MiR-483-3p as a Prognostic Marker In Non-Small Cell Lung Cancer: Suppression of Tumor Progression via KIF3B Downregulation

Summary

Downregulation of miR-483-3p is a poor prognostic marker in NSCLC. The overexpression of miR-483-3p suppresses the malignant phenotypes of NSCLC cells, whose function was reversed by the overexpression of KIF3B.

Abstract

MicroRNAs play wide roles in non-small cell lung cancer (NSCLC). To investigate the clinical value of miR-483-3p in NSCLC and its molecular target, 350 NSCLC patients were recruited in this study. RT-qPCR results showed that tumor histological expression of miR-483-3p progressively decreased as the tumor-node metastasis (TNM) stage increased. The receiver operating characteristic (ROC) curve displayed that histological miR-483-3p level can effectively distinguish NSCLC patients with high TNM stage (III) from those with low stage (I+II) (area under the ROC curve = 0.869). The Kaplan-Meier curve showed that NSCLC patients with low miR-483-3p expression demonstrated a lower 5-year overall survival rate. After adjusting for other confounding factors, multivariate Cox analysis further identified miR-483-3p as an independent protective factor for NSCLC survival. Mechanistically, RNA pull-down assay showed that upregulation of miR-483-3p was co-precipitated with KIF3B mRNA and inhibited its expression, thereby suppressing the malignant phenotypes of NSCLC cells and inducing apoptosis. In conclusion, downregulation of miR-483-3p serves as a poor prognostic marker in NSCLC, potentially affecting cancer progression by negatively regulating KIF3B.

Introduction

Among cancer-related deaths, non-small cell lung cancer (NSCLC) is one of the leading causes. Its high mortality rate is primarily attributed to the aggressive growth of tumors, early metastasis, and the development of acquired resistance^1,2,3. Despite advances in current clinical strategies, the overall prognosis for NSCLC patients remains poor^4,5,6. In addition to biological challenges, NSCLC patients often experience a heavy symptom burden, including pain, dyspnea, fatigue, and psychological distress, which significantly impairs their quality of life and complicates clinical management. Effective nursing care—such as symptom assessment, patient education, psychosocial support, and coordination of multidisciplinary care—plays a crucial role in improving patient outcomes and treatment adherence. Therefore, an in-depth investigation into the key molecular mechanisms driving the development and progression of NSCLC is of paramount importance for the development of novel prognostic biomarkers and effective therapeutic strategies, as well as for informing targeted nursing interventions that address both disease and patient-centered needs.

MicroRNAs (miRNAs) have been widely reported to regulate gene expression by either inhibiting the translation of target mRNAs or promoting their degradation at the post-transcriptional level⁷. Extensive research indicates that miRNAs play a crucial regulatory role in various cancers, including NSCLC. Their dysregulation is closely associated with tumor cell malignant phenotype and chemotherapy resistance^7,8,9,10,11. Therefore, identifying miRNAs that are abnormally expressed in NSCLC and possess significant functional roles has become a hot topic in current tumor research. Our preliminary bioinformatics analysis revealed consistent downregulation of miR-483-3p in both NSCLC patients and drug-resistant cell lines, suggesting its potential association with adverse disease progression. Therefore, this study focuses on miR-483-3p to explore its function in NSCLC. Existing evidence indicates that miR-483-3p functions as a tumor suppressor gene in various human cancers^12,13,14,15, whose silencing is believed to be associated with gefitinib resistance in NSCLC¹⁶. However, its specific expression pattern in NSCLC, clinical prognostic value, and underlying molecular mechanisms remain incompletely understood.

The objective of this study was to systematically clarify the clinical significance and biological functions of miR-483-3p in NSCLC, and to elucidate the role of its downstream target kinesin family member 3B (KIF3B). To achieve this, we first analyzed its expression in clinical tissue samples and its correlation with patients' clinical-pathological characteristics and prognosis. Subsequently, in vitro functional assays were conducted to investigate the effects of miR-483-3p on NSCLC cell functions. Furthermore, we identified KIF3B as a key downstream target gene of miR-483-3p through bioinformatics prediction and molecular biology experiments, and validated the regulatory relationship via functional rescue assays. High expression of KIF3B is associated with increased proliferation, enhanced migration, and chemotherapy resistance in cancer cells^{17,18,19,20,21,22}, but its functional role in NSCLC remains unclear. To our knowledge, this study is the first to characterize the role and clinical significance of the miR-483-3p/KIF3B axis in NSCLC from three perspectives—clinical prognosis, target gene identification, and functional mechanisms—thereby potentially providing new insights for the assessment of NSCLC prognosis and targeted therapy.

Protocol

The Ethics Committee of The Second Affiliated Hospital of Nanjing Medical University approved this study. The fundamental principles of the Declaration of Helsinki have been consistently applied throughout the entire research process. Written informed consent was obtained from all individual participants included in the study. Detailed information on all materials and reagents was provided in the Table of Materials.

Bioinformatics analysis:

The Gene Expression Omnibus database (www.ncbi.nlm.nih.gov) was applied to search the NSCLC-related datasets. GSE171517 is a non-coding RNA analysis based on the serum samples from NSCLC patients and healthy controls. GSE110815 is a non-coding RNA array analysis conducted on gefitinib-resistant and sensitive NSCLC cells. The differentially expressed miRNAs in these two datasets were screened by setting a threshold of |log₂FC| ≥ 2, p < 0.05. Although these datasets originate from different compartments (serum, cell lines), we used a complementary strategy: serum-derived miRNAs for non-invasive biomarker potential, and drug-resistant cell line-derived miRNAs for functional relevance to progression and resistance. The intersection nominated miR-483-3p for tissue validation, assuming cross-compartment dysregulation indicates robust biological relevance to NSCLC.

Potential targets of miR-483-3p were predicted simultaneously in the miRDB (https://mirdb.org/custom.html) and starbase (https://rnasysu.com/encori/index.php) databases. The screening threshold in these two databases was Target Score ≥ 60 and TDMDScore ≥ 1, respectively. Then, a Bioinformatics Analysis Platform (www.bioinformatics.com.cn) was used for GO analysis using the intersection of these targets.

Clinical sample inclusion:

This study is a retrospective observational cohort study based on surgically resected NSCLC specimens. This study included 350 NSCLC patients who underwent surgical treatment at the hospital, comprising 96 patients with tumor node metastasis (TNM) stage I disease, 96 patients with stage II disease, and 158 patients with stage III disease. Their detailed clinical characteristics were presented in Table 1. All of these patients were diagnosed with NSCLC through histological examination. Exclusion criteria include impaired cardiac, hepatic, or renal function, active infections or autoimmune diseases, severe psychiatric disorders or cognitive impairment, missing or incomplete clinical records, and failure to obtain informed consent from the patients. Clinical analysis was conducted by collecting their tumor tissue samples and survival status within five years after diagnosis. The follow-up methodology is as follows: All patients were followed up from the date of surgery until their death, loss to follow-up, or the end of the study. During the first year, follow-up was conducted every 3 months. Thereafter, it was carried out every 6 months through outpatient examinations and telephone interviews. At each follow-up, information on survival status, cause of death, disease recurrence, and subsequent treatment was recorded. The overall survival period was defined as the period from the date of surgery to the date of death due to any cause.

Cell processing:

BEAS-2B, a normal human lung epithelial cell line, was cultured in DMEM containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin (P/S). All NSCLC cell lines (HCC827, H1299, H520, A549) were cultured in the dedicated growth medium supplied by the same supplier. The basic formulation of the specialized media for HCC827, H1299, and H520 is RPMI-1640 + 10% FBS + 1% P/S, and which for A549 is Ham's F-12K + 10% FBS + 1% P/S. Frozen cells are rapidly thawed in a 37 °C water bath, centrifuged to remove the cryopreservation medium, and resuspended in fresh culture medium. When the cells reach 90% confluence, they are digested with 0.25% trypsin-EDTA and passaged at a 1:3 ratio. All cell lines have been verified by STR analysis (Supplementary File 1), and they are free of mycoplasma contamination. All in vitro experiments used cells from the 4th to the 10th generation.

The miR-483-3p agonist and its negative control (agonist-NC), the small interfering RNA of KIF3B (si-KIF3B) and its negative control (si-NC), as well as the KIF3B overexpression vector (oe-KIF3B) and its blank control (oe-NC) were transfected using a transfection reagent. The working concentration of the miR-483-3p agonist or agonist-NC was 100 nM, and the amount of the oe-KIF3B plasmid was 2.5 µg (6-well plate). Cells were harvested 48 h after transfection for subsequent experiments.

RT-qPCR:

Total RNA in the tumor tissue samples and cells was extracted using the TRIzol reagent. The reverse-transcribed cDNA was prepared using a RT reagent kit, and then qPCR was performed on a 7500 Fast RT-PCR system using SYBR Green Pro Taq HS Premix. The relative expression of miR-483-3p and KIF3B was normalized with housekeeping U6 and GAPDH through 2^-ΔΔCT method. The corresponding primer sequences are as follows:

miR-483-3p (F), 5’-ACACTCCAGCTGGGTCACTCCTCTCCTCC-3'

miR-483-3p (R), 5’-CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGAAGACGGG-3'

KIF3B (F), 5’-ATCCTGGAGCAGAAACGACAGG-3'

KIF3B (R), 5’-GTTCCAAGGTCTCCTCATCTCG-3'

U6 (F), 5’-ATGTTCCAGTATGACTCTA-3'

U6 (R), 5’-ATGTTCCAGTATGACTCTA-3'

GAPDH (F), 5’-GTAACCCGTTGAACCCCATT-3'

GAPDH (R), 5’-CCATCCAATCGGTAGTAGCG-3'

RT-qPCR was performed with three independent biological replicates.

Cell viability:

HCC827 (3000 cells/well) and A549 (2000 cells/well) cells, with or without transfection, were seeded into a 96-well plate for varying culture periods. After cells adhered to the surface, cell viability was assessed at specific time points in designated wells. Specifically, 10 µL of Cell Counting Kit-8 (CCK-8) and 90 µL of medium were added to the wells for a 2-h incubation at 37 °C. The absorbance of each well was then measured at 450 nm using a microplate reader. Cell viability was performed with three independent biological replicates.

Transwell assay:

The basement membrane matrix-coated or uncoated Transwell chamber device (8 µm) was used for the invasion/migration assay. After the upper chamber was seeded with the transfected NSCLC cells (8 × 10⁴, 500 µL), and the lower chamber was filled with 700 µL of DMEM (10% FBS). A 24-h incubation at 37 °C was performed. After the cells at the upper layer of the chamber membrane were gently wiped away using a cotton swab, the cells on the lower surface of the membrane were fixed with 4% paraformaldehyde for 20 min at room temperature, then stained with 0.1% crystal violet solution for 10 min at room temperature, followed by a brief wash with running tap water to remove excess stain. The migrated cells were manually counted using an optical microscope. For each Transwell chamber, three non-overlapping fields of view were randomly selected, and the number of stained cells in each field was counted. Then, the average cell count was calculated. This counting was performed by two independent researchers who were unaware of the experimental conditions, and the resulting average values were used for statistical analysis. The transwell assay was performed with three independent biological replicates.

Cell apoptosis detection

An Annexin V-FITC/PI staining Kit was used for NSCLC cell apoptosis detection. Briefly, a suspension containing 6 × 10⁴ cells was first prepared using 195 µL of Annexin V-FITC binding buffer. Then Annexin V-FITC (5 µL) and PI staining solution (10 µL) were sequentially added for 20-min incubation at room temperature in the dark. After incubation was complete, the flow cytometer was immediately used to detect the cells to be tested. For each sample, 10,000 events were acquired. The gating strategy was as follows: cells were first gated on FSC-A vs. SSC-A to exclude debris, followed by singlet gating on FSC-A vs. FSC-H. Apoptotic cells were then identified on Annexin V-FITC vs. PI dot plots. Quadrants were set using unstained and single-stained controls. The percentage of apoptosis was calculated as the sum of early apoptotic (Annexin V⁺/PI⁻) and late apoptotic (Annexin V⁺/PI⁺) cells. Cell apoptosis detection was performed with three independent biological replicates.

RNA pull-down

The segment of the KIF3B mRNA (KIF3B/NM004798.4/NP004789.1: 32334713–32334791, 5’-AGAAATCTGTCACCTTTCTGCCTGCCCTTGTTTCCTGAATGAAATGCTTCTGGGGTTATTTATGAAAGGAGTGATCCT-3', 78 nt) was synthesized in vitro and biotin-labeled using an RNA 3' End Desthiobiotinylation kit. After cell extracts were incubated with biotin-labeled KIF3B mRNA for 1.5 h at 4 °C, streptavidin magnetic beads were added for a 2-h incubation at room temperature. Finally, the level of miR-483-3p in each reaction was detected by RT-qPCR, with three independent biological replicates.

Statistical analysis

The continuous variables in this study were expressed as mean ± standard deviation (mean ± SD), while categorical data were presented as counts. Appropriate statistical analysis software was used for statistical analysis. One-way/two-way ANOVA was used for experimental data analysis, followed by Tukey's post hoc test. p < 0.05 was considered to be statistically significant.

Receiver operating characteristic (ROC) curve analysis was performed to determine the ability of miR-483-3p expression for distinguishing NSCLC patients with high-stage (III) from those with low-stage (I + II) TNM classification. The Youden index (sensitivity + specificity – 1) was used to identify the cutoff value that maximized the balance between sensitivity and specificity. The area under the curve (AUC) was calculated to evaluate the overall discriminatory ability of miR-483-3p expression. An AUC > 0.7 was considered acceptable. All ROC analyses were performed using GraphPad Prism.

For survival analysis, the Kaplan-Meier method was used to estimate overall survival curves. The log-rank test was applied to compare survival distributions between groups (miR-483-3p high- vs. low-expression groups). Kaplan-Meier curves were plotted with 95% confidence interval (CI). For the multivariate Cox proportional hazards regression model, the following variable selection strategy was applied: Univariate analysis was first performed for each candidate variable. Variables with a p-value < 0.10 in univariate analysis were considered as potential predictors and were subsequently entered into the multivariate Cox regression model. The multivariate analysis was conducted using the forward stepwise (conditional) selection method based on the likelihood ratio test, with entry and removal criteria set at p < 0.05 and p > 0.10, respectively. The proportional hazards assumption was verified for each variable using Schoenfeld residuals (p > 0.05 indicated no violation). Results were reported as hazard ratios (HR) with 95% CI. All tests were two-sided, and a p-value < 0.05 was considered statistically significant unless otherwise specified.

Results

Downregulated miR-483-3p represents a poor prognosis in NSCLC

The Venn diagram (Supplementary Figure 1) indicates that miR-483-3p appears downregulated in both serum samples of NSCLC patients and chemotherapy-resistant NSCLC cell lines. A one-way ANOVA analysis showed that the miR-483-3p expression in the tumor progressively decreased with increasing TNM stage (Figure 1A). ROC curve analysis was performed to evalu...

Discussion

This study systematically investigated the miR-483-3p's role in suppressing NSCLC tumors and its underlying mechanism through clinical sample analysis and molecular mechanism exploration. The objective of this study was two folds: (1) to determine whether miR-483-3p serves as an independent prognostic marker in NSCLC, and (2) to elucidate the molecular mechanism by which miR-483-3p may suppress malignant phenotypes through targeting KIF3B. Our findings suggest the clinical value of miR-483-3p as an independent progno...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
0.1% crystal violet	Solarbio/China	G1064
0.25% trypsin-EDTA	Gibco/USA	25200056
4% paraformaldehyde	Beyotime/China	P0099
7500 Fast RT-PCR system	Applied Bio-systems/USA	4351106
A549	Procell/China	CL-0016
A549-specific medium	Procell/China	CM-0016
Annexin V-FITC/PI staining Kit	Beyotime/China	C1062S
BEAS-2B	STEM RECELL/China	STM-CL-5102
Cell Counting Kit-8 (CCK-8)	Solarbio/China	CA1210
DMEM medium	MeilunBio/China	PWL003
Fetal bovine serum	Gibco/USA	A5256701
GraphPad Prism software	GraphPad	Version 7.0
H1299	Procell/China	CL-0165
H1299-specific medium	Procell/China	CM-0165
H520	Procell/China	CL-0402
H520-specific medium	Procell/China	CM-0402
HCC827	Procell/China	CL-0094
HCC827-specific medium	Procell/China	CM-0094
KIF3B mRNA	Genscript Biotech/China	customized
Lipo6000 reagent	Beyotime/China	C0526
miR-483-3p agonist/agonist-NC	MedChemExpress/USA	HY-R01451A
oe-KIF3B/oe-NC	RiboBio/China	customized
Penicillin/streptomycin	Solarbio/China	P1400
Pierce RNA 3’ End Desthiobiotinylation Kit	Thermo Fisher Scientific/USA	20163
PrimeScript RT Reagent Kit (Perfect Real Time)	TaKaRa/Japan	RR037A
si-KIF3B/si-NC	RiboBio/China	customized
SPSS	IBM	Version 23.0
Streptavidin magnetic beads	New England Biolabs/USA	S1420S
SYBR Green Pro Taq HS Premix	Accurate Biology/China	AG11701
Transwell chamber	Corning/USA	3428
TRIzol reagent	Invitrogen/USA	15596026CN