AURKB as a Promising Prognostic Biomarker in Hepatocellular Carcinoma.
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ABSTRACT:
SUBMITTER: Xiao J
PROVIDER: S-EPMC8637395 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background:Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC. Methods:Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC. Results:AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype. Conclusions:AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.
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Project description:Identifying novel prognostic biomarkers for hepatocellular carcinoma (HCC) and then, develop an effective individualized treatment strategy remain extremely warranted. The prognostic role of sulfiredoxin-1(SRXN1), an antioxidant enzyme, remains unknown in HCC. This study aimed to explore the prognostic implications of SRXN1 in HCC patients after partial hepatectomy. The expression of SRXN1 in HCC and normal tissue were analyzed using the patients from the public databases and Zhongshan Hospital. The Cox regression, Kaplan-Meier survival analysis, and time-dependent receiver operating characteristic curves were performed to identify the predictive role of SRXN1 expression on HCC patients. A prognostic nomogram based on SRXN1 expression was constructed and validated to further confirm the predictive power of SRXN1 as a prognostic biomarker. Finally, functional enrichment analysis and protein-protein interaction network analysis of SRXN1 and its associated genes were conducted. The results showed that SRXN1 was upregulated in HCC samples compared with the normal liver tissues. Patients with SRXN1 upregulation had shorter survival time. SRXN1 overexpression was significantly correlated with advanced clinicopathological parameters. The prognostic nomogram based on SRXN1 expression was proved to be more accurate than routine staging systems for the prediction of overall survival. Protein-protein interaction network analysis demonstrated the first neighbor genes of SRXN1 mainly participated in response to oxidative stress. In brief, SRXN1 could be a prognostic biomarker for the management of HCC.
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Project description:Purpose:This study aimed to explore serum lipoprotein (a) (Lp(a)) levels and investigate their prognostic value in hepatocellular carcinoma (HCC) patients after curative resection. Materials and methods:One cohort of 102 healthy individuals, one cohort of 172 HCC patients, and one cohort of 171 HCC patients undergoing curative resection were studied to evaluate serum Lp(a) levels and their prognostic significance, using Kaplan-Meier curves and log-rank tests. Results:The Lp(a) levels in HCC patients were significantly lower than those in healthy individuals. Furthermore, the levels in HCC patients were significantly associated with recurrence. HCC patients were stratified into high Lp(a) (>20 mg/L) and low Lp(a) (?20 mg/L) groups, using an optimal cutoff point for the Lp(a) of 20 mg/L. Low Lp(a) levels significantly correlated with tumor recurrence and survival time; HCC patients with low Lp(a) levels had higher recurrence rates and shorter survival time than those with high Lp(a) levels; Lp(a) was an independent prognostic factor for relapse-free survival and overall survival, and retained its prognostic value for ?-fetoprotein ?400 ng/mL and tumor size ?5 cm subgroups in the training and validation cohorts. Conclusion:Lp(a) was a promising and useful marker for assessing and monitoring recurrence and prognosis of patients with HCC, and improving Lp(a) levels may be a promising therapeutic strategy in HCC patients.
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Project description:We aimed to examine Notch2 expression in oesophageal squamous cell carcinoma (ESCC) patients and to evaluate its prognostic potential. Immunohistochemical (IHC) staining, quantitative real-time polymerase chain reaction (qRT-PCR) and western blot analysis were utilized to investigate the Notch2 expression status and prognostic value. Furtherly, CCK8 and clonogenic assays were conducted to determine if Notch2 inhibition by shRNA could lead to a decrease in the proliferation and survival of ESCC cells. A notably higher Notch2 expression level was found in ESCC tissues at the mRNA (P < 0.0001) and protein levels (IHC: P = 0.004; western blot: P = 0.021). Log-rank analysis demonstrated that Notch2 overexpression was significantly associated with worse overall survival (OS) (29.1% vs. 49.1%; P = 0.013) and progression-free survival (PFS) (15.3% vs. 34.4%; P = 0.006) rates in ESCC patients. The multivariate analysis revealed Notch2 as an independent prognostic factor for OS and PFS (P = 0.002 and 0.006, resp.). Besides, in vitro assays showed that OD450 values and colony formations were significantly reduced in Notch2-shRNA group (all P < 0.0001). In conclusion, these results show that Notch2 is up-regulated in ESCC tissues and could serve as a promising biomarker for identifying individuals with poor prognostic potential.
| S-EPMC4860585 | biostudies-other
Project description:C-Type Lectin Domain Family 3 Member B (CLEC3B) encodes proteins associated with tumor invasion and metastasis. However, the interrelation between CLEC3B gene expression, tumor immunity, and prognosis of patients with hepatocellular carcinoma (HCC) is unclear. This study was conducted to investigate the prognostic potential of CLEC3B and its association with tumor tissue infiltration markers. CLEC3B expression was examined using the TIMER and Oncomine databases, with its prognostic potential assessed using the GEPIA and Kaplan-Meier plotter databases. The relationship between CLEC3B and tumor immune cell infiltration biomarkers was analyzed using TIMER. Here, we revealed that CLEC3B expression was decreased in HCC and was correlated with a poor survival rate in patients with HCC. Additionally, the expression of CLEC3B was negatively correlated with differential immune cell infiltration and various immune biomarkers. These results indicate a potential mechanism by which the expression of CLEC3B might adjust tumor immunity by modulating the infiltration of HCC immune cells. Our study demonstrated that CLEC3B could be a potential prognostic biomarker and might be involved in tumor immune cell infiltration in HCC.
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Project description:Hepatocellular carcinoma (HCC) is significantly associated with adverse prognostic outcomes. The development and progression of different types of human tumors are significantly influenced by APOB. Nevertheless, the significance and pathomechanisms of APOB in HCC have not been conclusively determined. We assessed APOB expression levels in HCC using three publicly available databases of TIMER2.0, UALCAN and Human Protein Atlas. To identify the biological function of APOB, we conducted enrichment analysis via LinkedOmics. Moreover, UALCAN was employed to assess the relationship between APOB expression and clinicopathological features among HCC patients. Additionally, the Kaplan-Meier plotter was utilized to investigate the prognostic relevance of APOB in HCC. To explore potential regulatory ncRNAs that could bind to APOB, we utilized StarBase and GEPIA. Furthermore, the correlation between APOB expression and immune cell infiltration, as well as immune checkpoint genes, was investigated using Spearman's correlation analysis in TISIDB, GEPIA, and TIMER2.0. The findings of our investigation showed a notable decrease in the expression levels of APOB among individuals diagnosed with HCC. Moreover, a noteworthy correlation was observed between the expression of APOB and immune checkpoint genes, alongside the occurrence of immune cell infiltration. The levels of APOB expression in HCC tissues also showed correlations with various clinicopathological features. According to Cox regression analysis, decreased APOB expression emerged as a potential autonomous predictor for OS, RFS, DSS, and PFS among HCC patients. Furthermore, we identified six potential pathways associated with non-coding RNA (ncRNA) as the most promising pathway for APOB in HCC. Our results illuminate the possible involvement of APOB in HCC and offer understanding into its governing mechanisms and medical importance.
| S-EPMC10838261 | biostudies-literature
Project description:Background: About 90% of liver cancer-related deaths are caused by hepatocellular carcinoma (HCC). N7-methylguanosine (m7G) modification is associated with the biological process and regulation of various diseases. To the best of our knowledge, its role in the pathogenesis and prognosis of HCC has not been thoroughly investigated. Aim: To identify N7-methylguanosine (m7G) related prognostic biomarkers in HCC. Furthermore, we also studied the association of m7G-related prognostic gene signature with immune infiltration in HCC. Methods: The TCGA datasets were used as a training and GEO dataset "GSE76427" for validation of the results. Statistical analyses were performed using the R statistical software version 4.1.2. Results: Functional enrichment analysis identified some pathogenesis related to HCC. We identified 3 m7G-related genes (CDK1, ANO1, and PDGFRA) as prognostic biomarkers for HCC. A risk score was calculated from these 3 prognostic m7G-related genes which showed the high-risk group had a significantly poorer prognosis than the low-risk group in both training and validation datasets. The 3- and 5-years overall survival was predicted better with the risk score than the ideal model in the entire cohort in the predictive nomogram. Furthermore, immune checkpoint genes like CTLA4, HAVCR2, LAG3, and TIGT were expressed significantly higher in the high-risk group and the chemotherapy sensitivity analysis showed that the high-risk groups were responsive to sorafenib treatment. Conclusion: These 3 m7G genes related signature model can be used as prognostic biomarkers in HCC and a guide for immunotherapy and chemotherapy response. Future clinical study on this biomarker model is required to verify its clinical implications.
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Project description:BackgroundA growing body of evidence suggests that E2Fs, by regulating gene expression related to cell cycle progression and other cellular processes, play a pivotal role in human cancer. However, the distinct roles of each E2F in the development and treatment of hepatocellular carcinoma (HCC) remain unknown. In the present study, the mRNA expression and prognostic value of different E2Fs in HCC are analyzed.Materials and methodsTranscriptional and survival data related to E2F expression in patients with HCC were obtained through ONCOMINE and UALCAN databases. Survival analysis plots were drawn with Kaplan-Meier Plotter. The sequence alteration data for E2Fs were obtained from The Cancer Genome Atlas and c-BioPortal. Gene functional enrichment analyses were performed in Database for Annotation, Visualization and Integrated Discovery.ResultsThe mRNA expression levels of E2F1-E2F8 were all significantly upregulated in HCC patients, and high expression of each E2F was obviously related to poor prognosis. Similarly, the expression of E2Fs showed prognostic prediction value in HCC patients with different cancer stages and pathological grades. Moreover, the mutation rate of E2Fs was relatively high in HCC patients, and the DNA sequence alterations primarily occurred in E2F5, E2F3, and E2F6, which were associated with worse overall survival and disease-free survival in HCC patients. Network analysis confirmed that the expression levels of cell cycle-related genes were mostly affected by E2F mutations.ConclusionHigh expression of individual E2Fs was associated with poor prognosis in all liver cancer patients. E2Fs may be exploited as good prognostic targets for comprehensive management of HCC patients, but this notion should be further evaluated in clinical studies.
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Project description:Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors in the world with an increasing number of fatalities. Identification of novel prognosis biomarker for LIHC may improve treatment and therefore patient outcomes. The availability of public gene expression profiling data offers the opportunity to discover prognosis biomarkers for LIHC. We developed an online consensus survival analysis tool named OSlihc using gene expression profiling and long-term follow-up data to identify new prognosis biomarkers. OSlihc consists of 637 cases from four independent cohorts. As a risk assessment tool, OSlihc generates the Kaplan-Meier survival plot with hazard ratio (HR) and p value to evaluate the prognostic value of a gene of interest. To test the reliability of OSlihc, we analyzed 65 previous reported prognostic biomarkers in OSlihc and showed that all of which have significant prognostic values. Furthermore, we identified four novel potential prognostic biomarkers (ATG9A, WIPI1, CXCL1, and CSNK2A2) for LIHC, the elevated expression of which predict the unfavorable survival outcomes. These genes (ATG9A, WIPI1, CXCL1, and CSNK2A2) may be potentially new biomarkers to identify at-risk LIHC patients when further validated. By OSlihc, users can evaluate the prognostic abilities of genes of their interest, which provides a platform for researchers to identify prognostic biomarkers to further develop targeted therapy strategies for LIHC patients. OSlihc is public and free to the users at http://bioinfo.henu.edu.cn/LIHC/LIHCList.jsp.
| S-EPMC7298068 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) is the most common form of liver cancer and the 5-year relative overall survival (OS) rate is less than 20%. Since there are no specific symptoms, most patients with HCC are diagnosed in an advanced stage with poor prognosis. Therefore, identifying novel prognostic biomarkers to improve the survival of patients with HCC is urgently needed. In the present study, we attempted to identify SAMD13 (Sterile Alpha Motif Domain-Containing Protein 13) as a novel biomarker associated with the prognosis of HCC using various bioinformatics tools. SAMD13 was found to be highly expressed pan-cancer; however, the SAMD13 expression was significantly correlated with the worst prognosis in HCC. Clinicopathological analysis revealed that SAMD13 upregulation was significantly associated with advanced HCC stage and high-grade tumor type. Simultaneously, high SAMD13 expression resulted in association with various immune markers in the immune cell subsets by TIMER databases and efficacy of immunotherapy. Methylation analysis showed SAMD13 was remarkably associated with prognosis. Furthermore, a six-hub gene signature associated with poor prognosis was correlated with the cell cycle, transcription, and epigenetic regulation and this analysis may support the connection between SAMD13 expression and drug-resistance. Our study illustrated the characteristics of SAMD13 role in patients with HCC using various bioinformatics tools and highlights its potential role as a therapeutic target and promising biomarker for prognosis in HCC.
| S-EPMC10648382 | biostudies-literature