A novel hypoxia-driven gene signature that can predict the prognosis of hepatocellular carcinoma

Zeng, Zhirui; Lei, Shan; Wang, Jingya; Yang, Yuan; Lan, Jinzhi; Tian, Qianting; Chen, Tengxiang; Hao, Xiaojiang

doi:10.1080/21655979.2022.2073943

Cited by 9 publications

(7 citation statements)

References 47 publications

(47 reference statements)

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“…36 Similarly, our previous study indicated that CFHR3 was respond to hypoxia, and reduced in HCC with hypoxic microenvironment. 37 Consistent with previous studies, through qRT-PCR, ADH4, CFHR3, FTCD and PON1 levels were found to reduce in the HCC tissues compared with adjacent tissues, and APOA5, CXCL8 and G6PD expression was elevated. It is worth noting that the risk model constructed by them exhibited higher diagnostic value than each single genes.…”

Section: Discussionsupporting

confidence: 91%

“…Elevated G6PD was observed in HCC tissues, while it promotes the progression of HCC via suppressing ferroptosis 36 . Similarly, our previous study indicated that CFHR3 was respond to hypoxia, and reduced in HCC with hypoxic microenvironment 37 . Consistent with previous studies, through qRT‐PCR, ADH4 , CFHR3 , FTCD and PON1 levels were found to reduce in the HCC tissues compared with adjacent tissues, and APOA5 , CXCL8 and G6PD expression was elevated.…”

Section: Discussionsupporting

confidence: 86%

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An inflammation‐associated ferroptosis signature optimizes the diagnosis, prognosis evaluation and immunotherapy options in hepatocellular carcinoma

Ruan

Zhang

Lei

et al. 2023

J Cellular Molecular Medi

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Inflammation and ferroptosis crosstalk complexly with immune microenvironment of hepatocellular carcinoma (HCC), thus affecting the efficacy of immunotherapy.Herein, our aim was to identify the inflammation-associated ferroptosis (IAF) biomarkers for contributing HCC. A total of 224 intersecting DEGs identified from different inflammation-and ferroptosis-subtypes were set as IAF genes. Seven of them including ADH4, APOA5, CFHR3, CXCL8, FTCD, G6PD and PON1 were used for construction of a risk model which classified HCC patients into two groups (high and low risk). HCC patients in the high-risk group exhibited shorter survival rate and higher immune score, and were predicted to have higher respond rate in immune checkpoint inhibition (ICI) therapy. Levels of the seven genes were significantly changed in HCC tissues in comparison to adjacent tissues. After inserting the gene expression into the risk model, we found that the risk model exhibited the higher diagnostic value for distinguish HCC tissues compared each single gene. Furthermore, HCC tissues from our research group with high-risk score exhibited more cases of microsatellite instability (MSI), heavier tumour mutational burden (TMB), higher expression level of PDL1 and cells with CD8. Knockdown of APOA5 reduced HCC cell proliferation combining with elevating inflammation and ferroptosis levels. In conclusion, we considered APOA5 maybe a novel target for suppressing HCC via simultaneously elevating inflammation and ferroptosis levels, and signature constructed by seven IAF genes including ADH4, APOA5, CFHR3, CXCL8, FTCD, G6PD and PON1 can act as a biomarker for optimising the diagnosis, prognosis evaluation and immunotherapy options in HCC patients.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 86%

An inflammation‐associated ferroptosis signature optimizes the diagnosis, prognosis evaluation and immunotherapy options in hepatocellular carcinoma

Ruan

Zhang

Lei

et al. 2023

J Cellular Molecular Medi

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“…Overexpression of CFHR3 can affect the proliferation and apoptosis of hepatocellular carcinoma ( 62 ). Recent reports suggest that overexpression of CFHR3 may be a potential strategy for overcoming hypoxia and treating HCC ( 63 ). These studies confirm the significance and plausibility of these prognostic signatures.…”

Section: Discussionmentioning

confidence: 99%

Single-cell transcriptome analysis reveals the metabolic changes and the prognostic value of malignant hepatocyte subpopulations and predict new therapeutic agents for hepatocellular carcinoma

et al. 2023

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BackgroundThe development of HCC is often associated with extensive metabolic disturbances. Single cell RNA sequencing (scRNA-seq) provides a better understanding of cellular behavior in the context of complex tumor microenvironments by analyzing individual cell populations. MethodsThe Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data was employed to investigate the metabolic pathways in HCC. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were applied to identify six cell subpopulations, namely, T/NK cells, hepatocytes, macrophages, endothelial cells, fibroblasts, and B cells. The gene set enrichment analysis (GSEA) was performed to explore the existence of pathway heterogeneity across different cell subpopulations. Univariate Cox analysis was used to screen genes differentially related to The Overall Survival in TCGA-LIHC patients based on scRNA-seq and bulk RNA-seq datasets, and LASSO analysis was used to select significant predictors for incorporation into multivariate Cox regression. Connectivity Map (CMap) was applied to analysis drug sensitivity of risk models and targeting of potential compounds in high risk groups.ResultsAnalysis of TCGA-LIHC survival data revealed the molecular markers associated with HCC prognosis, including MARCKSL1, SPP1, BSG, CCT3, LAGE3, KPNA2, SF3B4, GTPBP4, PON1, CFHR3, and CYP2C9. The RNA expression of 11 prognosis-related differentially expressed genes (DEGs) in normal human hepatocyte cell line MIHA and HCC cell lines HCC-LM3 and HepG2 were compared by qPCR. Higher KPNA2, LAGE3, SF3B4, CCT3 and GTPBP4 protein expression and lower CYP2C9 and PON1 protein expression in HCC tissues from Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. The results of target compound screening of risk model showed that mercaptopurine is a potential anti-HCC drug.ConclusionThe prognostic genes associated with glucose and lipid metabolic changes in a hepatocyte subpopulation and comparison of liver malignancy cells to normal liver cells may provide insight into the metabolic characteristics of HCC and the potential prognostic biomarkers of tumor-related genes and contribute to developing new treatment strategies for individuals.

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“…They further developed a coagulation-related gene risk score to predict patient prognosis and treatment responses (50). Zeng et al developed a hypoxia-driven gene signature for predicting and improving outcomes for HCC patients (51). Liu et al established a prognostic model for HCC with cuproptosis-related genes and the RSF algorithm, which was used for patient risk stratification and treatment beneficiary selection (52).…”

Section: Discussionmentioning

confidence: 99%

“…Zeng et al. developed a hypoxia-driven gene signature for predicting and improving outcomes for HCC patients ( 51 ). Liu et al.…”

Section: Discussionmentioning

confidence: 99%

Identifying the programmed cell death index of hepatocellular carcinoma for prognosis and therapy response improvement by machine learning: a bioinformatics analysis and experimental validation

Shi,

Feng,

Qiu

et al. 2023

Front. Immunol.

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BackgroundDespite advancements in hepatocellular carcinoma (HCC) treatments, the prognosis for patients remains suboptimal. Cumulative evidence suggests that programmed cell death (PCD) exerts crucial functions in HCC. PCD-related genes are potential predictors for prognosis and therapeutic responses.MethodsA systematic analysis of 14 PCD modes was conducted to determine the correlation between PCD and HCC. A novel machine learning-based integrative framework was utilized to construct the PCD Index (PCDI) for prognosis and therapeutic response prediction. A comprehensive analysis of PCDI genes was performed, leveraging data including single-cell sequencing and proteomics. GBA was selected, and its functions were investigated in HCC cell lines by in vitro experiments.ResultsTwo PCD clusters with different clinical and biological characteristics were identified in HCC. With the computational framework, the PCDI was constructed, demonstrating superior prognostic predictive efficacy and surpassing previously published prognostic models. An efficient clinical nomogram based on PCDI and clinicopathological factors was then developed. PCDI was intimately associated with immunological attributes, and PCDI could efficaciously predict immunotherapy response. Additionally, the PCDI could predict the chemotherapy sensitivity of HCC patients. A multilevel panorama of PCDI genes confirmed its stability and credibility. Finally, the knockdown of GBA could suppress both the proliferative and invasive capacities of HCC cells.ConclusionThis study systematically elucidated the association between PCD and HCC. A robust PCDI was constructed for prognosis and therapy response prediction, which would facilitate clinical management and personalized therapy for HCC.

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A novel hypoxia-driven gene signature that can predict the prognosis of hepatocellular carcinoma

Cited by 9 publications

References 47 publications

An inflammation‐associated ferroptosis signature optimizes the diagnosis, prognosis evaluation and immunotherapy options in hepatocellular carcinoma

An inflammation‐associated ferroptosis signature optimizes the diagnosis, prognosis evaluation and immunotherapy options in hepatocellular carcinoma

Single-cell transcriptome analysis reveals the metabolic changes and the prognostic value of malignant hepatocyte subpopulations and predict new therapeutic agents for hepatocellular carcinoma

Identifying the programmed cell death index of hepatocellular carcinoma for prognosis and therapy response improvement by machine learning: a bioinformatics analysis and experimental validation

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