Disulfidptosis: disulfide stress-induced cell death

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.

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.

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.

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.

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.

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.

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.