Scientific Reports (Oct 2022)

An in silico comparative transcriptome analysis identifying hub lncRNAs and mRNAs in brain metastatic small cell lung cancer (SCLC)

  • Arsham Mikaeili Namini,
  • Motahareh Jahangir,
  • Maryam Mohseni,
  • Ali Asghar Kolahi,
  • Hossein Hassanian-Moghaddam,
  • Zeinab Mazloumi,
  • Marzieh Motallebi,
  • Mojgan Sheikhpour,
  • Abolfazl Movafagh

DOI
https://doi.org/10.1038/s41598-022-22252-7
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 14

Abstract

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Abstract Small cell lung cancer (SCLC) is a particularly lethal subtype of lung cancer. Metastatic lung tumours lead to most deaths from lung cancer. Predicting and preventing tumour metastasis is crucially essential for patient survivability. Hence, in the current study, we focused on a comprehensive analysis of lung cancer patients' differentially expressed genes (DEGs) on brain metastasis cell lines. DEGs are analysed through KEGG and GO databases for the most critical biological processes and pathways for enriched DEGs. Additionally, we performed protein–protein interaction (PPI), GeneMANIA, and Kaplan–Meier survival analyses on our DEGs. This article focused on mRNA and lncRNA DEGs for LC patients with brain metastasis and underlying molecular mechanisms. The expression data was gathered from the Gene Expression Omnibus database (GSE161968). We demonstrate that 30 distinct genes are up-expressed in brain metastatic SCLC patients, and 31 genes are down-expressed. All our analyses show that these genes are involved in metastatic SCLC. PPI analysis revealed two hub genes (CAT and APP). The results of this article present three lncRNAs, Including XLOC_l2_000941, LOC100507481, and XLOC_l2_007062, also notable mRNAs, have a close relation with brain metastasis in lung cancer and may have a role in the epithelial-mesenchymal transition (EMT) in tumour cells.