# Proliferation-cycle gene signatures predict immune landscape and prognosis in lung adenocarcinoma

## TL;DR

This study identifies gene signatures linked to cell proliferation that predict survival and immune response in lung adenocarcinoma patients.

## Contribution

The study introduces a novel risk model using proliferation-cycle genes to predict prognosis and immune landscape in LUAD.

## Key findings

- High-risk patients based on the gene signature have significantly poorer overall survival.
- The gene signature correlates with increased immune infiltration and immunosuppressive markers in the tumor microenvironment.
- The risk model reveals novel therapeutic targets with potential for further exploration.

## Abstract

Despite advancements in diagnostic techniques and therapeutic strategies, the prognosis for Lung adenocarcinoma (LUAD) patients remains poor. Cell proliferation and cycle dysregulation drive cancer via uncontrolled cell growth. These genes also modulate tumor immune microenvironment (TIME), yet the precise mechanisms in LUAD remain largely unknown.

This study aimed to identify key proliferation-cycle genes in LUAD, characterize the TIME associated with proliferation-cycle gene signatures and assess the impact of proliferation-cycle gene signatures on immunotherapy responsiveness. We analyzed The Cancer Genome Atlas (TCGA) LUAD transcriptomic data and identified eight proliferation-cycle-related risk genes (seven up-regulated: FAP, IL2RA, ITGA2, CHORDC1, PIM2, POU3F2, CD180; one down-regulated: FKBP1B). Independent cross-validation using the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) dataset confirmed the consistent expression patterns for all eight candidate genes in LUAD tumors. A risk model based on these genes stratified patients into distinct prognostic groups, revealing: (1) Survival disparity: High-risk patients exhibited poorer overall survival (p = 6.2e−05). (2) Immunosuppressive TIME: Elevated risk scores correlated with enhanced immune infiltration (p = 2.9e−12), enriched immunosuppressive populations (Tregs), reduced cytotoxic effectors (CD8+ T cells), and up-regulated immune checkpoint molecules (PDCD1/PD-L1, CTLA4). (3) Scientific implications: Risk signatures exhibited no significant correlation with tumor mutational burden (TMB), yet uncovered novel candidate targets with therapeutic potential, meriting further mechanistic exploration.

Proliferation-cycle gene signatures are robust biomarkers for LUAD risk stratification, prognosis, and immune landscape prediction. Their mechanistic integration into multi-dimensional oncological models could reveal previously unrecognized layers of antitumor immune regulation.

The online version contains supplementary material available at 10.1007/s12672-025-04346-6.