Construction and validation of an anoikis-related prognostic model for lung adenocarcinoma based on bulk and single-cell transcriptomic data

TL;DR

This study creates a 7-gene model to predict survival in lung adenocarcinoma patients by analyzing how genes related to anoikis resistance affect tumor progression and immune response.

Contribution

A novel 7-gene prognostic model for LUAD based on anoikis-related genes and validated using bulk and single-cell data.

Findings

The 7-gene model accurately predicted 1- to 3-year survival rates in two LUAD cohorts with AUC values above 0.68.

High TIMP1 expression in epithelial cells correlates with immunosuppressive tumor microenvironment and increased Treg cell activity.

The model is associated with clinical features, immune infiltration, and tumor microenvironment remodeling.

Abstract

Lung adenocarcinoma (LUAD) is a highly aggressive lung cancer with poor prognosis due to lack of reliable biomarkers. Resistance to anoikis drives tumor progression and metastasis. This study aims to develop and validate an anoikis-related prognostic model for LUAD. We employed univariate Cox regression analysis, LASSO regression, and random forest algorithms to identify anoikis-related genes (ARG) from bulk transcriptomic datasets, and establish a 7-gene prognostic signature, validated in two LUAD cohorts from GEO database. We evaluated immune infiltration, molecular functions, and genomic alterations between risk groups and analyzed single-cell RNA sequencing data. IHC and mIF validated TIMP1 expression and its interaction with Treg cells. We developed a 7-gene prognostic model (LDHA, PLK1, TRAF2, ITGB4, SLCO1B3, TIMP1, ZEB2) using machine learning to predict survival in LUAD patients. The model accurately predicted 1-year survival rates (GSE31210: AUC = 0.805; GSE30219: AUC = 0.787), 2-year survival rates (GSE31210: AUC = 0.769; GSE30219: AUC = 0.681), and 3-year survival rates (GSE31210: AUC = 0.695; GSE30219: AUC = 0.735) and correlated with clinical features, immune infiltration, and tumor microenvironment (TME) remodeling. Single-cell sequencing data showed that LUAD patients exhibited an immunosuppressive TME phenotype, which was exacerbated by high TIMP1 expression in epithelial cells, promoting Treg cell activity. The 7-gene ARG prognostic model established in this study shows promising potential as a clinically applicable tool for decision-making.

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