Understanding sorafenib-induced ferroptosis and resistance mechanisms: Implications for cancer therapy

European Journal of Pharmacology, Journal Year: 2023, Volume and Issue: 955, P. 175913 - 175913

Published: July 17, 2023

Language: Английский

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Targeting the regulation of iron homeostasis as a potential therapeutic strategy for nonalcoholic fatty liver disease

Metabolism, Journal Year: 2024, Volume and Issue: 157, P. 155953 - 155953

Published: June 15, 2024

Language: Английский

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AI-Enhanced Comprehensive Liver Tumor Prediction using Convolutional Autoencoder and Genomic Signatures

International Journal of Advanced Computer Science and Applications, Journal Year: 2024, Volume and Issue: 15(2)

Published: Jan. 1, 2024

Liver tumor prediction plays a pivotal role in optimizing treatment strategies and improving patient outcomes. In our proposed work, we present an innovative AI-driven framework for liver prediction, uniting cutting-edge techniques to enhance precision depth of analysis. The integrates Histological Convolutional Autoencoder (HistoCovAE) meticulous segmentation medical imaging, Genomic Feature Extraction (MIRSLiC) nuanced understanding molecular markers. Additionally, Multidimensional module amalgamates videomics, radiomics, acoustics, clinical data, creating comprehensive dataset. These dimensions synergize unified model, offering detailed predictions encompassing characteristics, subtypes, prognosis. Model evaluation continuous improvement, guided by real-world outcomes, underscore reliability. This integrative approach transcends conventional boundaries, providing clinicians’ actionable insights personalized heralding new era prediction. Our model undergoes rigorous against diverse datasets, the performance metrics its reliability accuracy. With exceeding 87%, recall rates above 92%, Dice coefficient surpassing 0.89 segmentation, showcases exceptional accuracy robustness. prognostic modeling, survival consistently surpasses 84%, highlighting model's ability provide valuable into future trajectory cancer.

Language: Английский

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Ferroptosis and hepatocellular carcinoma: the emerging role of lncRNAs

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: May 23, 2024

Hepatocellular carcinoma is the most common form of primary liver cancer and poses a significant challenge to medical community because its high mortality rate. In recent years, ferroptosis, unique cell death, has garnered widespread attention. Ferroptosis, which characterized by iron-dependent lipid peroxidation mitochondrial alterations, closely associated with pathological processes various diseases, including hepatocellular carcinoma. Long non-coding RNAs (lncRNAs), are type functional RNA, play crucial regulatory roles in variety biological processes. this manuscript, we review lncRNAs key aspects summarize research progress on ferroptosis-related

Language: Английский

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Development and validation of cuproptosis-related gene signature in the prognostic prediction of liver cancer

Frontiers in Oncology, Journal Year: 2022, Volume and Issue: 12

Published: Aug. 12, 2022

Liver cancer is a generic term referring to several types arising from the liver. Every year, liver causes lots of deaths and other burdens people all over world. Though techniques in diagnosis therapy have undergone significant advances, current status treating not satisfactory enough. The improvement for prognosis patients will be great supplement treatment cancer. Cuproptosis newly identified regulatory cell death type, which may close connection pathology. Here, we developed prognostic model based on cuproptosis-related mRNAs lncRNAs. This can only effectively predict potential survival patients, but also applied evaluate infiltration immune cell, tumor mutation burden, sensitivity anti-tumor drugs In addition, this has been successfully validated patients’ data. summary, wish become helpful tool clinical use

Language: Английский

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Integrating bioinformatics and experimental validation to unveil disulfidptosis-related lncRNAs as prognostic biomarker and therapeutic target in hepatocellular carcinoma

Cancer Cell International, Journal Year: 2024, Volume and Issue: 24(1)

Published: Jan. 13, 2024

Abstract Background Hepatocellular carcinoma (HCC) stands as a prevalent malignancy globally, characterized by significant morbidity and mortality. Despite continuous advancements in the treatment of HCC, prognosis patients with this cancer remains unsatisfactory. This study aims at constructing disulfidoptosis‑related long noncoding RNA (lncRNA) signature to probe personalized HCC. Methods The data HCC were extracted from Cancer Genome Atlas (TCGA) databases. Univariate, multivariate, least absolute selection operator Cox regression analyses performed build disulfidptosis-related lncRNAs (DRLs) signature. Kaplan–Meier plots used evaluate Functional enrichment analysis was identify key DRLs-associated signaling pathways. Spearman’s rank correlation elucidate association between DRLs immune microenvironment. function TMCC1-AS1 validated two cell lines (HEP3B HEPG2). Results We identified 11 prognostic TCGA dataset, three which selected construct DRLs. found that survival time low-risk considerably longer than high-risk patients. further observed composition subpopulations significantly different high- groups. Additionally, we sorafenib, 5-Fluorouracil, doxorubicin displayed better responses low-score group those high-score group, based on IC50 values. Finally, confirmed inhibition impeded proliferation, migration, invasion hepatocellular cells. Conclusions DRL signatures have been shown be reliable response indicator showed potential novel biomarker therapeutic target for

Language: Английский

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Construction of a Necroptosis-Associated Long Non-Coding RNA Signature to Predict Prognosis and Immune Response in Hepatocellular Carcinoma

Frontiers in Molecular Biosciences, Journal Year: 2022, Volume and Issue: 9

Published: July 13, 2022

Background: Necroptosis is a form of programmed cell death, and studies have shown that long non-coding RNA molecules (lncRNAs) can regulate the process necroptosis in various cancers. We sought to screen lncRNAs associated with predict prognosis tumor immune infiltration status patients hepatocellular carcinoma (HCC). Methods: Transcriptomic data from HCC samples normal tissues were extracted The Cancer Genome Atlas database. Necroptosis-associated obtained by co-expression analysis. then screened Cox regression least absolute shrinkage selection operator methods construct risk model for HCC. models also validated evaluated Kaplan-Meier analysis, univariate multivariate regression, time-dependent receiver operating characteristic (ROC) curves. In addition, Gene Ontology, Kyoto Encyclopedia Genes Genomes enrichment, gene set principal component, correlation, drug sensitivity analyses applied assess groups. To further differentiate microenvironment different subtypes, entire dataset was divided into three clusters, based on necroptosis-associated lncRNAs, series performed. Results: constructed comprising four lncRNAs: POLH-AS1, DUXAP8, AC131009.1, TMCC1-AS1. Overall survival (OS) duration significantly longer classified as low-risk than those who high-risk, according our model. Univariate confirmed score stability. analyzed had area under ROC curve values 0.786, 0.713, 0.639 prediction 1-, 3-, 5-year OS, respectively, ESTIMATE score. differences between high groups predicted half-maximal inhibitory concentration some targeted chemical drugs, providing potential basis treatment approach. Finally, cluster analysis facilitated more refined differentiation may allow effectiveness checkpoint inhibitors. Conclusions: This study contributes understanding function necroptosis-related predicting provide inform immunotherapeutic strategies.

Language: Английский

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An angiogenesis-related three-long non-coding ribonucleic acid signature predicts the immune landscape and prognosis in hepatocellular carcinoma

Heliyon, Journal Year: 2023, Volume and Issue: 9(3), P. e13989 - e13989

Published: Feb. 23, 2023

The tumour microenvironment is a key determinant of the efficacy immunotherapy. Angiogenesis closely linked to immunity. We aimed screen long non-coding ribonucleic acids (lncRNAs) associated with angiogenesis predict prognosis individuals hepatocellular carcinoma (HCC) and characterise immune (TIME). Patient data, including transcriptome clinicopathological parameters, were retrieved from Cancer Genome Atlas database. Moreover, co-expression algorithm was utilized obtain angiogenesis-related lncRNAs. Additionally, survival-related lncRNAs identified using Cox regression least absolute shrinkage selection operator algorithm, which aided in constructing an lncRNA signature (ARLs). ARLs validated Kaplan-Meier method, time-dependent receiver operating characteristic analyses, regression. independent external HCC dataset used for further validation. Then, gene set enrichment analysis, landscape, drug sensitivity analyses implemented explore role ARLs. Finally, cluster analysis divided entire into two clusters distinguish different subtypes TIME. This study provides insight involvement angiogenesis-associated predicting TIME characteristics HCC. Furthermore, developed can HCC, thereby aiding selecting appropriate therapeutic strategies involving checkpoint inhibitors targeted drugs.

Language: Английский

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A disulfidptosis-related lncRNAs signature in hepatocellular carcinoma: prognostic prediction, tumor immune microenvironment and drug susceptibility

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

Published: Jan. 7, 2024

Abstract Disulfidptosis, a novel type of programmed cell death, has attracted researchers’ attention worldwide. However, the role disulfidptosis-related lncRNAs (DRLs) in liver hepatocellular carcinoma (LIHC) not yet been studied. We aimed to establish and validate prognostic signature DRLs analyze tumor microenvironment (TME) drug susceptibility LIHC patients. RNA sequencing data, mutation clinical data were obtained from Cancer Genome Atlas Database (TCGA). Lasso algorithm cox regression analysis performed identify signature. Kaplan–Meier curves, principal component (PCA), nomogram calibration curve, function enrichment, TME, immune dysfunction exclusion (TIDE), burden (TMB), sensitivity analyses analyzed. External datasets used predictive value DRLs. qRT-PCR was also differential expression target tissue samples lines. established for (MKLN1-AS TMCC1-AS1) LIHC. The could divide patients into low- high-risk groups, with subgroup associated worse prognosis. observed discrepancies tumor-infiltrating cells, function, TIDE between two risk groups. group more sensitive several chemotherapeutic drugs. datasets, tissue, lines confirmed MKLN1-AS TMCC1-AS1 upregulated based on provide new insight prediction, potential therapeutic strategies.

Language: Английский

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Identification and validation of cuproptosis-related LncRNA signatures as a novel prognostic model for head and neck squamous cell cancer

Cancer Cell International, Journal Year: 2022, Volume and Issue: 22(1)

Published: Nov. 11, 2022

Head and neck squamous cell cancer (HNSCC) is a common malignant cancer. We aimed to explore prognostic cuproptosis-related lncRNAs (CRLs) risk models for HNSCC.The transcriptome profiles clinical data were obtained from the TCGA database, 19-cuproptosis-related genes (CRGs) acquired previous studies. Then, model based on seven CRLs was established. analysed its value evaluate prognosis, drug sensitivity, tumour immune functions of patients with HNSCC. Finally, we used quantitative reverse transcription polymerase chain reaction (qRT‒PCR) validate CRLs.We established 7-CRL signature. Kaplan‒Meier (K-M) curve analysis demonstrated significantly preferable prognosis in low-risk group. Multivariate Cox regression revealed that score could serve as an independent factor. Nomogram, ROC curve, principal component indicated signature presented significant predictive capability. Moreover, most high-risk group showed lower levels IC50 certain chemotherapy drugs, such cisplatin, cytarabine, docetaxel, doxorubicin, etoposide, gemcitabine, methotrexate, paclitaxel, dasatinib. expression AP001372.2, MIR9-3HG, AL160314.2, POLH-AS1, AL109936.2 upregulated, while AC090587.1 WDFY3-AS2 downregulated HNSCC lines compared normal by qRT‒PCR.The be novel biomarker predicting

Language: Английский

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