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

Biomarker Research, Journal Year: 2024, Volume and Issue: 12(1)

Published: April 29, 2024

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

Language: Английский

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Disulfidptosis-related signature predicts prognosis and characterizes the immune microenvironment in hepatocellular carcinoma

Cancer Cell International, Journal Year: 2024, Volume and Issue: 24(1)

Published: Jan. 9, 2024

Abstract Background Disulfidptosis is a type of programmed cell death caused by excessive cysteine-induced disulfide bond denaturation leading to actin collapse. Liver cancer has poor prognosis and requires more effective intervention strategies. Currently, the prognostic therapeutic value disulfidptosis in liver not clear. Methods We investigated features 16 disulfidptosis-related genes (DRGs) HCC patients TCGA classified into two pattern clusters consensus clustering analysis. Then, we constructed model using LASSO Cox regression. Next, microenvironment drug sensitivity were evaluated. Finally, used qPCR functional analysis verify reliability hub DRGs. Results Most DRGs showed significantly higher expression tissues than adjacent tissues. Our model, DRG score, can well predict survival patients. There significant differences survival, microenvironment, effects immunotherapy, between high- low-DRG score groups. Ultimately, demonstrated that few have differential mRNA cells normal protective gene LCAT inhibit metastasis vitro. Conclusion established novel risk based on scores patient prognosis, immunotherapy efficacy, which provides new insight relationship valuable assistance for personalized treatment HCC.

Language: Английский

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Integrated analysis of disulfidptosis-related immune genes signature to boost the efficacy of prognostic prediction in gastric cancer

Cancer Cell International, Journal Year: 2024, Volume and Issue: 24(1)

Published: March 25, 2024

Abstract Background Gastric cancer (GC) remains a malignant tumor with high morbidity and mortality, accounting for approximately 1,080,000 diagnosed cases 770,000 deaths worldwide annually. Disulfidptosis, characterized by the stress-induced abnormal accumulation of disulfide, is recently identified form programmed cell death. Substantial studies have demonstrated significant influence immune clearance on progression. Therefore, we aimed to explore intrinsic correlations between disulfidptosis immune-related genes (IRGs) in GC, as well potential value disulfidptosis-related (DRIGs) biomarkers. Methods This study incorporated single-cell RNA sequencing (scRNA-seq) dataset GSE183904 transcriptome GC from TCGA database. Disulfidptosis-related (DRGs) IRGs were derived representative literature both immunity. The expression distribution DRGs investigated at level different types. Pearson correlation analysis was used identify closely related disulfidptosis. prognostic signature DRIGs established using Cox LASSO analyses. We then analyzed evaluated differences long-term prognosis, Gene Set Enrichment Analysis (GSEA), infiltration, mutation profile, CD274 expression, response chemotherapeutic drugs two groups. A tissue array containing 63 paired specimens verify 4 regulator SLC7A11 through immunohistochemistry staining. Results scRNA-seq found that , SLC3A2 RPN1 NCKAP1 enriched specific types infiltration. Four DIRGs ( GLA HIF-1α VPS35 CDC37 ) successfully establish potently predict survival time patients. Patients risk scores generally experienced worse prognoses exhibited greater resistant classical chemotherapy drugs. Furthermore, elevated tissues. or associated more advanced clinical stage increased expression. Conclusion Current first highlights biomarkers GC. constructed robust model incorporating four accurately clinicopathological characteristics

Language: Английский

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Molecular map of disulfidptosis-related genes in lung adenocarcinoma: the perspective toward immune microenvironment and prognosis

Clinical Epigenetics, Journal Year: 2024, Volume and Issue: 16(1)

Published: Feb. 11, 2024

Abstract Background Disulfidptosis is a recently discovered form of programmed cell death that could impact cancer development. Nevertheless, the prognostic significance disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) requires further clarification. Methods This study systematically explores genetic and transcriptional variability, relevance, expression profiles DRGs. Clusters related to disulfidptosis were identified through consensus clustering. We used single-sample gene set enrichment analysis ESTIMATE assess tumor microenvironment (TME) different subgroups. conducted functional differentially expressed between subgroups, which involved ontology, Kyoto encyclopedia genomes, variation analysis, order elucidate their status. Prognostic risk models developed using univariate Cox regression least absolute shrinkage selection operator regression. Additionally, single-cell clustering communication enhance understanding importance signature genes. Lastly, qRT-PCR was employed validate model. Results Two clearly defined DRG clusters consensus-based, unsupervised analysis. Observations made concerning correlation changes multilayer various clinical characteristics, prognosis, infiltration TME cells. A well-executed assessment model, known as score, predict prognosis LUAD patients. high score indicates increased infiltration, higher mutation burden, elevated scores, poorer prognosis. showed significant with burden immune dysfunction exclusion score. Subsequently, nomogram established for facilitating application showing good predictive ability calibration. crucial DRGs validated by sequencing data. Finally, immunohistochemistry. Conclusion Our new can landscape LUAD. It also serves reference LUAD's immunotherapy chemotherapy.

Language: Английский

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

Immunity Inflammation and Disease, Journal Year: 2024, Volume and Issue: 12(4)

Published: April 1, 2024

Abstract Background Chronic obstructive pulmonary disease (COPD) is a globally prevalent respiratory disease, and programmed cell death plays pivotal role in the development of COPD. Disulfidptosis newly discovered type that may be associated with progression However, expression disulfidptosis‐related genes (DRGs) COPD remain unclear. Methods The DRGs was identified by analyzing RNA sequencing (RNA‐seq) data Further, patients were classified into two subtypes unsupervised cluster analysis to reveal their differences gene immune infiltration. Meanwhile, hub disulfidptosis screened weighted co‐expression network analysis. Subsequently, validated experimentally cells animals. In addition, we potential therapeutic drugs through genes. Results We distinct molecular clusters observed significant populations between them. nine genes, experimental validation showed CDC71, DOHH, PDAP1, SLC25A39 significantly upregulated cigarette smoke‐induced mouse lung tissues bronchial epithelial (BEAS‐2B) treated smoke extract. Finally, predicted 10 small molecule such as Atovaquone, Taurocholic acid, Latamoxef, Methotrexate. Conclusion highlighted strong association disulfidptosis, demonstrating discriminative capacity for Additionally, certain novel including SLC25A39, linked aid diagnosis assessment this condition.

Language: Английский

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Disulfidptosis-related signature elucidates the prognostic, immunologic, and therapeutic characteristics in ovarian cancer

Frontiers in Genetics, Journal Year: 2024, Volume and Issue: 15

Published: April 17, 2024

Ovarian cancer (OC) is the deadliest malignancy in gynecology, but mechanism of its initiation and progression poorly elucidated. Disulfidptosis a novel discovered type regulatory cell death. This study aimed to develop disulfidptosis-related prognostic signature (DRPS) for OC explore effects potential treatment by risk stratification.

Language: Английский

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Identification of core genes related to exosomes and screening of potential targets in periodontitis using transcriptome profiling at the single-cell level

BMC Oral Health, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 6, 2025

The progression and severity of periodontitis (PD) are associated with the release extracellular vesicles by periodontal tissue cells. However, precise mechanisms through which exosome-related genes (ERGs) influence PD remain unclear. This study aimed to investigate role potential key in using transcriptome profiling at single-cell level. current cited GSE16134, GSE10334, GSE171213 datasets 19,643 ERGs. Initially, differential expression analysis, three machine learning (ML) models, gene analysis receiver operating characteristic (ROC) were proceeded identify core genes. Subsequently, a gene-based artificial neural network (ANN) model was built evaluate predictive power for PD. Gene set enrichment (GSEA) immunoinfiltration conducted based on To pinpoint cell types influencing level, series analyses covering pseudo-time accomplished. verification performed quantitative reverse transcription polymerase chain reaction (qRT-PCR). CKAP2, IGLL5, MZB1, CXCL6, AADACL2 served as diagnosing Four elevated group addition down-regulated AADACL2. gene-based-ANN had AUC values 0.909 GSE16134 dataset, exceeded each gene, highlighting accurately credibly performance ANN model. GSEA revealed that ribosome co-enriched 5 genes, manifesting these might be critical protein structure or function. Immunoinfiltration found CXCL6 exhibited positive correlations most discrepant immune cells/discrepant stromal cells, highly infiltrated B cells T holding crucial parts identified types. Pseudo-time IGLL5 MZB1 increased during differentiation, then decreased differentiation. qRT-PCR proved mRNA levels CKAP2 blood patients compared controls. But is consistent trend amount dataset. exosomes, helping us understand

Language: Английский

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Revealing the therapeutic targets, mechanisms, and heterogeneity of Huatan Jieyu Granules for Parkinson's disease through single-cell sequencing

Journal of Pharmaceutical and Biomedical Analysis, Journal Year: 2025, Volume and Issue: 257, P. 116679 - 116679

Published: Jan. 19, 2025

Language: Английский

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Crotonylation-Related Prognostic Model of Esophageal Squamous Cell Carcinoma Based on Transcriptome Analysis and Single-Cell Sequencing Analysis

International Journal of General Medicine, Journal Year: 2025, Volume and Issue: Volume 18, P. 415 - 436

Published: Jan. 1, 2025

Crotonylation is an emerging lysine acylation modification implicated in various diseases, yet its role esophageal squamous cell cancer (ESCC) unexplored. This study aimed to investigate the of crotonylation-related genes (CRGs) ESCC using bioinformatics approaches. We included three datasets and 24 CRGs. Differentially expressed (DEGs) from TCGA-ESCA were intersected with key module related CRGs identify candidate genes. Univariate LASSO regression analyses conducted select prognostic genes, which then used construct risk models. Independent analysis nomogram construction followed. Functional enrichment immune infiltration performed Single-cell was assess communication pseudotemporal dynamics cells. Intersection 1529 DEGs 1,048 yielded 55 OSM, FABP3, MICB, FAM189A2 identified as These classify ESCA patients into different groups a nomogram. FABP3 enriched neuroactive ligand-receptor interaction ribosome terms. MICB showed strong positive correlations natural killer T (NKT) cells, while negatively correlated gamma delta (γδT) mast cells neutrophils differentiating seven states, respectively. Four (OSM, FAM189A2) ESCC, potentially involved pathogenesis. OSM positively correlated.

Language: Английский

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Disulfidptosis classification of pancreatic carcinoma reveals correlation with clinical prognosis and immune profile

Hereditas, Journal Year: 2025, Volume and Issue: 162(1)

Published: Feb. 22, 2025

Abstract Background Disulfidptosis, a novel form of metabolism-related regulated cell death, is promising intervention for cancer therapeutic intervention. Although aberrant expression long‐chain noncoding RNAs (lncRNAs) has been associated with pancreatic carcinoma (PC) development, the biological properties and prognostic potential disulfidptosis-related lncRNAs (DRLs) remain unclear. Methods We obtained RNA-seq data, clinical genomic mutations PC from TCGA database, then determined DRLs. developed risk score model analyzed role in predictive ability, immune infiltration, immunotherapy response, drug sensitivity. Results finally established including three DRLs (AP005233.2, FAM83A-AS1, TRAF3IP2-AS1). According to Kaplan–Meier curve analysis, survival time patients low-risk group was significantly longer than that high-risk group. Based on enrichment significant associations between metabolic processes differentially expressed genes were assessed two groups. In addition, we observed differences tumor microenvironment landscape. Tumor Immune Dysfunction Rejection (TIDE) analysis showed no statistically likelihood evasion both Patients exhibiting high mutation burden (TMB) had poorest times, while those falling into low TMB categories best prognosis. Moreover, identified by 3-DRLs profile Conclusions Our proposed 3-DRLs-based feature could serve as tool predicting prognosis, landscape, treatment response patients, thus facilitating optimal decision-making.

Language: Английский

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