Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk.
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ABSTRACT:
SUBMITTER: Kubota N
PROVIDER: S-EPMC7761278 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo explore dermatomyositis signature genes as potential biomarkers of hepatocellular carcinoma and their associated molecular regulatory mechanisms.MethodsBased on the mRNA-Seq data of dermatomyositis and hepatocellular carcinoma in public databases, five dermatomyositis signature genes were screened by LASSO regression analysis and support vector machine (SVM) algorithm, and their biological functions in dermatomyositis with hepatocellular carcinoma were investigated, and a nomogram risk prediction model for hepatocellular carcinoma was constructed and its predictive efficiency was initially evaluated. The immune profile in hepatocellular carcinoma was examined based on the CIBERSORT and ssGSEA algorithms, and the correlation between five dermatomyositis signature genes and tumor immune cell infiltration and immune checkpoints in hepatocellular carcinoma was investigated.ResultsThe expression levels of five dermatomyositis signature genes were significantly altered in hepatocellular carcinoma and showed good diagnostic efficacy for hepatocellular carcinoma, suggesting that they may be potential predictive targets for hepatocellular carcinoma, and the risk prediction model based on five dermatomyositis signature genes showed good risk prediction efficacy for hepatocellular carcinoma and has good potential for clinical application. In addition, we also found that the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through integrin-mediated activation, which in turn regulates the development and progression of hepatocellular carcinoma.ConclusionLY6E, IFITM1, GADD45A, MT1M, and SPP1 are potential predictive targets for new-onset hepatocellular carcinoma in patients with dermatomyositis, and the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through the mediation of integrins to promote the development and progression of hepatocellular carcinoma.
| S-EPMC10233868 | biostudies-literature
Project description:BACKGROUND: Interferon (IFN)-based therapies could eradicate hepatitis C (HCV) and reduce the risk of hepatocellular carcinoma (HCC). However, HCC could still happen after sustained virological response (SVR). We aimed to develop a simple scoring system to predict the risk of HCC development among HCV patients after antiviral therapies. METHODS: From 1999 to 2009, 1879 patients with biopsy-proven HCV infection treated with IFN-based therapies were analyzed. RESULTS: Multivariable analysis showed old age (adjusted HR (aHR)=1.73, 95% CI=1.13-2.65 for aged 60-69 and aHR=2.20, 95% CI=1.43-3.37 for aged ? 70), Male gender (aHR=1.74, 95% CI=1.26-2.41), platelet count <150 × 10(9)/l (HR=1.91, 95% CI=1.27-2.86), ?-fetoprotein ? 20 ng ml(-1) (HR=2.23, 95% CI=1.58-3.14), high fibrotic stage (HR=3.32, 95% CI=2.10-5.22), HCV genotype 1b (HR=1.53, 95% CI=1.10-2.14), and non SVR (HR=2.40, 95% CI=1.70-3.38) were independent risk factors for HCC. Regression coefficients were used to build up a risk score and the accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC). Three groups as low-, intermediate-, and high-risk are classified based on the risk scores. One hundred sixty patients (12.78%) in the derivation and 82 patients (13.08%) in the validation cohort developed HCC with AUC of 79.4%, sensitivity of 84.38%, and specificity of 60.66%. In the validation cohort, the 5-year HCC incidence was 1.81%, 12.92%, and 29.95% in low-, intermediate-, and high-risk groups, with hazard ratios 4.49 in intermediate- and 16.14 in high-risk group respectively. The risk reduction of HCC is greatest in patients with SVR, with a 5-year and 10-year risk reduction of 28.91% and 27.99% respectively. CONCLUSION: The risk scoring system is accurate in predicting HCC development for HCV patients after antiviral therapies.
| S-EPMC3817320 | biostudies-other
Project description:PurposePrediction of hepatocellular carcinoma (HCC) prognosis faced great difficulty due to tumor heterogeneity. We aimed to identify the prognosis-associated molecular subtypes existing in HCC patients and construct an evaluation model based on identified molecular classification.Materials and methodsNon-negative matrix factorization consensus clustering was performed using 371 HCC patients from The Cancer Genome Atlas (TCGA) to identify molecular subtypes, based on the expression profile of the survival-associated genes. Signature genes for different subtypes were identified by Significance Analysis of Microarray and Prediction Analysis for Microarrays. Model for subtype discrimination and prognosis evaluation was established using binary logistic regression. The model and its clinical implications were further validated in GSE5436 cohort and Fujian cohort.ResultsBased on TCGA data, we observed two molecular subtypes with distinct clinical outcomes including significantly different overall survival, tumor differentiation, TNM stage, and vascular invasion (all P<0.05). The existence of these two molecular subtypes was further validated in five other Gene Expression Omnibus datasets. Furthermore, we constructed an evaluation model based on six subtype signature genes, which can discriminate different subtypes with the cutoff of 0.385. Meanwhile, both Cox regression analysis and stratification analysis showed that the calculated continuous prognostic value could also effectively indicate HCC prognosis, regardless of patients' clinical conditions. The prognostic evaluation model was successfully validated in GSE54236 cohort and Fujian cohort.ConclusionTwo prognostic molecular subtypes existed among HCC patients, which provided promising strategies for overcoming HCC heterogeneity and could be utilized in future clinical application for predicting HCC prognosis.
| S-EPMC6225913 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) is the fifth most common cancer and the third leading cause of cancer deaths worldwide, seriously affecting human community health and care. Emerging evidence has shown that aberrant glycosylation is associated with tumor progression and metastasis. However, the role of glycosylation-related genes in HCC has notbeen reported.MethodsWeighted gene coexpression network analysis and non-negative matrix factorization analysis were applied to identify functional modules and molecularm subtypes in HCC. The least absolute shrinkage and selection operator Cox regression was used to construct the glycosylation-related signature. The independent prognostic value of the risk model was confirmed and validated by systematic techniques, including principal component analysis, T-distributed random neighbor embedding analysis, Kaplan-Meier survival analysis, the ROC curve, multivariate Cox regression, the nomogram, and the calibration curve. The single-sample gene set enrichment analysis, gene set variation analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses were evaluated by the immune microenvironment and potential biological processes. The quantitative real-time polymerase chain reaction and immunohistochemistry analysis were used to verify the expression of five genes.ResultsWe identified the glycosylation-related genes with bioinformatics analysis to construct and validate a five-gene signature for the prognosis of HCC patients. Patients with HCC in the high-risk group had a worse prognosis. The risk score could be an independent factor and was associated with clinical features, such as the grade and stage. The nomogram exhibited an accurate score that included the risk score and clinical parameters. The infiltration levels of antitumor cells were upregulated in the low-risk group, including B_cells, Mast_cells, neutrophils, NK_cells, and T_helper_cells. Moreover, glycosylation was more sensitive to immunotherapy, and may play a critical role in the metabolic processes of HCC, such as bile acid metabolism and fatty acid metabolism. In addition, the five-gene messenger RNA (mRNA) and protein expression were overexpressed in HCC cells and tissues.ConclusionsThe glycosylation-related signature is effective for prognostic recognition, immune efficacy evaluation, and substance metabolism in HCC, providing a novel insight for therapeutic target prediction and clinical decision-making.
| S-EPMC9807760 | biostudies-literature
Project description:Hypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also revealed the specific biological and clinical characteristics via bioinformatic methods. The principal component analysis algorithm was employed to develop a hypoxia-associated risk score (HARS). We identified the two hypoxia subtypes: low hypoxia pattern (C1) and high hypoxia pattern (C2). C1 was less sensitive to immunotherapy compared to C2, consistent with the lack of immune cells and immune checkpoints (ICPs) in C1, whereas C2 was the opposite. C2 displayed worse prognosis and higher sensitivity to obatoclax relative to C1, while C1 was more sensitive to sorafenib. The two subtypes also demonstrated subtype-specific genomic variations including mutation, copy number alteration, and methylation. Moreover, we developed and validated a risk signature: HARS, which had excellent performance for predicting prognosis and immunotherapy. We revealed two hypoxia subtypes with distinct biological and clinical characteristics in HCC, which enhanced the understanding of hypoxia pattern. The risk signature was a promising biomarker for predicting prognosis and immunotherapy.
| S-EPMC7846409 | biostudies-literature
Project description:Pancreatic adenocarcinoma (PAAD) has high mortality and a very poor prognosis. Both surgery and chemotherapy have a suboptimal therapeutic effect, and this caused a need to find new approaches such as immunotherapy. Therefore, it is essential to develop a new model to predict patient prognosis and facilitate early intervention. Our study screened out and validated the target molecules based on the TCGA-PAAD dataset. We established the risk signature using univariate and multivariate Cox regression analysis and used GSE62452 and GSE28735 to verify the accuracy and reliability of the model. Expanded application of PAAD-immune-related genes signature (-IRGS) on other datasets was conducted, and the corresponding nomograms were constructed. We also analyzed the correlation between immune-related cells/genes and potential treatments. Our research demonstrated that a high riskscore of PAAD-IRGS in patients with PAAD was correlated with poor overall survival, disease-specific survival and progression free interval. The same results were observed in patients with LIHC. The models constructed were confirmed to be accurate and reliable. We found various correlations between PAAD-IRGS and immune-related cells/genes, and the potential therapeutic agents. These findings indicate that PAAD-IRGS may be a promising indicator for prognosis and of the tumor-immune microenvironment status in PAAD.
| S-EPMC9279485 | biostudies-literature
Project description:BackgroundEmerging evidence suggests that long non-coding RNA (lncRNA) plays a crucial part in the development and progress of hepatocellular carcinoma (HCC). The objective was to develop novel molecular-clinicopathological prediction methods for overall survival (OS) and recurrence of HCC.ResultsAn 8-lncRNA-based classifier for OS and a 14-lncRNA-based classifier for recurrence were developed by LASSO COX regression analysis, both of which had high accuracy. The tdROC of OS-nomogram and recurrence-nomogram indicates the satisfactory accuracy and predictive power. The classifiers and nomograms for predicting OS and recurrence of HCC were validated in the Test and GEO cohorts.ConclusionsThese two lncRNA-based classifiers could be independent prognostic factors for OS and recurrence. The molecule-clinicopathological nomograms based on the classifiers could increase the prognostic value.MethodsHCC lncRNA expression profiles from the cancer genome atlas (TCGA) were randomly divided into 1:1 training and test cohorts. Based on least absolute shrinkage and selection operator method (LASSO) COX regression model, lncRNA-based classifiers were established to predict OS and recurrence, respectively. OS-nomogram and recurrence-nomogram were developed by combining lncRNA-based classifiers and clinicopathological characterization to predict OS and recurrence, respectively. The prognostic value was accessed by the time-dependent receiver operating characteristic (tdROC) and the concordance index (C-index).
| S-EPMC7377850 | biostudies-literature
Project description:Liver cancer is the sixth most commonly occurring cancer and costs millions of lives per year. The diagnosis of hepatocellular carcinoma (HCC) has relied on scanning techniques and serum-based markers such as α-fetoprotein. These measures have limitations due to their detection limits and asymptomatic conditions during the early stages, resulting in late-stage cancer diagnosis where targeted chemotherapy or systemic treatment with sorafenib is offered. However, the aid of conventional therapy for patients in the advanced stage of HCC has limited outcomes. Thus, it is essential to seek a new treatment strategy and improve the diagnostic techniques to manage the disease. Researchers have used the omics profile of HCC patients for sub-classification of tissues into different groups, which has helped us with prognosis. Despite these efforts, a promising target for treatment has not been identified. The hurdle in this situation is genetic and epigenetic variations in the tumor, leading to disparities in response to treatment. Understanding reversible epigenetic changes along with clinical traits help to define new markers for patient categorization and design personalized therapy. Many clinical trials of inhibitors of epigenetic modifiers (also known as epi-drugs) are in progress. Epi-drugs like azacytidine or belinostat are already approved for other cancer treatments. Furthermore, epigenetic changes have also been observed in drug-resistant HCC tumors. In such cases, combinatorial treatment of epi-drugs with systemic therapy or trans-arterial chemoembolization might re-sensitize resistant cells.
| S-EPMC8637668 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is an aggressive gastrointestinal malignancy with a high rate of mortality. Multiple studies have individually recognized members of RAP gene family as critical regulators of tumor progression in several cancers, including hepatocellular carcinoma. These studies suffer numerous limitations including a small sample size and lack of analysis of various clinicopathological and molecular features. In the current study, we utilized authoritative multi-omics databases to determine the association of RAP gene family expression and detailed molecular and clinicopathological features in hepatocellular carcinoma (HCC). All five RAP genes were observed to harbor dysregulated expression in HCC compared to normal liver tissues. RAP2A exhibited strongest ability to differentiate tumors from the normal tissues. RAP2A expression was associated with progressive tumor grade, TP53 and CTNNB1 mutation status. Additionally, RAP2A expression was associated with the alteration of its copy numbers and DNA methylation. RAP2A also emerged as an independent marker for patient prognosis. Further, pathway analysis revealed that RAP2A expression is correlated with tumor-infiltrating immune cell composition and oncogenic molecular pathways, such as cell cycle and cellular metabolism.
| S-EPMC8255377 | biostudies-literature
Project description:The roles of ubiquitin-related genes in hepatocellular carcinoma (HCC) have not been thoroughly investigated. This study aimed to systematically examine ubiquitin-related genes and identify subtypes and stratify prognosis of HCC by using ubiquitin-related signatures. Survival, biological processes, tumor microenvironment (TME), and genomic alterations of the HCC subtypes were investigated. Patients with HCC were classified into two subtypes (clusters 1 and 2) with distinct survival outcomes, pathways, and genomic alterations. Cluster 2 had better prognosis than did cluster 1. Hepatitis B, hepatitis C, Janus tyrosine kinase (JAK)-signal transducer and activator of transcription (STAT) pathway, and natural killer cell-mediated cytotoxicity were enriched in cluster 1. Moreover, cluster 2 had a higher immune score and immune cell infiltrations, whereas cluster 1 had a lower immune score and immune infiltrations. Additionally, mutations, amplifications, and deletions among the phosphatidylinositol 3-kinase (PI3K)-AKT, p53, and receptor tyrosine kinase (RTK)-RAS pathways more frequently occurred in cluster 1, while those among the Hippo, MYC, and Notch signaling pathways were found in cluster 2. Finally, a prognostic signature, consisting of eight ubiquitin-related genes, was established and validated. In brief, our study established a new classification and developed a prognostic signature for HCC.
| S-EPMC8138213 | biostudies-literature