scholarly journals DPP9: Comprehensive In Silico Analyses of Loss of Function Gene Variants and Associated Gene Expression Signatures in Human Hepatocellular Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1637
Author(s):  
Jiali Carrie Huang ◽  
Abdullah Al Emran ◽  
Justine Moreno Endaya ◽  
Geoffrey W. McCaughan ◽  
Mark D. Gorrell ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Tumors ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Nucleotide Polymorphisms ◽  
Loss Of Function ◽  
Poor Survival ◽  
Genomic Databases ◽  
Family Associations

Dipeptidyl peptidase (DPP) 9, DPP8, DPP4 and fibroblast activation protein (FAP) are the four enzymatically active members of the S9b protease family. Associations of DPP9 with human liver cancer, exonic single nucleotide polymorphisms (SNPs) in DPP9 and loss of function (LoF) variants have not been explored. Human genomic databases, including The Cancer Genome Atlas (TCGA), were interrogated to identify DPP9 LoF variants and associated cancers. Survival and gene signature analyses were performed on hepatocellular carcinoma (HCC) data. We found that DPP9 and DPP8 are intolerant to LoF variants. DPP9 exonic LoF variants were most often associated with uterine carcinoma and lung carcinoma. All four DPP4-like genes were overexpressed in liver tumors and their joint high expression was associated with poor survival in HCC. Increased DPP9 expression was associated with obesity in HCC patients. High expression of genes that positively correlated with overexpression of DPP4, DPP8, and DPP9 were associated with very poor survival in HCC. Enriched pathways analysis of these positively correlated genes featured Toll-like receptor and SUMOylation pathways. This comprehensive data mining suggests that DPP9 is important for survival and that the DPP4 protease family, particularly DPP9, is important in the pathogenesis of human HCC.

scholarly journals Associations Between DPP9 Expression, Survival and Gene Expression Signature in Human Hepatocellular Carcinoma: Comprehensive In Silico Analyses

2021 ◽  
Author(s):  
Jiali Carrie Huang ◽  
Abdullah Al Emran ◽  
Justine Moreno Endaya ◽  
Geoffrey W McCaughan ◽  
Mark D Gorrell ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Gene Expression Signature ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Nucleotide Polymorphisms ◽  
Loss Of Function ◽  
Poor Survival ◽  
Liver Tumours ◽  
Genomic Databases ◽  
Cancer Pathogenesis

Dipeptidyl peptidase (DPP) 9, DPP8, DPP4 and fibroblast activation protein (FAP) are the four enzymatically active members of the S9b protease family. Associations of DPP9 with human liver cancer, exonic single nucleotide polymorphisms (SNPs) in DPP9 and loss of function (LoF) variants have not been explored. Human genomic databases including The Cancer Genome Atlas (TCGA) were interrogated to identify DPP9 LoF variants and associated cancers. Survival and gene signature analyses were performed on hepatocellular carcinoma (HCC) data. We found that DPP9 and DPP8 are intolerant to LoF variants. DPP9 LoF variants were most often associated with uterine carcinoma. Two DPP9 intronic SNPs that have been associated with lung fibrosis and COVID-19 were not associated with liver fibrosis or cancer. All four DPP4-like genes were overexpressed in liver tumours and their joint high expression was associated with poor survival in HCC. Increased DPP9 expression was associated with obesity in HCC patients.. High expression of genes that positively correlated with overexpression of DPP4, DPP8, and DPP9 were associated with very poor survival in HCC. Enriched pathways analysis of these positively correlated genes featured Toll-like receptor and SUMOylation pathways. This comprehensive data mining suggests that DPP9 is essential for human survival and the DPP4 protease family is important in cancer pathogenesis.

scholarly journals DDX23 is a Metabolic Regulator in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Jianlong Zhou ◽  
Xiaoming Wang ◽  
Jing Liang ◽  
Chaohui Tan ◽  
Changnan Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Rna Sequencing ◽  
High Expression ◽  
Rna Seq ◽  
Loss Of Function ◽  
Rna Helicases ◽  
Poor Survival ◽  
Hcc Cells

Abstract Background: Although biochemical activities of RNA helicases have been well-studied, physiological meaning of those factors in both normal and disease condition remained to be clarified.Methods: RNA sequencing (RNA-seq) in HCC cells indicated DDX23 are highly expressed in HCC and high expression of DDX23 is responsible for poor survival of HCC patients. Next, The expression of DDX23 was establish for subsequent investigation. The roll of DDX23 in HCC was identified by RNA-seq, RT-qPCR, LC-MS, OCR, ECAR. The effect of DDX23 on proliferative, Cloning information as well as tumorigenicity of transfected cells in mice was examined using loss-of-function experiments.Results: Here, we investigated a new role of RNA helicase in a member of the DEAD box protein family, DDX23 in hepatocellular carcinoma (HCC). RNA level of DDX23 are highly expressed in HCC and high expression of DDX23 is responsible for poor survival of HCC patients. In addition, we demonstrated that DDX23 expression is important for in vitro and in vivo tumorigenesis. RNA sequencing (RNA-seq) in HCC cells indicated that metabolism is the most affected pathway by the DDX23 and most abundant DDX23-interacting RNA are involved in metabolism in HCC, especially glycolysis. Conclusions: These findings provide new insights on the unexpected HCC-related role of DDX23, an opportunities for the development of the therapeutic target which is a master regulator of genes involved in HCC-favorable metabolic reprogram at the RNA level.

scholarly journals Expression and clinical significance of CMTM1 in hepatocellular carcinoma

Open Medicine ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. 217-223
Author(s):  
Xin Song ◽  
Shidong Zhang ◽  
Run Tian ◽  
Chuanjun Zheng ◽  
Yuge Xu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Transmembrane Domain ◽  
Disease Free Survival ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Chi Square ◽  
Tumor Tissues ◽  
The Relationship ◽  
Low Expression

Abstract Background CKLF Like Marvel Transmembrane Domain Containing 1 (CMTM1) plays a role in breast cancer and lung cancer, but studies on the occurrence and development of CMTM1 in hepatocellular carcinoma (HCC) have not been reported. Methods The Cancer Genome Atlas (TCGA) database and immunohistochemistry (IHC) were used to detect CMTM1 expression in HCC tissues. The relationship between CMTM1 expression and the clinicopathological characteristics of HCC patients was analyzed by chi-square test, and the relationship between CMTM1 expression and the prognosis of HCC patients was tested by the Kaplan–Meier model. Results Bioinformatics analysis showed that the mRNA expression of CMTM1 was upregulated in HCC tissues, and low expression of CMTM1 is associated with longer disease-free survival in patients with HCC. Similarly, the survival time of HCC patients in CMTM1 high expression group was significantly shorter than that in CMTM1 low expression group. IHC detection indicated that CMTM1 protein was highly expressed in both HCC and adjacent non-tumor tissues, with a positive expression in 84% (63/75) of HCC tissues and 89.3% (67/75) of adjacent non-tumor tissues. Moreover, CMTM1 expression was related to family history and TNM stage of HCC patients (P < 0.05), but had no relationship with other clinicopathological characteristics. The survival analysis based on IHC results showed that the prognosis of HCC patients in CMTM1 negative group was significantly poorer than that in CMTM1 positive group (P < 0.05). Conclusion CMTM1 has a high expression in HCC tissues and is related to the prognosis of HCC patients.

scholarly journals A stemness-based eleven-gene signature correlates with the clinical outcome of hepatocellular carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Liang Hong ◽  
Yu Zhou ◽  
Xiangbang Xie ◽  
Wanrui Wu ◽  
Changsheng Shi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Molecular Subtypes ◽  
Prognostic Significance ◽  
Predictive Performance ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Cumulative Distribution ◽  
Gene Module ◽  
Expression Levels

Abstract Background Cumulative evidences have been implicated cancer stem cells in the tumor environment of hepatocellular carcinoma (HCC) cells, whereas the biological functions and prognostic significance of stemness related genes (SRGs) in HCC is still unclear. Methods Molecular subtypes were identified by cumulative distribution function (CDF) clustering on 207 prognostic SRGs. The overall survival (OS) predictive gene signature was developed, internally and externally validated based on HCC datasets including The Cancer Genome Atlas (TCGA), GEO and ICGC datasets. Hub genes were identified in molecular subtypes by protein-protein interaction (PPI) network analysis, and then enrolled for determination of prognostic genes. Univariate, LASSO and multivariate Cox regression analyses were performed to assess prognostic genes and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC) curve, Kaplan-Meier curve and nomogram were used to assess the performance of the gene signature. Results We identified four molecular subtypes, among which the C2 subtype showed the highest SRGs expression levels and proportions of immune cells, whereas the worst OS; the C1 subtype showed the lowest SRGs expression levels and was associated with most favorable OS. Next, we identified 11 prognostic genes (CDX2, PON1, ADH4, RBP2, LCAT, GAL, LPA, CYP19A1, GAST, SST and UGT1A8) and then constructed a prognostic 11-gene module and validated its robustness in all three datasets. Moreover, by univariate and multivariate Cox regression, we confirmed the independent prognostic ability of the 11-gene module for patients with HCC. In addition, calibration analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the 11-gene signature. Conclusions Findings in the present study shed new light on the role of stemness related genes within HCC, and the established 11-SRG signature can be utilized as a novel prognostic marker for survival prognostication in patients with HCC.

scholarly journals High Expression of ANXA2 Pseudogene ANXA2P2 Promotes an Aggressive Phenotype in Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Qiu-shuang Wang ◽  
Liang-Liang Shi ◽  
Fei Sun ◽  
Yi-fan Zhang ◽  
Ren-Wang Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Disease Free Survival ◽  
Annexin A2 ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Migration And Invasion ◽  
Targeted Drugs ◽  
Noncancerous Tissue ◽  
Expression Levels ◽  
Hcc Cells

Objective. Accumulating evidence suggests that pseudogenes play potential roles in the regulation of their cognate wild-type genes, oncogenes, and tumor suppressor genes. ANXA2P2 (annexin A2 pseudogene 2) is one of three pseudogenes of annexin A2 that have recently been shown to be aberrantly transcribed in hepatocellular carcinoma (HCC) cells. However, its clinical meaning and biological function in HCC have remained unclear. Therefore, the present study was aimed at exploring the prognostic value of a high expression of ANXA2P2 in HCC tissue and at identifying whether it can affect the efficacy of targeted drugs (sorafenib, regorafenib, and lenvatinib). Methods. We obtained ANXA2P2 mRNA expression levels from The Cancer Genome Atlas (TCGA) RNA sequence database. The expression levels of ANXA2P2 in 49 pairs of intratumoral and peritumoral liver tissues were examined by RT-PCR. Wound healing and transwell assays were performed to confirm the tumor-promoting properties of ANXA2P2 in HCC cells. CCK8 assay was conducted to identify whether ANXA2P2 can affect the growth of HCC cells when administered with targeted drugs (sorafenib, regorafenib, and lenvatinib). Results. The expression of ANXA2P2 in HCC tissues was significantly higher than that in adjacent cancerous tissues from TCGA database and validation group. Additionally, patients with high ANXA2P2 expression in HCC tissue had a shorter overall survival, whereas no statistically significant correlation was found between ANXA2P2 expression and disease-free survival (p=0.08) as well as other clinical parameters, such as age, gender, histological grade, T classification, stage, albumin level, alpha-fetoprotein, and vascular invasion (p=0.7323, 0.8807, 0.5762, 0.8515, 0.7113, 0.242, 1.0000, and 0.7685, respectively). Furthermore, in vitro experiments showed that knockdown of ANXA2P2 inhibited migration and invasion of HCC cells but did not have an influence on the HCC cell proliferation when treated with targeted drugs (sorafenib, regorafenib, and lenvatinib). Conclusion. Our study confirmed elevated ANXA2P2 expression levels in HCC tissue compared with adjacent noncancerous tissue and a worse prognosis of patients with high ANXA2P2 levels in the HCC tissue. The newly found properties of promoting migration and invasion of ANXA2P2 in HCC help to explain this phenomenon. ANXA2P2 could be a novel and suitable predicative biomarker for the risk assessment of recurrence or metastasis of HCC patients but may not be effective to predict the efficacy of targeted drugs.

Upregulation of SGOL2 Predicts Poor Prognosis and Facilitates Hepatocellular Carcinoma Progression via Dysregulating the Cell Cycle by Directly Activating MAD2

2021 ◽  
Author(s):  
Qingqing Hu ◽  
Xiaochu Hu ◽  
Yalei Zhao ◽  
Lingjian Zhang ◽  
Ya Yang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
The Cancer Genome Atlas ◽  
Loss Of Function ◽  
Protein Levels ◽  
Cancer Genome Atlas ◽  
Centromeric Protein ◽  
Hcc Cells

Abstract Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Shugoshin-like protein 2 (SGOL2) is a centromeric protein that ensures the correct and orderly process of mitosis by protecting and maintaining centripetal adhesions during meiosis and mitosis. However, the role of SGOL2 in cancer is not well understood. Methods: The mRNA and protein levels of SGOL2 and survival analysis were conducted in The Cancer Genome Atlas (TCGA) and further validated in 2 independent cohorts. Differential genes correlated with SGOL2 and mitotic arrest deficient 2 like 1 (MAD2) were obtained using LinkedOmics. Subsequently, loss-of-function and rescue assays were carried out in vitro and in vivo to assess the functions of SGOL2 in hepatic tumorigenisis. Findings: We found that SGOL2 was significantly overexpressed in HCC and predicted unfavorable overall survival in HCC patients. Next, we identified 47 differentially expressed genes positively correlated with both SGOL2 and MAD2 to be mainly involved in the cell cycle. In addition, SGOL2 downregulation suppressed the migration, invasion, proliferation, stemness and EMT of HCC cells and inhibited tumorigenesis in vivo. Furthermore, SGOL2 promoted tumor proliferation by activating MAD2-induced cell cycle dysregulation, which could be reversed by the MAD2 inhibitor M2I-1. We also proved that SGOL2 activated MAD2 by directly binding with MAD2. Conclusions: The results of this study showed that SGOL2 acts as an oncogene in HCC cells by directly activating MAD2 and then dysregulating the cell cycle, thereby providing a potential target for HCC patients in the future.

High expression of Golgi phosphoprotein-3 is associated with poor survival in patients with hepatocellular carcinoma

Tumor Biology ◽  
2014 ◽  
Vol 35 (9) ◽  
pp. 8625-8632 ◽  
Author(s):  
Guang-Sheng Hu ◽  
Ying-Qing Li ◽  
Yu-Ming Yang ◽  
Wei Shi ◽  
Ai-Jun Liao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Expression ◽  
Poor Survival

CYP3A5 is unlikely to mediate anticancer drug resistance in hepatocellular carcinoma

2019 ◽  
Vol 20 (15) ◽  
pp. 1085-1092 ◽  
Author(s):  
Volker M Lauschke ◽  
Åsa Nordling ◽  
Yitian Zhou ◽  
Sara Fontalva ◽  
Isabel Barragan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Drug Resistance ◽  
Anticancer Drug ◽  
Liver Tumors ◽  
Relative Increase ◽  
Loss Of Function ◽  
Wide Range ◽  
Peritumoral Tissue ◽  
Anticancer Drug Resistance ◽  
The Relationship

Recently, it was published that CYP3A5 contributes to chemotherapeutic drug resistance in a wide range of solid tumors, including hepatocellular carcinoma. However, CYP3A5 is highly polymorphic and 90% of Caucasians are homozygous for the loss-of-function allele CYP3A5*3. Here, we evaluate the relationship between CYP3A5 genotype and expression level of both CYP3A5 transcripts and protein in biopsies from 19 pairs of liver tumors and corresponding peritumoral tissue. We find that CYP3A5 transcript levels are reduced compared with peritumoral controls. Moreover, we do not detect CYP3A5 protein in homozygous CYP3A5*3 carriers and no relative increase of CYP3A5 in tumoral tissue of CYP3A5*1 carriers. We conclude that anticancer drug resistance is unlikely to be caused by increased CYP3A5 expression.

scholarly journals Novel Hypoxia-Related Gene Signature for Risk Stratification and Prognosis in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Quanxiao Li ◽  
Limin Jin ◽  
Meng Jin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Stratification ◽  
Risk Group ◽  
External Validation ◽  
Gene Signature ◽  
Cancer Genome ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Individual Risk ◽  
Tumor Node Metastasis Stage

Hepatocellular carcinoma (HCC) is the most common form of liver cancer with limited therapeutic options and low survival rate. The hypoxic microenvironment plays a vital role in progression, metabolism, and prognosis of malignancies. Therefore, this study aims to develop and validate a hypoxia gene signature for risk stratification and prognosis prediction of HCC patients. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used as a training cohort, and one Gene Expression Omnibus database (GSE14520) was served as an external validation cohort. Our results showed that eight hypoxia-related genes (HRGs) were identified by the least absolute shrinkage and selection operator analysis to develop the hypoxia gene signature and demarcated HCC patients into the high- and low-risk groups. In TCGA, ICGC, and GSE14520 datasets, patients in the high-risk group had worse overall survival outcomes than those in the low-risk group (all log-rank P &lt; 0.001). Besides, the risk score derived from the hypoxia gene signature could serve as an independent prognostic factor for HCC patients in the three independent datasets. Finally, a nomogram including the gene signature and tumor-node-metastasis stage was constructed to serve clinical practice. In the present study, a novel hypoxia signature risk model could reflect individual risk classification and provide therapeutic targets for patients with HCC. The prognostic nomogram may help predict individualized survival.

scholarly journals Identification of hepatocellular carcinoma prognostic markers based on 10-immune gene signature

2020 ◽  
Vol 40 (8) ◽  
Author(s):  
Kaifei Zhao ◽  
Lin Xu ◽  
Feng Li ◽  
Jin Ao ◽  
Guojun Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Prediction ◽  
Clinical Features ◽  
Risk Model ◽  
Risk Group ◽  
External Validation ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Immune Gene ◽  
Test Set

Abstract Background: Due to the heterogeneity of hepatocellular carcinoma (HCC), hepatocelluarin-associated differentially expressed genes were analyzed by bioinformatics methods to screen the molecular markers for HCC prognosis and potential molecular targets for immunotherapy. Methods: RNA-seq data and clinical follow-up data of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis and Lasso regression were used to identify robust immunity-related genes. Finally, a risk prognosis model of immune gene pairs was established and verified by clinical features, test set and Gene Expression Omnibus (GEO) external validation set. Results: A total of 536 immune-related gene (IRGs) were significantly associated with the prognosis of patients with HCC. Ten robust IRGs were finally obtained and a prognostic risk prediction model was constructed by feature selection of Lasso. The risk score of each sample is calculated based on the risk model and is divided into high risk group (Risk-H) and low risk group (Risk-L). Risk models enable risk stratification of samples in training sets, test sets, external validation sets, staging and subtypes. The area under the curve (AUC) in the training set and the test set were all &gt;0.67, and there were significant overall suvival (OS) differences between the Risk-H and Risk-L samples. Compared with the published four models, the traditional clinical features of Grade, Stage and Gender, the model performed better on the risk prediction of HCC prognosis. Conclusion: The present study constructed 10-gene signature as a novel prognostic marker for predicting survival in patients with HCC.

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