An anoikis-related gene signature predicts prognosis and reveals immune infiltration in hepatocellular carcinoma

Abstract

BackgroundHepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.Materials and methodsWe downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed via univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The “pRRophetic” R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.ResultsA total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.ConclusionThe novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC.

EZH2 Inhibition Enhances PD‐L1 Protein Stability Through USP22‐Mediated Deubiquitination in Colorectal Cancer

“…[ 15 , 16 , 39 ] Therefore, this study indicates that combination with immune therapy can compensate for the immunosuppressive effect of EZH2 inhibitors and exert synergistic antitumor effects. In addition, EZH2 is positively correlated with MSI‐H or TMB in pan‐cancer, [ 40 , 41 , 42 ] indicating a greater therapeutic potential for EZH2 inhibitors as well as higher sensitivity to immunotherapy, thereby further implying the rationality of the combination approach. In addition, recent studies have reported that PD‐L2 expressed by dendritic cells (DCs) can also modulate tumor immunity and attenuate the sensitivity of tumors to immunotherapy.…”

Comprehensive analysis of anoikis‐related lncRNAs for predicting prognosis and response of immunotherapy in hepatocellular carcinoma

“…Consequently, the application of an anoikis-related model may prove useful in predicting the prognosis of patients with HCC. For instance, Chen et al developed an innovative signature consisting of three anoikis-related genes (EZH2, KIF18A and NQO1), which demonstrated the ability to predict prognosis and provide valuable insights into personalised treatment strategies for HCC patients [39]. Furthermore, another study identified a prognostic signature based on anoikis-related genes that exhibited significant efficacy in predicting OS and may contribute to a better understanding of the molecular mechanisms and treatment options for HCC [28].…”

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

“…As for kinesin-8 family members, KIF18A was identified as an underlying prognostic biomarker exploited via bioinformatic analyses in multiple studies and was demonstrated to be closely associated with HCC malignancy [ 73 , 92 – 94 ]. KIF18A-mediated HCC promotion might be correlated with several abnormally activated signaling pathways, including the Akt/MMP7/9 axis to stimulate tumor invasion and migration, and the CyclinB1-related axis to promote proliferation [ 95 ].…”