Epigenetic regulation of diverse cell death modalities in cancer: a focus on pyroptosis, ferroptosis, cuproptosis, and disulfidptosis

Journal of Hematology & Oncology, Journal Year: 2024, Volume and Issue: 17(1)

Published: April 23, 2024

Abstract Tumor is a local tissue hyperplasia resulted from cancerous transformation of normal cells under the action various physical, chemical and biological factors. The exploration tumorigenesis mechanism crucial for early prevention treatment tumors. Epigenetic modification common important in cells, including DNA methylation, histone modification, non-coding RNA m6A modification. mode cell death programmed by death-related genes; however, recent researches have revealed some new modes death, pyroptosis, ferroptosis, cuproptosis disulfidptosis. regulation deaths mainly involved key proteins affects up-regulating or down-regulating expression levels proteins. This study aims to investigate epigenetic modifications regulating disulfidptosis tumor explore possible triggering factors development microscopic point view, provide potential targets therapy perspective antitumor drugs combination therapies.

Language: Английский

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Cuproptosis-related lncRNA signature as a prognostic tool and therapeutic target in diffuse large B cell lymphoma

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

Published: June 5, 2024

Abstract Cuproptosis is a newly defined form of programmed cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) play crucial roles in tumorigenesis and metastasis. However, whether cuproptosis-related lncRNAs are involved the pathogenesis diffuse large B lymphoma (DLBCL) remains unclear. This study aimed to identify prognostic signatures DLBCL investigate their potential molecular functions. RNA-Seq data clinical information for were collected from The Cancer Genome Atlas (TCGA) Gene Expression Omnibus (GEO). Cuproptosis-related screened out through Pearson correlation analysis. Utilizing univariate Cox, least absolute shrinkage selection operator (Lasso) multivariate Cox regression analysis, we identified seven developed risk prediction model evaluate its value across multiple groups. GO KEGG functional analyses, single-sample GSEA (ssGSEA), ESTIMATE algorithm used analyze mechanisms immune status between different Additionally, drug sensitivity analysis drugs with efficacy DLBCL. Finally, protein–protein interaction (PPI) network constructed based weighted gene co-expression (WGCNA). We set including LINC00294, RNF139-AS1, LINC00654, WWC2-AS2, LINC00661, LINC01165 LINC01398, which high-risk group was associated shorter survival time than low-risk group, signature-based score demonstrated superior ability patients compared traditional features. By analyzing landscapes two groups, found immunosuppressive types significantly increased group. Moreover, enrichment highlighted association differentially expressed genes metabolic, inflammatory immune-related pathways patients. also showed more vinorelbine pyrimethamine. A lncRNA signature established predict prognosis provide insights into therapeutic strategies

Language: Английский

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Machine learning-based identification of tumor-infiltrating immune cell-associated model with appealing implications in improving prognosis and immunotherapy response in bladder cancer patients

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: March 31, 2023

Background Immune cells are crucial components of the tumor microenvironment (TME) and regulate cancer cell development. Nevertheless, clinical implications immune infiltration-related mRNAs for bladder (BCa) still unclear. Methods A 10-fold cross-validation framework with 101 combinations 10 machine-learning algorithms was employed to develop a consensus signature (IRS). The predictive performance IRS in terms prognosis immunotherapy comprehensively evaluated. Results demonstrated high accuracy stable prediction across multiple datasets including TCGA-BLCA, eight independent GEO datasets, our in-house cohort (PUMCH_Uro), thirteen checkpoint inhibitors (ICIs) cohorts. Additionally, superior traditional clinicopathological features (e.g., stage grade) 94 published signatures. Furthermore, an risk factor overall survival TCGA-BLCA several recurrence-free PUMCH_Uro. In PUMCH_Uro cohort, patients high-IRS group were characterized by upregulated CD8A PD-L1 TME inflamed immunosuppressive phenotypes. As predicted, these should benefit from ICI therapy chemotherapy. cohorts, related favorable responders have dramatically higher compared non-responders. Conclusions Generally, indicators suggested promising application urological practices early identification high-risk potential candidates prolong individual BCa patients.

Language: Английский

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Prognostic analysis of hepatocellular carcinoma based on cuproptosis -associated lncRNAs

BMC Gastroenterology, Journal Year: 2024, Volume and Issue: 24(1)

Published: April 23, 2024

Abstract Objectives Cuproptosis represents an innovative type of cell death, distinct from apoptosis, driven by copper dependency, yet the involvement apoptosis-associated long non-coding RNAs (CRLncRNAs) in hepatocellular carcinoma (HCC) remains unclear. This study is dedicated to unveiling role and significance these apoptosis-related lncRNAs within context HCC, focusing on their impact both development disease its prognosis. Methods We conducted analysis gene transcriptomic clinical data for HCC cases sourcing information The Cancer Genome Atlas database. By incorporating cuproptosis-related genes, we established prognostic features associated with lncRNAs. Furthermore, elucidated mechanism prognosis treatment through comprehensive approaches, including Lasso Cox regression analyses, survival analyses samples, as well examinations tumor mutation burden immune function. Results developed a model featuring six lncRNAs: AC026412.3, AC125437.1, AL353572.4, MKLN1-AS, TMCC1-AS1, SLC6A1-AS1. demonstrated exceptional accuracy training validation cohorts patients tumors, showing significantly longer times those categorized low-risk group compared high-risk group. Additionally, our burden, function, Gene Ontology, Kyoto Encyclopedia Genes Genomes pathway enrichment, drug sensitivity, further potential mechanisms which cuproptosis-associated may influence outcome. Conclusions using (lncRNAs) demonstrates promising predictive capabilities immunotherapy outcomes patients. could play crucial patient management optimization immunotherapeutic strategies, offering valuable insights future research.

Language: Английский

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Construction and significance of a breast cancer prognostic model based on cuproptosis-related genotyping and lncRNAs

Journal of the Formosan Medical Association, Journal Year: 2024, Volume and Issue: unknown

Published: May 1, 2024

/Purpose: Cuproptosis may play a significant role in breast cancer (BC). We aimed to investigate the prognostic impact of cuproptosis-related lncRNAs BC. Consensus clustering analysis categorized TCGA-BRCA samples into 3 clusters, followed by survival and immune analyses clusters. LASSO-COX was performed on differentially expressed BC construct model. Gene Ontology/Kyoto Encyclopedia Genes Genomes (GO/KEGG) enrichment, immune, drug prediction were high-risk low-risk groups. Cell experiments conducted analyze results two (AC104211.1 LINC01863). Significant differences observed outcomes infiltration levels among three clusters (p < 0.05). The validation model showed between groups both training sets Differential mRNAs significantly enriched Neuroactive ligand-receptor interaction cAMP signaling pathway. Additionally, found levels, human leukocyte antigen (HLA) expression, Immunophenoscore (IPS) scores, Tumor Immune Dysfunction Exclusion (TIDE) scores Drug corresponding cell experimental that Trametinib, 5-fluorouracil, AICAR inhibited viability MCF-7 cells AC104211.1 LINC01863 proliferation cells. risk-scoring obtained this study serve as robust biomarker, potentially aiding clinical decision-making for patients.

Language: Английский

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PANoptosis-related genes in the prognosis and immune landscape of hepatocellular carcinoma

Immunologic Research, Journal Year: 2025, Volume and Issue: 73(1)

Published: Feb. 13, 2025

Language: Английский

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Subtype cluster analysis unveiled the correlation between m6A- and cuproptosis-related lncRNAs and the prognosis, immune microenvironment, and treatment sensitivity of esophageal cancer

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 17, 2025

Objective Esophageal cancer (EC) is characterized by a high degree of malignancy and poor prognosis. N6-methyladenosine (m6A), prominent post-transcriptional modification mRNA in mammalian cells, plays pivotal role regulating various cellular biological processes. Similarly, cuproptosis has garnered attention for its potential implications biology. This study seeks to elucidate the impact m6A- cuproptosis-related long non-coding RNAs (m6aCRLncs) on prognosis patients with EC. Methods The EC transcriptional data corresponding clinical information were retrieved from Cancer Genome Atlas (TCGA) database, comprising 11 normal samples 159 samples. Data 23 m6A regulators 25 genes sourced latest literature. m6aCRLncs linked identified through co-expression analysis. Differentially expressed associated screened using limma package R univariate Cox regression Subtype clustering was performed classify patients, enabling investigation differences outcomes immune microenvironment across patient clusters. A risk prognostic model constructed least absolute shrinkage selection operator (LASSO) regression. Its robustness evaluated survival analysis, stratification curves, receiver operating characteristic (ROC) curves. Additionally, model’s applicability features molecular subtypes assessed. To further explore utility predicting microenvironment, single-sample gene set enrichment analysis (ssGSEA), cell infiltration checkpoint differential expression conducted. Drug sensitivity identify therapeutic agents Finally, levels lines validated reverse transcription quantitative polymerase chain reaction (RT-qPCR). Results We developed based five m6aCRLncs, namely ELF3-AS1, HNF1A-AS1, LINC00942, LINC01389, MIR181A2HG, predict characterize patients. Analysis revealed significant cluster distribution, disease stage, N stage between high- low-risk groups. Immune profiling distinct populations functional pathways scores, including positive correlations naive B resting CD4+ T plasma negative macrophages M0 M1. we key checkpoint-related groups, TNFRSF14, TNFSF15, TNFRSF18, LGALS9, CD44, HHLA2, CD40. Furthermore, nine candidate drugs efficacy identified: Bleomycin, Cisplatin, Cyclopamine, PLX4720, Erlotinib, Gefitinib, RO.3306, XMD8.85, WH.4.023. RT-qPCR validation demonstrated that ELF3-AS1 significantly upregulated KYSE-30 KYSE-180 compared esophageal epithelial cells. Conclusion elucidates shaping it identifies against These findings hold promise enhancing provide valuable insights inform decision-making management this disease.

Language: Английский

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Big data analysis and machine learning of the role of cuproptosis-related long non-coding RNAs (CuLncs) in the prognosis and immune landscape of ovarian cancer

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 25, 2025

Ovarian cancer (OC) is a severe malignant tumor with significant threat to women's health, characterized by high mortality rate and poor prognosis despite conventional treatments such as cytoreductive surgery platinum-based chemotherapy. Cuproptosis, novel form of cell death triggered copper ion accumulation, has shown potential in therapy, particularly through the involvement CuLncs. This study aims identify risk signatures associated CuLncs OC, construct prognostic model, explore therapeutic drugs impact on OC behavior. We analyzed ovarian data (TCGA-OV) from TCGA database, including transcriptomic clinical 376 patients. Using Pearson correlation LASSO regression, we identified 8 signature model. Patients were categorized into high- low-risk groups based their scores. performed survival analysis, model validation, drug sensitivity vitro experiments assess model's performance functional key proliferation, invasion, migration. The demonstrated predictive power, an area under curve (AUC) 0.702 for 1-year, 0.640 3-year, 0.618 5-year survival, outperforming pathological features stage grade. High-risk patients exhibited higher Tumor Immune Dysfunction Exclusion (TIDE) scores, indicating stronger immune evasion ability. Drugs JQ12, PD-0325901, sorafenib showed reduced IC50 values high-risk group, suggesting benefits. In revealed that knockdown LINC01956, CuLnc signature, significantly inhibited migration cells (P<0.05). Our explored targets OC. findings highlight importance response, providing new insights future research applications.

Language: Английский

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Bioinformatics analysis and experimental validation of m6A and cuproptosis-related lncRNA NFE4 in clear cell renal cell carcinoma

Discover Oncology, Journal Year: 2024, Volume and Issue: 15(1)

Published: May 26, 2024

Abstract Purpose This study aimed to construct an m6A and cuproptosis-related long non-coding RNAs (lncRNAs) signature accurately predict the prognosis of kidney clear cell carcinoma (KIRC) patients using information acquired from The Cancer Genome Atlas (TCGA) database. Methods First, co-expression analysis was performed identify lncRNAs linked with N6-methyladenosine (m6A) cuproptosis in ccRCC. Then, a model encompassing four candidate constructed via univariate, least absolute shrinkage together selection operator (LASSO), multivariate regression analyses. Furthermore, Kaplan–Meier, principal component, functional enrichment annotation, nomogram analyses were develop risk that could effectively assess medical outcomes for ccRCC cases. Moreover, cellular function NFE4 Caki-1/OS-RC-2 cultures elucidated through CCK-8/EdU assessments Transwell experiments. Dataset indicated can have possible implications cuproptosis, may promote progression. Results We panel prognostic prediction model. Kaplan–Meier ROC curves showed feature had acceptable predictive validity TCGA training, test, complete groups. lncRNA higher diagnostic efficiency than other clinical features. gene associated It also revealed proliferation migration Caki-1 /OS-RC-2 cells inhibited knockdown group. Conclusion Overall, this our potential value.

Language: Английский

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Cuproptosis related gene PDHB is identified as a biomarker inversely associated with the progression of clear cell renal cell carcinoma

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

Published: Aug. 28, 2023

Cuproptosis is a newly discovered programmed cell death dependent on mitochondrial respiratory disorder induced by copper overload. Pyruvate dehydrogenase E1 subunit beta (PDHB) one of the cuproptosis genesand nuclear-encoded pyruvate dehydrogenase, which catalyzes conversion to acetyl coenzyme A. However, mechanism PDHB in clear renal carcinoma (ccRCC) remains unclear.We used data from TCGA and GEO assess expression normal tumor tissues. We further analyzed relationship between somatic mutations immune infiltration. Finally, we preliminarily explored impact ccRCC.The level was lower tissue compared with tissue. Meanwhile, also high-grade tumors than low-grade tumors. positively correlated prognosis ccRCC. Furthermore, may be associated decreased risk VHL, PBRM1 KDM5C mutations. In 786-O cells, chloride could promote genes (DLAT, FDX1) inhibit growth. Last but not least, found that proliferation migration ccRCC cells.Our results demonstrated proliferation, invasion might prognostic predictor Targeting this molecular provide new therapeutic strategy for patients advanced

Language: Английский

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