Identification and Functional Characterization of PI3K/Akt/mTOR Pathway-Related lncRNAs in Lung Adenocarcinoma: A Retrospective Study

Document Type : Original Article

Authors

1 The Marine Biomedical Research Institute of Guangdong Zhanjiang, School of Ocean and Tropical Medicine, Guangdong Medical University, Zhanjiang, China

2 Department of Clinical Laboratory, The Third People's Hospital of Hubei Province, Wuhan, China

3 Laboratory of General Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

Abstract

Objective: This paper aimed to investigate the PI3K/Akt/mTOR signal-pathway regulator factor-related lncRNA
signatures (PAM-SRFLncSigs), associated with regulators of the indicated signaling pathway in patients with lung
adenocarcinoma (LUAD) undergoing immunotherapy.
Materials and Methods: In this retrospective study, we employed univariate Cox, multivariate Cox, and least absolute
shrinkage and selection operator (LASSO) regression analyses to identify prognostically relevant long non-coding
RNAs (lncRNAs), construct prognostic models, and perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes
and Genomes (KEGG) analyses. Subsequently, immunoassay and chemotherapy drug screening were conducted.
Finally, the prognostic model was validated using the Imvigor210 cohort, and tumor stem cells were analyzed.
Results: We identified seven prognosis-related lncRNAs (AC084757.3, AC010999.2, LINC02802, AC026979.2,
AC024896.1, LINC00941 and LINC01312). We also developed prognostic models to predict survival in patients
with LUAD. KEGG enrichment analysis confirmed association of LUAD with the PI3K/Akt/mTOR signaling pathway.
In the analysis of immune function pathways, we discovered three good prognostic pathways (Cytolytic_activity,
Inflammation-promoting, T_cell_co-inhibition) in LUAD. Additionally, we screened 73 oncology chemotherapy drugs
using the "pRRophetic" algorithm.
Conclusion: Identification of seven lncRNAs linked to regulators of the PI3K/Akt/mTOR signaling pathway provided
valuable insights into predicting the prognosis of LUAD, understanding the immune microenvironment and optimizing
immunotherapy strategies.

Keywords

Main Subjects

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