Clinical information on the study participants, as well as remaining samples, were obtained from our two previous studies following ethics approval from the Human Research Ethics Committee of the Faculty of Medicine, Prince of Songkla University (Songkhla, Thailand; approval nos. 59-011-05-1 and 60-350-04-2) (11,20). The participants were enrolled at Songklanagarind Hospital (Songkhla, Thailand) between January 2016 and December 2018. From the original 230 samples (117 NSCLC and 113 OLDs) of the previous study, 215 samples (106 NSCLC and 109 OLDs) were adequately obtained for the analysis of miR-145 expression and 183 samples (92 NSCLC and 91 OLDs) for VEGF determination. Patients with suspected lung cancer were included if they presented with a chronic cough for ≥8 weeks or hemoptysis more than once. In addition, information on smoking and drinking status, as well as the family history of cancer, for each participant were obtained by interviewing the patients. The demographic and clinical characteristics of the patients were retrieved from the hospital registry. Patients with a previous history of cancer or chemotherapy were excluded. During or after data collection, no personal information that could be used to identify individuals was available.

Confirmation of cancer was obtained via a pathological diagnosis. The histological type of NSCLC was diagnosed according to the 2015 World Health Organization classification of lung and pleural tumors (21). The clinical staging was based on the Tumor Node Metastasis staging system of the Cancer Staging Manual (7th Edition) of the American Joint Committee on Cancer (22). Patients with OLDs were diagnosed via routine procedures, including laboratory tests, chest X-rays and tissue biopsies. The mortality data were obtained from the civil registry.

Peripheral blood (5 ml) was collected at the time of diagnosis after the patients had provided their written informed consent, and samples were processed as previously described (11,20). Briefly, blood samples were coagulated for 30 min at room temperature and centrifuged at 3,400 × g for 10 min at room temperature. Isolated serum was filtered through a polyvinylidene difluoride syringe filter with a pore size of 0.22-mm (cat. no. SLGS033SB; MilliporeSigma) and prepared for miRNA isolation.

Human NSCLC cell lines, A549 and H1792 (both lung adenocarcinoma), were purchased from the American Type Culture Collection. Cells were cultured in RPMI-1640 medium (cat. no. R6504; Sigma-Aldrich; Merck KGaA) supplemented with 10% (v/v) FBS (cat. no. 10091148; Gibco; Thermo Fisher Scientific, Inc.), and maintained at 37°C in a 5% CO₂ atmosphere.

miR-145 mimic (50 nM, 5′-GUCCAGUUUUCCCAGGAAUCCCU-3′) and mimic negative control (NC) (50 nM, 5′-UCACAACCUCCUAGAAAGAGUAGA-3′) were purchased from GE Healthcare Dharmacon, Inc. Transfection was conducted using Lipofectamine^® 2000 (cat. no. 11668019; Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's instructions. Briefly, A549 (2×10⁵) and H1792 (4×10⁵) cells were suspended in medium containing 10% FBS and seeded into a T25 cell culture flask (Corning, Inc.) for 24 h before miRNA transfection. miR-145 mimic and mimic NC were diluted in Opti-MEM (cat. no. 31985088; Gibco; Thermo Fisher Scientific, Inc.), mixed with Lipofectamine 2000, and incubated for 30 min at room temperature. Subsequently, cells were incubated with the transfection mixture at 37°C in a 5% CO₂ atmosphere. Culture medium was replaced after 10 h, and the cells were further incubated at 37°C in a 5% CO₂ atmosphere for 4 days. After transfection, the cells were harvested and subjected to subsequent experiments. The efficiency of miRNA transfection was confirmed via reverse transcription-quantitative PCR (RT-qPCR). Untreated cells (cell group), cells treated with Opti-MEM and Lipofectamine 2000 (mock group) and cells transfected with mimic NC (mimic NC groups) were assigned as the control groups.

Total RNA was extracted from cells using TRIzol^® reagent (cat. no. 15596018; Invitrogen; Thermo Fisher Scientific, Inc.) and from serum (250 µl) using a miRNeasy serum/plasma kit (cat. no. 217184; Qiagen GmbH), according to the manufacturers' protocols. miR-145 expression levels were measured using RT-qPCR, as previously described (11). Briefly, total RNA (50 ng) was reverse transcribed into cDNA using the miScript II RT kit (cat. no. 218161; Qiagen GmbH) at 37°C for 60 min and 95°C for 5 min using a thermal cycler (Bio-Rad Laboratories, Inc.). After dilution in 200 µl RNase-free water, miRNA amplification was performed using a miScript SYBR^® Green PCR kit (cat. no. 218073; Qiagen, Inc.) on a CFX96 Touch Real-time qPCR Detection system (Bio-Rad Laboratories, Inc.). The miScript primer assay used for miR-145 and U6 small nuclear RNA 2 (RNU6-2, an internal control) was purchased from Qiagen, Inc. Mature miRNA sequences were used for designing the forward primers: miR-145, 5′-GUCCAGUUUUCCCAGGAAUCCCU-3′ (cat. no. MS00003528; Qiagen GmbH) and RNU6-2, 5′-CGCTTCGGCAGCACATATACTA-3′ (cat. no. MS00033740; Qiagen GmbH). The reverse primer was specifically designed for use with and contained in the miScript SYBR Green PCR kits (cat. no. 218073; Qiagen, Inc.). The qPCR amplification conditions were as follows: 95°C for 15 min for polymerase activation, followed by 50 cycles of denaturation at 94°C for 15 sec, amplification at 55°C for 30 sec and extension at 70°C for 30 sec. The difference between the cycle quantification (Cq) value of miR-145 and RNU6-2 (∆Cq) was calculated and the relative expression levels were quantified using the 2^−∆∆Cq method (23).

Total RNA was extracted from the cells using TRIzol reagent, according to the manufacturer's protocol. To synthesize cDNA, 50 ng total RNA was reverse transcribed using iScript™ Reverse Transcription SuperMix (cat. no. 1708840; Bio-Rad Laboratories, Inc.) at 46°C for 20 min and 95°C for 1 min using a thermal cycler. qPCR was subsequently performed using a Luna^® Universal qPCR Master Mix (cat. no. M3003L; New England BioLabs, Inc.). The following thermocycling conditions were used for the amplification of CDK4, cyclin A, CDK1 and GAPDH: 95°C for 5 min for polymerase activation, followed by 40 cycles of denaturation at 95°C for 10 sec, amplification at 60°C for 30 sec and extension at 72°C for 30 sec. A CFX96 Touch Real-time qPCR Detection system was used for the analysis and the relative expression levels of the genes were calculated using the 2^−∆∆Cq method (24), using GAPDH as the endogenous control. The following primer sequences were used for qPCR: CDK4, forward 5′-GGAGGCCTTTGAACATCCCA-3′ and reverse 5′-ACTGGCGCATCAGATCCTTA-3′; cyclin A, forward 5′-TAGACACCGGCAACTCAAG-3′ and reverse 5′-TCTTCAGACTGGGAGAGGAGA-3′; CDK1, forward 5′-TGGAGAAGGTACCTATGGAGTTG-3′ and reverse 5′-AGGAACCCCTTCCTCTTCAC-3′; and GAPDH, forward, 5′-GACTTCAACAGCGACACCCACTCC-3′ and reverse 5′-AGGTCCACCACCCTGTTGCTGTAG-3′.

Serum VEGF levels were measured using a sandwich human ELISA kit (cat. no. 900-K10; PeproTech, Inc.) according to the manufacturer's instructions. Briefly, an ELISA plate was coated with 100 µl capture antibody and incubated overnight at room temperature. After blocking with 1% BSA (cat. no. A9418; Sigma-Aldrich; Merck KGaA) for 1 h at room temperature, 100 µl serum sample was added to each well, followed by 100 µl HRP-conjugated detection antibody, after which the reaction was incubated for 1 h at room temperature. After washing, colorimetric detection was performed using an avidin-HRP conjugate (1:2,000) using ABTS liquid substrate solution (cat. no. 002024; Thermo Fisher Scientific, Inc.) for 10 min. Color development was measured at a wavelength of 405 nm, with a reference wavelength of 650 nm, using a microplate reader (Molecular Devices, LLC). VEGF levels were quantified using the constructed standard curve.

Cell suspension aliquots were mixed with an equal amount of 0.4% (w/v) trypan blue solution (cat. no. 15250061; Gibco; Thermo Fisher Scientific, Inc.) and the viable cells were counted under light microscopy using a hemocytometer. The number of cells in the cell group was considered as 100%, whereas the number of cells in the other groups was expressed as a percentage of that compared with the cell group.

In addition, a cell suspension was prepared at a concentration of 1×10⁶ cells/ml in culture medium and a 50-µl cell suspension was mixed with 450 µl Muse^® Count & Viability reagent (cat. no. 637365; MilliporeSigma). The mixed cells were incubated at room temperature in the dark for 5 min, then the live and dead cells were counted using a Muse cell analyzer (MilliporeSigma). The number of total cells in the cell group was considered as 100%, whereas the number of total cells in the other groups was expressed as a percentage of that compared with the cell group. The percentage of live and dead cells in a population was determined.

After transfection, cells were trypsinized and centrifuged at 300 × g for 5 min at room temperature. Subsequently, 1×10⁶ cells were fixed with ice-cold 70% methanol (cat. no. 67-56-1; RCI Labscan Ltd.) overnight at −20°C. Fixed cells were centrifuged at 300 × g for 5 min and washed with 500 µl cold PBS. The cells were subsequently resuspended in 1 ml 1X binding buffer and a 100-µl cell suspension (1×10⁵ cells) was mixed with 5 µl PI (cat. no. 556463; BD Biosciences) and 1 µl RNase A, DNase and protease-free (10 mg/ml; cat. no. EN0531; Invitrogen; Thermo Fisher Scientific, Inc.). After incubation for 15 min at room temperature in the dark, 400 µl 1X binding buffer was added to the cells, and the cell cycle distribution was analyzed using an Amnis^® ImageStream^®X Mk II and IDEAS software, version 6.0 (both Luminex Corporation). The percentage of cells distributed in each phase of the cell cycle was determined.

Statistical analysis was performed using R statistical software, version 3.4.4 (RStudio, Inc.) and GraphPad Prism 5.0 software (GraphPad Software, Inc.). The experiments were performed in triplicate. Clinical characteristics of the patients were presented as numbers and percentages. The continuous data of the cell viability assay and cell cycle analysis, which were obtained from three independent experiments, were presented as the mean ± SD. Serum miR-145 and VEGF levels were presented as the median and interquartile range (IQR). The association between clinical variables and patient status (NSCLC and OLDs) was analyzed using a χ² test. The statistical differences between multiple groups were determined using one-way ANOVA followed by Tukey's post hoc test. Logistic regression was used to evaluate the variables associated with the cancer diagnosis. The diagnostic performance was assessed using a receiver operating characteristic (ROC) curve and area under the curve (AUC) analysis, which was reported with 95% CIs. The cut-off values for miR-145 and VEGF were obtained from the best coordinate in the ROC to provide a maximum sum of sensitivity and specificity. For the survival analysis, a Kaplan-Meier curve was constructed and the statistical differences in overall survival (OS) among the various categories of variables were determined using a log-rank test. A multivariate Cox proportional hazards model was used to identify independent prognostic variables. P<0.05 was considered to indicate a statistically significant difference.

The present study included 215 patients, 106 with NSCLC and 109 with OLDs. The diagnoses for the patients with OLDs were tuberculosis, bronchiectasis, interstitial lung disease, pneumonia or chronic obstructive pulmonary disease. Table I lists the clinicopathological characteristics of the patients, and shows the significant differences identified in sex (P=0.030), age (P<0.001) and smoking status (P<0.001) between the NSCLC and control groups. There were no significant differences identified between the two groups for alcohol consumption and family history of cancer.

The median serum miR-145 level was lower in the NSCLC group (17.15; IQR, 1.50-136.72) compared with that in the control group (25.46; IQR, 4.56-109.90). The median VEGF level was higher in the NSCLC group (0.04; IQR, 0.02-0.05) compared with that in the control group (0.02; IQR, 0.00-0.03). The cut-off values for miR-145 and VEGF levels were set as follows: ≤3.434 for miR-145 and ≤0.032 for VEGF for the lower value and >0.434 for miR-145 and >0.032 for VEGF for the upper value. A larger proportion of the NSCLC group had lower miR-145 levels compared with those in the control group (36.8 vs. 18.3%; P=0.002; Table I). By contrast, a larger proportion of the NSCLC group had higher VEGF levels compared with those in the control group (55.4 vs. 27.5%; P<0.001).

The logistic regression analysis revealed that smoking status, and miR-145 and VEGF levels were significant predictors for diagnosing NSCLC (Table II). Age also exhibited a moderate trend as a predictor (P=0.023). Low miR-145 expression levels [adjusted odds ratio (aOR), 0.26; 95% CI, 0.12-0.57] and high VEGF expression levels (aOR, 3.19; 95% CI, 1.64-6.20) were associated with a NSCLC diagnosis.

The diagnostic power of miR-145 and VEGF, with or without other risk factors, was evaluated using ROC curve analysis. The AUC was 0.61 (95% CI, 0.55-0.68) for miR-145 alone and 0.64 (95% CI, 0.57-0.71) for VEGF alone. When combined, miR-145 and VEGF improved the discrimination, with an AUC of 0.69 (95% CI, 0.62-0.76) (Fig. 1A). The combination of age, smoking status, miR-145 and VEGF expression proved to be the best model for differentiating patients with NSCLC from those with OLDs (AUC, 0.76; 95% CI, 0.69-0.83), with an optimal sensitivity and specificity of 80.4 and 65.9%, respectively (Table III; Fig. 1B).

The patients had a median survival time of 14.24 months. The Kaplan-Meier curve showed that low miR-145 levels were associated with a significantly shorter OS (P=0.028), whereas low VEGF levels were associated with a longer OS (P=0.027) (Fig. 1C and D). Table IV shows the results of the multivariate Cox regression analysis. High miR-145 expression was independently associated with a higher OS [hazard ratio (HR), 0.48; 95% CI, 0.27-0.85]. By contrast, high VEGF levels were associated with a lower OS (HR, 1.47; 95% CI, 0.81-2.68); however, the association was not statistically significant. Stage and histological types were also significantly associated with OS, whereas age, smoking status, drinking status and family history of cancer were not.

The functional role of miR-145 in A549 and H1792 adenocarcinoma cells was further explored following its overexpression. Transfection success was confirmed by measuring miR-145 expression levels using RT-qPCR. The results revealed that miR-145 expression levels were upregulated by 494- and 330-fold in transfected A549 and H1792 cells, respectively, compared with the cell group (P≤0.001; Fig. 2A and B). The expression of miR-145 was not significantly different among the control groups.

As determined using the trypan blue assay, miR-145 overexpression resulted in a 58.5% reduction in total A549 cell numbers and a 42.9% reduction in H1792 cell numbers compared with the cell group (P≤0.001; Fig. 2C and D). Similarly, the results of the cell viability assay using the Muse cell analyzer revealed that the total cell numbers were significantly decreased following the overexpression of miR-145, by ~45.0% for A549 and 49.4% for H1792 cells compared with those in the cell group (P≤0.001; Fig. 2E and F). However, miR-145 overexpression had no effect on the number of viable and dead cells compared with in the control cells.

To further explore whether a reduction in total cell numbers following miR-145 overexpression was caused by cell cycle arrest, cell cycle analysis was performed using flow cytometry. Since there were no significant differences among the three control groups (data not shown), untreated cells and mock cells were used as the controls for subsequent experiments on the effects of miR-145 overexpression on cell cycle distribution and the expression of cell cycle regulatory genes. In A549 cells, the results revealed that the percentage of cells in G₀/G₁ phase was significantly increased by 42.7% (P≤0.001) in the miR-145 mimic-transfected cells compared with the cell group. Significant reductions in the number of cells in the S-phase (38.5%; P≤0.01) and G2/M-phase (88.9%; P≤0.001) were also observed compared with the cell group (Fig. 3A and B). By contrast, the miR-145 mimic-transfected H1792 cells exhibited an 18.1% decrease in the percentage of cells in G₀/G₁ phase compared with that in the cell group (P≤0.05), and a 36.4% increase in the percentage of cells in the S phase compared with in the cell group (P≤0.05; Fig. 4A and B).

In A549 cells, the expression levels of CDK4, cyclin A and CDK1 were significantly downregulated in the miR-145 mimic-transfected cells by 81.0 (P≤0.01), 88.6 (P≤0.001) and 91.5% (P≤0.05), respectively, compared with those in the cell group (Fig. 3C). Similar to the A549 cells, there was a significant reduction in CDK4 (76.1%; P≤0.001), cyclin A (91.7%; P≤0.01) and CDK1 (68.5%; P≤0.05) expression in the miR-145 mimic-transfected H1792 cells when compared with the cell group (Fig. 4C).