Computational assessment of MCM2 transcriptional expression and identification of the prognostic biomarker for human breast cancer. Issue 10 (October 2020)

• Record Type: Journal Article
• Authors: Samad, Abdus; Haque, Farhana; Nain, Zulkar; Alam, Rahat; Al Noman, Md Abdullah; Rahman Molla, Mohammad Habibur; Hossen, Md Saddam; Islam, Md Raquibul; Khan, Md Iqbal; Ahammad, Foysal
• Is Part Of: Heliyon. Volume 6:Issue 10(2020)
• Publication Date: 2020-10
• Subjects: Data analysis -- Information retrieval -- Computational chemistry -- Computational biology -- Bioinformatics -- Biocomputational method -- Gene expression -- Gene mutation -- Gene regulation -- Microarray -- Cancer research -- MCM2 -- Breast cancer -- Mutation analysis -- Prognostic biomarker -- Transcriptional expressions; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2020.e05087
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: Minichromosome maintenance protein 2 (MCM2) is a highly conserved protein from the MCM protein family that plays an important role in eukaryotic DNA replication as well as in cell cycle progression. In addition, it maintains the ploidy level consistency in eukaryotic cells, hence, mutations or alteration of this protein could result in the disintegration of the fine-tuned molecular machinery that can lead to uncontrolled cell proliferation. Moreover, MCM2 has been found to be an important marker for progression and prognosis in different cancers. Therefore, we aimed to analyze the MCM2 expression and the associated outcome in breast cancer (BC) patients based on the publicly available online databases. In this study, server-based gene expression analyses indicate the upregulation of MCM2 ( p < 10 −6 ; fold change>2.0) in various BC subtypes as compared to the respective normal tissues. Besides, the evaluation of histological sections from healthy and cancer tissues showed strong staining signals indicating higher expression of MCM2 protein. The overexpression of MCM2 was significantly correlated to promoter methylation and was related to patients' clinical features. Further, mutation analysis suggested missense as the predominant type of mutation (71.4%) with 18 copy-number alterations and 0.2% mutation frequency in the MCM2 gene. This study revealed a significant correlation (Cox p ≤ 0.05) between the higher MCM2 expression and lower patient survival. Finally, we identified the co-expressed genes with gene ontological features and signaling pathways associated in BC development. We believe that this study will provide a basis for MCM2 to be a significant biomarker for human BC prognosis. Abstract : Data analysis; Information retrieval; Computational chemistry; Computational biology; Bioinformatics; Biocomputational method; Gene expression; Gene mutation; Gene regulation; Microarray; Cancer research; MCM2; Breast cancer; Mutation analysis; Prognostic biomarker; Transcriptional expressions