Identification of Prognostic Glycolysis-Related lncRNA Signature in Tumor Immune Microenvironment of Hepatocellular Carcinoma

Bai, Yang; Lin, Hanyang; Chen, Jiaqi; Wu, Yulian; Yu, Shi-an

doi:10.3389/fmolb.2021.645084

Cited by 33 publications

(24 citation statements)

References 54 publications

(60 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, it was reported that HCC forms a unique immune microenvironment in the process of development 40 . The study elucidated the crucial role of immune cell infiltration and immunotherapy, which might contribute to clinical strategies and clinical outcome prediction of HCC 41 . It has been reported that the inflammatory cells such as T lymphocytes activate HSCs, which are the major source of myofibroblasts in the liver 42 .…”

Section: Discussionmentioning

confidence: 99%

β-arrestin2 regulating β2-adrenergic receptor signaling in hepatic stellate cells contributes to hepatocellular carcinoma progression

Li¹,

Peng²,

Shan³

et al. 2021

J. Cancer

View full text Add to dashboard Cite

Background: β-arrestin2 and β2-adrenergic receptor (β2-AR) have important roles in malignant tumors, the present study aims to investigate the role of activated β2-AR in hepatic stellate cells (HSCs) during hepatocellular carcinoma (HCC) progression and the regulatory effect of β-arrestin2. Methods: Immunofluorescence and Western blot were used to detect the expression of β-arrestin2 and β2-AR in HSCs of liver tissues from human HCC samples and diethylnitrosamine (DEN)-induced HCC model mice. We next used β-arrestin2 -/- mice to demonstrate the regulatory role of β-arrestin2 in DEN mice. The subsets of T cells were quantified by flow cytometry. MTT and wound healing assay were applied to detect the proliferation and migration of cells. Co-immunoprecipitation assay was used to detect the link of β-arrestin2 and β2-AR in HSCs. Effect of β-arrestin2 overexpression on β2-AR downstream signaling pathway was verified by Western blot. The secretion of CCL2 was detected by ELISA. Results: The expression of β2-AR was significantly increased, while β-arrestin2 was decreased in HSCs of HCC tissues. And β-arrestin2 deficiency exacerbates DEN-induced HCC accompanied with increased β2-AR expression. The results of flow cytometry showed that the percentage of activated T cells decreased gradually after DEN injection. β-arrestin2 knockout down-regulated the ratio of activated T cells. In vitro , selective activation of β2-AR in HSCs promoted the proliferation and migration of HCC cells. β-arrestin2 overexpression enhanced co-immunoprecipitation of β-arrestin2 and β2-AR in activated HSCs, and decreased its downstream Akt phosphorylation. Akt inhibitor decreased secretion of CCL2 in activated HSCs. Conclusion: Our study demonstrated that β2-AR activation in HSCs induces the proliferation and migration of HCC cells may be through Akt signaling, and this effect appears to be regulated by β-arrestin2.

show abstract

Section: Discussionmentioning

confidence: 99%

β-arrestin2 regulating β2-adrenergic receptor signaling in hepatic stellate cells contributes to hepatocellular carcinoma progression

Li¹,

Peng²,

Shan³

et al. 2021

J. Cancer

View full text Add to dashboard Cite

show abstract

“…Finally, we compared the resulting GIlncSig to the latest published signatures related to lncRNAs; the first signature is the 4-lncRNA signature (BailncSig), and the second signature is the 3-lncRNA signature (LilncSig). The results showed that the AUCs for BailncSig (Bai et al, 2021), LilncSig (Li et al, 2021), and GILncSig OS were 0.724, 0.671, and 0.727 (Figure 7C). Based on the above results, GlncSig has independent research value in HCC.…”

Section: Independent Prognostic Analysis Of Gilncsigmentioning

confidence: 99%

Development and Validation of Genome Instability-Associated lncRNAs to Predict Prognosis and Immunotherapy of Patients With Hepatocellular Carcinoma

et al. 2022

View full text Add to dashboard Cite

The pathophysiology of hepatocellular carcinoma (HCC) is prevalently related to genomic instability. However, research on the association of extensive genome instability lncRNA (GILnc) with the prognosis and immunotherapy of HCC remains scarce. We placed the top 25% of somatic mutations into the genetically unstable group and placed the bottom 25% of somatic mutations into the genetically stable group, and then to identify different expression of GILnc between the two groups. Then, LASSO was used to identify the most powerful prognostic GILnc, and a risk score for each patient was calculated according to the formula. Based on a computational frame, 245 different GILncs in HCC were identified. An eight GILnc model was successfully established to predict overall survival in HCC patients based on LASSO, then we divided HCC patients into high-risk and low-risk groups, and a significantly shorter overall survival in the high-risk group was observed compared to those in the low-risk group, and this was validated in GSE76427 and Tongji cohorts. GSEA revealed that the high-risk group was more likely to be enriched in cancer-specific pathways. Besides, the GILnc signature has greater prognostic significance than TP53 mutation status alone, and it is capable of identifying intermediate subtype groups existing with partial TP53 functionality in TP53 wild-type patients. Importantly, the high-risk group was associated with the therapeutic efficacy of PD-L1 blockade, suggesting that the development of potential drugs targeting these GILnc could aid the clinical benefits of immunotherapy. Finally, the GILnc signature model is better than the prediction performance of two recently published lncRNA signatures. In summary, we applied bioinformatics approaches to suggest that an eight GILnc model could serve as prognostic biomarkers to provide a novel direction to explore the pathogenesis of HCC.

show abstract

“…For example, Wei et al developed a 20-miRNA signature to predict post-surgery survival in HCC patients [ 16 ]; Nault et al constructed a 5-gene signature to evaluate the overall survival in HCC patients [ 17 ]; Kim et al established a 233-gene signature to predict late recurrence in HCC patients [ 18 ]. Recently, prognostic signatures based on specific groups of genes such as glycolyis-related genes, metabolic-related genes and autophagy-related genes were also reported [ 19 – 21 ]. However, those multi-gene signatures of HCC mainly focus on overall survival and later recurrence, and few multi-gene signatures have been established to predict early recurrence in HCCs.…”

Section: Introductionmentioning

confidence: 99%

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Wei

Han

et al. 2021

BMC Cancer

View full text Add to dashboard Cite

Background Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence. Methods The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database. Results Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group. Conclusions Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients.

show abstract

Identification of Prognostic Glycolysis-Related lncRNA Signature in Tumor Immune Microenvironment of Hepatocellular Carcinoma

Cited by 33 publications

References 54 publications

β-arrestin2 regulating β2-adrenergic receptor signaling in hepatic stellate cells contributes to hepatocellular carcinoma progression

β-arrestin2 regulating β2-adrenergic receptor signaling in hepatic stellate cells contributes to hepatocellular carcinoma progression

Development and Validation of Genome Instability-Associated lncRNAs to Predict Prognosis and Immunotherapy of Patients With Hepatocellular Carcinoma

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Contact Info

Product

Resources

About