Role of several cytokines and adhesion molecules in the diagnosis and prediction of survival of hepatocellular carcinoma

İliaz, Raim; Akyüz, Ümit; Tekin, Didem; Serilmez, Murat; Evirgen, Sami; Çavuş, Bilger; Soydinc, Hilal Oguz; Duranyıldız, Derya; Karaca, Çetin; Demır, Kadir; Beşışık, Fatih; Kaymakoğlu, Sabahattin; Akyüz, Filiz

doi:10.1016/j.ajg.2016.10.002

Cited by 7 publications

(6 citation statements)

References 25 publications

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“…It promotes cancer cell adhesion to the endothelium and is associated with immune and inflammatory responses of tumors (45). High VCAM1 serum levels have been reported for various cancer types, including HCC, chronic liver disease, breast cancer and CRC, and VCAM1 is considered a potential predictor for cancer prognosis (46–50). The amount of VCAM1 in the serum is dependent on tumor stage and neoplasm metastasis (51).…”

Section: Discussionmentioning

confidence: 99%

Identification of key pathways and biomarkers in sorafenib‑resistant hepatocellular carcinoma using bioinformatics analysis

Huang

Yuan

et al. 2018

Exp Ther Med

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Hepatocellular carcinoma (HCC) is one of the most common malignant types of cancer, with a high mortality rate. Sorafenib is the sole approved oral clinical therapy against advanced HCC. However, individual patients exhibit varying responses to sorafenib and the development of sorafenib resistance has been a new challenge for its clinical efficacy. The current study identified gene biomarkers and key pathways in sorafenib-resistant HCC using bioinformatics analysis. Gene dataset GSE73571 was obtained from the Gene Expression Omnibus (GEO) database, including four sorafenib-acquired resistant and three sorafenib-sensitive HCC phenotypes. Differentially expressed genes (DEGs) were identified using the web tool GEO2R. Functional and pathway enrichment of DEGs were analyzed using the Database for Annotation, Visualization and Integrated Discovery and the protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. A total of 1,319 DEGs were selected, which included 593 upregulated and 726 downregulated genes. Functional and pathway enrichment analysis revealed DEGs enriched in negative regulation of endopeptidase activity, cholesterol homeostasis, DNA replication and repair, coagulation cascades, insulin resistance, RNA transport, cell cycle and others. Eight hub genes, including kininogen 1, vascular cell adhesion molecule 1, apolipoprotein C3, alpha 2-HS glycoprotein, erb-b2 receptor tyrosine kinase 2, secreted protein acidic and cysteine rich, vitronectin and vimentin were identified from the PPI network. In conclusion, the present study identified DEGs and key genes in sorafenib-resistant HCC, which further the knowledge of potential mechanisms in the development of sorafenib resistance and may provide potential targets for early diagnosis and new treatments for sorafenib-resistant HCC.

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Section: Discussionmentioning

confidence: 99%

Identification of key pathways and biomarkers in sorafenib‑resistant hepatocellular carcinoma using bioinformatics analysis

Huang

Yuan

et al. 2018

Exp Ther Med

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“…CAMs play an important role in cell communication 47 and are associated with HCC diagnosis and survival prediction. 48 , 49 Our findings suggest a novel hypothetical biological mechanism between CAMs and TP53 expression status in HBV-related HCC.…”

Section: Discussionmentioning

confidence: 68%

Genome-wide association pathway analysis to identify candidate single nucleotide polymorphisms and molecular pathways associated with TP53 expression status in HBV-related hepatocellular carcinoma

Liao

Liu

et al. 2018

CMAR

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BackgroundThe aim of this investigation was to identify candidate single nucleotide polymorphisms (SNPs) and molecular pathways associated with tumor protein p53 (TP53) expression status in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), clarify their potential mechanisms, and generate SNP-to-gene to pathway hypothesis.Materials and methodsIdentify candidate Causal SNPs and Pathways (ICSNPathway) was used to perform pathway analysis based on the results of our previous genome-wide association study of TP53 expression status in 387 HBV-related HCC patients.ResultsThrough the ICSNPathway analysis, we identified 18 candidate SNPs and 10 candidate pathways that are associated with TP53 expression status in HBV-related HCC. The strongest mechanism involved the modulation of major histocompatibility complex, class II, DP beta 1 (human leukocyte antigen [HLA]-DPB1-rs1042153), major histocompatibility complex, class II, DQ beta 1 (HLA-DQB1-rs1130399, HLA-DQB1-rs1049056, HLA-DQB1-rs1049059, and HLA-DQB1-rs1049060), and major histocompatibility complex, class II, DR beta 1 (HLA-DRB1-rs35445101). SNPs consequently affected regulatory roles in all the candidate pathways except hematopoietic cell lineage pathways. Association analysis using the GSE14520 data set, Gene Multiple Association Network Integration Algorithm, and Search Tool for the Retrieval of Interacting Genes/Proteins suggests that all genes of the candidate SNPs were associated with TP53. Survival analysis showed that the collagen type VI alpha 3 chain (COL6A3) rs111231885 and COL6A3-rs113155945 and COL6A3 block 4 CC haplotypes with TP53 negative status may have protective effects in HBV-related HCC patients after hepatectomy.ConclusionOur pathway analysis identified 18 candidate SNPs and 10 candidate pathways that were associated with TP53 expression status in HBV-related HCC. Among these candidate SNPs, the genetic variation of COL6A3 may be a potential prognostic biomarker of HBV-related HCC.

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“…The miR-1303 inhibitor significantly decreased the invasion capability of liver-cancer cells compared to the NC inhibitor (p<0.01) (Figure 3B and C). Previous studies showed that the levels of ICAM-1 and VCAM-1 are higher in liver-cancer (22)(23)(24). The protein-expression levels of ICAM-1 and VCAM-1 were significantly decreased by the miR-1303 inhibitor compared to the NC inhibitor (p<0.01) (Figure 3D).…”

Section: Knockdown Of Mir-1303 Inhibits In Vitro Migration and Invasi...mentioning

confidence: 67%

Micro RNA miR-1303 Promotion of Proliferation, Migration and Invasion of Human Liver Cancer Cells Is Enhanced by Low Talin 1 (TLN1) Expression

Huang

XIONG

et al. 2022

Anticancer Res

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Background/Aim: Liver cancer is the third-most lethal cancer worldwide. Abnormal expression of microRNAs (miRNAs) modulates gene expression to exert oncogenic or tumor-suppressive effects in liver cancer. However, the biological role of miR-1303 in the progression of liver cancer and its regulatory mechanism has not been elucidated. Materials and Methods: The expression levels of miR-1303 were measured in liver-cancer tissues of patients and cell lines by RT-qPCR. Huh-7 and HepG2 liver-cancer cells were co-transfected by TLN1 and miR-1303 constructs. Cell viability was measured by the CCk-8 assay and colony-formation assay. Flow cytometry was used to measure cell apoptosis. Cell migration and invasion were determined by wound-healing and transwell-chamber assays. RT-PCR and western-blotting were used to determine miR-1303 inhibitor-associated marker expression, such as Bax, cleavedcaspase-3 and cleaved-caspase-9. Results: miR-1303 expression was strongly up-regulated in liver-cancer tissues and cells. Knockdown of miR-1303 attenuated cell proliferation, migration and invasion, and induced apoptosis in liver-cancer cells. Talin 1 (TLN1) and miR-1303 expression were negatively correlated, possibly by miR-1303 targeting the TLN1 gene. TLN1 expression enhanced the efficacy of an miR-1303 inhibitor to reduce liver-cancer cell proliferation and invasion. Conclusion: miR-1303 plays an important role in liver cancer, which is inhibited by TLN1 expression.Liver cancer is the third-most lethal cancer worldwide and the second-largest cancer-related cause of death in China (1). The long-term survival rate for liver-cancer patients remains poor due to lack of effective treatment (2, 3) . A greater understanding of the potential mechanism and progression of liver cancer is vital for developing more effective therapies.Micro-RNAs (miRNAs) are a class of small noncoding RNAs with a length of approximately 20-24 nucleotides. miRNAs play a large part in modulating the expression of diverse genes participating in the progression of numerous cancer types, via regulating mRNA expression (4-6). Knockdown of miRNAs which target proto-oncogenes and ectopic expression of oncogenic miRNA, can inhibit or enhance cancer progression, respectively (7-11). miR-20b, miR-27a and miR-181a which regulate HIPK2, HIF1A and MDR1, respectively, were expressed in gastric cancer during chemotherapy (12). miRNAs are candidate biomarkers for diagnosis or prognosis of pancreatic cancer which are in critical need (13). miRNAs in the cells of the tumor microenvironment, have been suggested as a target for liver cancer ( 14). miR-182-5p promotes hepatocellular carcinoma progression by repressing FOXO3a (15). miR-3662 suppresses liver-cancer growth via inhibition of the HIF-1αmediated Warburg Effect (16). miR-3 inhibited liver-cancer progression by targeting XRCC5 through the PI3K/AKT signaling pathway (17).miRNA-1303 has been shown to promote a number of different cancer types (18,19). However, the role of miR-1303 in liver cancer remains poorly understood. T...

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Role of several cytokines and adhesion molecules in the diagnosis and prediction of survival of hepatocellular carcinoma

Cited by 7 publications

References 25 publications

Identification of key pathways and biomarkers in sorafenib‑resistant hepatocellular carcinoma using bioinformatics analysis

Identification of key pathways and biomarkers in sorafenib‑resistant hepatocellular carcinoma using bioinformatics analysis

Genome-wide association pathway analysis to identify candidate single nucleotide polymorphisms and molecular pathways associated with TP53 expression status in HBV-related hepatocellular carcinoma

Micro RNA miR-1303 Promotion of Proliferation, Migration and Invasion of Human Liver Cancer Cells Is Enhanced by Low Talin 1 (TLN1) Expression

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