Dataset Information

Dual roles of WISP2 in the progression of hepatocellular carcinoma: implications of the fibroblast infiltration into the tumor microenvironment.

ABSTRACT: The dismal outcome of hepatocellular carcinoma (HCC) patients is attributable to high frequency of metastasis and. Identification of effective biomarkers is a key strategy to inform prognosis and improve survival. Previous studies reported inconsistent roles of WISP2 in carcinogenesis, while the role of WISP2 in HCC progression also remains unclear. In this study, we confirmed that WISP2 was downregulated in HCC tissues, and WISP2 was acting as a protective factor, especially in patients without alcohol intake using multiple online datasets. In addition, we reported that upregulation of WISP2 in HCC was related to inhibition of the malignant phenotype in vitro, but these alterations were not observed in vivo. WISP2 also negatively correlated with tumour purity, and increased infiltration of fibroblasts promoted malignant progression in HCC tissues. The enhanced infiltration ability of fibroblasts was related to upregulated HMGB1 after overexpression of WISP2 in HCC. The findings shed light on the anticancer role of WISP2, and HMGB1 is one of the key factors involved in the inhibition of the efficiency of WISP2 through reducing the tumour purity with fibroblast infiltration.

SUBMITTER: Jia Q

PROVIDER: S-EPMC8457598 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundEpigenetics regulate gene expression without altering the DNA sequence. Epigenetics targeted chemotherapeutic approach can be used to overcome treatment resistance and low response rate in HCC. However, a comprehensive review of genomic data was carried out to determine the role of epigenesis in the tumor microenvironment (TME), immune cell-infiltration characteristics in HCC is still insufficient.MethodsThe association between epigenetic-related genes (ERGs), inflammatory response-related genes (IRRGs) and CRISPR genes was determined by merging genomic and CRISPR data. Further, characteristics of immune-cell infiltration in the tumor microenvironment was evaluated.ResultsNine differentially expressed genes (ANP32B, ASF1A, BCORL1, BMI1, BUB1, CBX2, CBX3, CDK1, and CDK5) were shown to be independent prognostic factors based on lasso regression in the TCGA-LIHC and ICGC databases. In addition, the results showed significant differences in expression of PDCD-1 (PD-1) and CTLA4 between the high- and low-epigenetic score groups. The CTRP and PRISM-derived drug response data yielded four CTRP-derived compounds (SB-743921, GSK461364, gemcitabine, and paclitaxel) and two PRISM-derived compounds (dolastatin-10 and LY2606368). Patients with high ERGs benefited more from immune checkpoint inhibitor (ICI) therapy than patients with low ERGs. In addition, the high ERGs subgroup had a higher T cell exclusion score, while the low ERGs subgroup had a higher T cell dysfunction. However, there was no difference in microsatellite instability (MSI) score among the two subgroups. Further, genome-wide CRISPR-based loss-of function screening derived from DepMap was conducted to determine key genes leading to HCC development and progression. In total, 640 genes were identified to be essential for survival in HCC cell lines. The protein-protein interaction (PPI) network demonstrated that IRRGs PSEN1 was linked to most ERGs and CRISPR genes such as CDK1, TOP2A, CBX2 and CBX3.ConclusionEpigenetic alterations of cancer-related genes in the tumor microenvironment play a major role in carcinogenesis. This study showed that epigenetic-related novel biomarkers could be useful in predicting prognosis, clinical diagnosis, and management in HCC.

Project description:Accumulating studies have highlighted the biologic significances of ferroptosis modification in tumor progression, but little is known whether ferroptosis modification patterns have potential roles in tumor microenvironment (TME) immune cell infiltration of hepatocellular carcinoma (HCC). In this study, we evaluated 51 ferroptosis regulators and performed consensus clustering algorithm to determine ferroptosis modification patterns and the ferroptosis related gene signature in HCC. Gene set variation analysis (GSVA) was employed to explore biological molecular variations in distinct ferroptosis modification patterns. Single sample gene set enrichment analysis (ssGSEA) algorithm was performed to quantify the relative infiltration levels of various immune cell subsets. Principal component analysis (PCA) algorithm was used to construct the ferroptosisSig score to quantify ferroptosis modification patterns of individual tumors with immune responses. Three distinct ferroptosis modification patterns were identified. GSVA enrichment analysis indicated that three ferroptosis modification subgroups were enriched in different metabolic pathways. ssGSEA analysis determined that 19 of 24 immune infiltrating cells had significant differences in three distinct ferroptosis patterns. A 91-ferroptosis gene signature was constructed to stratify patients into two ferroptosisSig score groups. Patients in the higher ferroptosisSig score were characterized by significantly prolonged survival time compared with patients in the lower ferroptosisSig score group (p < .0001). An immunotherapy cohort confirmed patients with higher ferroptosisSig score determined significant therapeutic advantages and clinical benefits. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of anti-PD/L1 immunotherapy by ferroptosisSig score. Our study indicated the ferroptosis modification played a significant role in TME heterogeneity and complexity. Evaluating the ferroptosis modification pattern of individual tumor could strengthen our cognition of TME infiltration characteristics and guide more effective clinic immunotherapy strategies.

Dataset Information

Dual roles of WISP2 in the progression of hepatocellular carcinoma: implications of the fibroblast infiltration into the tumor microenvironment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets