Bioinformatics combined with single-cell analysis reveals the molecular mechanism of pyroptosis in hepatocellular carcinoma DOI Creative Commons

Wei Luo,

Junxia Wang, Hongfei Wang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 13, 2024

Abstract Purpose Hepatocellular carcinoma (HCC) is the third leading cause of cancer related death, and its molecular mechanisms have not been fully elucidated. The aim this work to discover association between immune microenvironment changes pyroptosis in HCC. Methods Select gene expression profiles from comprehensive database, establish protein-protein interaction networks, perform functional enrichment analysis using databases such as Kyoto Encyclopedia Genes Genomes (KEGG). Single cell identification HCC types malignant cells, trajectory intercellular signal communication further analyze cells liver cells. Bioinformatics combined with single-cell elucidate mechanism underlying development Results key hub genes were validated through immunohistochemistry vitro experiments. Molecular biology has identified six focal death Enrichment shows that intersecting are enriched responses, chemokine mediated signaling pathways, inflammatory responses. cellular clustering single revealed infiltration especially polarization macrophages, which plays an important role. Immunohistochemistry suggests HMGB1, CYCS, GSDMD, IL-1β, NLRP3, IL18 link macrophage during development. Conclusions In summary, main pathogenesis infiltration, particularly promotes secretion factors hepatocyte pyroptosis. Our study may guide future research on pathway

Language: Английский

Construction of T-Cell-Related Prognostic Risk Models and Prediction of Tumor Immune Microenvironment Regulation in Pancreatic Adenocarcinoma via Integrated Analysis of Single-Cell RNA-Seq and Bulk RNA-Seq DOI Open Access
Dingya Sun, Yijie Hu, Jun Peng

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(6), P. 2384 - 2384

Published: March 7, 2025

Pancreatic adenocarcinoma (PAAD) is a fatal malignant tumor of the digestive system, and immunotherapy has currently emerged as key therapeutic approach for treating PAAD, with its efficacy closely linked to T-cell subsets immune microenvironment. However, reliable predictive markers guide clinical PAAD are not available. We analyzed single-cell RNA sequencing (scRNA-seq) data focused on from GeneExpressionOmnibus (GEO) database. Then, information Cancer Genome Atlas (TCGA) database was integrated develop validate prognostic risk model derived marker genes. Subsequently, correlation between these models effectiveness explored. Analysis scRNA-seq uncovered six subtypes 1837 differentially expressed genes (DEGs). Combining TCGA dataset, we constructed containing 16 DEGs, which can effectively predict patient survival outcomes. have found that patients in low-risk group had better outcomes, increased cell infiltration, signs activation compared those high-risk group. Additionally, analysis mutation burden showed higher rates Risk scores checkpoint gene expression drug sensitivity provide multiple targets options. Our study based genes, providing valuable insights into predicting prognosis immunotherapy.

Language: Английский

Citations

0
Transcriptome Data Combined With Mendelian Randomization Analysis Identifies Key Genes Associated With Mitochondria and Programmed Cell Death in Intervertebral Disc Degeneration DOI Creative Commons

Hongfei Nie,

Xiao Hu,

Jiaxiao Wang

et al.

JOR Spine, Journal Year: 2025, Volume and Issue: 8(1)

Published: March 1, 2025

ABSTRACT Background Intervertebral disc degeneration (IDD) is a major cause of cervical and lumbar diseases, significantly impacting patients' quality life. Mitochondria cell death have been implicated in IDD, but the key related genes remain unknown. Methods Differentially expressed (DEGs) between IDD control samples were identified using GSE70362. Mitochondria‐related (MRGs) programmed death‐related (PCDRGs) intersected with DEGs to find DE‐MRGs DE‐PCDRGs. Weighted gene co‐expression network analysis (WGCNA) module genes, overlap revealed candidate genes. Mendelian randomization (MR) was used determine causally linked IDD. Machine learning expression validation further refined which then build nomogram predict risk. Additionally, set enrichment (GSEA), immune infiltration, single‐cell performed. Results A total 515 224 yielding 31 Six genes—BCKDHB, BID, TNFAIP6, VRK1, CAB39L, TMTC1—showed causal relationship TMTC1 as through machine validation. developed based on these GSEA BID enriched N‐glycan biosynthesis, TNFAIP6 aminoacyl tRNA ribosomal pathways. Activated dendritic cells, CD56dim natural killer monocytes, other cells elevated strongly correlating activated cells. Key at higher levels degraded samples. Conclusion TMTC1, mitochondria offering new insights for diagnosis treatment.

Language: Английский

Citations

0
Based on single-cell and transcriptome data, ferroptosis and the immunological landscape in osteosarcoma were discovered DOI Creative Commons

Yingcun Jiang,

Chao Song,

Jiyuan Yan

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 29, 2025

Language: Английский

Citations

0
Correlation analysis of disulfidptosis-related gene signatures with clinical prognosis and immunotherapy response in sarcoma DOI Creative Commons
Juan Xu,

Kangwen Guo,

Xiaoan Sheng

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 26, 2024

Abstract Disulfidptosis, a newly discovered type of programmed cell death, could be mechanism death controlled by SLC7A11. This closely associated with tumor development and advancement. Nevertheless, the biological behind disulfidptosis-related genes (DRGs) in sarcoma (SARC) is uncertain. study identified three valuable ( SLC7A11, RPN1, GYS1 ) disulfidptosis developed prognostic model. The multiple databases RT-qPCR data confirmed upregulated expression DRGs SARC. TCGA internal ICGC external validation cohorts were utilized to validate predictive model capacity. Our analysis DRG riskscores revealed that low-risk group exhibited more favorable prognosis than high-risk group. Furthermore, we observed significant association between different clinical features, immune infiltration, therapeutic sensitivity, drug RNA modification regulators. In addition, two independent immunetherapy datasets tissue samples collected, validating value risk predicting immunotherapy response. Finally, SLC7A11/hsa-miR-29c-3p/LINC00511, RPN1/hsa-miR-143-3p/LINC00511 regulatory axes constructed. provided riskscore signatures predict response SARC, guiding personalized treatment decisions.

Language: Английский

Citations

3
Leveraging a disulfidptosis/ferroptosis-based signature to predict the prognosis of lung adenocarcinoma DOI Creative Commons
Xiaoqing Ma, Zilin Deng, Zhen Li

et al.

Cancer Cell International, Journal Year: 2023, Volume and Issue: 23(1)

Published: Nov. 9, 2023

Abstract Background Disulfidptosis and Ferroptosis are two novel forms of cell death. Although their mechanisms differ, research has shown that there is a relationship between the two. Investigating connection these death can further deepen our understanding development progression cancer, provide better prediction models for accurate prognosis. Methods In this study, RNA sequencing (RNA-seq) data, clinical single nucleotide polymorphism (SNP) single-cell data were obtained from public databases. We used weighted gene co-expression network analysis (WGCNA) unsupervised clustering to identify new Disulfidptosis/Ferroptosis-Related Genes (DFRG), constructed LASSO COX prognosis model was externally validated. To explore signature, pathway function performed, differences in mutation frequency high- low-risk groups studied. Importantly, we also conducted on immune checkpoint, infiltration levels resistance indicators, addition analyzing real immunotherapy data. Results have identified four optimal disulfidptosis/ferroptosis-related genes (ODFRGs) differentially expressed associated with Lung Adenocarcinoma (LUAD). These include GMPR, MCFD2, MRPL13, SALL2. Based ODFRGs, robust prognostic high-risk group showed significantly lower overall survival (OS) compared group. Furthermore, predict outcomes LUAD patients some extent.

Language: Английский

Citations

7
Disulfidptosis‑related lncRNA prognosis model to predict survival therapeutic response prediction in lung adenocarcinoma DOI Open Access
Xiaoming Sun, Jia Li,

Xuedi Gao

et al.

Oncology Letters, Journal Year: 2024, Volume and Issue: 28(2)

Published: May 29, 2024

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, and disulfidptosis a newly discovered mechanism programmed cell death. However, effects disulfidptosis‑related lncRNAs (DR‑lncRNAs) in LUAD have yet to be fully elucidated. The aim present study was identify validate novel lncRNA‑based prognostic marker that associated with disulfidptosis. RNA‑sequencing clinical data were obtained from Cancer Genome Atlas database. Univariate Cox regression lasso algorithm analyses used DR‑lncRNAs establish model. Kaplan‑Meier curves, receiver operating characteristic principal component analysis, regression, nomograms calibration curves assess reliability Functional enrichment immune infiltration somatic mutation tumor microenvironment drug predictions applied risk Reverse transcription‑quantitative PCR subsequently performed mRNA expression levels normal cells cells. These enabled DR‑lncRNA prognosis signature constructed, consisting nine lncRNAs; U91328.1, LINC00426, MIR1915HG, TMPO‑AS1, TDRKH‑AS1, AL157895.1, AL512363.1, AC010615.2 GCC2‑AS1. This model could serve as an independent tool for patients LUAD. Numerous evaluation algorithms indicated low‑risk group may exhibit more robust active response against tumor. Moreover, dysfunction exclusion suggested immunotherapy would effective group. drug‑sensitivity results showed high‑risk sensitive treatment crizotinib, erlotinib or savolitinib. Finally, AL157895.1 found lower A549. In summary, which provided new index predict efficacy therapeutic interventions

Language: Английский

Citations

2
A novel prognostic signature and immune microenvironment characteristics associated with disulfidptosis in papillary thyroid carcinoma based on single-cell RNA sequencing DOI Creative Commons
Zhenyu Liao,

Ye Cheng,

Huiru Zhang

et al.

Frontiers in Cell and Developmental Biology, Journal Year: 2023, Volume and Issue: 11

Published: Nov. 14, 2023

Background: Disulfidptosis is a newly discovered form of regulated cell death. The research on disulfidptosis and tumor progression remains unclear. Our aims to explore the relationship between disulfidptosis-related genes (DRGs) clinical outcomes papillary thyroid carcinoma (PTC), its interaction microenvironment. Methods: single-cell RNA seq data PTC was collected from GEO dataset GSE191288. We illustrated expression patterns in different cellular components cancer. LASSO analyses were performed construct associated risk model TCGA-THCA database. GO KEGG used for functional analyses. CIBERSORT ESTIMATE algorithm helped with immune infiltration estimation. qRT‒PCR flow cytometry validate hub gene samples. Results: clustered scRNA into 8 annotated types. With further DRGs based scoring analyses, we found endothelial cells exhibited most disulfidptosis. A 4-gene established pattern related subset. showed good independent prognostic value both training validation dataset. Functional enrichment genomic feature analysis significant correlation signature. results estimation higher scores immuno-suppressive microenvironment PTC. Conclusion: study role signature regulation survival patients. (including SNAI1, STC1, PKHD1L1 ANKRD37) built basis cells. significance outcome validated robustly.

Language: Английский

Citations

4
Creation of signatures and identification of molecular subtypes based on disulfidptosis-related genes for glioblastoma patients' prognosis and immunological activity DOI Creative Commons
Dongjun Li, Xiaodong Li, Jianfeng Lv

et al.

Asian Journal of Surgery, Journal Year: 2024, Volume and Issue: 47(8), P. 3464 - 3477

Published: March 11, 2024

In recent times, disulfidptosis, an intricate form of cellular demise, has garnered attention due to its impact on prognosis, tumor progression and treatment response. Nevertheless, the exact significance disulfidptosis-related genes (DisRGs) in glioblastoma (GBM) remains enigmatic. The GEO TCGA databases provided transcriptional clinically relevant data samples, while GTEx database healthy tissues. Disulfidptosis-related were procured from previous scholarly investigations. expression profile DisRGs was initially scrutinized among patients diagnosed with GBM, subsequent which their prognostic value explored. Through consensus clustering, we constructed DisRGs-related clusters gene subtypes. Our results established that DisRG-related had differentially expressed genes, resulting a DisulfidptosisScore model, positive value. differential 24 between GBM samples acquired. cluster analysis, two distinct disulfidptosis subtypes, namely DisRGcluster A B, identified. Then, model including 4 characteristic constructed.Notably, assigned lower score demonstrated considerably longer overall survival (OS) compared those higher score. We have effectively devised associated presenting autonomous predictions for GBM. These findings serve as valuable addition current comprehension offer fresh theoretical substantiation development enhanced strategies.

Language: Английский

Citations

1
Construction of a mitophagy-related prognostic signature for predicting prognosis and tumor microenvironment in lung adenocarcinoma DOI Creative Commons

W.K. Liu,

Rumei Li,

Yong-Hong Le

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(15), P. e35305 - e35305

Published: July 31, 2024

Mitophagy is the selective degradation of mitochondria by autophagy. It becomes increasingly clear that mitophagy pathways are important for cancer cells to adapt their high-energy needs. However, which genes associated with could be used prognosis unknown.

Language: Английский

Citations

1
Development of the RF-GSEA Method for Identifying Disulfidptosis-Related Genes and Application in Hepatocellular Carcinoma DOI Creative Commons
Linghao Ni, Yu Q,

Ruijia You

et al.

Current Issues in Molecular Biology, Journal Year: 2023, Volume and Issue: 45(12), P. 9450 - 9470

Published: Nov. 24, 2023

Disulfidptosis is a newly discovered cellular programmed cell death mode. Presently, considerable number of genes related to disulfidptosis remain undiscovered, and its significance in hepatocellular carcinoma remains unrevealed. We have developed powerful analytical method called RF-GSEA for identifying potential associated with disulfidptosis. This draws inspiration from gene regulation networks graph theory, it implemented through combination random forest regression model Gene Set Enrichment Analysis. Subsequently, validate the practical application value this method, we applied carcinoma. Based on disulfidptosis-related signature. Lastly, looked into how signature connected HCC prognosis, tumor microenvironment, effectiveness immunotherapy, sensitivity chemotherapy drugs. The identified total 220 genes, which 7 were selected construct high-disulfidptosis-related score group had worse prognosis compared low-disulfidptosis-related showed lower infiltration levels immune-promoting cells. higher likelihood benefiting immunotherapy group. tool genes. effectively predicts response, drug sensitivity.

Language: Английский

Citations

2