Unveiling Anoikis‐related genes: A breakthrough in the prognosis of bladder cancer

The Journal of Gene Medicine, Journal Year: 2024, Volume and Issue: 26(1)

Published: Jan. 1, 2024

Abstract Background Bladder cancer (BLCA) is a prevalent malignancy worldwide. Anoikis remains new form of cell death. It necessary to explore Anoikis‐related genes in the prognosis BLCA. Methods We obtained RNA expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases for dimensionality reduction analysis isolated epithelial cells, T cells fibroblasts copy number variation analysis, pseudotime transcription factor based on R package. integrated machine‐learning algorithms develop artificial intelligence‐derived prognostic signature (AIDPS). Results performance AIDPS with clinical indicators was stable robust predicting BLCA showed better every validation dataset compared other models. Mendelian randomization conducted. Single nucleotide polymorphism (SNP) sites rs3100578 (HK2) rs66467677 (HSP90B1) exhibited significant correlation bladder problem (not cancer) cancer, whereasSNP rs947939 (BAD) had between stone cancer. immune infiltration TCGA‐BLCA cohort calculated via ESTIMATE (i.e. Estimation STromal Immune MAlignantTumours using data) algorithm which contains stromal, estimate scores. also found differences IC 50 values Bortezomib_1191, Docetaxel_1007, Staurosporine_1034 Rapamycin_1084 among high‐ low‐risk groups. Conclusions In conclusion, these findings indicated constructed an innovative model high value

Language: Английский

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Death-associated protein 3 in cancer—discrepant roles of DAP3 in tumours and molecular mechanisms

Frontiers in Oncology, Journal Year: 2024, Volume and Issue: 13

Published: Jan. 30, 2024

Cancer, ranks as the secondary cause of death, is a group diseases that are characterized by uncontrolled tumor growth and distant metastasis, leading to increased mortality year-on-year. To date, targeted therapy intercept aberrant proliferation invasion crucial for clinical anticancer treatment, however, mutant expression target genes often leads drug resistance. Therefore, it essential identify more molecules can be facilitate combined therapy. Previous studies showed death associated protein 3 (DAP3) exerts pivotal role in regulating apoptosis signaling tumors, meanwhile, DAP3 with tumorigenesis disease progression various cancers. This review provides an overview molecule structure discrepant roles played types tumors. Considering molecular mechanism DAP3-regulated cancer development, new potential treatment strategies might developed future.

Language: Английский

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HMGB1 promotes mitochondrial transfer between hepatocellular carcinoma cells through RHOT1 and RAC1 under hypoxia

Cell Death and Disease, Journal Year: 2024, Volume and Issue: 15(2)

Published: Feb. 20, 2024

Mitochondrial transfer plays an important role in various diseases, and many mitochondrial biological functions can be regulated by HMGB1. To explore the of hepatocellular carcinoma (HCC) its relationship with HMGB1, field emission scanning electron microscopy, immunofluorescence, flow cytometry were used to detect between HCC cells. We found that cells was confirmed using tunnel nanotubes (TNTs). The mitochondria from highly invasive less could enhance migration invasion ability latter. hypoxic conditions increased Then mechanism identified co-immunoprecipitation, luciferase reporter assay, chromatin immunoprecipitation. RHOT1, a transport protein, promoted metastasis during this process. Under hypoxia, HMGB1 further RHOT1 expression increasing NFYA NFYC subunits NF-Y complex. RAC1, protein associated TNTs formation, development. Besides, RAC1 aggregation cell membrane under hypoxia. Finally, changes significance related molecules clinical samples analyzed bioinformatics tissue microarray analyses. patients high or exhibited relatively shorter overall survival period. In conclusion, conditions, formation-related RAC1.

Language: Английский

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Immunotherapy and drug sensitivity predictive roles of a novel prognostic model in hepatocellular carcinoma

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

Published: April 25, 2024

Abstract Hepatocellular carcinoma (HCC) is one of the most significant causes cancer-related deaths in worldwide. Currently, predicting survival patients with HCC and developing treatment drugs still remain a challenge. In this study, we employed prognosis-related genes to develop externally validate predictive risk model. Furthermore, correlation between signaling pathways, immune cell infiltration, immunotherapy response, drug sensitivity, score was investigated using different algorithm platforms HCC. Our results showed that 11 differentially expressed including UBE2C, PTTG1, TOP2A, SPP1, FCN3, SLC22A1, ADH4, CYP2C8, SLC10A1, F9, FBP1 were identified as being related prognosis, which integrated construct prediction model could accurately predict patients’ overall both internal external datasets. Moreover, strong revealed pathway, score. Importantly, novel potential candidate for discovered based on also validated through ex vivo experiments. finds offer perspective prognosis exploration cancer patients.

Language: Английский

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Roles of anoikis in hepatocellular carcinoma: mechanisms and therapeutic potential

Medical Oncology, Journal Year: 2025, Volume and Issue: 42(3)

Published: Jan. 30, 2025

Language: Английский

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HMOX1 as a therapeutic target associated with diabetic foot ulcers based on single‐cell analysis and machine learning

International Wound Journal, Journal Year: 2024, Volume and Issue: 21(3)

Published: March 1, 2024

Diabetic foot ulcers (DFUs) are a serious chronic complication of diabetes mellitus and leading cause disability death in diabetic patients. However, current treatments remain unsatisfactory. Although macrophages associated with DFU, their exact role this disease remains uncertain. This study sought to detect macrophage-related genes DFU identify possible therapeutic targets. Single-cell datasets (GSE223964) RNA-seq (GSM68183, GSE80178, GSE134431 GSE147890) were retrieved from the gene expression omnibus (GEO) database for study. Analysis provided single-cell data revealed distribution macrophage subpopulations DFU. Four independent merged into single cohort further analysed using bioinformatics. included differential (DEG) analysis, multiple machine learning algorithms biomarkers enrichment analysis. Finally, key results validated reverse transcription-quantitative polymerase chain reaction (RT-qPCR) Western bolt. findings RT-qPCR western blot. We obtained 802 Differential analysis yielded 743 DEGs. Thirty-seven macrophage-associated DEGs identified by cross-analysis marker intersections screened cross-analysed four algorithms. HMOX1 was as potentially valuable biomarker. significantly biological pathways such insulin signalling pathway. The showed that overexpressed samples. In conclusion, analytical biomarker our improve understanding mechanism action may be useful developing targeted therapies

Language: Английский

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Develop a prognostic and drug therapy efficacy prediction model for hepatocellular carcinoma based on telomere maintenance-associated genes

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: Feb. 14, 2025

Background Hepatocellular carcinoma (HCC) poses a substantial global health challenge because of its grim prognosis and limited therapeutic options. Telomere maintenance mechanisms (TMM) significantly influence cancer progression, yet their prognostic value in HCC remains largely unexamined. This research aims to establish telomere maintenance-associated genes(TMGs)-based model using transcriptomic clinical data evaluate effectiveness predicting patient outcomes HCC. Methods The identified differentially expressed genes (DEGs) were derived from the analysis information sourced database Cancer Genome Atlas (TCGA) cross-referenced with TMGs. Candidate risk factors initially assessed univariate Cox regression, subsequently followed by LASSO, then refined through multivariate regression prediction model. model’s predictive accuracy was validated Kaplan-Meier(K-M) survival analysis, external validation Gene Expression Omnibus (GEO) dataset. Additionally, nomogram incorporating age tumor stage developed. Tumor mutation burden (TMB), immune profile, drug sensitivity also analyzed. Furthermore, we employed RT-PCR confirm expression levels related TMGs HepG2 cell lines. Results A comprising 3 core constructed, high-risk individuals showing lower overall (OS). association between elevated TMB diminished patients uncovered analysis. Immune profiling indicated notable disparities infiltration among these groups, displaying Dysfunction Exclusion (TIDE) scores, suggesting potential evasion. Conclusion In short, our based on effectively categorized enabling dependable forecasts identification targets for personalized treatment management. Future studies should explore integrating this into practice improve outcomes.

Language: Английский

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BDNF is a prognostic biomarker involved in the immune infiltration of lung adenocarcinoma and associated with programmed cell death

Oncology Letters, Journal Year: 2025, Volume and Issue: 29(4), P. 1 - 24

Published: Feb. 20, 2025

It is well established that genes associated with cell death can serve as prognostic markers for patients cancer. Programmed (PCD) known to play a role in cancer apoptosis and antitumor immunity. With the continuous discovery of new forms PCD, roles PCD lung adenocarcinoma (LUAD) require ongoing evaluation. In present study, mRNA expression data clinical information 15 were extracted from publicly available databases systematically analyzed. Utilizing these data, robust risk prediction model was incorporates six PCD-related (PRGs). Datasets Gene Expression Omnibus database employed validate exhibiting risk-associated characteristics. The PRG-based reliably predicted prognosis LUAD, high-risk group showing poor prognosis, reduced levels immune infiltration molecules diminished human leukocyte antigens. Additionally, relationships among PRGs, somatic mutations, tumor stemness index assessed. Based on characteristics, nomogram constructed, patient stratification performed, small-molecule drug candidates predicted, mutations chemotherapy responses Furthermore, reverse transcription-quantitative PCR used assess PDGs vitro, critical brain-derived neurotrophic factor LUAD development identified through Mendelian randomization, gene knockdown, wound healing, western blot colony formation assays. These findings offer insights into targeted therapies particularly high BDNF expression.

Language: Английский

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Prediction and validation of anoikis-related genes in neuropathic pain using machine learning

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0314773 - e0314773

Published: Feb. 27, 2025

Background Neuropathic pain (NP) can be induced by a variety of clinical conditions, such as spinal cord injury, lumbar disc herniation (LDH), stenosis, diabetes, herpes zoster, and tumors, inflammatory stimuli. The pathogenesis NP is extremely complex. Specifically, in LDH, the herniated nucleus pulposus exerts mechanical pressure on nerve roots, triggering local inflammation consequent NP. Anoikis, special form programmed cell death, closely related to progression In this study, we sought clarify molecular characteristics anoikis-related genes NP, providing novel insights for diagnosis treatment Methods We screened NP-related based GSE124272 dataset obtained 439 from GeneCards database. Through Least Absolute Shrinkage Selection Operator (LASSO) Support Vector Machine (SVM) machine learning algorithms, six key hub were identified: hepatocyte growth factor ( HGF ), matrix metalloproteinase 13 MMP13 c-abl oncogene 1, non-receptor tyrosine kinase ABL1 elastase neutrophil expressed ELANE fatty acid synthase FASN long non-coding RNA Linc00324 ). Functional enrichment analyses, including Gene Ontology (GO) Kyoto Encyclopedia Genes Genomes (KEGG), alongside Set Enrichment Analysis (GSEA) immune infiltration analysis, performed these genes. Additionally, transcription factors potential therapeutic drugs predicted. also used rats construct an model validated analyzed using hematoxylin eosin (H&E) staining, real-time polymerase chain reaction (PCR), Western blotting assays. Results Our data indicated that have diagnostic value patients, confirmed experimental results. Moreover, study elucidated role during identified targeting Conclusion This further explores provides certain reference developing targeted strategies, thereby improving management.

Language: Английский

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Multi-cohort validation based on a novel prognostic signature of anoikis for predicting prognosis and immunotherapy response of esophageal squamous cell carcinoma

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 17, 2025

Immunotherapy is recognized as an effective and promising treatment modality that offers a new approach to cancer treatment. However, identifying responsive patients remains challenging. Anoikis, distinct form of programmed cell death, plays crucial role in progression metastasis. Thus, we aimed investigate prognostic biomarkers based on anoikis their guiding immunotherapy decisions for esophageal squamous carcinoma (ESCC). By consensus clustering, the GSE53624 cohort ESCC was divided into two subgroups anoikis-related genes (ARGs), with significant differences survival outcomes between subgroups. Subsequently, constructed ARGs signature four genes, its reliability accuracy were validated both internally externally. Additional, different risk groups showed notable variances terms response, tumor infiltration, functional enrichment, immune function, mutation burden. Notably, effectiveness predicting response confirmed across multiple cohorts, including GSE53624, GSE53625, TCGA-ESCC, IMvigor210, highlighting potential utility response. In conclusion, has serve innovative dependable biomarker ESCC, facilitating personalized strategies this field, may represent valuable tool decision-making.

Language: Английский

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