A demonstration based on multi-omics transcriptome sequencing data revealed disulfidptosis heterogeneity within the tumor microenvironment of esophageal squamous cell carcinoma

Identification and Characterization of Metastasis-Initiating Cells in ESCC in a Multi-Timepoint Pulmonary Metastasis Mouse Model

Metastasis is the biggest obstacle to esophageal squamous cell carcinoma (ESCC) treatment. Single-cell RNA sequencing analyses are applied to investigate lung metastatic ESCC cells isolated from pulmonary metastasis mouse model at multiple timepoints to characterize early metastatic microenvironment. A small population of parental KYSE30 cell line (Cluster S) resembling metastasis-initiating cells (MICs) is identified because they survive and colonize at lung metastatic sites. Differential expression profile comparisons between Cluster S and other subpopulations identified a panel of 7 metastasis-initiating signature genes (MIS), including CD44 and TACSTD2, to represent MICs in ESCC. Functional studies demonstrated MICs (CD44high) exhibited significantly enhanced cell survival (resistances to oxidative stress and apoptosis), migration, invasion, stemness, and in vivo lung metastasis capabilities, while bioinformatics analyses revealed enhanced organ development, stress responses, and neuron development, potentially remodel early metastasis microenvironment. Meanwhile, early metastasizing cells demonstrate quasi-epithelial-mesenchymal phenotype to support both invasion and anchorage. Multiplex immunohistochemistry (mIHC) staining of 4 MISs (CD44, S100A14, RHOD, and TACSTD2) in ESCC clinical samples demonstrated differential MIS expression scores (dMISs) predict lymph node metastasis, overall survival, and risk of carcinothrombosis.

Identification of Key Disulfidptosis-Related Genes and Their Association with Gene Expression Subtypes in Crohn's Disease

Background

Crohn's disease (CD) is a persistent inflammatory condition that impacts the gastrointestinal system and is characterized by a multifaceted pathogenesis involving genetic, immune, and environmental components. This study primarily investigates the relationship between gene expression and immune cell infiltration in CD, focusing on disulfidptosis-a novel form of cell death caused by abnormal disulfide accumulation-and its impact on various immune cell populations. By identifying key disulfidptosis-related genes (DRGs) and exploring their association with distinct gene expression subtypes, this research aims to enhance our understanding of CD and potentially other autoimmune diseases.

Methods

Gene expression data from intestinal biopsy samples were collected from both individuals with CD and healthy controls, and these data were retrieved from the GEO database. Through gene expression level comparisons, various differentially expressed genes (DEGs) were identified. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to reveal the biological processes and pathways linked to these DEGs. Later, immune cell infiltration was evaluated. Hub candidate DRGs were identified using machine learning algorithms. Validation of the expression of hub DRGs was carried out using quantitative real-time polymerase chain reaction. The hub DRGs were subjected to unsupervised hierarchical clustering to classify CD patients into subtypes. The characteristics of each subtype were then analyzed.

Results

Two hub DRGs (NDUFA11 and LRPPRC) were identified. NDUFA11 showed a significantly positive association with the abundance of Th17 cells. Conversely, higher expression levels of LRPPRC were associated with a reduced abundance of various immune cells, particularly monocytes. CD patients were classified into two disulfidptosis-related subtypes. Cluster B patients exhibited lower immune infiltration and milder clinical presentation.

Conclusion

LRPPRC and NDUFA11 are identified as hub DRGs in CD, with potential roles in disulfidptosis and immune regulation. The disulfidptosis subtypes provide new insights into disease progression.

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 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.

Construction of disulfidptosis-based immune response prediction model with artificial intelligence and validation of the pivotal grouping oncogene c-MET in regulating T cell exhaustion

Background

Given the lack of research on disulfidptosis, our study aimed to dissect its role in pan-cancer and explore the crosstalk between disulfidptosis and cancer immunity.

Methods

Based on TCGA, ICGC, CGGA, GSE30219, GSE31210, GSE37745, GSE50081, GSE22138, GSE41613, univariate Cox regression, LASSO regression, and multivariate Cox regression were used to construct the rough gene signature based on disulfidptosis for each type of cancer. SsGSEA and Cibersort, followed by correlation analysis, were harnessed to explore the linkage between disulfidptosis and cancer immunity. Weighted correlation network analysis (WGCNA) and Machine learning were utilized to make a refined prognosis model for pan-cancer. In particular, a customized, enhanced prognosis model was made for glioma. The siRNA transfection, FACS, ELISA, etc., were employed to validate the function of c-MET.

Results

The expression comparison of the disulfidptosis-related genes (DRGs) between tumor and nontumor tissues implied a significant difference in most cancers. The correlation between disulfidptosis and immune cell infiltration, including T cell exhaustion (Tex), was evident, especially in glioma. The 7-gene signature was constructed as the rough model for the glioma prognosis. A pan-cancer suitable DSP clustering was made and validated to predict the prognosis. Furthermore, two DSP groups were defined by machine learning to predict the survival and immune therapy response in glioma, which was validated in CGGA. PD-L1 and other immune pathways were highly enriched in the core blue gene module from WGCNA. Among them, c-MET was validated as a tumor driver gene and JAK3-STAT3-PD-L1/PD1 regulator in glioma and T cells. Specifically, the down-regulation of c-MET decreased the proportion of PD1+ CD8+ T cells.

Conclusion

To summarize, we dissected the roles of DRGs in the prognosis and their relationship with immunity in pan-cancer. A general prognosis model based on machine learning was constructed for pan-cancer and validated by external datasets with a consistent result. In particular, a survival-predicting model was made specifically for patients with glioma to predict its survival and immune response to ICIs. C-MET was screened and validated for its tumor driver gene and immune regulation function (inducing t-cell exhaustion) in glioma.

Pan-Cancer Analysis Reveals Disulfidoptosis-Associated Genes as Promising Immunotherapeutic Targets: Insights Gained from Bulk Omics and Single-Cell Sequencing Validation

Disulfidoptosis, a novel form of cell death, is distinct from other well-known cell death mechanisms. Consequently, a profound investigation into disulfidoptosis elucidates the fundamental mechanisms underlying tumorigenesis, presenting promising avenues for therapeutic intervention. Comprehensive analysis of disulfidoptosis-associated gene (DRG) expression in pan cancer utilized TCGA, GEO, and ICGC datasets, including survival and Cox-regression analyses for prognostic evaluation. We analyzed the association between DRG expression and both immune cell infiltration and immune-related gene expression using the ESTIMATE and TISDIB datasets. We obtained our single-cell RNA sequencing (scRNA-seq) data from the GEO repository. Subsequently, we assessed disulfidoptosis activity in various cell types. Evaluation of immune cell infiltration and biological functions was analyzed via single-sample gene set enrichment (ssGSEA) and gene set variation analysis (GSVA). For in vitro validation experiments, the results from real-time PCR (RT-qPCR) and Western blot were used to explore the expression of SLC7A11 in hepatocellular carcinoma (HCC) tissues and different cancer cell lines, while siRNA-mediated SLC7A11 knockdown effects on HCC cell proliferation and migration were examined. Expression levels of DRGs, especially SLC7A11, were significantly elevated in tumor samples compared to normal samples, which was associated with poorer outcomes. Except for SLC7A11, DRGs consistently exhibited high CNV and SNV rates, particularly in HCC. In various tumors, DRGs were negatively associated with DNA promoter methylation. TME analyses further illustrated a negative correlation of DRG expression with ImmuneScore and StromalScore and a positive correlation with tumor purity. Our analysis unveiled diverse cellular subgroups within HCC, particularly focusing on Treg cell populations, providing insights into the intricate interplay of immune activation and suppression within the tumor microenvironment (TME). These findings were further validated through RT-qPCR, Western blot analyses, and immunohistochemical analyses. Additionally, the knockdown of SLC7A11 induced a suppression of proliferation and migration in HCC cell lines. In conclusion, our comprehensive pan-cancer analysis research has demonstrated the significant prognostic and immunological role of disulfidoptosis across a spectrum of tumors, notably HCC, and identified SLC7A11 as a promising therapeutic target.

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.