Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma

Zheng, Jianglin; Cheng, Qi; Yang, Xiaoyan; Fu, Qin

doi:10.3389/fgene.2022.900713

Cited by 5 publications

(4 citation statements)

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“…identified frequent amplification of USP21 (22%) in human pancreatic ductal adenocarcinoma, and USP21 deubiquitinase promoted pancreatic cancer cell stemness via Wnt pathway activation [ 36 ]. Although there have been studies on hepatocellular carcinoma necrosis genes, validation by PCR alone is not sufficient [ 37 ]. In the present study, we observed high expression of HSP90AA1, PPIA, SQSTM1, and USP21 in HCC tissues by immunohistochemistry experiments, which indirectly validated the value of the necroptosis-related signature in HCC.…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma

Peng

Wang

et al. 2023

PLoS ONE

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Background Necroptosis is a necrotic programmed cell death with potent immunogenicity. Due to the dual effects of necroptosis on tumor growth, metastasis and immunosuppression, we evaluated the prognostic value of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC). Methods We first analyzed RNA sequencing and clinical HCC patient data obtained to develop an NRG prognostic signature based on the TCGA dataset. Differentially expressed NRGs were further evaluated by GO and KEGG pathway analyses. Next, we conducted univariate and multivariate Cox regression analyses to build a prognostic model. We also used the dataset obtained from the International Cancer Genome Consortium (ICGC) database to verify the signature. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the immunotherapy response. Furthermore, we investigated the relationship between the prediction signature and chemotherapy treatment response in HCC. Results We first identified 36 differentially expressed genes out of 159 NRGs in hepatocellular carcinoma. Enrichment analysis showed that they were mainly enriched in the necroptosis pathway. Four NRGs were screened by Cox regression analysis to establish a prognostic model. The survival analysis revealed that the overall survival of patients with high-risk scores was significantly shorter than that of patients with low-risk scores. The nomogram demonstrated satisfactory discrimination and calibration. The calibration curves validated a fine concordance between the nomogram prediction and actual observation. The efficacy of the necroptosis-related signature was also validated by an independent dataset and immunohistochemistry experiments. TIDE analysis revealed that patients in the high-risk group were possibly more susceptible to immunotherapy. Furthermore, high-risk patients were found to be more sensitive to conventional chemotherapeutic medicines such as bleomycin, bortezomib, and imatinib. Conclusion We identified 4 necroptosis-related genes and established a prognostic risk model that could potentially predict prognosis and response to chemotherapy and immunotherapy in HCC patients in the future.

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Section: Discussionmentioning

confidence: 99%

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma

Peng

Wang

et al. 2023

PLoS ONE

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“…For instance, Zhao et al analyzed the prognostic values of necroptosis-associated lncRNA in stomach cancer [ 38 ]. Ren et al constructed a 13-NRG signature for predicting HCC prognosis using univariate cox and lasso cox regression analyses [ 39 ]. However, these prognostic signatures were established only through analysis of public databases and lacked validation in clinical cohorts.…”

Section: Discussionmentioning

confidence: 99%

Exploration and validation of a novel signature of seven necroptosis-related genes to improve the clinical outcome of hepatocellular carcinoma

Tao,

Lang,

et al. 2023

BMC Cancer

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Necroptosis has been reported to be involved in cancer progression and associated with cancer prognosis. However, the prognostic values of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC) remain largely unknown. This study aimed to build a signature on the basis of NRGs to evaluate the prognosis of HCC patients. In this study, using bioinformatic analyses of transcriptome sequencing data of HCC (n = 370) from The Cancer Genome Atlas (TCGA) database, 63 differentially expressed NRGs between HCC and adjacent normal tissues were determined. 24 differentially expressed NRGs were found to be related with overall survival (OS). Seven optimum NRGs, determined using Lasso regression and multivariate Cox regression analysis, were used to construct a new prognostic risk signature for predicting the prognosis of HCC patients. Then survival status scatter plots and survival curves demonstrated that the prognosis of patients with high-Riskscore was worse. The prognostic value of this 7-NRG signature was validated by the International Cancer Genome Consortium (ICGC) cohort and a local cohort (Wenzhou, China). Notably, Riskscore was defined as an independent risk factor for HCC prognosis using multivariate cox regression analysis. Immune infiltration analysis suggested that higher macrophage infiltration was found in patients in the high-risk group. Finally, enhanced 7 NRGs were found in HCC tissues by immunohistochemistry. In conclusion, a novel 7-NRG prognostic risk signature is generated, which contributes to the prediction in the prognosis of HCC patients for the clinicians.

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“…However, gemcitabine, selumetinib, and sorafenib possessed higher IC50 values in the low-risk group. The lower the IC50 value, the more effective the treatment of drugs [ 51 ]. A nomogram integrates the effects of predictors on the outcomes and allows clinicians to predict patient survival by evaluating the whole effect [ 52 ].…”

Section: Discussionmentioning

confidence: 99%

Identification and Analysis of Immune-Related Gene Signature in Hepatocellular Carcinoma

Shen

Zhang

Liu

et al. 2022

Genes

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Background: Hepatocellular carcinoma (HCC) originates from the hepatocytes and accounts for 90% of liver cancer. The study intends to identify novel prognostic biomarkers for predicting the prognosis of HCC patients based on TCGA and GSE14520 cohorts. Methods: Differential analysis was employed to obtain the DEGs (Differentially Expressed Genes) of the TCGA-LIHC-TPM cohort. The lasso regression analysis was applied to build the prognosis model through using the TCGA cohort as the training group and the GSE14520 cohort as the testing group. Next, based on the prognosis model, we performed the following analyses: the survival analysis, the independent prognosis analysis, the clinical feature analysis, the mutation analysis, the immune cell infiltration analysis, the tumor microenvironment analysis, and the drug sensitivity analysis. Finally, the survival time of HCC patients was predicted by constructing nomograms. Results: Through the lasso regression analysis, we obtained a prognosis model of ten genes including BIRC5 (baculoviral IAP repeat containing 5), CDK4 (cyclin-dependent kinase 4), DCK (deoxycytidine kinase), HSPA4 (heat shock protein family A member 4), HSP90AA1 (heat shock protein 90 α family class A member 1), PSMD2 (Proteasome 26S Subunit Ubiquitin Receptor, Non-ATPase 2), IL1RN (interleukin 1 receptor antagonist), PGF (placental growth factor), SPP1 (secreted phosphoprotein 1), and STC2 (stanniocalcin 2). First, we found that the risk score is an independent prognosis factor and is related to the clinical features of HCC patients, covering AFP (α-fetoprotein) and stage. Second, we observed that the p53 mutation was the most obvious mutation between the high-risk and low-risk groups. Third, we also discovered that the risk score is related to some immune cells, covering B cells, T cells, dendritic, macrophages, neutrophils, etc. Fourth, the high-risk group possesses a lower TIDE score, a higher expression of immune checkpoints, and higher ESTIMATE score. Finally, nomograms include the clinical features and risk signatures, displaying the clinical utility of the signature in the survival prediction of HCC patients. Conclusions: Through the comprehensive analysis, we constructed an immune-related prognosis model to predict the survival of HCC patients. In addition to predicting the survival time of HCC patients, this model significantly correlates with the tumor microenvironment. Furthermore, we concluded that these ten immune-related genes (BIRC5, CDK4, DCK, HSPA4, HSP90AA1, PSMD2, IL1RN, PGF, SPP1, and STC2) serve as novel targets for antitumor immunity. Therefore, this study plays a significant role in exploring the clinical application of immune-related genes.

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Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma

Cited by 5 publications

References 64 publications

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma

Exploration and validation of a novel signature of seven necroptosis-related genes to improve the clinical outcome of hepatocellular carcinoma

Identification and Analysis of Immune-Related Gene Signature in Hepatocellular Carcinoma

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