Identification of candidate genes that may contribute to the metastasis of prostate cancer by bioinformatics analysis

Liu, Lingyun; Guo, Kaimin; Zhu, Liang; Li, Fubiao; Wang, Hongliang

doi:10.3892/ol.2017.7404

Cited by 10 publications

(12 citation statements)

References 55 publications

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“…The results showed that a total of 2,000 DEGs were identified in PCa compared to normal group, including 1,000 upregulated and 1,000 downregulated genes respectively. Previous studies have demonstrated that co-expression genes were frequently involved in similar biological function and signal pathway ( 2 , 9 ). Therefore, GO analysis and KEGG pathway analysis was further performed.…”

Section: Discussionmentioning

confidence: 99%

“…Prostate cancer (PCa) is one of the most common malignancies in men globally and the second leading cause of cancer associated mortality in developed countries ( 1 , 2 ). Like other cancers, PCa is considered to be a disease which caused by age, diet and gene aberrations ( 3 ).…”

Section: Introductionmentioning

confidence: 99%

“…At present, the underlying mechanism of PCa occurrence is still unclear, which limits the diagnosis and therapy. Therefore, it is urgent to identify the key genes and pathways involved in the occurrence of PCa ( 2 , 5 ).…”

Section: Introductionmentioning

confidence: 99%

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Identification of the key genes and pathways in prostate cancer

et al. 2018

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Prostate cancer (PCa) is one of the most common malignancies in men globally. The aim of the present study was to identify the key genes and pathways involved in the occurrence of PCa. Gene expression profile (GSE55945) was downloaded from Gene Expression Omnibus, and the differentially expressed genes (DEGs) were identified. Subsequently, Gene ontology analysis, KEGG pathway analysis and protein-protein interaction (PPI) analysis of DEGs were performed. Finally, the identified key genes were confirmed by immunohistochemistry. The GO analysis results showed that the DEGs were mainly participated in cell cycle, cell division, cell development and cell junction. The KEGG pathway analysis showed that the DEGs were mainly enriched in proteoglycans in cancer, endocytosis, focal adhesion and hippo signaling pathway. The PPI analysis results showed that RPS21, FOXO1, BIRC5, POLR2H, RPL22L1 and NPM1 were the key genes involved in the occurrence of PCa, and the Module analysis indicated that the occurrence of PCa was associated with cell cycle, oocyte meiosis and ribosome biogenesis. IHC result showed that the expression of RPS21, BIRC5, POLR2H, RPL22L1 and NPM1 were significantly upregulated in PCa, while the expression of FOXO1 was significantly downregulated in PCa, matching with the bioinformatics analysis. Taken together, several key genes and pathways were identified involved in PCa, which might provide the potential biomarker for prognosis, diagnosis and drug targets.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of the key genes and pathways in prostate cancer

et al. 2018

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“…Many of the putative drug targets for metastasis have no known function or enzymatic activity and in silico analysis often finds these genes categorized into seemingly unrelated pathways such as lipid metabolism or vesicular transport [94][95][96][97].…”

Section: Discussionmentioning

confidence: 99%

Novel therapeutic targets for cancer metastasis

Stoletov

Beatty

Lewis

2020

Expert Review of Anticancer Therapy

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Introduction: Metastatic cancers are extremely difficult to treat, and account for the vast majority of cancer-related deaths. The dissemination of tumor cells to distant sites is highly dynamic, asynchronous, and involves both tumor and host intrinsic factors. Effective therapeutic targets to block metastasis will need to disrupt key pathways that are required for multiple stages of metastasis. Areas covered: This review discusses the heterogeneity of cancers and metastasis, with an emphasis on motility as a key driver trait of metastasis. Recent metastatic cancer studies that identified either host or cancer cell intrinsic factors important for metastasis, using single gene-deficient animal models or 3D intravital imaging of avian embryo models, are also discussed. Potential metastatic blocking targets are listed as they relate to metastatic cancer therapy. Expert opinion: The development of metastatic disease is a complex interplay of genetic and epigenetic factors from the host and cancer cells acting in a patient-specific manner. Inhibiting key driver traits of metastasis should yield survival benefit at any stage of the disease, and we look forward to the next generation of personalized medicines for cancer therapy that target cancer cell motility for increased therapeutic efficacy. ARTICLE HISTORY

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“…In breast cancer, CCL4 can contribute to the metastasis to the bone by binding to CC chemokine receptor type 5 (Sasaki, Baba et al 2016). The genes in the "regulation of T cell activation" category, HLA-DR or CD4, also play a critical role in the metastasis in the metastasis of melanoma (Costantini and Barbieri 2017), breast cancer (DeNardo, Barreto et al 2009), and prostate cancer (Liu, Guo et al 2018).…”

Section: Discussionmentioning

confidence: 99%

Study of the co-expression gene modules of non-small cell lung cancer metastases

Wang¹,

Bie²,

Li³

et al. 2019

Preprint

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Background: Metastasis regularly is a marker of the disease development of cancers. Some metastatic sites significantly showed a more serious clinical outcome in non-small cell lung cancer (NSCLC). Whether they are caused by tissue-specific (TS) or non-tissue-specific (NTS) mechanisms is still unclear. Methods: Weighted Correlation Network Analysis (WGCNA) was used to identify the gene modules among the metastases of NSCLC. The clinical significance of those gene modules was evaluated with the Cox hazard proportional model with another independent dataset. Functions of each gene module were analyzed with gene ontology. Typical genes were further studied. Results: There were two TS gene modules and two NTS gene modules identified. One TS gene module (green module) and one NTS gene module (purple module) significantly correlated with survival. This NTS gene module (purple module) was significantly enriched in the epithelial-to-mesenchymal transition (EMT) process. Higher expression of the typical genes ( CA14 , SOX10 , TWIST1, and ALX1 ) from EMT process was significantly associated with a worse survival. Conclusion: The lethality of NSCLC metastases was caused by TS gene modules and NTS gene modules, among which the EMT-related gene module was critical for a worse clinical outcome.

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Identification of candidate genes that may contribute to the metastasis of prostate cancer by bioinformatics analysis

Cited by 10 publications

References 55 publications

Identification of the key genes and pathways in prostate cancer

Identification of the key genes and pathways in prostate cancer

Novel therapeutic targets for cancer metastasis

Study of the co-expression gene modules of non-small cell lung cancer metastases

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