A bioinformatics approach to decode core genes and molecular pathways shared by breast cancer and endometrial cancer

Rahman, Foyzur; Rahman, Rezanur; Islam, Tania; Zaman, Toyfiquz; Shuvo, Abu Hena; Hossain, Tofazzal; Islam, Rafiqul; Karim, Rezaul; Moni, Mohammad Ali

doi:10.1016/j.imu.2019.100274

Cited by 7 publications

(2 citation statements)

References 29 publications

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“…SARS-CoV has a number of functional proteins [ 29 , 30 ], of which many are still unknown or poorly understood [ 31 , 32 ]. Advances in computer biology have created a variety of platforms and methods for predicting protein structure, binding sites, and biological activity [ 33 , 34 ]. Protein studies using bioinformatics methods make it possible to evaluate 3D structural conformations, classify novel domains, and determine functions of the proteins [ 35 , 36 ].…”

Section: Introductionmentioning

confidence: 99%

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Rahman¹,

Hasan²,

Biswas³

et al. 2023

Genomics Inform

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Characterization as well as prediction of the secondary and tertiary structure of hypothetical proteins from their amino acid sequences uploaded in databases by in silico approach are the critical issues in computational biology. Severe acute respiratory syndrome–associated coronavirus (SARS-CoV), which is responsible for pneumonia alike diseases, possesses a wide range of proteins of which many are still uncharacterized. The current study was conducted to reveal the physicochemical characteristics and structures of an uncharacterized protein Q6S8D9_SARS of SARS-CoV. Following the common flowchart of characterizing a hypothetical protein, several sophisticated computerized tools e.g., ExPASy Protparam, CD Search, SOPMA, PSIPRED, HHpred, etc. were employed to discover the functions and structures of Q6S8D9_SARS. After delineating the secondary and tertiary structures of the protein, some quality evaluating tools e.g., PROCHECK, ProSA-web etc. were performed to assess the structures and later the active site was identified also by CASTp v.3.0. The protein contains more negatively charged residues than positively charged residues and a high aliphatic index value which make the protein more stable. The 2D and 3D structures modeled by several bioinformatics tools ensured that the proteins had domain in it which indicated it was functional protein having the ability to trouble host antiviral inflammatory cytokine and interferon production pathways. Moreover, active site was found in the protein where ligand could bind. The study was aimed to unveil the features and structures of an uncharacterized protein of SARS-CoV which can be a therapeutic target for development of vaccines against the virus. Further research are needed to accomplish the task.

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Section: Introductionmentioning

confidence: 99%

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Rahman¹,

Hasan²,

Biswas³

et al. 2023

Genomics Inform

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“…To identify such DEGs, microarray gene expression profiling is widely used [13,14], and several such studies have been performed on thyroid cancer subtypes [15]. For example, Huang et al [16] studied gene expression profiles of thyroid cancers, although not functional interactions between gene products.…”

Section: Introductionmentioning

confidence: 99%

Network-Based Genetic Profiling Reveals Cellular Pathway Differences Between Follicular Thyroid Carcinoma and Follicular Thyroid Adenoma

Hossain

Akter

Rahman

et al. 2020

IJERPH

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Molecular mechanisms underlying the pathogenesis and progression of malignant thyroid cancers, such as follicular thyroid carcinomas (FTCs), and how these differ from benign thyroid lesions, are poorly understood. In this study, we employed network-based integrative analyses of FTC and benign follicular thyroid adenoma (FTA) lesion transcriptomes to identify key genes and pathways that differ between them. We first analysed a microarray gene expression dataset (Gene Expression Omnibus GSE82208, n = 52) obtained from FTC and FTA tissues to identify differentially expressed genes (DEGs). Pathway analyses of these DEGs were then performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) resources to identify potentially important pathways, and protein-protein interactions (PPIs) were examined to identify pathway hub genes. Our data analysis identified 598 DEGs, 133 genes with higher and 465 genes with lower expression in FTCs. We identified four significant pathways (one carbon pool by folate, p53 signalling, progesterone-mediated oocyte maturation signalling, and cell cycle pathways) connected to DEGs with high FTC expression; eight pathways were connected to DEGs with lower relative FTC expression. Ten GO groups were significantly connected with FTC-high expression DEGs and 80 with low-FTC expression DEGs. PPI analysis then identified 12 potential hub genes based on degree and betweenness centrality; namely, TOP2A, JUN, EGFR, CDK1, FOS, CDKN3, EZH2, TYMS, PBK, CDH1, UBE2C, and CCNB2. Moreover, transcription factors (TFs) were identified that may underlie gene expression differences observed between FTC and FTA, including FOXC1, GATA2, YY1, FOXL1, E2F1, NFIC, SRF, TFAP2A, HINFP, and CREB1. We also identified microRNA (miRNAs) that may also affect transcript levels of DEGs; these included hsa-mir-335-5p, -26b-5p, -124-3p, -16-5p, -192-5p, -1-3p, -17-5p, -92a-3p, -215-5p, and -20a-5p. Thus, our study identified DEGs, molecular pathways, TFs, and miRNAs that reflect molecular mechanisms that differ between FTC and benign FTA. Given the general similarities of these lesions and common tissue origin, some of these differences may reflect malignant progression potential, and include useful candidate biomarkers for FTC and identifying factors important for FTC pathogenesis.

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Differential Expression of MicroRNAs and Predicted Drug Target in Amyotrophic Lateral Sclerosis

2023

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A bioinformatics approach to decode core genes and molecular pathways shared by breast cancer and endometrial cancer

Cited by 7 publications

References 29 publications

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

A bioinformatics approach to characterize a hypothetical protein Q6S8D9_SARS of SARS-CoV

Network-Based Genetic Profiling Reveals Cellular Pathway Differences Between Follicular Thyroid Carcinoma and Follicular Thyroid Adenoma

Differential Expression of MicroRNAs and Predicted Drug Target in Amyotrophic Lateral Sclerosis

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