Gene-knockdown Methods for Silencing Nuclear-localized Insulin Receptors in Lung Adenocarcinoma Cells: A Bioinformatics Approach
Authors: Ren Qiu , Ma Hui , Wang Lingling , Qin Jiayu , Tian Miao , Zhang Wei 
Published: July 2024

Background:
Lung adenocarcinoma, the predominant subtype of lung cancer, presents
a significant challenge to public health due to its notably low five-year survival rate. Recent epidemiological
data highlights a concerning trend: patients with pulmonary adenocarcinoma and comorbid
diabetes exhibit substantially elevated mortality rates compared to those without diabetes,
suggesting a potential link between hyperinsulinemia in diabetic individuals and accelerated progression
of pulmonary adenocarcinoma. Insulin Receptor (IR) is a tyrosine-protein kinase on the
cell surface, and its over-expression is considered the pathological hallmark of hyperinsulinemia
in various cancer cell types. Research indicates that IR can translocate to the nucleus of lung adenocarcinoma
cells to promote their proliferation, but its precise molecular targets remain unclear.
This study aims to silence IRs in lung adenocarcinoma cells and identify key genes within the
ERK pathway that may serve as potential molecular targets for intervention.

Methods:
Gene expression data from lung adenocarcinoma and para cancer tissues were retrieved
from the Gene Expression Omnibus (GEO) database and assessed through "pheatmap", GO annotation,
KEGG analysis, R calculations, Cytoscape mapping, and Hub gene screening. Significant
genes were visualized using the ggplot2 tool to compare expression patterns between the two
groups. Additionally, survival analysis was performed using the R "survminer" and "survival"
packages, along with the R "pathview" package for pathway visualization. Marker genes were
identified and linked to relevant signaling pathways. Validation was conducted utilizing real-time
quantitative polymerase chain reaction and immunoblotting assays in an A549 lung cancer cell
model to determine the roles of these marker genes in associated signaling cascades.

Results:
The study examined 58 lung adenocarcinoma samples and paired para-neoplastic tissues.
Analysis of the GSE32863 dataset from GEO revealed 1040 differentially expressed genes, with
421 up-regulated and 619 down-regulated. Visualization of these differences identified 172 significant
alterations, comprising 141 up-regulated and 31 down-regulated genes. Functional enrichment
analysis using Gene Ontology (GO) revealed 56 molecular functions, 77 cellular components,
and 816 biological processes. KEGG analysis identified 17 strongly enriched functions, including
cytokine interactions and tumor necrosis factor signaling. Moreover, the ERK signaling
pathway was associated with four Hub genes (FGFR4, ANGPT1, TEK, and IL1B) in cellular biological
processes. Further validation demonstrated a positive correlation between IL-1B expression
in the ERK signaling pathway and lung cancer through real-time fluorescence quantitative enzyme-
linked reaction with immunoblotting assays.

Conclusion:
In IR-silenced lung adenocarcinoma, the expression of the IL-1B gene exhibited a
positive correlation with the ERK signaling pathway.