A Computational Approach to Justifying Stratifin As a Candidate Diagnostic and Prognostic Biomarker for Pancreatic Cancer

Overview

Journal Biomed Res Int

Publisher Wiley

Specialties Biomedical Engineering
Biotechnology
General Medicine

Date 2022 May 13

PMID 35547358

Authors

Md Roman Mogal

Asadullah Junayed

Md Rashel Mahmod

Sagarika Adhikary Sompa

Suzana Afrin Lima

Newton Kar

TasminaTarin

Marina Khatun

Md Abu Zubair

Md Asaduzzaman Sikder

Affiliations

Soon will be listed here.

Abstract

Pancreatic cancer (PC) is considered a silent killer because it does not show specific symptoms at an early stage. Thus, identifying suitable biomarkers is important to avoid the burden of PC. Stratifin (SFN) encodes the 14-3-3 protein, which is expressed in a tissue-dependent manner and plays a vital role in cell cycle regulation. Thus, SFN could be a promising therapeutic target for several types of cancer. This study was aimed at investigating, using online bioinformatics tools, whether SFN could be used as a diagnostic and prognostic biomarker in PC. SFN expression was explored by utilizing the ONCOMINE, UALCAN, GEPIA2, and GENT2 tools, which revealed that SFN expression is higher in PC than in normal tissues. The clinicopathological analysis using the ULCAN tool showed that the intensity of SFN expression is commensurate with cancer progression. GEPIA2, R2, and OncoLnc revealed a negative correlation between SFN expression and survival probability in PC patients. The ONCOMINE, UCSC Xena, and GEPIA2 tools showed that cofilin 1 is strongly coexpressed with SFN. Moreover, enrichment and network analyses of SFN were performed using the Enrichr and NetworkAnalyst platforms, respectively. Receiver operating characteristic (ROC) curves revealed that tissue-dependent expression of the SFN gene could serve as a diagnostic and prognostic biomarker. However, further wet laboratory studies are necessary to determine the relevance of SFN expression as a biomarker.

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