scholarly journals Microarray Data Mining and Preliminary Bioinformatics Analysis of Hepatitis D Virus-Associated Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Zhe Yu ◽  
Xuemei Ma ◽  
Wei Zhang ◽  
Xiujuan Chang ◽  
Linjing An ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
The Cancer Genome Atlas ◽  
Venn Diagram ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Hepatitis D ◽  
Increased Risk ◽  
Key Genes

Several studies have demonstrated that chronic hepatitis delta virus (HDV) infection is associated with a worsening of hepatitis B virus (HBV) infection and increased risk of hepatocellular carcinoma (HCC). However, there is limited data on the role of HDV in the oncogenesis of HCC. This study is aimed at assessing the potential mechanisms of HDV-associated hepatocarcinogenesis, especially to screen and identify key genes and pathways possibly involved in the pathogenesis of HCC. We selected three microarray datasets: GSE55092 contains 39 cancer specimens and 81 paracancer specimens from 11 HBV-associated HCC patients, GSE98383 contains 11 cancer specimens and 24 paracancer specimens from 5 HDV-associated HCC patients, and 371 HCC patients with the RNA-sequencing data combined with their clinical data from the Cancer Genome Atlas (TCGA). Afterwards, 948 differentially expressed genes (DEGs) closely related to HDV-associated HCC were obtained using the R package and filtering with a Venn diagram. We then performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the biological processes (BP), cellular component (CC), molecular function (MF), and KEGG signaling pathways most enriched for DEGs. Additionally, we performed Weighted Gene Coexpression Network Analysis (WGCNA) and protein-to-protein interaction (PPI) network construction with 948 DEGs, from which one module was identified by WGCNA and three modules were identified by the PPI network. Subsequently, we validated the expression of 52 hub genes from the PPI network with an independent set of HCC dataset stored in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, seven potential key genes were identified by intersecting with key modules from WGCNA, including 3 reported genes, namely, CDCA5, CENPH, and MCM7, and 4 novel genes, namely, CDC6, CDC45, CDCA8, and MCM4, which are associated with nucleoplasm, cell cycle, DNA replication, and mitotic cell cycle. The CDCA8 and stage of HCC were the independent factors associated with overall survival of HDV-associated HCC. All the related findings of these genes can help gain a better understanding of the role of HDV in the underlying mechanism of HCC carcinogenesis.

scholarly journals Novel Biomarker NEDD1 and Its Analysis in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xiaopeng Ding ◽  
Jiahao Yu ◽  
Xin Shi ◽  
Kangwei Li ◽  
Shuoyi Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
External Validation ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Related Data ◽  
Significant Difference

Abstract Background: NEDD1 (NEDD1 Gamma-Tubulin Ring Complex Targeting Factor) plays a crucial impact in regulating cell cycle and the development of scirrhous gastric cancer. However, the role of NEDD1 hasn’t been reported in hepatocellular carcinoma (HCC) so far. The aim of this research is to explore the role of NEDD1 on the development and prognosis of HCC. Methods: HCC-related data were download from The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA) were conducted by the LinkedOmics database. Results: The expression of NEDD1 has significant difference between tumor and adjacent normal tissues in HCC (P＜0.01). We also found that NEDD1 was an independent risk factor in HCC patients (HR 1.643, 95%CI 1.125–2.398; P = 0.01). The study also demonstrated that NEDD1 expression was significantly relevant to the expression of several immune checkpoint genes, including CTLA-4, PD-L1 and PD-1. GSEA revealed that Cell cycle, MicroRNAs in cancer and Ribosome pathways were significantly enriched in NEDD1 overexpression phenotype. By integrating NEDD1 with other relevant factors, we constructed the prognostic nomogram to help the improvement of the prognosis for patients with HCC. The data from the International Cancer Genome Consortium (ICGC) database were used as an independent external validation of our prognostic model. Conclusion: The expression level of NEDD1 was negatively correlated to the prognosis of HCC patients and it may be a promising therapeutic target of HCC, which probably be able to predict the efficacy of immunotherapy for HCC patients.

scholarly journals Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhuolin Li ◽  
Yao Lin ◽  
Bizhen Cheng ◽  
Qiaoxin Zhang ◽  
Yingmu Cai
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Reduction Process ◽  
The Cancer Genome Atlas ◽  
Ppi Network ◽  
Hub Genes ◽  
Gene Interaction Network ◽  
Poor Overall Survival ◽  
Primary Liver Tumor ◽  
Key Genes

BackgroundHepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research.MethodsThe bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network.ResultsWe ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes.ConclusionThe present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.

scholarly journals Bioinformatics analysis to identify the key genes affecting the progression and prognosis of hepatocellular carcinoma

2019 ◽  
Vol 39 (2) ◽  
Author(s):  
Yingai Zhang ◽  
Shunlan Wang ◽  
Jingchuan Xiao ◽  
Hailong Zhou
Keyword(s):  
Hepatocellular Carcinoma ◽  
Primary Liver Cancer ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Ppi Network ◽  
Sequencing Data ◽  
Protein Coding ◽  
Qrt Pcr ◽  
Protein Coding Genes ◽  
Key Genes

Abstract Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer, which has poor outcome. The present study aimed to investigate the key genes implicated in the progression and prognosis of HCC. The RNA-sequencing data of HCC was extracted from The Cancer Genome Atlas (TCGA) database. Using the R package (DESeq), the differentially expressed genes (DEGs) were analyzed. Based on the Cluepedia plug-in in Cytoscape software, enrichment analysis for the protein-coding genes amongst the DEGs was conducted. Subsequently, protein–protein interaction (PPI) network was built by Cytoscape software. Using survival package, the genes that could distinguish the survival differences of the HCC samples were explored. Moreover, quantitative real-time reverse transcription-PCR (qRT-PCR) experiments were used to detect the expression of key genes. There were 2193 DEGs in HCC samples. For the protein-coding genes amongst the DEGs, multiple functional terms and pathways were enriched. In the PPI network, cyclin-dependent kinase 1 (CDK1), polo-like kinase 1 (PLK1), Fos proto-oncogene, AP-1 transcription factor subunit (FOS), serum amyloid A1 (SAA1), and lysophosphatidic acid receptor 3 (LPAR3) were hub nodes. CDK1 interacting with PLK1 and FOS, and LPAR3 interacting with FOS and SAA1 were found in the PPI network. Amongst the 40 network modules, 4 modules were with scores not less than 10. Survival analysis showed that anterior gradient 2 (AGR2) and RLN3 could differentiate the high- and low-risk groups, which were confirmed by qRT-PCR. CDK1, PLK1, FOS, SAA1, and LPAR3 might be key genes affecting the progression of HCC. Besides, AGR2 and RLN3 might be implicated in the prognosis of HCC.

scholarly journals HAMP Downregulation Contributes to Aggressive Hepatocellular Carcinoma via Mechanism Mediated by Cyclin4-Dependent Kinase-1/STAT3 Pathway

Diagnostics ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 48 ◽  
Author(s):  
Ying Shen ◽  
Xin Li ◽  
Yanwei Su ◽  
Shaikh Atik Badshah ◽  
Bin Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Cellular Proliferation ◽  
Flow Cytometric Analysis ◽  
Enrichment Analysis ◽  
Cell Cycle Checkpoints ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Cycle Gene

Background: Hepcidin encoded by HAMP is vital to regulating proliferation, metastasis, and migration. Hepcidin is secreted specifically by the liver. This study sought to examine the functional role of hepcidin in hepatocellular carcinoma (HCC). Methods: Data in the Cancer Genome Atlas database was used to analyze HAMP expression as it relates to HCC prognosis. We then used the 5-ethynyl-20-deoxyuridine (EdU) incorporation assay, transwell assay, and flow cytometric analysis, respectively, to assess proliferation, migration, and the cell cycle. Gene set enrichment analysis (GSEA) was used to find pathways affected by HAMP. Results: HAMP expression was lower in hepatocellular carcinoma samples compared with adjacent normal tissue controls. Low HAMP expression was linked with a higher rate of metastasis and poor disease-free status. Downregulation of HAMP induced SMMC-7721 and HepG-2 cell proliferation and promoted their migration. HAMP could affect the cell cycle pathway and Western blotting, confirming that reduced HAMP levels activated cyclin-dependent kinase-1/stat 3 pathway. Conclusion: Our findings indicate that HAMP functions as a tumor suppressor gene. The role of HAMP in cellular proliferation and metastasis is related to cell cycle checkpoints. HAMP could be considered as a diagnostic biomarker and targeted therapy in HCC.

scholarly journals Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5822 ◽  
Author(s):  
Mu Liu ◽  
Yu-lu Qiu ◽  
Tong Jin ◽  
Yin Zhou ◽  
Zhi-yuan Mao ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Thyroid Carcinoma ◽  
Expression Pattern ◽  
Chromosome Segregation ◽  
Drug Targets ◽  
Anaplastic Thyroid Carcinoma ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Key Genes ◽  
Cancer Testis

Aim Anaplastic thyroid carcinoma (ATC) is the most lethal thyroid malignancy. Identification of novel drug targets is urgently needed. Materials & Methods We re-analyzed several GEO datasets by systematic retrieval and data merging. Differentially expressed genes (DEGs) were filtered out. We also performed pathway enrichment analysis to interpret the data. We predicted key genes based on protein–protein interaction networks, weighted gene co-expression network analysis and genes’ cancer/testis expression pattern. We also further characterized these genes using data from the Cancer Genome Atlas (TCGA) project and gene ontology annotation. Results Cell cycle-related pathways were significantly enriched in upregulated genes in ATC. We identified TRIP13, DLGAP5, HJURP, CDKN3, NEK2, KIF15, TTK, KIF2C, AURKA and TPX2 as cell cycle-related key genes with cancer/testis expression pattern. We further uncovered that most of these putative key genes were critical components during chromosome segregation. Conclusion We predicted several key genes harboring potential therapeutic value in ATC. Cell cycle-related processes, especially chromosome segregation, may be the key to tumorigenesis and treatment of ATC.

scholarly journals SCUBE3 downregulation modulates hepatocellular carcinoma by inhibiting CCNE1 via TGFβ/PI3K/AKT/GSK3β pathway

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Pan Xu ◽  
Aoran Luo ◽  
Chuan Xiong ◽  
Hong Ren ◽  
Liang Yan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cell Lines ◽  
Signalling Pathway ◽  
Cell Counting ◽  
Pathway Enrichment Analysis

Abstract Objectives We aimed to verify the role of signal peptide-CUB-EGF-like domain-containing protein3 (SCUBE3) in the hepatocellular carcinoma (HCC) progression. Methods The role of SCUBE3 in HCC cell proliferation, apoptosis, and cell cycle in vitro were detected using MTT assay, colony formation assay, 5-ethynyl-2´-deoxyuridine assay (EDU), Celigo cell counting assay, Caspase3/7 activity assay, and flow cytometry. The effect of SCUBE3 on HCC cell proliferation in vivo was inspected by a xenograft tumour model in nude mice. The related mechanisms were further studied. Results The level of SCUBE3 was upregulated in HCC tissues and cell lines. Knockdown of SCUBE3 inhibited proliferation, promoted apoptosis, and induced cell cycle arrest in HCC cell lines in vitro and in vivo. Screening of cell cycle-related proteins revealed that CCNL2, CDK6, CCNE1, and CCND1 exhibited a significantly different expression profile. We found that SCUBE3 may promote the proliferation of HCC cells by regulating CCNE1 expression. The pathway enrichment analysis showed that the TGFβ signalling pathway and the PI3K/AKT signalling pathway were significantly altered. Co-immunoprecipitation results showed that SCUBE3 binds to the TGFβRII receptor. SCUBE3 knockdown inhibited the PI3K/AKT signalling pathway and the phosphorylation of GSK3β to inhibit its kinase activity. Conclusions SCUBE3 promotes HCC development by regulating CCNE1 via TGFβ/PI3K/AKT/GSK3β pathway. In addition, SCUBE3 may be a new molecular target for the clinical diagnosis and treatment of HCC.

scholarly journals Integrative and Comprehensive Pancancer Analysis of Regulator of Chromatin Condensation 1 (RCC1)

2021 ◽  
Vol 22 (14) ◽  
pp. 7374
Author(s):  
Changwu Wu ◽  
Yingjuan Duan ◽  
Siming Gong ◽  
Sonja Kallendrusch ◽  
Nikolas Schopow ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Chromatin Condensation ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Malignant Neoplasms ◽  
Nucleotide Exchange ◽  
Genome Database

Regulator of Chromatin Condensation 1 (RCC1) is the only known guanine nucleotide exchange factor that acts on the Ras-like G protein Ran and plays a key role in cell cycle regulation. Although there is growing evidence to support the relationship between RCC1 and cancer, detailed pancancer analyses have not yet been performed. In this genome database study, based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases, the potential role of RCC1 in 33 tumors’ entities was explored. The results show that RCC1 is highly expressed in most human malignant neoplasms in contrast to healthy tissues. RCC1 expression is closely related to the prognosis of a broad variety of tumor patients. Enrichment analysis showed that some tumor-related pathways such as “cell cycle” and “RNA transport” were involved in the functional mechanism of RCC1. In particular, the conducted analysis reveals the relation of RCC1 to multiple immune checkpoint genes and suggests that the regulation of RCC1 is closely related to tumor infiltration of cancer-associated fibroblasts and CD8+ T cells. Coherent data demonstrate the association of RCC1 with the tumor mutation burden and microsatellite instability in various tumors. These findings provide new insights into the role of RCC1 in oncogenesis and tumor immunology in various tumors and indicate its potential as marker for therapy prognosis and targeted treatment strategies.

scholarly journals Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Guangyu Gao ◽  
Zhen Yao ◽  
Jiaofeng Shen ◽  
Yulong Liu
Keyword(s):  
Drug Resistance ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Obvious Association

Dabrafenib resistance is a significant problem in melanoma, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism of drug resistance of dabrafenib and to explore the key genes and pathways that mediate drug resistance in melanoma. GSE117666 was downloaded from the Gene Expression Omnibus (GEO) database and 492 melanoma statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Besides, differentially expressed miRNAs (DEMs) were identified by taking advantage of the R software and GEO2R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) and FunRich was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential pathways and functional annotations linked with melanoma chemoresistance. 9 DEMs and 872 mRNAs were selected after filtering. Then, target genes were uploaded to Metascape to construct protein-protein interaction (PPI) network. Also, 6 hub mRNAs were screened after performing the PPI network. Furthermore, a total of 4 out of 9 miRNAs had an obvious association with the survival rate ( P < 0.05 ) and showed a good power of risk prediction model of over survival. The present research may provide a deeper understanding of regulatory genes of dabrafenib resistance in melanoma.

scholarly journals Identification of Hypoxia-Related Differentially Expressed Genes and Construction of the Clinical Prognostic Predictor in Hepatocellular Carcinoma by Bioinformatic Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hao Guo ◽  
Jing Zhou ◽  
Yanjun Zhang ◽  
Zhi Wang ◽  
Likun Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Model ◽  
Molecular Mechanisms ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Clinical Prognosis ◽  
Prognostic Predictor ◽  
Key Genes

Background. Hypoxia closely relates to malignant progression and appears to be prognostic for outcome in hepatocellular carcinoma (HCC). Our research is aimed at mining the hypoxic-related genes (HRGs) and constructing a prognostic predictor (PP) model on clinical prognosis in HCC patients. Methods. RNA-sequencing data about HRGs and clinical data of patients with HCC were obtained from The Cancer Genome Atlas (TCGA) database portal. Differentially expressed HRGs between HCC and para-carcinoma tissue samples were obtained by applying the Wilcox analysis in R statistical software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for gene functional enrichment analyses. Then, the patients who were asked to follow up for at least one month were enrolled in the following study. Cox proportional risk regression model was applied to obtain key HRGs which related to overall survival (OS) in HCC. PP was constructed and defined, and the accuracy of PP was validated by constructing the signature in a training set and validation set. Connectivity map (CMap) was used to find potential drugs, and gene set cancer analysis (GSCA) was also performed to explore the underlying molecular mechanisms. Results. Thirty-seven differentially expressed HRGs were obtained. It contained 28 upregulated and 9 downregulated genes. After the univariate Cox regression model analysis, we obtained 27 prognosis-related HRGs. Of these, 25 genes were risk factors for cancer, and 2 genes were protective factors. The PP was composed by 12 key genes (HDLBP, SAP30, PFKP, DPYSL4, SLC2A1, HMOX1, PGK1, ERO1A, LDHA, ENO2, SLC6A6, and TPI1). GSCA results showed the overall activity of these 12 key genes in 10 cancer-related pathways. Besides, CMap identified deferoxamine, crotamiton, talampicillin, and lycorine might have effects with HCC. Conclusions. This study firstly reported 12 prognostic HRGs and constructed the model of the PP. This comprehensive research of multiple databases helps us gain insight into the biological properties of HCC and provides deferoxamine, crotamiton, talampicillin, and lycorine as potential drugs to fight against HCC.

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.

Sign in / Sign up

Export Citation Format

Share Document