• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7315-7319
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• 2013

Background: The metastasis gene osteopontin (OPN) is subject to alternative splicing, which yields three messages, osteopontin-a, osteopontin-b and osteopontin-c. Osteopontin-c is selectively expressed in invasive, but not in noninvasive tumors. In the present study, we examined the expression of OPN-c in esophageal squamous cell carcinomas (ESCCs) and assessed its value as a diagnostic biomarker. Methods: OPN-c expression was assessed by immunohistochemistry in 63 ESCC samples and correlated with clinicopathologic factors. Expression was also examined in peripheral blood mononuclear cells (PBMCs) from 120 ESCC patients and 30 healthy subjects. The role of OPN-c mRNA as a tumor marker was investigated by receiver operating characteristic curve (ROC) analysis. Results: Immunohistochemistry showed that OPN-c was expressed in 30 of 63 cancer lesions (48%)and significantly associated with pathological T stage (P=0.038) and overall stage (P=0.023). Real time PCR showed that OPN-c mRNA was expressed at higher levels in the PBMCs of ESCC patients than in those of healthy subjects (P<0.0001) with a sensitivity as an ESCC biomarker of 86.7%. Conclusion: Our findings suggest that expression of OPN-c is significantly elevated in ESCCs and this upregulation could be a potential diagnostic marker.

• Biomedical Science Letters
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• v.28 no.4
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• pp.260-275
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• 2022

Sterile alpha motif (SAM) domains bind to various proteins, lipids, and RNAs. However, these domains have not yet been analyzed as prognostic biomarkers. In this study, SAM domain containing 13 (SAMD13), a member of the SAM domain, was evaluated to identify a novel prognostic biomarker in various human cancers, including hepatocellular carcinoma (HCC). Moreover, we identified a correlation between SAMD13 expression and immune cell infiltration in HCC. We performed bioinformatics analysis using online databases, such as Tumor Immune Estimation Resource, UALCAN, Kaplan-Meier plotter, LinkedOmics, and Gene Expression Profiling Interactive Analysis2. SAMD13 expression in HCC samples was significantly higher than that in normal liver tissue; additionally, SAMD13 was higher in primary tumors, various stages of cancer and grades of tumor, and status of nodal metastasis. Higher SAMD13 expression was also associated with poorer prognosis. SAMD13 expression positively correlated with CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. In the analysis of SAMD13 co-expression networks, positively related genes of SAMD13 were associated with a high hazard ratio in different types of cancer, including HCC. In biological function of SAMD13, SAMD13 mainly include spliceosome, ribosome biogenesis in eukaryote, ribosome, etc. These results suggest that SAMD13 may serve as a novel prognostic biomarker for HCC diagnosis and provide novel insights into tumor immunology in HCC.

• BMB Reports
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• v.57 no.6
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• pp.287-292
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• 2024

Hepatocellular Carcinoma (HCC), the predominant primary hepatic malignancy, is the prime contributor to mortality. Despite the availability of multiple surgical interventions, patient outcomes remain suboptimal. Immunotherapies have emerged as effective strategies for HCC treatment with multiple clinical advantages. However, their curative efficacy is not always satisfactory, limited by the dysfunctional T cell status. Thus, there is a pressing need to discover novel potential biomarkers indicative of T cell exhaustion (Tex) for personalized immunotherapies. One promising target is Cyclin-dependent kinase inhibitor 2 (CDKN2) gene, a key cell cycle regulator with aberrant expression in HCC. However, its specific involvement remains unclear. Herein, we assessed the potential of CDKN2 expression as a promising biomarker for HCC progression, particularly for exhausted T cells. Our transcriptome analysis of CDKN2 in HCC revealed its significant role involving in HCC development. Remarkably, single-cell transcriptomic analysis revealed a notable correlation between CDKN2 expression, particularly CDKN2A, and Tex markers, which was further validated by a human cohort study using human HCC tissue microarray, highlighting CDKN2 expression as a potential biomarker for Tex within the intricate landscape of HCC progression. These findings provide novel perspectives that hold promise for addressing the unmet therapeutic need within HCC treatment.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.6
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• pp.529-537
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• 2019

Lung cancer is the most common cause of cancer deaths worldwide and several molecular signatures have been developed to predict survival in lung cancer. Increasing evidence suggests that proliferation and migration to promote tumor growth are associated with dysregulated ion channel expression. In this study, by analyzing high-throughput gene expression data, we identify the differentially expressed $K^+$ channel genes in lung cancer. In total, we prioritize ten dysregulated $K^+$ channel genes (5 up-regulated and 5 down-regulated genes, which were designated as K-10) in lung tumor tissue compared with normal tissue. A risk scoring system combined with the K-10 signature accurately predicts clinical outcome in lung cancer, which is independent of standard clinical and pathological prognostic factors including patient age, lymph node involvement, tumor size, and tumor grade. We further indicate that the K-10 potentially predicts clinical outcome in breast and colon cancers. Molecular signature discovered through $K^+$ gene expression profiling may serve as a novel biomarker to assess the risk in lung cancer.

• Biomedical Science Letters
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• v.29 no.1
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• pp.11-25
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• 2023

In hepatocellular carcinoma (HCC), chromosome 4 open-reading frame 47 (C4orf47) has not been so far investigated for its prognostic value or association with infiltrating immune cells. We performed bioinformatics analysis on HCC data and analyzed the data using online databases such as TIMER, UALCAN, Kaplan-Meier plotter, LinkedOmics, and GEPIA2. We found that C4orf47 expression in HCC was higher compared to normal tissues. High C4orf47 expression was associated with a worse prognosis in HCC. The correlation between C4orf47 and infiltrating immune cells is positively associated with CD4+T cells, B cells, neutrophils, macrophages, and dendritic cells in HCC. Moreover, high C4orf47 expression was correlated with a poor prognosis of infiltrating immune cells. Analysis of C4orf47 gene co-expression networks revealed that 12501 genes were positively correlated with C4orf47, whereas 7200 genes were negatively correlated. The positively related genes of C4orf47 are associated with a high hazard ratio in different types of cancer, including HCC. Regarding the biological functions of C4orf47 gene, it mainly regulates RNA metabolic process, DNA replication, and cell cycle. The C4orf47 gene may play a prognostic role by regulating the global transcriptome process in HCC. Our findings demonstrate that high C4orf47 expression correlates with poor prognosis and tumor-infiltrating immune cells in HCC. We suggest that C4orf47 is a novel prognostic biomarker and potential immune therapeutic target for HCC.

• Genomics & Informatics
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• v.12 no.4
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• pp.171-180
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• 2014

Aberrant DNA methylation, as an epigenetic marker of cancer, influences tumor development and progression. We downloaded publicly available DNA methylation and gene expression datasets of matched cancer and normal pairs from the Cancer Genome Atlas Data Portal and performed a systematic computational analysis. This study has three aims to screen genes that show hypermethylation and downregulated patterns in colorectal cancers, to identify differentially methylated regions in one of these genes, SFRP1, and to test whether the SFRP genes affect survival or not. Our results show that 31 hypermethylated genes had a negative correlation with gene expression. Among them, SFRP1 had a differentially methylated pattern at each methylation site. We also show that SFRP1 may be a potential biomarker for colorectal cancer survival.

• Journal of Gastric Cancer
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• v.17 no.1
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• pp.43-51
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• 2017

Purpose: This study aimed to analyze G3BP1 and VEZT expression profiles in patients with gastric cancer, and examine the possible relationship between the expressions of each gene and clinicopathological factors. Materials and Methods: Expression of these genes in formalin-fixed paraffin embedded (FFPE) tissues, collected from 40 patients with gastric cancer and 40 healthy controls, was analyzed. Differences in gene expression among patient and normal samples were identified using the GraphPad Prism 5 software. For the analysis of real-time polymerase chain reaction products, GelQuantNET software was used. Results: Our findings demonstrated that both VEZT and G3BP1 mRNA expression levels were downregulated in gastric cancer samples compared with those in the normal controls. No significant relationship was found between the expression of these genes and gender (P-value, 0.4835 vs. 0.6350), but there were significant changes associated with age (P-value, 0.0004 vs. 0.0001) and stage of disease (P-value, 0.0019 vs. 0.0001). In addition, there was a direct relationship between VEZT gene expression and metastasis (P-value, 0.0462), in contrast to G3BP1 that did not demonstrate any significant correlation (P-value, 0.1833). Conclusions: The results suggest that expression profiling of VEZT and G3BP1 can be used for diagnosis of gastric cancer, and specifically, VEZT gene could be considered as a biomarker for the detection of gastric cancer progression.

• Molecules and Cells
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• v.28 no.2
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• pp.99-103
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• 2009

Human endogenous retroviruses (HERVs) have been implicated in the pathogenesis of several human diseases as multi-copy members in the human genome. Their gene expression profiling could provide us with important insights into the pathogenic relationship between HERVs and cancer. In this study, we have evaluated the genomic structure and quantitatively determined the expression patterns in the env gene of a variety of HERV family members located on six specific loci by the RetroTector 10 program, as well as real-time RT-PCR amplification. The env gene transcripts evidenced significant differences in the human tumor/normal adjacent tissues (colon, liver, uterus, lung and testis). As compared to the adjacent normal tissues, high levels of expression were noted in testis tumor tissues for HERV-K, in liver and lung tumor tissues for HERV-R, in liver, lung, and testis tumor tissues for HERV-H, and in colon and liver tumor tissues for HERV-P. These data warrant further studies with larger groups of patients to develop biomarkers for specific human cancers.

• Journal of Microbiology and Biotechnology
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• v.31 no.1
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• pp.123-129
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• 2021

Polyhydroxyalkanoate (PHA) synthase is a key enzyme for PHA production in microorganisms. The class IV PHA synthase is composed of two subunits: PhaC and PhaR. The PhaR subunit, which encodes the phaR gene, is only present in class IV PHA synthases. Therefore, the phaR gene is used as a biomarker for bacteria that contain a class IV PHA synthase, such as some Bacillus spp. The phaR gene was developed to screen phaR-containing Bacillus spp. The phaR screening method involved two steps: phaR gene amplification by PCR and phaR amplicon detection using a DNA lateral flow assay. The screening method has a high specificity for phaR-containing Bacillus spp. The lowest amount of genomic DNA of B. thuringiensis ATCC 10792 that the phaR screening method could detect was 10 pg. This novel screening method improves the specificity and sensitivity of phaR gene screening and reduces the time and cost of the screening process, which could enhance the opportunity to discover good candidate PHA producers. Nevertheless, the screening method can certainly be used as a tool to screen phaR-containing Bacillus spp. from environmental samples.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9367-9373
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• 2014

In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are requentlyused lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.