scholarly journals Associations of Serum Tumor Biomarkers with Integrated Genomic and Clinical Characteristics of Hepatocellular Carcinoma

Liver Cancer ◽  
2021 ◽  
pp. 1-13
Author(s):  
Keun Soo Ahn ◽  
Daniel R. O’Brien ◽  
Yong Hoon Kim ◽  
Tae-Seok Kim ◽  
Hiroyuki Yamada ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Lens Culinaris ◽  
Acid Metabolism ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Genetic Profile ◽  
Vegf Signaling ◽  
The Usa ◽  
Cancer Genome Atlas ◽  
Liver Hepatocellular Carcinoma

<b><i>Introduction:</i></b> Serum α-fetoprotein (AFP), <i>Lens culinaris</i> agglutinin-reactive AFP (AFP-L3), and des-γ-carboxy­pro­thrombin (DCP) are useful biomarkers of hepatocellular carcinoma (HCC). However, associations among molecular characteristics and serum biomarkers are unclear. We analyzed RNA expression and DNA variant data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) to examine their associations with serum biomarker levels and clinical data. <b><i>Methods:</i></b> From 371 TCGA-LIHC patients, we selected 91 seen at 3 institutions in Korea and the USA and measured AFP, AFP-L3, and DCP from preoperatively obtained serum. We conducted an integrative clinical and molecular analysis, focusing on biomarkers, and validated the findings with the remaining 280 patients in the TCGA-LIHC cohort. <b><i>Results:</i></b> Patients were categorized into 4 subgroups: elevated AFP or AFP-L3 alone (↑AFP&amp;L3), elevated DCP alone (↑DCP), elevation of all 3 biomarkers (elevated levels of all 3 biomarkers [↑All]), and reference range values for all biomarkers (RR). <i>CTNNB1</i> variants were frequently observed in ↑DCP patients (53.8%) and RR patients (38.5%), but ↑DCP patients with a <i>CTNNB1</i> variant had worse survival than RR patients. <i>TP53</i> sequence variants were associated with ↑AFP (30.8%) and ↑DCP (30.8%). The Wnt-β-catenin signaling pathway was activated in the ↑AFP&amp;L3, whereas liver-related Wnt signaling was activated in the RR. TGF-β and VEGF signaling were activated in ↑AFP&amp;L3, whereas dysregulated bile acid and fatty acid metabolism were dominant in ↑DCP. We validated these findings by showing similar results between the test cohort and the remainder of the TCGA-LIHC cohort. <b><i>Conclusions:</i></b> Serum AFP, AFP-L3, and DCP levels can help predict variants in the genetic profile of HCC, especially for <i>TP53</i> and <i>CTNNB1</i>. These findings may facilitate development of an evidence-based approach to treatment.

scholarly journals From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3089 ◽  
Author(s):  
Hong Yang ◽  
Xin Zhang ◽  
Xiao-yong Cai ◽  
Dong-yue Wen ◽  
Zhi-hua Ye ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Big Data ◽  
Natural Language Processing ◽  
Language Processing ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Liver Hepatocellular Carcinoma ◽  
Genome Atlas

BackgroundLiver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in.MethodsBig data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected genes with top priority were evaluated and assessed in terms of their diagnostic and prognostic values.ResultsA list of 389 genes was generated by overlapping genes from The Cancer Genome Atlas and Natural Language Processing. Three pathways demonstrated top priorities, and the one with specific associations with cancers, ‘pathways in cancer,’ was analyzed with its four highlighted genes, namely, BIRC5, E2F1, CCNE1, and CDKN2A, which were validated using Oncomine. The detection pool composed of the four genes presented satisfactory diagnostic power with an outstanding integrated AUC of 0.990 (95% CI [0.982–0.998],P < 0.001, sensitivity: 96.0%, specificity: 96.5%). BIRC5 (P = 0.021) and CCNE1 (P = 0.027) were associated with poor prognosis, while CDKN2A (P = 0.066) and E2F1 (P = 0.088) demonstrated no statistically significant differences.DiscussionThe study illustrates liver hepatocellular carcinoma gene signatures, related pathways and networks from the perspective of big data, featuring the cancer-specific pathway with priority, ‘pathways in cancer.’ The detection pool of the four highlighted genes, namely BIRC5, E2F1, CCNE1 and CDKN2A, should be further investigated given its high evidence level of diagnosis, whereas the prognostic powers of BIRC5 and CCNE1 are equally attractive and worthy of attention.

scholarly journals High expression of PARD3 predicts poor prognosis in hepatocellular carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Songwei Li ◽  
Jian Huang ◽  
Fan Yang ◽  
Haiping Zeng ◽  
Yuyun Tong ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dendritic Cells ◽  
Poor Prognosis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Predictive Capacity ◽  
Immune Infiltration ◽  
Cancer Genome Atlas ◽  
Liver Hepatocellular Carcinoma ◽  
The Relationship

AbstractHepatocellular carcinoma (HCC) is one of the most commonly cancers with poor prognosis and drug response. Identifying accurate therapeutic targets would facilitate precision treatment and prolong survival for HCC. In this study, we analyzed liver hepatocellular carcinoma (LIHC) RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), and identified PARD3 as one of the most significantly differentially expressed genes (DEGs). Then, we investigated the relationship between PARD3 and outcomes of HCC, and assessed predictive capacity. Moreover, we performed functional enrichment and immune infiltration analysis to evaluate functional networks related to PARD3 in HCC and explore its role in tumor immunity. PARD3 expression levels in 371 HCC tissues were dramatically higher than those in 50 paired adjacent liver tissues (p < 0.001). High PARD3 expression was associated with poor clinicopathologic feathers, such as advanced pathologic stage (p = 0.002), vascular invasion (p = 0.012) and TP53 mutation (p = 0.009). Elevated PARD3 expression also correlated with lower overall survival (OS, HR = 2.08, 95% CI = 1.45–2.98, p < 0.001) and disease-specific survival (DSS, HR = 2.00, 95% CI = 1.27–3.16, p = 0.003). 242 up-regulated and 71 down-regulated genes showed significant association with PARD3 expression, which were involved in genomic instability, response to metal ions, and metabolisms. PARD3 is involved in diverse immune infiltration levels in HCC, especially negatively related to dendritic cells (DCs), cytotoxic cells, and plasmacytoid dendritic cells (pDCs). Altogether, PARD3 could be a potential prognostic biomarker and therapeutic target of HCC.

Decreased expression of ARID1A invasively downregulates the expression of ribosomal proteins in hepatocellular carcinoma

2021 ◽  
Author(s):  
Jing Zhao ◽  
Weiran Xu ◽  
Yu Zhang ◽  
Xiaomin Lv ◽  
Yiran Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Cells ◽  
Ribosomal Proteins ◽  
Bioinformatic Analysis ◽  
The Cancer Genome Atlas ◽  
Reverse Transcription Pcr ◽  
Adaptive Mechanisms ◽  
Tumor Mutational Burden ◽  
Cancer Genome Atlas ◽  
Liver Hepatocellular Carcinoma

Background: There was increasing evidence showing that ARID1A alterations correlated with higher tumor mutational burden, but there were limited studies focusing on the adaptive mechanisms for tumor cells to survive under excessive genomic alterations. Materials & methods: To further explore the adaptive mechanisms under ARID1A alterations, we performed RNA sequencing in ARID1A knockdown hepatocellular carcinoma cell lines, and demonstrated that decreased expression of ARID1A controlled global ribosomal proteins synthesis. The results were further confirmed by quantitative reverse transcription-PCR and bioinformatic analysis in The Cancer Genome Atlas Liver Hepatocellular Carcinoma database. Conclusion: The present study was the first to demonstrate that ARID1A might be involved in the translation pathway and served as an adaptive mechanism for tumor cells to survive under stress.

scholarly journals Integrated bioinformatics analysis identified MTHFD1L as a potential biomarker and correlated with immune infiltrates in hepatocellular carcinoma

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Junhui Chen ◽  
Jie Yang ◽  
Qingchun Xu ◽  
Zhenyu Wang ◽  
Jun Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Proportional Hazards ◽  
Liver Tumors ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Potential Biomarker ◽  
Methylenetetrahydrofolate Dehydrogenase ◽  
Cancer Genome Atlas ◽  
Malignant Liver ◽  
Liver Hepatocellular Carcinoma

Abstract Liver hepatocellular carcinoma (LIHC) is one of the most frequently occurring primary malignant liver tumors and seriously harms people’s health in the world. Methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L) has been shown to be associated with colon cancer cell proliferation, colony formation and invasion. In the present study, a total of 370 LIHC and 51 normal samples data were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatics and immunohistochemistry (IHC) analysis showed that MTHFD1L is highly expressed in liver tumors. Correlation analysis suggested the differences of vital status between high- and low-expression MTHFD1L groups of LIHC. Univariate and multivariate Cox proportional hazards regression were performed to identify the relationship between clinical characteristics and overall survival (OS). In addition, to explore whether MTHFD1L has an effect on the immune infiltration of LIHC. The correlation between MTHFD1L expression and 24 immune cells were analyzed by ImmuneCellAI database. Furthermore, we combined three databases CIBERSORT, TIMER and ImmuneCellAI to do a comprehensive validation and determined that dendritic cells (DCs) resting, macrophage M0 and macrophage M2 closely related to the expression of MTHFD1L. The results showed that MTHFD1L was a potential prognostic biomarker for LIHC, and could help to elucidate that how the immune microenvironment promotes liver cancer development.

scholarly journals Study of the G Protein Nucleolar 2 Value in Liver Hepatocellular Carcinoma Treatment and Prognosis

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yiwei Dong ◽  
Qianqian Cai ◽  
Lisheng Fu ◽  
Haojie Liu ◽  
Mingzhe Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
G Protein ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Functional Assays ◽  
Close Relationship ◽  
Cancer Genome Atlas ◽  
And Function ◽  
Liver Hepatocellular Carcinoma

LIHC (liver hepatocellular carcinoma) mostly occurs in patients with chronic liver disease. It is primarily induced by a vicious cycle of liver injury, inflammation, and regeneration that usually last for decades. The G protein nucleolar 2 (GNL2), as a protein-encoding gene, is also known as NGP1, Nog2, Nug2, Ngp-1, and HUMAUANTIG. Few reports are shown towards the specific biological function of GNL2. Meanwhile, it is still unclear whether it is related to the pathogenesis of carcinoma up to date. Here, our study attempts to validate the role and function of GNL2 in LIHC via multiple databases and functional assays. After analysis of gene expression profile from The Cancer Genome Atlas (TCGA) database, GNL2 was largely heightened in LIHC, and its overexpression displayed a close relationship with different stages and poor prognosis of carcinoma. After enrichment analysis, the data revealed that the genes coexpressed with GNL2 probably participated in ribosome biosynthesis which was essential for unrestricted growth of carcinoma. Cell functional assays presented that GNL2 knockdown by siRNA in LIHC cells MHCC97-H and SMCC-7721 greatly reduced cell proliferation, migration, and invasion ability. All in all, these findings capitulated that GNL2 could be a promising treatment target and prognosis biomarker for LIHC.

Signatures of gene expression, DNA methylation and microRNAs of hepatocellular carcinoma with vascular invasion

2019 ◽  
Vol 15 (22) ◽  
pp. 2603-2617 ◽  
Author(s):  
Siti A Sulaiman ◽  
Nadiah Abu ◽  
Nurul-Syakima Ab-Mutalib ◽  
Teck Yew Low ◽  
Rahman Jamal
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Vascular Invasion ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Methylated Genes ◽  
Cancer Genome Atlas ◽  
Poor Outcomes ◽  
Liver Hepatocellular Carcinoma ◽  
Genome Atlas

Aim: Micro and macro vascular invasion (VI) are known as independent predictors of tumor recurrence and poor survival after surgical treatment of hepatocellular carcinoma (HCC). Here, we aimed to re-analyze The Cancer Genome Atlas of liver hepatocellular carcinoma datasets to identify the VI-expression signatures. Materials & methods: We filtered The Cancer Genome Atlas liver hepatocellular carcinoma (LIHC) datasets into three groups: no VI (NVI = 198); micro VI (MIVI = 89) and macro VI (MAVI = 16). We performed differential gene expression, methylation and microRNA analyses. Results & conclusion: We identified 12 differentially expressed genes and 55 differentially methylated genes in MAVI compared with no VI. The GPD1L gene appeared in all of the comparative analyses. Higher GPD1L expression was associated with VI and poor outcomes in the HCC patients.

scholarly journals Dopamine and dopamine receptor D1 as a novel favourable biomarker for hepatocellular carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihui Wang ◽  
Peihao Wen ◽  
Bowen Hu ◽  
Shengli Cao ◽  
Xiaoyi Shi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Dopamine Receptor ◽  
Systematic Investigation ◽  
The Cancer Genome Atlas ◽  
Malignant Tumours ◽  
Functional Activities ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Liver Hepatocellular Carcinoma

Abstract Background Hepatocellular carcinoma (HCC) remains one of the most common malignant tumours worldwide. Therefore, the identification and development of sensitivity- genes as novel diagnostic markers and effective therapeutic targets is urgently needed. Dopamine and dopamine receptor D1 (DRD1) are reported to be involved in the progression of various cancers. However, the crucial role of DRD1 in HCC malignant activities remains unclear. Methods We enrolled 371 patients with liver hepatocellular carcinoma (LIHC) from The Cancer Genome Atlas (TCGA) to detect the expression and functions of DRD1. The Tumour Immune Estimation Resource (TIMER), UALCAN database, Kaplan–Meier plotter, cBioPortal database, and LinkedOmics database were utilized for the systematic investigation of DRD1 expression and related clinical features, coexpressed genes, functional pathways, mutations, and immune infiltrates in HCC. Results In this study, we determined that DRD1 expression was decreased in HCC tumour tissues versus normal tissues and that low DRD1 expression indicated a poor prognosis. The significance of DRD1 expression varied among different tumour samples. The somatic mutation frequency of DRD1 in the LIHC cohort was 0.3%. The biological functions of DRD1 were detected and validated, and DRD1 was shown to be involved in various functional activities, including metabolism, oxidation, mitochondrial matrix-related processes and other related signaling pathways. In addition, out study indicated that DRD1 had significant correlations with the infiltration of macrophages, B cells and CD+ T cells in HCC. Conclusions These findings demonstrated the rationality of the potential application of DRD1 function as a novel biomarker for HCC diagnosis and a therapeutic target for HCC treatment.

Biomarker Identification for Liver Hepatocellular Carcinoma and Cholangiocarcinoma Based on Gene Regulatory Network Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Qiuyan Huo ◽  
Yuying Ma ◽  
Yu Yin ◽  
Guimin Qin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Networks ◽  
Primary Liver Cancer ◽  
Endocrine Resistance ◽  
Molecular Characteristics ◽  
Network Clustering ◽  
Resistance Pathway ◽  
Gene Regulatory ◽  
Tf Gene ◽  
Liver Hepatocellular Carcinoma

Aims: We aimed to find common and distinct molecular characteristics between LIHC and CHOL based on miRNA-TF-gene FFL. Background: Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are two main histological subtypes of primary liver cancer with a unified molecular landscape, and feed-forward loops (FFLs) have been shown to be relevant in these complex diseases. Objective: To date, there has been no comparative analysis of the pathogenesis of LIHC and CHOL based on regulatory relationships. Therefore, we investigated the common and distinct regulatory properties of LIHC and CHOL in terms of gene regulatory networks. Method: Based on identified FFLs and an analysis of pathway enrichment, we constructed pathway-specific co-expression networks and further predicted biomarkers for these cancers by network clustering. Resul: We identified 20 and 36 candidate genes for LIHC and CHOL, respectively. The literature from PubMed supports the reliability of our results. Conclusion: Our results indicated that the hsa01522-Endocrine resistance pathway was associated with both LIHC and CHOL. Additionally, six genes (SPARC, CTHRC1, COL4A1, EDIL3, LAMA4 and OLFML2B) were predicted to be highly associated with both cancers, of which SPARC was significantly highly ranked. Other: In addition, we inferred that the Collagen gene family, which appeared more frequently in our overall prediction results, might be closely related to cancer development.

scholarly journals Identification of glycolysis related pathways in pancreatic adenocarcinoma and liver hepatocellular carcinoma based on TCGA and GEO datasets

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ji Li ◽  
Chen Zhu ◽  
Peipei Yue ◽  
Tianyu Zheng ◽  
Yan Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Energy Metabolism ◽  
Pancreatic Adenocarcinoma ◽  
Digestive System ◽  
Prognostic Significance ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
System Structure ◽  
Liver Hepatocellular Carcinoma

Abstract Background Abnormal energy metabolism is one of the characteristics of tumor cells, and it is also a research hotspot in recent years. Due to the complexity of digestive system structure, the frequency of tumor is relatively high. We aim to clarify the prognostic significance of energy metabolism in digestive system tumors and the underlying mechanisms. Methods Gene set variance analysis (GSVA) R package was used to establish the metabolic score, and the score was used to represent the metabolic level. The relationship between the metabolism and prognosis of digestive system tumors was explored using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Volcano plots and gene ontology (GO) analyze were used to show different genes and different functions enriched between different glycolysis levels, and GSEA was used to analyze the pathway enrichment. Nomogram was constructed by R package based on gene characteristics and clinical parameters. qPCR and Western Blot were applied to analyze gene expression. All statistical analyses were conducted using SPSS, GraphPad Prism 7, and R software. All validated experiments were performed three times independently. Results High glycolysis metabolism score was significantly associated with poor prognosis in pancreatic adenocarcinoma (PAAD) and liver hepatocellular carcinoma (LIHC). The STAT3 (signal transducer and activator of transcription 3) and YAP1 (Yes1-associated transcriptional regulator) pathways were the most critical signaling pathways in glycolysis modulation in PAAD and LIHC, respectively. Interestingly, elevated glycolysis levels could also enhance STAT3 and YAP1 activity in PAAD and LIHC cells, respectively, forming a positive feedback loop. Conclusions Our results may provide new insights into the indispensable role of glycolysis metabolism in digestive system tumors and guide the direction of future metabolism–signaling target combined therapy.

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