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A miRNAs Based Exploration of promising Biomarkers in Cervical Cancer using Bioinformatic Methods

Elumalai, E.; A, M.; T, S. S.; OM, A. D.; Gupta, K. K.

2021-12-30 bioinformatics
10.1101/2021.12.27.474313 bioRxiv
Show abstract

Cervical Cancer (CC) is a gynecologic cancer. In this cancer early detection is incredibly tough because most of the patients are not have any specific symptoms that results in suspending the proper identification. In this work, we selected TCGA CESC datasets and miRNA Seq analysis was done. The expression profiles of miRNAs in cervical cancer datasets were investigated using bioinformatics tools. The expression profiles of miRNA in Normal tissue, primary tumor and metastatic samples were analyzed. Based on p-value, principal component analysis and comparative literature survey, we reported 6 over-expressed (5X) miRNA at metastatic stage namely, hsa-mir-363, hsa-mir-429, hsa-mir-141, hsa-mir-93, hsa-mir-203b and hsa-mir-18a. Expression profiles were compared in heatmap. The target genes for the selected miRNAs were investigated for interaction and pathway details. The identification of two hub proteins (PTEN and MYC) in Protein-Protein Interaction Network was followed by pathway analysis. Our results indicate that hsa-mir-363, hsa-mir-429, hsa-mir-141, hsa-mir-93, hsa-mir-203b and hsa-mir-18a could be a potential diagnostic biomarkers for early-stage CESC and serve as prognostic predictors for patients with CESC.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.