Using a novel gene signature for predicting the efficacy of the transarterial chemoembolization in patients with hepatocellular carcinoma.
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA413131 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Sorafenib has been a cornerstone in hepatocellular carcinoma (HCC) therapy; however, its efficacy is limited, and identifying patients that will respond to sorafenib is challenging. Gene expression data from 33 HCC tumors treated with sorafenib were analyzed to construct a prediction model aimed at identifying patients with greater benefit from sorafenib treatment. The analysis of transcriptome data revealed a 50-gene signature, KUSS50 (Korea University Sorafenib Signature with 50 genes), that exhibited high predictive power in identifying patients responded to sorafenib treatment in a training cohort. Extensive validation across 2 independent cohorts (IMbrave150 and BIOSTORM) given sorafenib demonstrated KUSS50's high specificity in predicting sorafenib response. Genomic analyses identified distinct molecular characteristics linked with KUSS50 subtypes, including an increased mutation rate and activation of ferroptosis, suggesting increased baseline ferroptotic activity in HCCs, which may sensitize them to sorafenib. The benefit subtype also overlapped with those in previously defined genomic HCC subtypes associated with stemness and aggressiveness. Conversely, the non-benefit subtype correlated with -catenin mutations and increased tumor purity, underscoring the biological significance of the signature. In conclusion, KUSS50 is a clinically actionable biomarker for optimizing HCC patient selection for treatment with sorafenib, providing an opportunity to improve outcomes. Further exploration of KUSS50's underlying biology, particularly the involvement of ferroptosis in sorafenib sensitivity, could provide additional therapeutic insights.
2025-12-31 | GSE285625 | GEO
Project description:Introduction: Anoikis is a form of programmed cell death. Anoikis resistance in hepatocellular carcinoma (HCC) promotes cancer cells shedding from the primary tumor site, thus contributing to survival and distant metastasis. However, the prognostic significance of anoikis-related genes (ARGs) and the biological functions of crucial genes in HCC have not been reported. Objectives: This study aimed to construct a model for predicting the outcome of patients with HCC based on ARGs and to investigate the clinicopathological significance and function of Rac family small GTPase 3 (RAC3) in HCC.
2025-05-07 | PXD057450 | Pride
Project description:Finding Sorafenib-Responding Signature in Hepatocellular Carcinoma (HCC)
| PRJNA1204978 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE9843: Gene expression profiling of 91 hepatocellular carcinomas with hepatitis C virus etiology, Samples with "vascular invasion: Yes/No" were included in the study. GSE20017: Gene Signature to Identify Vascular Invasion in Hepatocellular Carcinoma Refer to individual Series
2011-07-30 | E-GEOD-20238 | biostudies-arrayexpress
Project description:The risk of locoregional or distant failure in advanced HPV-negative head and neck squamous cell carcinoma (HNSCC) patients is high. However, no suitable markers for stratification are clinically available. Thus, we aimed to identify a microRNA(miRNA)-signature predicting disease recurrence. For this purpose the miRNA profiles from 162 HNSCC samples were analysed with regard to identification of a low-complex porgnostic signature. The data set consists of a discovery dataset (n=85) and a validation dataset (n=77). The study resulted in a prognostic 5-miRNA signature significantly predicting the relevant clinical endpoint freedom from recurrence.
2018-09-06 | E-MTAB-5793 | biostudies-arrayexpress
Project description:A novel genomic signature predicting FDG uptake in diverse metastatic tumors
| PRJNA421282 | ENA
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
2017-03-19 | GSE96795 | GEO
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
2017-03-19 | GSE96792 | GEO
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
2017-03-19 | GSE96793 | GEO
Project description:Sorafenib is the only approved targeted drug for hepatocellular carcinoma (HCC), but its effect on patients’ survival gain is limited and varies over a wide range depending on patho-genetic conditions. Thus, enhancing the efficacy of sorafenib and finding a reliable predictive biomarker are crucuial to achieve efficient control of HCCs. In this study, we employed a systems approach by combining transcriptome analysis of the mRNA changes in HCC cell lines in response to sorafenib with network analysis to investigate the action and resistance mechanism of sorafenib. Gene ontology and gene set analysis revealed that proteotoxic stress and apoptosis modules are activated in the presence of sorafenib. Further analysis of the endoplasmic reticulum (ER) stress network model combined with in vitro experiments showed that introducing an additional stress by treating the orally active protein disulfide isomerase (PDI) inhibitor (PACMA 31) can synergistically increase the efficacy of sorafenib in vitro and in vivo, which was confirmed using a mouse xenograft model. We also found that HCC patients with high PDI expression show resistance to sorafenib and poor clinical outcomes, compared to the low PDI expression group. These results suggest that PDI is a promising therapeutic target for enhancing the efficacy of sorafenib and can also be a biomarker for predicting sorafenib responsiveness.
2017-03-19 | GSE96794 | GEO