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An interaction network driven approach for identifying biomarkers for progressing cervical intraepithelial neoplasia

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Overlapping genes across high-grade squamous intraepithelial lesions (CIN2 and 3) and cancer may serve as potential biomarkers for this progressive disease. Differentially expressed genes (DEGs) of dysplastic (CIN2 and CIN3)… Click to show full abstract

Overlapping genes across high-grade squamous intraepithelial lesions (CIN2 and 3) and cancer may serve as potential biomarkers for this progressive disease. Differentially expressed genes (DEGs) of dysplastic (CIN2 and CIN3) and cancer cells were identified by microarray data analysis. Gene interaction network was constructed using the 98 common DEGs among the dysplastic and cancer cells and analysed for the identification of common modules, hubs and significant motifs. Two significant modules and 10 hubs of the common gene interaction network, with 125 nodes and 201 edges were found. DEGs namely NDC80, ZWINT, CDC7, MCM4, MCM2 and MCM6 were found to be common in both the significant modules as well as the hubs. Of these, ZWINT, CDC7, MCM4, MCM2 and MCM6 were further identified to be part of most significant motifs. This overlapping relationship provides a list of common disease related genes among pre-cancerous and cancer stages which could help in targeting the proliferating cancerous cells during onset. Capitalizing upon and targeting Minichromosome maintenance protein complex - specifically the MCM2, MCM4 and MCM6 subunits, ZWINT and CDC7 for experimental validation, may provide valuable insights in understanding and detection of progressing cervical neoplasia to cervical cancer at an early stage.

Keywords: cancer; interaction network; zwint cdc7; progressing cervical

Journal Title: Scientific Reports
Year Published: 2018

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