Integrated analysis of disulfidptosis-related immune genes signature to boost the efficacy of prognostic prediction in gastric cancer
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ABSTRACT:
SUBMITTER: Li J
PROVIDER: S-EPMC10962090 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundDisulfidptosis 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.MethodsWe 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.ResultsTwo 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.ConclusionsThis 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.
| S-EPMC11325698 | biostudies-literature
Project description:Disulfidptosis, a novel type of programmed cell death, has attracted researchers' attention worldwide. However, the role of disulfidptosis-related lncRNAs (DRLs) in liver hepatocellular carcinoma (LIHC) not yet been studied. We aimed to establish and validate a prognostic signature of DRLs and analyze tumor microenvironment (TME) and drug susceptibility in LIHC patients. RNA sequencing data, mutation data, and clinical data were obtained from the Cancer Genome Atlas Database (TCGA). Lasso algorithm and cox regression analysis were performed to identify a prognostic DRLs signature. Kaplan-Meier curves, principal component analysis (PCA), nomogram and calibration curve, function enrichment, TME, immune dysfunction and exclusion (TIDE), tumor mutation burden (TMB), and drug sensitivity analyses were analyzed. External datasets were used to validate the predictive value of DRLs. qRT-PCR was also used to validate the differential expression of the target lncRNAs in tissue samples and cell lines. We established a prognostic signature for the DRLs (MKLN1-AS and TMCC1-AS1) in LIHC. The signature could divide the LIHC patients into low- and high-risk groups, with the high-risk subgroup associated with a worse prognosis. We observed discrepancies in tumor-infiltrating immune cells, immune function, function enrichment, and TIDE between two risk groups. LIHC patients in the high-risk group were more sensitive to several chemotherapeutic drugs. External datasets, clinical tissue, and cell lines confirmed the expression of MKLN1-AS and TMCC1-AS1 were upregulated in LIHC and associated with a worse prognosis. The novel signature based on the two DRLs provide new insight into LIHC prognostic prediction, TME, and potential therapeutic strategies.
| S-EPMC10772085 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is one of the most common causes of cancer-related death worldwide. As a novel form of programmed cell death, disulfidptosis is characterized by excessive cysteine accumulation, disulfide stress and actin destruction. There is evidence that targeting disulfidptosis is a promising anticancer strategy. Further improvement of GC risk stratification based on disulfidptosis has positive clinical significance.MethodsWe analyzed the expression levels of disulfidptosis-associated genes (DPAGs) in normal and GC tissues and characterized the molecular subtypes of GC patients. Based on the characteristics of DPAG subtypes, differentially expressed prognosis-related genes were selected by LASSO-univariate Cox analysis and multivariate Cox analysis analyzed to establish a prognostic model. Using single-cell sequencing analysis reveals the cell subpopulation for GC. The function of the selected target in GC was verified by in vitro experimental means, including siRNA, qRT-PCR, Western blot, CCK-8, and Transwell assay.ResultsDPAG score was verified to be an independent prognostic factor of GC and was significantly associated with poor prognosis of gastric cancer. Subsequent studies on subgroup immunoinfiltration characteristics, drug sensitivity analysis, immunotherapy response and somatic mutation characteristics of DPAG score comprehensively confirmed the potential guiding significance of DPAG score for individualized treatment of gastric cancer patients. Single-cell sequencing analysis revealed the expression characteristics of DPAG-related prognostic signatures across cell subpopulations. In vitro experiments showed APC11, as one of the selected DPAGs, was highly expressed in gastric cancer, and knockdown of APC11 could significantly inhibit the proliferation and migration of GC cells, demonstrating the reliability of bioinformatics results.ConclusionThe results of this study provide a new perspective for exploring the role of disulfidptosis in the occurrence and development of GC.
| S-EPMC11861452 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is one of the most common malignant tumors in the digestive system with high mortality globally. However, the biomarkers that accurately predict the prognosis are still lacking. Therefore, it is important to screen for novel prognostic markers and therapeutic targets.MethodsWe conducted differential expression analysis and survival analysis to screen out the prognostic genes. A stepwise method was employed to select a subset of genes in the multivariable Cox model. Overrepresentation enrichment analysis (ORA) was used to search for the pathways associated with poor prognosis.ResultsIn this study, we designed a seven-gene-signature-based Cox model to stratify the GC samples into high-risk and low-risk groups. The survival analysis revealed that the high-risk and low-risk groups exhibited significantly different prognostic outcomes in both the training and validation datasets. Specifically, CGB5, IGFBP1, OLFML2B, RAI14, SERPINE1, IQSEC2, and MPND were selected by the multivariable Cox model. Functionally, PI3K-Akt signaling pathway and platelet-derived growth factor receptor (PDGFR) were found to be hyperactive in the high-risk group. The multivariable Cox regression analysis revealed that the risk stratification based on the seven-gene-signature-based Cox model was independent of other prognostic factors such as TNM stages, age, and gender.ConclusionIn conclusion, we aimed at developing a model to predict the prognosis of gastric cancer. The predictive model could not only effectively predict the risk of GC but also be beneficial to the development of therapeutic strategies.
| S-EPMC7468614 | biostudies-literature
Project description:ObjectiveDisulfidptosis is a newly identified type of nonapoptotic programmed cell death related to mechanisms such as ferroptosis, cuproptosis, pyroptosis, and necrotic apoptosis. This study explores the role of disulfidptosis-related long non-coding RNAs (DRLs) in gastric cancer and their potential as prognostic biomarkers.MethodWe developed a prognostic model using DRL scores to classify patients based on disulfidptosis activity. We evaluated these scores for correlations with drug sensitivity, tumor microenvironment (TME) features, tumor mutational burden (TMB), and prognosis. Potential disulfidptosis-related signaling pathways were screened, identifying FRMD6-AS as a promising therapeutic target. FRMD6-AS expression was further validated using real-time fluorescent quantitative PCR (qRT-PCR).ResultsThe DRL-based prognostic model, established through univariate and multivariate Cox regression and LASSO regression analyses, outperformed traditional models in predicting prognosis. We divided samples into high-risk and low-risk groups based on DRL scores, finding that the low-risk group had a significantly higher survival rate (P < 0.05). A high-precision prediction model incorporating DRL scores, age, sex, grade, and stage showed strong predictive value and consistency with actual outcomes. High DRL scores correlated with higher TME scores and lower TMB. Key signaling axes identified were AC129507.1/(FLNA, TLN1)/FOCAL ADHESION and AC107021.2/MYH10/(TIGHT JUNCTION, VIRAL MYOCARDITIS, REGULATION OF ACTIN CYTOSKELETON). Potentially effective drugs, including BMS-754807, dabrafenib, and JQ1, were identified. FRMD6-AS emerged as a potential target for gastric cancer treatment.ConclusionsThis study developed a novel prognostic model for gastric cancer using DRLs, identifying two key signaling axes related to prognosis. JQ1 may be an effective treatment, and FRMD6-AS could be a promising therapeutic target.
| S-EPMC11913695 | biostudies-literature
Project description: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.
| S-EPMC10770353 | biostudies-literature
Project description:BackgroundGastric cancer (GC) has been divided into four molecular subtypes, of which the mesenchymal subtype has the poorest survival. Our goal is to develop a prognostic signature by integrating the immune system and molecular modalities involved in the mesenchymal subtype.MethodsThe gene expression profiles collected from 6 public datasets were applied to this study, including 1,221 samples totally. Network analysis was applied to integrate the mesenchymal modalities and immune signature to establish an immune-based prognostic signature for GC (IPSGC).ResultsWe identified six immune genes as key factors of the mesenchymal subtype and established the IPSGC. The IPSGC can significantly divide patients into high- and low-risk groups in terms of overall survival (OS) and relapse-free survival (RFS) in discovery (OS: P < 0.001) and 5 independent validation sets (OS range: P = 0.05 to P < 0.001; RFS range: P = 0.03 to P < 0.001). Further, in multivariate analysis, the IPSGC remained an independent predictor of prognosis and performed better efficiency compared to clinical characteristics. Moreover, macrophage M2 was significantly enriched in the high-risk group, while plasma cells were enriched in the low-risk group.ConclusionsWe propose an immune-based signature identified by network analysis, which is a promising prognostic biomarker and help for the selection of GC patients who might benefit from more rigorous therapies. Further prospective studies are warranted to test and validate its efficiency for clinical application.
| S-EPMC7171688 | biostudies-literature
Project description:Disulfidptosis, a newly revealed form of cell death, regulated by numerous genes that has been recently identified. The exact role of disulfidptosis in lung adenocarcinoma (LUAD) still uncertain. Objective of this study was to explore potential prognostic markers among disulfidptosis genes in LUAD. By combining transcriptomic information from Gene Expression Omnibus databases and The Cancer Genome Atlas, we identified differentially expressed and prognostic disulfidptosis genes. By conducting least absolute shrinkage and selection operator with multivariate Cox regression, four disulfidptosis genes were selected to create the prognostic signature. The implementation of the signature separated the training and validation cohorts into groups with high- and low-risk. Subsequently, the model was verified by conducting an independent analysis of receiver operating characteristic (ROC) curves. Further comparisons were made between the two risk-divided groups with regards the tumor microenvironment, immune cell infiltration, immunotherapy response, and drug sensitivity. The signature was constructed using four disulfidptosis-related genes: SLC7A11, SLC3A2, NCKAP1, and GYS1. According to ROC curves, the signature was effective for predicting LUAD prognosis. In addition, the prognostic signature correlated with sensitivity to chemotherapeutic agents and the efficacy of immunotherapy in LUAD. Finally, through external validation, we showed that NCKAP1 are correlated with tumor migration, proliferation, and invasion of LUAD cells. GYS1 affects immune cell, especially M2 macrophage infiltration in the tumor microenvironment. The disulfidptosis four-gene model can reliably predict the prognosis of patients diagnosed with LUAD, thereby providing valuable information for clinical applications and immunotherapy.
| S-EPMC10784160 | biostudies-literature
Project description:PurposeDisulfidptosis, a newly identified form of cell death, is triggered by disulfide stress. Herein, a unique signature was developed based on disulfidptosis-related lncRNAs (DRlncRNAs) for the prognostic and immune landscape prediction of head and neck squamous cell carcinoma (HNSCC).MethodsTranscriptome, somatic mutation, and clinical data were acquired at The Cancer Genome Atlas database. Individuals were partitioned into training and test cohorts at a 1:1 ratio to facilitate the development of a DRlncRNA signature using the least absolute shrinkage and selection operation method. Based on the median risk score, all HNSCC individuals were stratified into the high-risk group (HRG) and low-risk group (LRG). Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were used to estimate the prognostic value, and a nomogram was generated for survival prediction. To provide a more comprehensive assessment, the tumor microenvironment, functional enrichment, immune cell infiltration, and immunotherapeutic sensitivity were explored between LRG and HRG.ResultsA DRlncRNA signature was established with 10 DRlncRNAs. The corresponding values of areas under the ROC curves for 1-, 3-, and 5-year overall survival were 0.710, 0.692, and 0.640. A more favorable prognosis was noted in the patients with lower risk, along with higher immune scores, increased immune-related functions, and immune cell infiltration, as well as improved response to the immunotherapeutic intervention in comparison with individuals at higher risk.ConclusionThese findings demonstrate that the developed DRlncRNA signature holds promise as a reliable prognostic marker and predictor of immunotherapy response in HNSCC patients.
| S-EPMC10940567 | biostudies-literature
Project description:BackgroundHCC is an extremely malignant tumor with a very poor prognosis. In 2023, a brand-new kind of cell death known as disulfidptosis was identified. Although, the prognosis as well as expression of immune checkpoints that are closely connected with it in HCC remain unknown.MethodsIn this work, we identified 49 genes with abnormal expression in liver cancer and normal liver tissue, with 23 of them being differentially expressed genes. To create a signature, we classified all HCC cases into three subtypes and used the TCGA database to evaluate each relevant gene's prognostic value for survival.ResultsFive gene signatures were identified using the LASSO Cox regression approach, while those diagnosed with HCC were split into either low- or high-risk groups. Patients having low-risk HCC showed a much greater likelihood of surviving than those with high risk (p < 0.05). Through immune cell infiltration analysis, it was found that immune-related genes were abundant in high-risk groups and had reduced immune status.ConclusionIn conclusion, immune checkpoint genes highly associated with disulfidptosis contribute to tumor immunity and can be used to evaluate HCC prognosis. When it comes to predicting overall survival (OS) time in HCC, risk score has been set to be a separate predictor. Through immune cell infiltration analysis, it was found that immune-related genes were abundant in high-risk groups and had reduced immune status. It is possible to measure the prognosis of HCC based on immune checkpoints genes strongly linked to disulfidptosis.
| S-EPMC10587022 | biostudies-literature