Research Paper Volume 16, Issue 3 pp 2887—2907

Identification of crucial anoikis-related genes as novel biomarkers and potential therapeutic targets for lung adenocarcinoma via bioinformatic analysis and experimental verification

Jie Wu3, , Yuting Zhang1,2, , Guoxing You1,2, , Wenjie Guo2, , Yupeng Wang2, , Jiaming Li1,2, , Rongzhi Tan2, , Xihua Fu4, , Yukuan Tang5, , Jie Zan2, , Jianfen Su1, ,

  • 1 Department of Pharmacy, Guangzhou Panyu Central Hospital, Guangzhou 511400, China
  • 2 School of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou 510006, China
  • 3 The Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China
  • 4 Department of Infectious Diseases and Hepatology Unit, Guangzhou Panyu Central Hospital, Guangzhou 511400, China
  • 5 Department of Minimally Invasive Interventional Radiology, Guangzhou Panyu Central Hospital, Guangzhou 511400, China

Received: May 30, 2023       Accepted: December 26, 2023       Published: February 9, 2024
How to Cite

Copyright: © 2024 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Lung adenocarcinoma (LUAD) is a malignant tumor of the respiratory system that has a poor 5-year survival rate. Anoikis, a type of programmed cell death, contributes to tumor development and metastasis. The aim of this study was to develop an anoikis-based stratified model, and a multivariable-based nomogram for guiding clinical therapy for LUAD. Through differentially expressed analysis, univariate Cox, LASSO Cox regression, and random forest algorithm analysis, we established a 4 anoikis-related genes-based stratified model, and a multivariable-based nomogram, which could accurately predict the prognosis of LUAD patients in the TCGA and GEO databases, respectively. The low and high-risk score LUAD patients stratified by the model showed different tumor mutation burden, tumor microenvironment, gemcitabine sensitivity and immune checkpoint expressions. Through immunohistochemical analysis of clinical LUAD samples, we found that the 4 anoikis-related genes (PLK1, SLC2A1, ANGPTL4, CDKN3) were highly expressed in the tumor samples from clinical LUAD patients, and knockdown of these genes in LUAD cells by transfection with small interfering RNAs significantly inhibited LUAD cell proliferation and migration, and promoted anoikis. In conclusion, we developed an anoikis-based stratified model and a multivariable-based nomogram of LUAD, which could predict the survival of LUAD patients and guide clinical treatment.


NSCLC: non-small cell lung cancers; LUAD: lung adenocarcinomas; PLK1: polo like kinase 1; SLC2A1: solute carrier family 2 member 1; ANGPTL4: angiopoietin like 4; CDKN3: cyclin dependent kinase inhibitor 3; ECM: extracellular matrix; DEGs: differentially expressed genes; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Ontology; ROC: receiver operating curve; ssGSEA: single-sample gene set enrichment analysis; BP: biological process; CC: cellular component; MF: molecular function.