Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis

Zheng, Hong; Zhang, Guosen; Zhang, Lu; Wang, Qiang; Li, Huimin; Han, Yali; Xie, Longxiang; Yan, Zhongyi; Li, Yongqiang; An, Yang; Dong, H.; Zhu, Wan; Guo, Xiangqian

doi:10.3389/fonc.2020.00068

Cited by 91 publications

(70 citation statements)

References 65 publications

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“…Prognostic and diagnostic biomarkers play crucial roles in predicting the treatment response, prognosis and disease progression in cancer, developing new therapies, and elucidating tumorigenesis mechanisms (10,11). High throughput profiling methods including next-generation sequencing and gene microarray have shown great potentials for identifying reliable prognostic biomarkers for different cancers (12,13).…”

Section: Introductionmentioning

confidence: 99%

FAM83A as a Potential Biological Marker Is Regulated by miR-206 to Promote Cervical Cancer Progression Through PI3K/AKT/mTOR Pathway

Zhaodong

et al. 2020

Front. Med.

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Background and Objective: Chemotherapy and radiotherapy are effective treatment options for cervical cancer (CC), but their efficacy is limited by short survival rate of about 5 years particularly for advance stage CC. Bioinformatics analysis combined with experimental in vivo and in vitro data can identify potential markers of tumorigenesis and cancer progression to improve CC prognosis and survival rate of the patients. This study aims to investigate the prognostic value of family with sequence similarity 83, member A (FAM83A) gene and miR-206 in promoting CC progression and the involved genetic signaling pathways.Method: This was a bioinformatic analysis study based on RNA sequencing data of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and verification by in vivo and in vitro experimental data. It was designed to evaluate whether the aberrantly expressed gene signatures could serve as new potential biomarker to improve prognosis prediction in CC. The TCGA RNA sequencing data [306 cervical squamous cell carcinoma (SCC) and endocervical adenocarcinoma samples and 13 adjacent samples] and GEO data (GSE9750 and GSE52903 datasets) were integrated and performed a bioinformatics analysis.Results: The results showed that CC-associated FAM83A gene serves as a key regulator of CC development and progression. Functionally, we observed that FAM83A is significantly overexpressed in CC, which is linked to poor overall survival as well as disease-free survival in CC patients. The in-vitro and in-vivo assessments performed after silencing FAM83A revealed that cell proliferation was significantly inhibited and the S-phase cell cycle arrest was induced. Mechanistically, FAM83A plays a role in PI3K/AKT signaling, and its downstream molecules could promote CC cell proliferation. Furthermore, functionality assessments by in-vitro luciferase reporter system and immunoblot analysis showed that miR-206 was the upstream of FAM83A and negatively correlated with FAM83A.Conclusion: The miR-206/FAM83A/PI3K/AKT signaling pathway possibly serves as a critical effector in CC progression indicating the potential prognostic value of FAM83A gene as a novel biomarker for CC progression.

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Section: Introductionmentioning

confidence: 99%

FAM83A as a Potential Biological Marker Is Regulated by miR-206 to Promote Cervical Cancer Progression Through PI3K/AKT/mTOR Pathway

Zhaodong

et al. 2020

Front. Med.

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“…The database is publicly accessible at http://www.prognoscan.org/ ( Mizuno et al, 2009 ). Online consensus Survival for Ovarian Cancer (OSov) encompasses 22 expression datasets and provides six types of survival terms for 3212 patients of OC, which can be available at http://bioinfo.henu.edu.cn/OV/OVList.jsp ( Zheng et al, 2020 ). In this study, PROGgenesV2, PrognoScan, and OSov database was used to assess the prognostic value of hub genes.…”

Section: Functional Enrichment Analysis Of 342 Intersecting Genesmentioning

confidence: 99%

Three Genes Predict Prognosis in Microenvironment of Ovarian Cancer

Guo

Wang

et al. 2020

Front. Genet.

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Ovarian cancer (OC) is the deadliest gynecological cancer in women. Immune cell infiltration has a critical role in regulating carcinogenesis and prognosis in OC. To identify prognostic genes relevant to the tumor microenvironment in OC, we investigated the association between OC and gene expression profiles. Results obtained with the ESTIMATE R tool showed that immune score and stromal score were correlated with lymphatic invasion, and high immune score predicted a favorable prognosis. A total of 342 common differentially expressed genes were identified according to the two scores; these genes were mainly involved in immune response, extracellular region, and serine-type endopeptidase activity. Three immune-related prognostic genes were selected by univariate and multivariate Cox regression analysis. We further established a prognostic model and validated the prognostic value of three hub genes in different databases; our results showed that this model could accurately predict survival and evaluate prognosis independent of clinical characteristics. Three hub genes have prognostic value in OC. TIMER analysis revealed that the three genes were correlated with different immune cells. Low levels of macrophage infiltration and high levels of CD4+ T cell infiltration were associated with favorable survival outcomes. Arm-level gain of GYPC was correlated with neutrophils and dendritic cells. These findings indicate that CXCR4, GYPC, and MMP12 modulate prognosis via effects on the infiltration of immune cells. Thus, these genes represent potential targets for immune therapy in OC.

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“…The cBioPortal online platform provides a visual analysis instrument for interactive exploration of diverse cancer genome datasets [18,19], and Users can perform survival analysis based on DNA mutation data and CNA data, and visually display the patient's OS and DFS results in the form of Kaplan-Meier diagrams [20]. Draw Kaplan-Meier curve through cBioPortal to analyze the overall survival of hub genes.…”

Section: Survival Analysismentioning

confidence: 99%

Overexpression of CCNE1 confers a poorer prognostic in triple negative breast cancer identified by bioinformatic analysis

Yuan

Zheng

Liao

et al. 2020

Preprint

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Background. Triple-negative breast cancer (TNBC) is a major subtype of breast cancer. Due to the lack of effective therapeutic targets, the prognosis is poor. In order to find an effective target, despite many efforts, the molecular mechanisms of TNBC are still not well understood which remain to be a profound clinical challenge.Methods. To identify the candidate genes in the carcinogenesis and progression of TNBC, microarray datasets GSE36693 and GSE65216 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and functional and pathway enrichment analyses were performed using the Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) databases via DAVID. We constructed the protein-protein interaction network (PPI) and the performed the module analysis using STRING and Cytoscape. Then we reanalyzed the selected DEGs genes and the survival analysis was performed using cBioportal.Results. A total of 140 DEGs were identified, consisting of 69 upregulated genes and 71 downregulated genes. Three hub genes were up-regulated among the selected genes from PPI and biological process analysis uncovered the fact that these genes were mainly enriched in p53 pathway and the pathways in cancer. Survival analysis showed that only CCNE1 may be involved in the carcinogenesis, invasion or recurrence of TNBC. Conclusion. CCNE1 could confer a poorer prognostic in TNBC identified by bioinformatic analysis and play key roles in the progression of TNBC which may contribute potential targets for the diagnosis, treatment and prognosis assessment of TNBC.

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Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis

Cited by 91 publications

References 65 publications

FAM83A as a Potential Biological Marker Is Regulated by miR-206 to Promote Cervical Cancer Progression Through PI3K/AKT/mTOR Pathway

FAM83A as a Potential Biological Marker Is Regulated by miR-206 to Promote Cervical Cancer Progression Through PI3K/AKT/mTOR Pathway

Three Genes Predict Prognosis in Microenvironment of Ovarian Cancer

Overexpression of CCNE1 confers a poorer prognostic in triple negative breast cancer identified by bioinformatic analysis

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