Identification of key genes associated with the progression of intrahepatic cholangiocarcinoma using weighted gene co‑expression network analysis

Ye, Zi; Zeng, Zhirui; Da, Wang; Lei, Shan; Shen, Yiyi; Chen, Zubing

doi:10.3892/ol.2020.11600

Cited by 9 publications

(8 citation statements)

References 43 publications

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“…Images were captured with a light orthophoto microscope (magnification, ×200). Immunohistochemical staining was evaluated using a semiquantitative scoring method based on the staining intensity and the percentage of positively-stained cells ( 39 ). The staining intensity was scored as follows: 0 (no staining), 1 (+), 2 (++) and 3 (+++); the percentage of positive-stained cells was scored as follows: 0 (0-1%), 1 (1-33%), 2 (34-66%) and 3 (67-100%).…”

Section: Methodsmentioning

confidence: 99%

Identification of prognostic biomarkers associated with metastasis and immune infiltration in osteosarcoma

Yang

Chen

et al. 2021

Oncol Lett

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Osteosarcoma is the most common primary malignancy of the bones, and is associated with a high rate of metastasis and a poor prognosis. A tight association between the tumor microenvironment (TME) and osteosarcoma metastasis has been established. In the present study, the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to calculate the immune and stromal scores of patients with osteosarcoma based on data from The Cancer Genome Atlas database. A metagene approach and deconvolution method were used to reveal distinct TME landscapes in patients with osteosarcoma. Bioinformatics analysis was used to identify differentially expressed genes (DEGs) associated with metastasis and immune infiltration in osteosarcoma, and a risk model was constructed using the DEGs with potential prognostic significance. Subsequently, gene set enrichment and Spearman's correlation analyses were used to delineate the biological processes associated with these prognostic biomarkers. Finally, immunohistochemical (IHC) analysis was performed to evaluate the expression levels of immune infiltrates and prognostic biomarkers in clinical osteosarcoma tissues. The results of the ESTIMATE demonstrated that patients with non-metastatic osteosarcoma presented with higher immune/stromal scores and a more favorable prognosis compared with those with metastatic osteosarcoma. The TME landscapes in patients with osteosarcoma suggested that high levels of tumor-infiltrating immune cells (TIICs) may suppress metastasis. Increased numbers of CD56 bright natural killer cells, immature B cells, M1 macrophages and neutrophils, and lower levels of M2 macrophages were observed in the non-metastatic tissues compared with those in the metastatic tissues. A total of 69 DEGs were identified to be associated with metastasis and immune infiltration in osteosarcoma. Of these, GATA3, LPAR5, EVI2B, RIAM and CFH exhibited prognostic potential and were highly expressed in non-metastatic osteosarcoma tissues based on the IHC analysis results. These biomarkers were involved in various immune-related biological processes and were positively associated with multiple TIICs and immune signatures. The risk model constructed using these prognostic biomarkers demonstrated high predictive accuracy for the prognosis of osteosarcoma. In conclusion, the present study proposed a five-biomarker prognostic signature for the prediction of metastasis and immune infiltration in patients with osteosarcoma.

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Section: Methodsmentioning

confidence: 99%

Identification of prognostic biomarkers associated with metastasis and immune infiltration in osteosarcoma

Yang

Chen

et al. 2021

Oncol Lett

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“…The determination of the molecular mechanism about tumorigenesis is very important for the diagnosis and treatment of cancer patients [ 24 ]. There is an urgent need to study the pathogenesis of intrahepatic cholangiocarcinoma and the knowledge gained may help us to develop new clinical treatment strategies [ 25 ]. In recent years, high-throughput sequencing technology and bioinformatics analysis have been increasingly applied to biological research [ 26 ].…”

Section: Discussionmentioning

confidence: 99%

A2M is a potential core gene in intrahepatic cholangiocarcinoma

et al. 2022

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Background Intrahepatic cholangiocarcinoma (ICC) is a type of malignant tumor ranking the second in the incidence of primary liver cancer following hepatocellular carcinoma. Both the morbidity and mortality have been increasing in recent years. Small duct type of ICC has potential therapeutic targets. But overall, the prognosis of patients with ICC is usually very poor. Methods To search latent therapeutic targets for ICC, we programmatically selected the five most suitable microarray datasets. Then, we made an analysis of these microarray datasets (GSE26566, GSE31370, GSE32958, GSE45001 and GSE76311) collected from the Gene Expression Omnibus (GEO) database. The GEO2R tool was effective to find out differentially expressed genes (DEGs) between ICC and normal tissue. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were executed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v 6.8. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to analyze protein–protein interaction of these DEGs and protein–protein interaction of these DEGs was modified by Cytoscape3.8.2. Survival analysis was performed using Gene Expression Profiling Interactive Analysis (GEPIA) online analysis tool. Results A total of 28 upregulated DEGs and 118 downregulated DEGs were screened out. Then twenty hub genes were selected according to the connectivity degree. The survival analysis results showed that A2M was closely related to the pathogenesis and prognosis of ICC and was a potential therapeutic target for ICC. Conclusions According to our study, low A2M expression in ICC compared to normal bile duct tissue was an adverse prognostic factor in ICC patients. The value of A2M in the treatment of ICC needs to be further studied.

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“…A similar but different approach has been performed using a dataset from GEO (GSE26566) to find the potential candidate treatment agents for CCA without validation (Chujan et al, 2018). Recently, Ye et al (2020) has identified the key genes associated with the progression of intrahepatic CCA using three GEO dataset including GSE107943, GSE119336 and GSE26566. The present study provided several target candidates different from those reported in the previous studies.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis identified CDC20 as a potential drug target for cholangiocarcinoma

Sungwan

Lert-itthiporn

Silsirivanit

et al. 2021

PeerJ

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Background Cholangiocarcinoma (CCA) is a malignancy that originates from bile duct cells. The incidence and mortality of CCA are very high especially in Southeast Asian countries. Moreover, most CCA patients have a very poor outcome. Presently, there are still no effective treatment regimens for CCA. The resistance to several standard chemotherapy drugs occurs frequently; thus, searching for a novel effective treatment for CCA is urgently needed. Methods In this study, comprehensive bioinformatics analyses for identification of novel target genes for CCA therapy based on three microarray gene expression profiles (GSE26566, GSE32225 and GSE76297) from the Gene Expression Omnibus (GEO) database were performed. Based on differentially expressed genes (DEGs), gene ontology and pathway enrichment analyses were performed. Protein-protein interactions (PPI) and hub gene identifications were analyzed using STRING and Cytoscape software. Then, the expression of candidate genes from bioinformatics analysis was measured in CCA cell lines using real time PCR. Finally, the anti-tumor activity of specific inhibitor against candidate genes were investigated in CCA cell lines cultured under 2-dimensional and 3-dimensional cell culture models. Results The three microarray datasets exhibited an intersection consisting of 226 DEGs (124 up-regulated and 102 down-regulated genes) in CCA. DEGs were significantly enriched in cell cycle, hemostasis and metabolism pathways according to Reactome pathway analysis. In addition, 20 potential hub genes in CCA were identified using the protein-protein interaction (PPI) network and sub-PPI network analysis. Subsequently, CDC20 was identified as a potential novel targeted drug for CCA based on a drug prioritizing program. In addition, the anti-tumor activity of a potential CDC20 inhibitor, namely dinaciclib, was investigated in CCA cell lines. Dinaciclib demonstrated huge anti-tumor activity better than gemcitabine, the standard chemotherapeutic drug for CCA. Conclusion Using integrated bioinformatics analysis, CDC20 was identified as a novel candidate therapeutic target for CCA.

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Identification of key genes associated with the progression of intrahepatic cholangiocarcinoma using weighted gene co‑expression network analysis

Cited by 9 publications

References 43 publications

Identification of prognostic biomarkers associated with metastasis and immune infiltration in osteosarcoma

Identification of prognostic biomarkers associated with metastasis and immune infiltration in osteosarcoma

A2M is a potential core gene in intrahepatic cholangiocarcinoma

Bioinformatics analysis identified CDC20 as a potential drug target for cholangiocarcinoma

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