptosis in hepatocellular carcinoma. The clinical and transcriptional information of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA) and divided into test and validation sets. Furthermore, 1668 lncRNAs associated with disulfidptosis were identified using Pearson correlation. Six lncRNA constructs were finally identified for the risk prognostic model using one-way Cox proportional hazards (COX), multifactorial COX, and lasso regression. Kaplan-Meier (KM) analysis, principal component analysis, receiver operating characteristic curve (ROC), C-index, and column-line plot results confirmed that the constructed model was an independent prognostic factor. Based on the disulfidptosis risk score, risk groups were identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. Finally, we confirmed that phospholipase B domain containing 1 antisense RNA 1 (PLBD1-AS1) and muskelin 1 antisense RNA (MKLN1-AS) were highly expressed in hepatocellular carcinoma and might be potential biomarkers in HCC by KM analysis and quantitative real-time PCR (RT-qPCR). This study demonstrated that lncRNA related to disulfidptosis could serve as a biomarker to predict prognosis and treatment targets for HCC.

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.

Construction of disulfidptosis-related lncRNA signature for predicting the prognosis and immune escape in colon adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most frequent types of cancer worldwide. Disulfidptosis has been identified as a new mode of cell death recently. The goal of this study was to explore the possibility of a connection between disulfidptosis and COAD. RNA sequencing data from COAD patients were retrieved from the The Cancer Genome Atlas (TCGA) database for this investigation. R software and various methods were used to identify disulfidptosis-related lncRNAs (DRLs) in COAD, and a prognostic model was created based on 6 DRLs (AP003555.1, AL683813.1, SNHG7, ZEB1-AS1, AC074212.1, RPL37A-DT). The prognostic model demonstrated a good accuracy in predicting the prognosis of COAD patients, according to receiver operating characteristic (ROC) curve and Concordance index (C-index) analyses. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed significant differences in biological functions and signaling pathways involved in differential genes in risk subgroups, including protein - DNA complex subunit organization, Hippo signaling pathway, Wnt signaling pathway. TIDE analysis was done on risk groupings in this study, and it found that patients in the high-risk group had more immune escape potential and were less probable to react to immunotherapy. Real-time quantitative pcr (qRT-PCR) was used to identify the relatively high expression of 6 DRLs in colon cancer cell lines. In summary, 6 DRLs were identified as possible novel molecular therapy targets for COAD in this investigation. This prognostic model has the potential to be a novel tool for forecasting COAD prognosis in clinical practice, as well as providing new insights on the potential function and mechanism of disulfidptosis in the COAD process.