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. 2025 Jan 21;16(1):69.
doi: 10.1007/s12672-024-01551-7.

NOL-7 serves as a potential prognostic-related biomarker for hepatocellular carcinoma

Affiliations

NOL-7 serves as a potential prognostic-related biomarker for hepatocellular carcinoma

Qiucheng Lei et al. Discov Oncol. .

Abstract

Background: Nucleolar protein 7 (NOL7), a specific protein found in the nucleolus, is crucial for maintaining cell division and proliferation. While the involvement of NOL7 in influencing the unfavorable prognosis of metastatic melanoma has been reported, its significance in predicting the prognosis of patients with Hepatocellular Carcinoma (HCC) remains unclear.

Methods: Aberrant expression of NOL7 in HCC and its prognostic value were evaluated using multiple databases, including TCGA, GTEx, Xiantao Academic, HCCDB, UALCAN, TISCH, and STRING. Immunohistochemistry (IHC) and quantitative real-time PCR were used to validate NOL7 expression levels in patients with HCC.

Results: NOL7 expression was higher in the HCC samples than in the normal samples (P < 0.05). NOL7 was strongly associated with elevated AFP levels, vascular invasion, TNM stage, poorer tumor differentiation, and poorer survival (all P < 0.05). Elevated NOL7 expression correlated with decreased overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) (all P < 0.05). Multivariate analysis revealed that NOL7 was an independent prognostic factor that was significantly related to OS and DSS. The nomogram showed a good predictive performance based on the calibration plot. In addition, NOL7 expression was significantly correlated with cell cycle modulators, immune checkpoints, and various immune cell populations. In addition, we identified eight potential pathways associated with NOL7 as the most promising pathways for NOL7 in HCC. Low-risk specimens were more sensitive to oxaliplatin, cisplatin, irinotecan, sorafenib, and cytarabine than high-risk specimens.

Conclusion: NOL7 may serve as a potential biomarker for predicting clinical outcomes and may provide guidance for clinical therapy in patients with HCC.

Keywords: Biomarker; Chemosensitivity; Hepatocellular carcinoma; NOL7; Tumor immune microenvironment.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: This study was carried out in line with the principles of the Declaration of Helsinki. The protocol was approved by the institutional review board of The First People’s Hospital of Foshan (approval number: medical ethics 2023 No. 74). All methods have been performed in accordance with the regulations of the Institutional Research Ethics Committee at Foshan First People’ s Hospital. All patients or their authorized family members in the study provided thorough and accurate informed consent prior to inclusion. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
NOL7 mRNA and protein expression in HCC. A NOL7 expression levels in tumor tissues and their matched normal tissues in various cancers in the TCGA cohort. B The NOL7 mRNA expression level in HCC patients was elevated in TCGA databases. C NOL7 expression in tumor tissues and their matched normal tissues from HCC patients in TCGA databases. D Significant differences in NOL7 mRNA levels in HCC and the adjacent normal tissues in TCGA and GTEx databases. E Figure and plot of NOL7 expression in HCC and their matched normal tissues based on the HCCDB database. F ROC curves for classifying HCC versus normal liver tissue in TCGA databases. G NOL7 protein levels in HCC patents from UALCAN database (P < 0.001). *P < 0.05, **P < 0.01, ***P < 0.001
Fig. 2
Fig. 2
NOL7 expression from our validation set. A qRT-PCR, using t-tests of unpaired samples. B qRT-PCR, using t-test paired samples. C HE images of HCC tumor tissue and adjacent noncancerous tissue (left). D IHC images and expression of NOL7 protein in HCC tumor tissues and adjacent noncancerous tissues (right), Magnification =  × 400, The positive stain appears brown. E Using t-tests of unpaired samples. F Using a paired t-test sample. *P < 0.05, **P < 0.01, ***P < 0.001
Fig. 3
Fig. 3
Multifaceted prognostic value of NOL7 in the training set. A Expression of NOL7 in different pathologic T stages in HCC. B Expression of NOL7 in different histologic stages in HCC. C Expression of NOL7 in different histologic grades in HCC. D Cox regression model estimates OS, DSS (E) and PFI (F) based on NOL7 mRNA levels in TCGA databases. *P < 0.05, **P < 0.01, ***P < 0.001
Fig. 4
Fig. 4
A Independent risk factors were evaluated for OS using multivariate Cox regression and were combined into the nomogram model. B ROC curves and nomogram AUC values for predicting 1-, 3-, and 5-year OS for HCC patients in the TCGA cohort. C Calibration charts for the nomogram depicting 1-year, 3-year and 5-year OS. D Independent risk factors were evaluated for DSS using multivariate Cox regression and were combined into the nomogram model. E ROC curves and nomogram AUC values for predicting 1-, 3-, and 5-year DSS for HCC patients in the TCGA cohort. F Calibration charts for the nomogram depicting 1-year, 3-year and 5-year DSS
Fig. 5
Fig. 5
Functional validation of NOL7 and potential pathway enrichment analysis. A Volcano plot for co-expressed genes associated with NOL7 expression. B The top 30 genes positively associated with NOL7 and the top 30 genes negatively associated with NOL7 in HCC (C). D GO/KEGG pathway analysis of 300 genes that had the strongest positive association with NOL7. E KEGG pathway analysis revealed 5 positively correlated pathways, and (F) KEGG pathway analysis showed 5 negatively correlated pathways, P < 0.05. G TMB was significantly linked to NOL7 expression. H A PPI network of NOL7 using the STRING tool. I NOL7 and 9 immune checkpoints and 15 core cell cycle modulators in HCC. ICI-related gene: LAG3、IDO1、CD47、CD274、CD276、CTLA4、TIGIT、PDCD1、HAVCR2. Cell cycle modulator: CDK1、CDK4、CDK2、CDK6、CCNB1、CCNA1、CCND2、CCND1、CCND3、CDKN2A、CDKN2B、CDKN2C、CDKN2D、E2F1、RB1; P < 0.001
Fig. 6
Fig. 6
Comparison of immune checkpoints (A) and cell cycle modulators (B) between high and low NOL7 groups in HCC. *P <0.05, **P <0.01, ***P <0.001, ****P <0.0001, ns no significant
Fig. 7
Fig. 7
Infiltration of immune cells and NOL7 expression levels. A Correlation of NOL7 expression with StromalScore, ESTIMATEScore and ImmuneScore. B Relationship between NOL7 and TILs abundance. CF Correlation of NOL7 expression with immune cell enrichment fraction.GJ Comparing groups with high and low expression of NOL7 in terms of immune infiltration levels. *P < 0.05, **P < 0.01, ***P < 0.001, ns no significant
Fig. 8
Fig. 8
NOL7-related cell type distribution using the TISCH database. A Cell types and their distribution in the four datasets. B Distribution of NOL7 in different cells in the four datasets. C The specific distribution of immune cells
Fig. 9
Fig. 9
Correlation plot of the NOL7 mRNA expression with the cell pathway score. AH mRNA expression of NOL7 was positively correlated with the expression of many cell pathway
Fig. 10
Fig. 10
Relationship between NOL7 expression and drug sensitivity. Box plots for estimated IC50 of (A) 5 − fluorouracil, B cyclophosphamide, C afatinib, D gefitinib, E osimertinib, F oxaliplatin, G cisplatin, H irinotecan, I sorafenib, J cytarabine between high and low-risk HCC specimens

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