What question did this study set out to answer?

The aim was to identify prognostic genes related to lymph node metastasis and immune cells in lung adenocarcinoma.

April 16, 2026The FASEB Journal0 citations

Integration of Single‐Cell RNA Sequencing and Machine Learning to Identify and Validate Prognostic Genes With Lymph Node Metastasis and Immune Cell Signatures in Lung Adenocarcinoma

CLChuan LinNanchang University XCXuan ChenNanchang University YSYong SunNanchang University

Key Points

The aim was to identify prognostic genes related to lymph node metastasis and immune cells in lung adenocarcinoma.
Utilized public databases to obtain lung adenocarcinoma-related datasets.
Conducted bioinformatics analyses to identify prognostic genes and models.
Assessed immunotherapy responses across different risk groups.
Performed inferCNV analysis to explore malignant cell differentiation mechanisms.
Conducted in vitro experiments to examine the effects of silencing and overexpressing FURIN.
Identified prognostic genes including RGS20, KYNU, RAET1E, and FURIN associated with lymph node metastasis.
Patients with high lymph node and immune cell-related risk scores exhibited higher mortality rates.
Low-risk patients showed a better response to immunotherapeutic interventions.
FURIN was found to enhance migration and proliferation of lung adenocarcinoma cells.

Abstract

The poor prognosis of lung adenocarcinoma (LUAD) remains unimproved. This study aimed to identify lymph node metastasis (LNM)-related and cellular immunity-related prognostic genes in LUAD and propose novel strategies to improve its prognosis. LUAD-related datasets were obtained from public databases. Prognostic genes and a prognostic model were obtained through various bioinformatics analyzes, and the immunotherapy response in risk groups was assessed. Subsequently, the expression levels of prognostic genes and the intercellular communication relationships were explored at the single-cell level. Moreover, malignant cells were identified, and their differentiation mechanisms were explored via inferCNV analysis. Additionally, FURIN was silenced and overexpressed to investigate its effects on the invasion, metastasis, and lymphangiogenesis of LUAD cells in vitro. RGS20, KYNU, RAET1E, FGF12, GJB2, CACNA2D2, FURIN, and GDF10 were identified as prognostic genes with LNM. In 4 datasets, LUAD patients with the high LNM and immune cell-related risk scores exhibited higher mortality rates compared to those in the low-risk group. Furthermore, individuals in the low-risk group demonstrated a greater propensity to derive advantages from immunotherapeutic interventions. Epithelial cells were identified as key cells, with CACNA2D2 being significantly up-regulated during their late-stage differentiation. Basal cells, the malignant subset within epithelial cells, showed elevated FURIN expression in the pre-differentiation phase, which declined in the middle and late phases. Functionally, FURIN was found to enhance the migratory and proliferative capacities of LUAD cells. Moreover, we demonstrated that FURIN accelerated lymphatic metastasis and lymphangiogenesis in vitro. In this paper, we identified LUAD prognostic genes with LNM and immune cell signatures, emphasized treating LUAD patients according to LNM- and immune cell-related risk scores, and provided novel ideas on how to improve poor prognosis and develop targeted therapy for LUAD.

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