Identification and Validation of a Tumor Microenvironment-Related Gene Signature in Hepatocellular Carcinoma Prognosis

Huang, Changjing; Zhang, Chenyue; Sheng, Jie; Wang, Dan; Zhao, Yingke; Qian, Ling; Xie, Lin; Meng, Zhiqiang

doi:10.3389/fgene.2021.717319

Cited by 12 publications

(6 citation statements)

References 54 publications

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“…Previous studies have proven that NQO1, ETV4, BSG, and HMGA1 are highly expressed in HCC (Jin et al, 2019;Teng et al, 2019;Yang et al, 2021;Zheng et al, 2022). In addition, the upregulation of PBK, BIRC5, PLK1, and EZH2 was also validated in HCC tissues (Xiao et al, 2019;Yang et al, 2019;Tian et al, 2020;Huang et al, 2021;Lin et al, 2021;Peng et al, 2021). However, the…”

Section: Dap3 Was Upregulated In Hepatocellular Carcinoma Tissuesmentioning

confidence: 97%

An anoikis-based signature for predicting prognosis in hepatocellular carcinoma with machine learning

et al. 2023

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Background: Hepatocellular carcinoma (HCC) is a common malignancy with high mortality worldwide. Despite advancements in diagnosis and treatment in recent years, there is still an urgent unmet need to explore the underlying mechanisms and novel prognostic markers. Anoikis has received considerable attention because of its involvement in the progression of human malignancies. However, the potential mechanism of anoikis-related genes (ANRGs) involvement in HCC progression remains unclear.Methods: We use comprehensive bioinformatics analyses to determine the expression profile of ANRGs and their prognostic implications in HCC. Next, a risk score model was established by least absolute shrinkage and selection operator (Lasso) Cox regression analysis. Then, the prognostic value of the risk score in HCC and its correlation with clinical characteristics of HCC patients were further explored. Additionally, machine learning was utilized to identify the outstanding ANRGs to the risk score. Finally, the protein expression of DAP3 was examined on a tissue microarray (TMA), and the potential mechanisms of DAP3 in HCC was explored.Results: ANRGs were dysregulated in HCC, with a low frequency of somatic mutations and associated with prognosis of HCC patients. Then, nine ANRGs were selected to construct a risk score signature based on the LASSO model. The signature presented a strong ability of risk stratification and prediction for overall survival in HCC patients.Additionally, high risk scores were closely correlated with unfavorable clinical features such as advanced pathological stage, poor histological differentiation and vascular invasion. Moreover, The XGBoost algorithm verified that DAP3 was an important risk score contributor. Further immunohistochemistry determined the elevated expression of DAP3 in HCC tissues compared with nontumor tissues. Finally, functional analyses showed that DAP3 may promote HCC progression through multiple cancer-related pathways and suppress immune infiltration.Conclusion: In conclusion, the anoikis-based signature can be utilized as a novel prognostic biomarker for HCC, and DAP3 may play an important role in the development and progression of HCC.

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Section: Dap3 Was Upregulated In Hepatocellular Carcinoma Tissuesmentioning

confidence: 97%

An anoikis-based signature for predicting prognosis in hepatocellular carcinoma with machine learning

et al. 2023

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“…BIRC5 appears to be an independent, unfavorable prognostic biomarker in multiple types of tumors and has potential as a clinical target for future cancer therapies 30 . Moreover, BIRC5 has been shown to play a role in the construction of prognostic models for various types of LIHC [31][32][33] , suggesting its potential as a valuable biomarker in the clinical management of cancer. Studies indicated that MMPs are directly or indirectly involved in the regulation of mitochondrial oxidative stress.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of Mitochondrial Oxidative Stress- Related Prognostic Signature with Clinical Characteristics and Immune Filtration in Liver Hepatocellular Carcinoma

Wang,

Zhou,

Zhang

et al. 2024

Preprint

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Mitochondrial oxidative stress plays a critical role in cancer development and progression. However, there is limited research on the relationship between mitochondrial oxidative stress and liver hepatocellular carcinoma (LIHC). Mitochondrial oxidative stress-related genes were collected from Genecards Portal. Prognosis-linked genes (PLGs) were identified by univariate Cox regression analysis. A risk model was constructed based on the PLGs using least absolute shrinkage and selection operator (LASSO) analysis. Receiver operating characteristic (ROC) curves were used to determine the predictive ability of the model. The expression levels of the prognostic genes were verified in the cell lines. We constructed a novel risk model based on 9 prognostic genes (CYP2C19, CASQ2, LPL, TXNRD1, CACNA1S, SLC6A3, OXTR, BIRC5, and MMP1). Survival analysis showed that patients with a low-risk score had a much better overall survival (OS). Prognostic risk score was found to be an independent predictor of prognosis. Patients in the high-risk group had a less favorable tumor microenvironment characterized by a lower degree of immune cell infiltration. In contrast, the low-risk group demonstrated a higher degree of immune cell infiltration, which could potentially contribute to a more effective antitumor immune response. Our investigation reveals the oncogenic role of mitochondrial oxidative stress in LIHC. For the first time, we established a risk prediction model for mitochondrial oxidative stress in patients with LIHC.

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“…BIRC5 appeared to be an independent unfavorable prognostic biomarker in multiple types of tumors and had the potential as a clinical target for future cancer therapy (30). Moreover, BIRC5 had been demonstrated to play a role in constructing prognostic models for various types of LIHC (31)(32)(33), suggesting its potential as a valuable biomarker in the clinical management of cancer. Studies indicated that MMPs were able to be directly or indirectly involved in the regulation of mitochondrial oxidative stress.…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of mitochondrial oxidative stress- related prognostic signature with clinical characters and immune filtration in liver hepatocellular carcinoma

Wang,

Zhou,

Zhang

et al. 2023

Preprint

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Background Mitochondrial oxidative stress has been shown to play a critical role in cancer development and progression. But there was relatively less research on the relationship between mitochondrial oxidative stress and LIHC. Methods Mitochondrial oxidative stress-related genes were collected from Genecards portals. Prognosis-linked genes (PLGs) were identified by univariate Cox regression analysis. A risk model was constructed based on PLGs using the least absolute shrinkage and selection operator (LASSO) analysis. The receiver operational feature (ROC) curve was used to detect the model’s prediction ability. The gene expression level of prognostic genes were verified in cell lines. Results We constructed a novel risk model on the basis of 9 prognostic genes (CYP2C19, CASQ2, LPL, TXNRD1, CACNA1S, SLC6A3, OXTR, BIRC5, and MMP1). The Kaplan-Meier survival analysis showed that patients with a low-risk score had a much better overall survival (OS) rate than those with a high-risk score. The prognostic risk score was determined to be an independent predictor of prognosis. Patients in the high-risk group had a less favorable tumor microenvironment, characterized by a lower degree of immune cell infiltration. In contrast, the low-risk group demonstrated a higher degree of immune cell infiltration, which could potentially contribute to a more effective anti-tumor immune response. Conclusion Our investigation uncovered the oncogenic role of mitochondrial oxidative stress in LIHC. For the first time, we established a risk prediction model for mitochondrial oxidative stress in LIHC.

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Identification and Validation of a Tumor Microenvironment-Related Gene Signature in Hepatocellular Carcinoma Prognosis

Cited by 12 publications

References 54 publications

An anoikis-based signature for predicting prognosis in hepatocellular carcinoma with machine learning

An anoikis-based signature for predicting prognosis in hepatocellular carcinoma with machine learning

Identification and Validation of Mitochondrial Oxidative Stress- Related Prognostic Signature with Clinical Characteristics and Immune Filtration in Liver Hepatocellular Carcinoma

Identification and validation of mitochondrial oxidative stress- related prognostic signature with clinical characters and immune filtration in liver hepatocellular carcinoma

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