• rs201365744 promotes lung adenocarcinoma by disturbing interactions of LCN2 protein: an in- silico approach
  • Ghazaleh Sheikhi,1 Mohammad Rezaei,2 Mansoureh Azadeh,3,*
    1. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran
    2. Department of Biology and Biotechnology, University of Pavia, Pavia, Italy
    3. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran


  • Introduction: Lung cancer remains the leading cause of cancer related deaths worldwide despite the advancement in screening, diagnosis, and treatment. Among different sub-types of lung cancer, lung adenocarcinoma (LUAD) has become the most prevalent one. One of the challenges in the treatment of LUAD is early diagnosis to increase survival rate. Over the years, molecular methods such as DNA microarrays have been developed to have better insights into the biology of lung cancer. Moreover, using reliable biomarkers such as single nucleotide polymorphisms (SNP) would immensely improve prognosis of the disease. Thus, this study aimed to identify novel SNPs affecting protein interactions by means of bioinformatics tools.
  • Methods: NCBI Gene Expression Omnibus database (GEO) was used to obtain GSE136043, which was analyzed using GEO2R online software to identify differentially expressed genes (DEG). Genes with logFC > 3 and adjusted p-value < 0.01 were selected and validation was performed by GEPIA2 and ENCORI online soft wares. One of the most significant up-regulated genes, Lipocalin 2(LCN2), was chosen for further analysis. Signaling pathway of the selected gene was achieved using Kyoto Encyclopedia of Genes and Genomes (KEGG). Next, SNPs in coding sequence (CDS) for LCN2 were extracted from NCBI dbSNP database and then taken to SIFT ( a sequence homology-based tool) to identify deleterious SNPs. Biophysical validation of these SNPs was performed using HOPE web server.
  • Results: According to GEO2R analysis, LCN2 was one of the most significant up-regulated genes (logFC = 5.17, adjusted p-value = 0.0002). Results from GEPIA2 showed that overexpression of LCN2 in LUAD is significant (p-value < 0.05). This was further validated by ENCORI using gene differential expression tool (p-value = 4.6e-10, FDR = 3.2e-9). Results from KEGG showed that LCN2 is involved in Interleukin 17 signaling pathway, as well. 21 deleterious SNPs were identified in the coding region using SIFT. Three SNPs with the highest SIFT score were taken to HOPE web server to ensure that the mutation would change protein interactions. It was revealed that rs201365744 is the most significant deleterious SNP in the protein coding region of LCN2. In this SNP, Tyrosine mutates into Histidine at position 76. Based on the data achieved from HOPE, the mutant residue is smaller and more hydrophobic than the wild-type residue. The changes in size and hydrophobicity will affect formation of hydrogen bonds. Since the mutated residue is situated in a domain that is essential for binding of other molecules and is in contact with residues in a domain that is also important for binding, the mutation can alter the interactions between these domains, which can disturb function of the protein, subsequently.
  • Conclusion: According to results of this study, rs201365744 can promote LUAD development by changing interactions and function of LCN2, which can act as a potential biomarker in prognosis of lung adenocarcinoma.
  • Keywords: Cancer, LUAD, LCN2, Single nucleotide polymorphism, Microarray