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BACKGROUND: Ischemic stroke (IS) is a severe neurological disorder with a pathogenesis that remains incompletely understood. Recently, a novel form of cell death known as disulfidptosis has garnered significant attention in the field of ischemic stroke research. This study aims to investigate the mechanistic roles of disulfidptosis-related genes (DRGs) in the context of IS and to examine their correlation with immunopathological features. METHODS: To enhance our understanding of the mechanistic underpinnings of disulfidptosis in IS, we initially retrieved the expression profile of peripheral blood from human IS patients from the GEO database. We then utilized a suite of machine learning algorithms, including LASSO, random forest, and SVM-RFE, to identify and validate pivotal genes. Furthermore, we developed a predictive nomogram model, integrating multifactorial logistic regression analysis and calibration curves, to evaluate the risk of IS. For the analysis of single-cell sequencing data, we employed a range of analytical tools, such as "Monocle" and "CellChat," to assess the status of immune cell infiltration and to characterize intercellular communication networks. Additionally, we utilized an oxygen-glucose deprivation (OGD) model to investigate the effects of SLC7A11 overexpression on microglial polarization. RESULTS: This study successfully identified key genes associated with disulfidptosis and developed a reliable nomogram model using machine learning algorithms to predict the risk of ischemic stroke. Examination of single-cell sequencing data showed a robust correlation between disulfidptosis levels and the infiltration of immune cells. Furthermore, "CellChat" analysis elucidated the intricate characteristics of intercellular communication networks. Notably, the TNF signaling pathway was found to be intimately linked with the disulfidptosis signature in ischemic stroke. In an intriguing finding, the OGD model demonstrated that SLC7A11 expression suppresses M1 polarization while promoting M2 polarization in microglia. CONCLUSION: The significance of our findings lies in their potential to shed light on the pathogenesis of ischemic stroke, particularly by underscoring the pivotal role of disulfidptosis-related genes (DRGs). These insights could pave the way for novel therapeutic strategies targeting DRGs to mitigate the impact of ischemic stroke.

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Background: Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown. Methods: In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified. Results: We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy. Conclusion: This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

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Background: Disulfidptosis regulate various biological processes in cancer. However, there is limited research on the genes related to disulfidptosis in predicting the prognosis of hepatocellular carcinoma (HCC). We aimed to develop a reliable disulfidptosis-related gene signature, which will characterize different HCC subtypes and predict their prognosis. Methods: The Cancer Genome Atlas (TCGA)-HCC dataset, comprising RNA sequencing data and clinical information, was obtained from the TCGA database. The crucial disulfidptosis-related genes were selected for bioinformatic analysis in HCC. HCC tumor classification was established through a consistent cluster analysis. The prognosis and immune-cell infiltration were investigated in association with a disulfidptosis-related HCC model. Results: In TCGA-HCC patients, a total of 3,621 prognostic genes and 30 key prognostic disulfidptosis-related genes were identified. Using key prognostic disulfidptosis-related genes, TCGA-HCC patients were categorized into low- and high-risk clusters. The upregulated differentially expressed genes (DEGs) in high-risk cluster 1 (C1) could significantly impact cell cycle, DNA replication, and the p53 signaling pathway, whereas the pathways associated with the downregulated DEGs in high-risk C1 could significantly impact metabolism of xenobiotics by cytochrome P450, the PPAR signaling pathway, and tyrosine metabolism. Furthermore, the immune activity of the high-risk C1 group was different to that of the low-risk cluster 2 (C2) group. The 13 disulfidptosis-related genes were finally screened using least absolute shrinkage and selection operator (LASSO) regression analysis, including ANP32E, BOP1, RPN1, SLC7A11, PPIH, PCBP2, ME1, PRDX1, FLNC, INF2, MYH11, LRPPRC, and HNRNPM. Conclusions: The genes related to disulfidptosis are closely associated with tumor classification and immunity in patients with HCC. This is the first gene signature related to disulfidptosis demonstrated a strong predictive performance for the prognosis of HCC, which provide new perspectives for the diagnosis and treatment of HCC.

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

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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.

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Background: Ferroptosis and disulfidptosis are regulatory forms of cell death that play an important role in tumorigenesis and progression. However, few biomarkers about disulfidptosis and ferroptosis related genes (DFRGs) have been developed to predict the prognosis of bladder cancer (BC). Methods: We conducted a bioinformatics analysis using public BC datasets to examine the prognostic significance of differentially expressed DFRGs. A Lasso regression was employed to create a prognostic prediction model from these DFRGs. Hub DFRGs that play a role in immunotherapy response and immunoregulation were pinpointed. Immunohistochemistry (IHC) experiment was performed to assess NUBPL and c-MYC expression in BC patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy at Peking University Cancer Hospital. Results: We constructed a valid model to predict the prognosis of BC based on DFRGs and performed relevant validation, the results demonstrated that the model was an independent prognostic factor for BC. Further analysis indicated that the model score, combined with the expression of various immune factors and tumor mutation burden (TMB), could predict the prognosis for BC. In addition, we also found that NUBPL was strongly associated with prognosis and response to ICI treatment, and NUBPL may influence BC malignant progression through the c-MYC pathway. Conclusions: Our research findings highlight the satisfactory predictive value of DFRGs in the immune microenvironment and suggest that NUBPL may be a highly promising biomarker for predicting the prognosis and efficacy of ICI treatment in BC patients.

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BACKGROUND: Limited supply of certain nutrients and deregulation of nucleus pulposus (NP) plays a key role in the pathogenesis of intervertebral disc degeneration (IVDD). However, whether nutrient deprivation-induced cell death, particularly disulfidptosis, contributes to the depletion of NP cells and the development of IVDD, is unknown. METHODS: RNA-seq, single-cell RNA-seq, and Genome-wide DNA methylation datasets of nucleus pulposus tissue were collected for bioinformatic analysis. Predictive models of disulfidptosis related genes in IVDD were constructed by machine learning and their differential expression was analyzed. In addition, we performed cell subsets identification analysis, cell-cell communications analysis, and functional enrichment analysis of key genes in the core subset based on single-cell RNA-seq data of NP tissues isolated from one normal sample and one IVDD sample. Finally, glucose deprivation-induced disulfidptosis in human NP cells (HNPCs) was verified by various cell death inhibitors and disulfidptosis-related molecular markers. RESULTS: We found the disulfidptosis signal was significantly activated in the IVDD group. Using single-cell RNA-seq analysis, we focused on the chondrocytes and found that disulfidptosis-related genes significantly highly expressed in the IVDD C4 chondrocyte subset, which was identified as a new disulfidptosis-associated cell subset. Correlation analysis revealed the negative correlation between SLC7A11 (driving gene of disulfidptosis) and the glucose transporter GLUTs (SLC2A1-4) family genes (suppressing genes of disulfidptosis) in the IVDD group. We also found obvious cell death in HNPC upon glucose starvation, while employment of various cell death inhibitors could not inhibit glucose starvation-induced death in HNPCs. Moreover, the accumulation of disulfide bonds in cytoskeletal proteins was indicated by slowed migration in non-reducible protein blotting experiments. 2-DG, a key disulfidptosis inhibitor, significantly rescued cell death caused by glucose starvation through lowering the NADP+/NADPH ratio. CONCLUSIONS: We validated the occurrence of disulfidptosis in HPNCs and identified a novel disulfidptosis-associated cell subset, followed by experimental verification of disulfidptosis in a glucose-limited context to mimic a fall in nutrient supply during the development disc degeneration. These findings provided new insights into the pathological mechanisms of IVDD and encourage us to explore potential therapeutic targets involved in the regulation of disulfidptosis for the prevention of intervertebral disc degeneration.

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Background: Sepsis-induced acute lung injury (ALI) is a common and serious complication of sepsis that eventually progresses to life-threatening hypoxemia. Disulfidptosis is a newly discovered type of cell death associated with the pathogenesis of different diseases. This study investigated the potential association between sepsis-induced acute lung injury and disulfidptosis by bioinformatics analysis. Methods: In order to identify differentially expressed genes (DEGs) linked to sepsis, we screened appropriate data sets from the GEO database and carried out differential analysis. The key genes shared by DEGs and 39 disulfidptosis-related genes were identified: ACSL4 and MYL6 mRNA levels of key genes were detected in different datasets. We then used a series of bioinformatics analysis techniques, such as immune cell infiltration analysis, protein-protein interaction (PPI) network, genetic regulatory network, and receiver operating characteristic (ROC), to investigate the possible relationship between key genes and sepsis. Then, experimental verification was obtained for changes in key genes in sepsis-induced acute lung injury. Finally, to investigate the relationship between genetic variants of MYL6 or ACSL4 and sepsis, Mendelian randomization (MR) analysis was applied. Results: Two key genes were found in this investigation: myosin light chain 6 (MYL6) and Acyl-CoA synthetase long-chain family member 4 (ACSL4). We verified increased mRNA levels of key genes in training datasets. Immune cell infiltration analysis showed that key genes were associated with multiple immune cell levels. Building the PPI network between MYL6 and ACSL4 allowed us to determine that their related genes had distinct biological functions. The co-expression genes of key genes were involved in different genetic regulatory networks. In addition, both the training and validation datasets confirmed the diagnostic capabilities of key genes by using ROC curves. Additionally, both in vivo and in vitro experiments confirmed that the mRNA levels of ACSL4 and MYL6 in sepsis-induced acute lung injury were consistent with the results of bioinformatics analysis. Finally, MR analysis revealed a causal relationship between MYL6 and sepsis. Conclusion: We have discovered and confirmed that the key genes ACSL4 and MYL6, which are linked to disulfidptosis in sepsis-induced acute lung injury, may be useful in the diagnosis and management of septic acute lung injury.

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This study explores the role of disulfidptosis in monocytes and its relation to postmenopausal osteoporosis (PMOP). Using single-cell RNA sequencing and microarray assays, we identified key genes: LONRF1, ACAP2, IPO9, and PGRMC2. Through differential analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and machine learning, these genes were linked to PMOP. Functional enrichment and ROC curve analysis demonstrated their effectiveness in distinguishing postmenopausal fracture patients from healthy individuals. Notably, PGRMC2 exhibited significant expression differences, highlighted by a notable Area Under the Curve (AUC) value of 0.665. Further investigation involved Western blotting and immunohistochemical assays, revealing decreased PGRMC2 expression in ovariectomized (OVX) mice. This decrease was consistent across both experimental methods, emphasizing PGRMC2's role in PMOP. Moreover, PGRMC2 was predominantly present in macrophages compared to monocytes within bone tissue and was significantly located in bone marrow mesenchymal stem cells (BM-MSCs) in PMOP patients. It was also abundantly found in osteoblasts and adipocytes. Additionally, a Mendelian randomization analysis using the TwoSampleMR R package, with data from decode and GWAS databases, was conducted. This analysis showed a significant impact of PGRMC2 on osteoporosis risk (p = 0.0048, OR = 0.6836), suggesting a potential protective effect against the disease. Our results suggest that PGRMC2 may facilitate the differentiation of monocytes into macrophages in bone tissue, influencing the behavior of BM-MSCs. This, in turn, could impact the progression and severity of PMOP. The study provides new insights into the molecular mechanisms underlying postmenopausal osteoporosis and highlights the potential of PGRMC2 as a therapeutic target or biomarker for this condition.

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BACKGROUND: Pancreatic adenocarcinoma (PAAD), known for its high lethality, has not been thoroughly explored in terms of its mechanisms and patterns of immune infiltration. Disulfidptosis, a newly identified mode of cell death, is likely associated with tumorigenesis and progression but remains poorly understood in PAAD at the genetic and mechanistic levels. METHODS: Sixteen PAAD samples from the GSE154778 scRNA-seq dataset were subjected to single-cell analysis. Disulfidptosis grouping and scores were established across various immune cell populations. Using the TCGA-PAAD database, LASSO regression was employed to construct prognostic markers linked to disulfidptosis. The performance of this model was assessed in both training and independent validation cohorts. Subsequent analyses explored the correlations between disulfidptosis scores, immune infiltration, and drug sensitivity. Cellular experiments further confirmed the significant positive relationship of the gene MET with disulfidptosis and its role in influencing the invasion and metastasis of PAAD. RESULTS: WGCNA identified Disulf-High and Disulf-Low as modules strongly correlated with disulfidptosis. Five prognostically significant genes were selected to construct prognostic models. Survival analysis demonstrated that the disulfidptosis-related biological model successfully achieved prognostic stratification in PAAD patients. Additionally, the disulfidptosis score was significantly correlated with both immune infiltration and drug sensitivity. Knockdown of the MET gene substantially inhibited cell multiplication and cell cycle progression in two PAAD cell lines, effects potentially induced by the activation of the PI3K/AKT signalling pathway in the tumour. CONCLUSION: Key genes associated with disulfidptosis significantly correlate with immune infiltration and the development of PAAD. Biomarkers based on disulfidptosis present potential avenues for novel therapies and clinical treatments in PAAD.

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

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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.

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Limited treatment options and poor prognosis present significant challenges in the treatment of lung squamous cell carcinoma (LUSC). Disulfidptosis impacts cancer progression and prognosis. We developed a prognostic signature using disulfidptosis-related long non-coding RNAs (lncRNAs) to predict the prognosis of LUSC patients. Gene expression matrices and clinical information for LUSC were downloaded from the TCGA database. Co-expression analysis identified 209 disulfidptosis-related lncRNAs. LASSO-Cox regression analysis identified nine key lncRNAs, forming the basis for establishing a prognostic model. The model's validity was confirmed by Kaplan-Meier and ROC curves. Cox regression analysis identified the risk score (RS) as an independent prognostic factor inversely correlated with overall survival. A nomogram based on the RS demonstrated good predictive performance for LUSC patient prognosis. The relationship between RS and immune function was explored using ESTIMATE, CIBERSORT, and ssGSEA algorithms. According to the TIDE database, a negative correlation was found between RS and immune therapy responsiveness. The GDSC database revealed that 49 drugs were beneficial for the low-risk group and 25 drugs for the high-risk group. Silencing C10orf55 expression in SW900 cells reduced invasiveness and migration potential. In summary, this lncRNA model based on TCGA-LUSC data effectively predicts prognosis and assists clinical decision-making.

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This study aims to investigate the role and prognostic significance of long non-coding RNAs (lncRNAs) associated with disulfidptosis in colon adenocarcinoma (COAD). The TCGA database's clinical data and transcriptome profiles were employed. Analysis of previous studies identified 10 disulfidptosis-related genes (DRGs). We used these genes to construct a signature that could independently and accurately predict the prognosis of patients with COAD. The Kaplan-Meier (K-M) curve analysis showed that the lower-risk group had a better prognosis. With the help of multivariate Cox regression analysis, the risk score produced from the patient's signature might independently predict the outcomes. Utilizing a nomogram, the receiver operating characteristic (ROC) curve, and principal component analysis (PCA), the signature's predictive ability was also confirmed. It's interesting to note that immunotherapy, especially PD-1 immune checkpoint suppression, was more likely to benefit low-risk patients. The IC50 levels for certain anticancer agents were lower in the high-risk group. Finally, qRT-PCR analyses in colon cancer cell lines revealed elevated levels of lncRNAs CASC9, ZEB1-AS1, ATP2A1-AS1, SNHG7, AL683813.1, and AP003555.1, and reduced levels of FAM160A1-DT and AC112220.2, compared to normal cell lines. This signature offers insights into prognosis, tumor microenvironment, and options for immunotherapy and antitumor drugs in patients with COAD.

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BACKGROUND: Disulfidptosis is a newly identified mechanism of cell death triggered by disulfide stress. Thus, gaining a comprehensive understanding of the disulfidptosis signature present in gastric cancer (GC) could greatly enhance the development of personalized treatment strategies for this disease. METHODS: We employed consensus clustering to identify various subtypes of disulfidptosis and examined the distinct tumor microenvironment (TME) associated with each subtype. The Disulfidptosis (Dis) score was used to quantify the subtype of disulfidptosis in each patient. Subsequently, we assessed the predictive value of Dis score in terms of GC prognosis and immune efficacy. Finally, we conducted in vitro experiments to explore the impact of Collagen X (COL10A1) on the progression of GC. RESULTS: Two disulfidptosis-associated molecular subtypes (Discluster A and B) were identified, each with distinct prognosis, tumor microenvironment (TME), immune cell infiltration, and biological pathways. Discluster A, characterized by high expression of disulfidptosis genes, exhibited a high immune score but poor prognosis. Furthermore, the Dis score proved useful in predicting the prognosis and immune response in GC patients. Those in the low Dis score group showed better prognosis and increased sensitivity to immunotherapy. Finally, our experimental findings validated that downregulation of COL10A1 expression attenuates the proliferation and migration capabilities of GC cells while promoting apoptosis. CONCLUSIONS: This study demonstrates that the disulfidptosis signature can assist in risk stratification and personalized treatment for patients with GC. The results offer valuable theoretical support for anti-tumor strategies.

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Objective: Ulcerative Colitis (UC) manifests as a chronic inflammatory condition of the intestines, marked by ongoing immune system dysregulation. Disulfidptosis, a newly identified cell death mechanism, is intimately linked to the onset and advancement of inflammation. However, the role of disulfidptosis in UC remains unclear. Methods: We screened differentially expressed genes (DEGs) associated with disulfidptosis in multiple UC datasets, narrowed down the target gene number using lasso regression, and conducted immune infiltration analysis and constructed a clinical diagnostic model. Additionally, we explored the association between disulfidptosis-related key genes and disease remission in UC patients receiving biologic therapy. Finally, we confirmed the expression of key genes in FHC cells and UC tissue samples. Results: In the differential analysis, we identified 20 DEGs associated with disulfidptosis. Immune infiltration results revealed that five genes (PDLIM1, SLC7A11, MYH10, NUBPL, OXSM) exhibited strong correlations with immune cells and pathways. Using GO, KEGG and WGCNA analyses, we discovered that gene modules highly correlated with disulfidptosis-related gene expression were significantly enriched in inflammation-related pathways. Additionally, we developed a nomogram based on these five immune-related disulfidptosis genes for UC diagnosis, showing robust diagnostic capability and clinical efficacy. Kaplan-Meier survival analysis revealed a significant link between changes in the expression levels of these cell genes and disease remission in UC patients receiving biologic therapy. In line with previous studies, similar expression changes of the target gene were seen in both UC cell models and tissue samples. Conclusions: This study utilized bioinformatic analysis and machine learning to identify and analyze features associated with disulfidptosis in multiple UC datasets. This enhances our comprehension of the role disulfidptosis plays in intestinal immunity and inflammation in UC, providing new perspectives for developing innovative treatments for UC.

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Background: Lung adenocarcinoma accounts for the majority of lung cancer cases and impact survival rate of patients severely. Immunotherapy is an effective treatment for lung adenocarcinoma but is restricted by many factors including immune checkpoint expression and the inhibitory immune microenvironment. This study aimed to explore the immune microenvironment in lung adenocarcinoma via disulfidptosis. Methods: Public datasets of lung adenocarcinoma from the TCGA and GEO was adopted as the training and validation cohort. Based on the differences in the expression of disulfidptosis -related genes, a glucose metabolism and immune response prognostic model was constructed. The prognostic value and clinical relationship of the model were further explored. Immune-related analyses were performed according to CIBERSORT, ssGSEA, TIDE, IPS. Results: We verified that the model could accurately predict the survival expectancy of lung adenocarcinoma patients. Patients with lung adenocarcinoma and a low-risk score had better survival outcomes according to the model. Moreover, the high-risk group tended to have an immunosuppressive effect, as reflected by the immune cell components, phenotypes and functions. We also found that the clinically relevant immune checkpoint CTLA-4 was significantly higher in low-risk group (P<0.05), indicating that the high-risk group may suffer worse tumor immunotherapy efficacy. Finally, we found that this model has accurate predictive value for the efficacy of immune checkpoint blockade in non-small cell lung cancer (P<0.05). Conclusion: The prognostic model demonstrated the feasibility of predicting survival and immunotherapy efficacy via disulfidptosis-related genes and will facilitate the development of personalized anticancer therapy.

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BACKGROUND: Kidney renal clear cell carcinoma (KIRC) represents a significant proportion of renal cell carcinomas and is characterized by high aggressiveness and poor prognosis despite advancements in immunotherapy. Disulfidptosis, a novel cell death pathway, has emerged as a critical mechanism in various cellular processes, including cancer. This study leverages machine learning to identify disulfidptosis-related long noncoding RNAs (DRlncRNAs) as potential prognostic biomarkers in KIRC, offering new insights into tumor pathogenesis and treatment avenues. RESULTS: Our analysis of data from The Cancer Genome Atlas (TCGA) led to the identification of 431 DRlncRNAs correlated with disulfidptosis-related genes. Five key DRlncRNAs (SPINT1-AS1, AL161782.1, OVCH1-AS1, AC131009.3, and AC108673.3) were used to develop a prognostic model that effectively distinguished between low- and high-risk patients with significant differences in overall survival and progression-free survival. The low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. Conversely, the high-risk group displayed aggressive tumor features and poor immunotherapy outcomes. Validation through qRT‒PCR confirmed the differential expression of these DRlncRNAs in KIRC cells compared to normal kidney cells, underscoring their potential functional significance in tumor biology. CONCLUSIONS: This study established a robust link between disulfidptosis-related lncRNAs and patient prognosis in KIRC, underscoring their potential as prognostic biomarkers and therapeutic targets. The differential expression of these lncRNAs in tumor versus normal tissue further highlights their relevance in KIRC pathogenesis. The predictive model not only enhances our understanding of KIRC biology but also provides a novel stratification tool for precision medicine approaches, improving treatment personalization and outcomes in KIRC patients.

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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.

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BACKGROUND: Disulfidptosis is an emerging form of cellular death resulting from the binding of intracellular disulfide bonds to actin cytoskeleton proteins. This study aimed to investigate the expression and prognostic significance of hub disulfidptosis-related lncRNAs (DRLRs) in R0 resected hepatocellular carcinoma (HCC) as well as their impact on the malignant behaviour of HCC cells. METHODS: A robust signature for R0 resected HCC was constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and was validated in an independent internal validation cohort to predict the prognosis of R0 HCC patients. Comprehensive bioinformatics analysis was performed on the hub DRLRs (KDM4A-AS1, MKLN1-AS, and TMCC1-AS1), followed by experimental validation using quantitative real-time polymerase chain reaction (qRT‒PCR) and cellular functional assays. RESULTS: The signature served as an independent prognostic factor applicable to R0 HCC patients across different age groups, tumour stages, and pathological characteristics. Gene Ontology (GO) and gene set enrichment analysis (GSEA) revealed hub pathways associated with this signature. The high-risk group presented an increased abundance of M0 macrophages and activated memory CD4 T cells as well as elevated macrophage and major histocompatibility complex (MHC) class I expression. High-risk R0 HCC patients also presented increased tumour immune dysfunction and exclusion scores (TIDEs), mutation frequencies, and tumour mutational burdens (TMBs). Drug sensitivity analysis revealed that high-risk patients were more responsive to drugs, including GDC0810 and osimertinib. High expression levels of the three hub DRLRs were detected in R0 HCC tissues and HCC cell lines. Functional assays revealed that the three hub DRLRs enhanced HCC cell proliferation, migration, and invasion. CONCLUSIONS: A signature was constructed on the basis of three DRLRs, providing novel insights for personalized precision therapy in R0 HCC patients.

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