Abstract
BACKGROUND: Lung adenocarcinoma (LUAD) presents a considerable danger to human health and has evolved into a major public health concern. Ribosome biogenesis (RiboSis) is a critical process for synthesizing ribosomes, closely associated with cancer initiation, progression, and treatment resistance, potentially serving as a target for future cancer therapies. METHODS: Utilizing single-cell RNA sequencing (scRNA-seq) technology, a single-cell atlas of LUAD was delineated, focusing on the analysis of T cell subpopulations. Cells were scored based on the expression patterns of 331 genes associated with RiboSis across different cell types, and monocle2 was employed to analyze the developmental trajectory of CD4(+) T cells. Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. The relationship between RBS risk scores and various factors in LUAD patients, including prognosis, the tumor immune microenvironment (TIME), responsiveness to immunotherapy, and sensitivity to pharmacological treatments was specifically analyzed. Immunohistochemistry was utilized to validate the expression levels of immune markers in the high- and low- RBS groups, and in vitro experiments were performed to validate the functional role of the pivotal gene KIF23 in the progression of LUAD. RESULTS: Using single-cell analysis, two distinct T cell subtypes were identified: CD8(+) interferon (IFN) response T cells and CD4(+) stress response T cells. It was observed that CD4(+) naive-like T cells exhibit high expression of RiboSis-related genes, with a gradual decrease in RiboSis activity as CD4(+) T cells develop. Compared to other prognostic models, RBS demonstrated superior performance in prognosis prediction. The low-RBS group exhibited a tumor microenvironment (TME) more favorable for efficient immune monitoring and reaction, higher responsiveness to immunotherapy, and a better prognosis. Immunohistochemistry confirmed higher expression levels of immune markers in the low-RBS group, while in vitro experiments validated the promoting role of KIF23 in LUAD cell proliferation, migration and invasion. CONCLUSION: This study delves into the relationship between RiboSis and LUAD cell subpopulations, identifying a potent prognostic biomarker for LUAD. This biomarker aids in assessing immunotherapy efficacy in LUAD patients, ultimately enhancing their prognosis and guiding clinical decision-making.