To analyze the differential expression profiles of small nucleolar RNAs (snoRNAs) in lung adenocarcinoma and their association with prognosis, screen and validate lung adenocarcinoma-related snoRNAs, and explore their roles in tumorigenesis and progression.

Differentially expressed snoRNAs between lung adenocarcinoma and normal tissues were screened using Arraystar Small RNA expression microarrays. The obtained candidates were validated through the GEO database (GSE261702), followed by selecting snoRNAs that passed molecular cloning experiments, and finally RT-qPCR. By constructing SCARNA4 overexpression models (Vector group and SCARNA4 group) and knockdown models (siNC group and si SCARNA4 group), proliferation, migration and invasion assays were carried out to assess the biological functions of SCARNA4 in lung adenocarcinoma cells. Based on tumor tissues from 108 lung adenocarcinoma patients (Second Affiliated Hospital of Army Medical University, between February 2013 and May 2015), the expression level of SCARNA4 was detected by RT-qPCR. Using X-tile software to determine the optimal cut-off value (3.48), the patients were accordingly stratified into high (57 cases) and low SCARNA4 expression (51 cases) groups. Kaplan-Meier survival curves and Cox proportional hazards regression models were constructed to analyze the impact of SCARNA4 expression on prognosis.

Small RNA microarray identified 62 up-regulated and 4 down-regulated snoRNAs in lung adenocarcinoma tissues. Integration with GEO database and molecular cloning yielded 8 candidate snoRNAs. RT-qPCR results revealed significantly elevated SCARNA4 expression in lung adenocarcinoma tissues than normal tissues (P=0.0427). Overexpression of SCARNA4 significantly promoted the proliferative, migrative, and invasive capacities in A549 cells (P<0.01), whereas its knockdown obviously inhibited these functions (P<0.01). Kaplan-Meier survival analysis demonstrated significantly shorter overall survival in the high-expression group when compared with the low-expression group (P=0.034). Univariate Cox regression analysis further confirmed that high SCARNA4 expression was significantly associated with poor prognosis (HR=2.285, 95%CI: 1.040 to 5.020, P=0.039). Multivariate Cox regression analysis confirmed that, after adjusting for relevant covariates, the expression level of SCARNA4 was an independent risk factor of overall survival of lung adenocarcinoma patients, and its high expression was notably associated with shortened overall survival of patients (HR=3.038, 95%CI: 1.261 to 7.323, P=0.013).

SCARNA4 is up-regulated in lung adenocarcinoma tissues and associated with poor prognosis. It may be involved in the tumorigenesis and development of lung adenocarcinoma by regulating cell proliferation, migration, and invasion. The molecule might hold promise as a novel therapeutic target and prognostic biomarker for lung adenocarcinoma.