Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial

Crosara, Karla Tonelli Bicalho; Moffa, Eduardo Buozi; Xiao, Yiming; Siqueira, Walter L.

doi:10.1016/j.jprot.2017.08.002

Cited by 60 publications

(47 citation statements)

References 31 publications

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“…We further analyzed the topological structure of the summarized interaction network using Cytoscape software. 29 , 30 , 31 , 32 We discovered 19 genes at the central of the interaction network of the 73 genes based on the topological structure. Genes with a degree of connection exceeding 15, except for SPAG5 , have been previously linked to the development of gastric cancer.…”

Section: Discussionmentioning

confidence: 99%

Analysis of cyclin E co‐expression genes reveals nuclear transcription factor Y subunit alpha is an oncogene in gastric cancer

Bie

et al. 2019

Chronic Diseases and Translational Medicine

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Objective To explore genes potentially co-expressed with cyclin E in gastric cancer and discover possible targets for gastric cancer treatment. Methods The Cancer Genome Atlas (TCGA) stomach adenocarcinoma sequencing data were used to predict genes co-expressed with cyclin E. Co-expression genes predicted by cBioPortal online analysis with Pearson correlation coefficient ≥0.4 were analyzed by gene ontology (GO) enrichment annotation using the PANTHER online platform (Ver. 7). Interactions between proteins encoded by these genes were analyzed using the STRING online platform (Ver. 10.5) and Cytoscape software (Ver. 3.5.1). Genes displaying a high degree of connection were analyzed by transcription factor enrichment prediction using FunRich software (Ver. 3). The significant transcription factor and cyclin E expression levels and their impact on gastric cancer progression were analyzed by Western blotting and Kaplan–Meier survival curve analysis. Results After filtering the co-expression gene prediction results, 78 predicted genes that included 73 protein coding genes and 5 non-coding genes with Pearson correlation coefficient ≥0.4 were selected. The expressions of the genes were considered to be correlated with cyclin E expression. Among the 78 genes co-expressed with cyclin E, 19 genes at the central of the regulatory network associated with cyclin E were discovered. Nuclear transcription factor Y subunit alpha (NF-YA) was identified as a significant transcription factor associated with cyclin E co-expressing genes. Analysis of specimen donors’ clinical records revealed that high expression of NF-YA tended to be associated with increased cyclin E expression. The expression of both was associated with progression of gastric cancer. Western blotting results showed that compared with normal tissues, NF-YA and cyclin E were highly expressed in tumor tissues ( P < 0.001). Survival curve analysis clearly demonstrated relatively poor overall survival of gastric cancer patients with high cyclin E or high NF-YA expression level, compared to patients with low cyclin E or NF-YA expression ( P < 0.05). Conclusions NF-YA may promote gastric cancer progression by increasing the transcription of cyclin E and other cell cycle regulatory genes. NF-YA might be a potential therapeutically useful prognostic factor for gastric cancer.

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Section: Discussionmentioning

confidence: 99%

Analysis of cyclin E co‐expression genes reveals nuclear transcription factor Y subunit alpha is an oncogene in gastric cancer

Bie

et al. 2019

Chronic Diseases and Translational Medicine

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“…Protein–protein interactions are a common physiological mechanism for the protection and function of proteins in saliva. The STRING protein database was found to be useful for studying and predicting protein–protein associations [ 33 ]. In our previous study, the STRING online database, we identified 63 interactions in saliva samples from children with and without dental caries, and reported associations among histatin-1, mucin-5B, mucin-7, and cystatin S [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

iTRAQ-based quantitative analysis of age-specific variations in salivary proteome of caries-susceptible individuals

Wang

Zheng

et al. 2018

J Transl Med

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BackgroundHuman saliva is a protein-rich, easily accessible source of potential biomarkers for the diagnosis of oral and systemic diseases. However, little is known about the changes in salivary proteome associated with aging of patients with dental caries. Here, we applied isobaric tags for relative and absolute quantitation (iTRAQ) in combination with multiple reaction monitoring mass spectrometry (MRM-MS) to characterize the salivary proteome profiles of subjects of different ages, presenting with and without caries, with the aim of identifying age-related biomarkers for dental caries.MethodsUnstimulated whole saliva samples were collected from 40 caries-free and caries-susceptible young adults and elderly individuals. Salivary proteins were extracted, reduced, alkylated, digested with trypsin and then analyzed using iTRAQ-coupled LC–MS/MS, followed by GO annotation, biological pathway analysis, hierarchical clustering analysis, and protein–protein interaction analysis. Candidate verification was then conducted using MRM-MS.ResultsAmong 658 salivary proteins identified using tandem mass spectrometry, 435 proteins exhibited altered expression patterns in different age groups with and without caries. Of these proteins, 96 displayed age-specific changes among caries-susceptible adults and elderly individuals, and were mainly associated with salivary secretion pathway, while 110 age-specific proteins were identified among healthy individuals. It was found that the age factor caused significant variations and played an important role in both healthy and cariogenic salivary proteomes. Subsequently, a total of 136 target proteins with complex protein–protein interactions, including 14 age-specific proteins associated with caries, were further successfully validated using MRM analysis. Moreover, non-age-specific proteins (histatin-1 and BPI fold-containing family B member 1) were verified to be important candidate biomarkers for common dental caries.ConclusionsOur proteomic analysis performed using the discovery-through-verification pipeline revealed distinct variations caused by age factor in both healthy and cariogenic salivary proteomes, highlighting the significance of age in the great potential of saliva for caries diagnosis and biomarker discovery.Electronic supplementary materialThe online version of this article (10.1186/s12967-018-1669-2) contains supplementary material, which is available to authorized users.

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“…To analyze the interaction and function of differential genes and hub genes, Metascape database and STRING database (https://string-db.org/) 22 were used to construct PPI network, and Cytoscape 3.6.1 software was used to correct the results. Cytoscape software is a widely used tool, which can intuitively analyze the interaction network of different genes.…”

Section: Methodsmentioning

confidence: 99%

Identification of potential hub genes via bioinformatics analysis combined with experimental verification in colorectal cancer

Zhou

Yang

Yue

et al. 2020

Molecular Carcinogenesis

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Colorectal cancer (CRC) is a kind of malignant cancer with high morbidity and mortality. The purpose of this study was to explore potential regulated key genes involved in CRC through bioinformatics analysis and experimental verification. The gene expression profile data were downloaded from the Gene Expression Omnibus, and the differential expression genes were detected in cancerous and paracancerous samples of CRC patients, respectively. Then functional enrichment analysis, such as the Kyoto Encyclopedia of Genes and Genomes pathway analysis as well as the protein‐protein interaction network were constructed, and the highly related genes were clustered by Molecular COmplex DEtection algorithm to find out the core interaction in different genes' crosstalk. The genes affecting CRC prognosis were screened by the Human Protein Atlas database. In addition, the expression level of core genes was detected by GEPIA database, and the core genes' changes in large‐scale cancer genome data set were directly analyzed by cBioPortal database. The expression of the predicted hub genes DSN1, AHCY, and ERCC6L was verified by reverse‐transcription quantitative polymerase chain reaction in CRC cells. The gene function of DSN1 was analyzed by wound healing and colony formation assays. The results showed that silencing of DSN1 could significantly reduce the migration and proliferation of CRC cells. Further, BUB1B, the potential interacting protein of DSN1, was also predicted via bioinformatics analysis. Above all, this study shows that bioinformatics analysis combined with experimental method verification provide more potential vital genes for the prevention and therapy of CRC.

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Merging in-silico and in vitro salivary protein complex partners using the STRING database: A tutorial

Cited by 60 publications

References 31 publications

Analysis of cyclin E co‐expression genes reveals nuclear transcription factor Y subunit alpha is an oncogene in gastric cancer

Analysis of cyclin E co‐expression genes reveals nuclear transcription factor Y subunit alpha is an oncogene in gastric cancer

iTRAQ-based quantitative analysis of age-specific variations in salivary proteome of caries-susceptible individuals

Identification of potential hub genes via bioinformatics analysis combined with experimental verification in colorectal cancer

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