The human LC cell lines A549 (cat. no. CCL-185), NCI-H358 (cat. no. CRL-5807), SK-MES-1 (cat. no. HTB-58) and NCI-H146 (cat. no. HTB-173) were obtained from the American Type Culture Collection and cultured in RPMI-1640 (cat. no. LM011-06; Welgene, Inc.) in a humidified 5% CO₂ incubator at 37°C, supplemented with 10% fetal bovine serum (cat. no. S001-04, Welgene, Inc.). Normal human bronchial epithelial (NHBE) cells were purchased from Cambrex Bio Science Rockland, Ltd. (cat. no. CC2540) and cultured in BEBM (cat. no. cc-3171; Cambrex Bio Science Rockland, Ltd.) in a humidified 5% CO₂ incubator at 37°C. The cultured cells were tested for mycoplasma every month to ensure that they were not contaminated using a MycoStrip kit (cat. no. rep-mys-20; InvivoGen). Cells were authenticated by short tandem repeat analysis using GenePrint^® 10 System (cat. no. B9510; Promega Corporation).

Fresh-frozen primary tumors and paired adjacent non-tumor tissue from 13 patients with non-small cell LC (NSCLC) at various stages (I, n=5; II, n=5; III, n=3) were obtained from the Biobank of Chungnam National University Hospital (Daejeon, South Korea), which participates in the Korea Biobank Project (KBP). Tissue specimens were collected at the time of surgery between February 2014 and December 2019. Every tumor specimen was histologically verified by a board-certified pathologist.

All BW samples were provided by Konyang University Hospital (Daejeon, South Korea). All individuals donating BW samples for the present study were investigated for suspected LC. All BW samples were collected during flexible fiberoptic bronchoscopy (Olympus Corporation) by aspiration with a flexible bronchoscope from the region of the suspicious lesion between April 2022 and March 2023. Cytological diagnostics was performed by a board-certified pathologist. Briefly, 5–10 ml sterile normal saline was instilled two or three times. Fluid (≥10 ml) was then retrieved into a preservative buffer (Genomictree, Inc.). A total of 101 BW samples were obtained from 68 patients with LC (49 NSCLC and 19 SCLC) and 33 individuals with benign diseases and were used for methylation analysis. The patient clinicopathological and demographical information is shown in Table I.

The present study adhered to local ethics guidelines and was approved by the Institutional Review Board of the Chungnam National University Hospital (approval no. 2022-02-061-002, Dajeon, South Korea) and Konyang University Hospital (approval no. 2022-03-025, Dajeon, South Korea). Written informed consent was obtained from all patients.

To identify differentially methylated genes in primary lung tumors and paired adjacent non-tumor tissues, CpG methylation microarray analyses were conducted using 0.5 µg genomic DNA isolated from 13 patients with LC. CpG methylation microarray analysis was performed as described previously (24) using human CpG island microarray kit, 244k (Agilent Technologies, Inc.) according to the manufacturer's instructions. Raw CpG methylation microarray data were submitted to Gene Expression Omnibus (accession no. GSE246510; ncbi.nlm.nih.gov/geo). The hybridized images were analyzed and quantified using Agilent Feature Extraction (version 9.3.2.1; Agilent Technologies, Inc.) and GeneSpring (version 7.3.1; Agilent Technologies, Inc.).

To determine differentially hypermethylated candidate genes in primary tumor compared with paired adjacent non-tumor tissue samples, statistical analysis was performed using a parametric ANOVA test with Benjamini and Hochberg multiple testing correction (P<0.05), followed by fold-change analysis. Mean fold change was calculated by dividing mean methylation levels in tumor tissue by mean methylation levels in non-tumor tissue. Multiple-probe enriched genes were selected as methylation candidate genes if their probes yielded a positive call for methylation in the lung primary tumor compared with non-tumor tissue with at least two adjacent probes, allowing for a one-gap probe within CpG islands.

Genomic DNA was isolated from cell lines and tissues using the QIAmp DNA Mini kit (cat. no. 51304; Qiagen GmbH) according to the manufacturer's instructions. Genomic DNA was isolated from BW samples using a solid phase magnetic bead-based GT NUCLEIC ACID PREP kit (cat. no. GT-PREP-1; Genomictree, Inc.) according to the manufacturer's instructions. Genomic DNA was chemically modified with sodium bisulfite using an EZ DNA Methylation Gold kit (cat. no. D5006; Zymo Research Corp.) according to the manufacturer's instructions. Bisulfite-converted DNA was purified and eluted with an elution buffer using a Zymo-Spin IC column (Zymo Research Corp.).

Candidate methylation targets were analyzed for methylation levels using bisulfite-pyrosequencing, as previously described, with slight modifications (24). Bisulfite-treated genomic DNA underwent PCR amplification targeting the region of interest, employing a specific primer set. Either the forward or reverse primer was biotinylated, facilitating generation of a single-stranded DNA template for subsequent pyrosequencing on a PyroMark Q48 Autoprep (Qiagen GmbH). Pyrosequencing primers were designed to detect methylated cytosine by analyzing CpG dinucleotide sites within the target sequences of bisulfite-treated DNA. To facilitate primer design, nucleotide sequences of the candidate genes were retrieved from the NCBI Reference Sequence database (ncbi.nlm.nih.gov/refseq/) and converted into bisulfite-treated sequences. Both PCR primers and sequencing primers were designed to complementarily bind to the bisulfite-converted sequences within the regions of the interest, while avoiding CpGs within the primer sequences, using PyroMark Assay Design Software V 2.0 (Qiagen GmbH). Primer sequences are listed in Table SI. Briefly, 20 ng bisulfite-modified DNA was amplified in a 20 µl reaction with a gene-specific primer set and TOPsimple PCR DryMix-HOT (cat. no. P581H; Enzynomics, Inc.). PCR amplification was conducted under the following thermocycling conditions: 95°C for 10 min, followed by 40 cycles of 95°C for 45 sec, optimal annealing temperature for 45 sec, and 70°C for 45 sec for each target. Pyrosequencing was performed using a PyroMark Gold Q48 reagent cartridge and a PyroMark Q48 instrument (Qiagen GmbH) according to the manufacturer's instructions.

The methylation index (MtI) of every gene in every sample was calculated as the mean value of methylated cytosine/(methylated cytosine + unmethylated cytosine) for all examined CpGs in target regions. All pyrosequencing reactions included a negative control without DNA template. Methylation-positive was considered if the MtI of the primary tumor was greater than that of the corresponding non-tumor tissue.

A 3-plex LTE-qMSP assay was developed, integrating two methylation targets from candidate genes, and the control gene collagen type II α1 (COL2A1) within a closed single-tube system to assess the methylation status of candidate targets in BW-derived DNA samples. This method involves two sequential rounds of PCR. LTE first employs one-direction PCR targeting to linearly enrich DNA of methylation candidates, followed by qMSP for exponential amplification of both the methylated target and the control gene.

In the first round of PCR, high annealing temperature (70°C) was applied to facilitate unidirectional DNA synthesis while preventing other primers with regular melting temperatures from initiating DNA synthesis. Two specific primers with a universal tag sequence (UTS) at the 5′ end were designed to anneal to two distinct methylation target genes. The template DNA synthesis occurred in one direction only, replicating with each cycle of PCR.

In the subsequent PCR, the reaction was conducted at a reduced temperature (60°C). A total of three sets of primers and probes were utilized targeting amplification of the two methylation targets and the control gene. The forward primers for the methylation targets were designed to bind specifically to the respective methylation target sites and UTS was used as reverse primer. The control target utilized a primer set specific to a DNA region of COL2A1 gene lacking CpG dinucleotides, with annealing at 60°C. Probes were designed to bind internal sites of each PCR product, thereby generating signals indicated of PCR product formation.

To design primers and probes for LTE-qMSP, nucleotide sequences corresponding to the genes of interest were obtained from the NCBI Reference Sequence database (ncbi.nlm.nih.gov/refseq/). The primer and probe sequences were designed to bind complementarily to the bisulfite-converted sequences of the methylation target regions using MethPrimer program (version 2.0; urogene.org/cgi-bin/methprimer/methprimer.cgi). The primer and probe sequences are provided in Table SII.

For every reaction, 20 ng BW-derived DNA underwent bisulfite conversion. The bisulfite-converted DNA was purified and eluted with 12 µl elution buffer, serving as input for the LTE-qMSP assay. The reaction mixture (25 µl) comprised 10 µl input DNA and 15 µl reagent containing two methylation target methylation-specific reverse primer with a 5′ UTS, two methylation-specific forward primers, UTS as reverse primer, two probes for specific methylation sites of targets, COL2A1-specific forward and reverse primers, COL2A1 probe and 5 µl of the master mix, TOPreal™ Fast qPCR 5X PreMIX TaqMan-Probe (Enzynomics, Inc.). LTE-qMSP reaction was performed on an AB7500 FAST Real-Time PCR system (Thermo Fisher Scientific, Inc.) under the following thermocycling conditions: 95°C for 5 min, 5 cycles of 95°C for 15 sec and 70°C for 45 sec, followed by 35 cycles of 95°C for 15 sec and 60°C for 45 sec.

The relative methylation in each sample was calculated as 35-ΔC_T [C_T of the amplified target gene-C_T of COL2A1 (human reference gene)] (25). A higher value indicates a greater level of methylation. If the C_T of the target gene was undetectable, the value was set to 25, the closest value to the lowest 35-ΔC_T among all test results. The assay was conducted by trained personnel blinded to the bronchoscopy or the histopathology results.

All statistical analyses were performed using MedCalc (version 9.3.2.0, medcalc.org/). Receiver operating characteristic (ROC) curves were constructed to evaluate the test performance, with calculation of the area under ROC (AUC) and 95% confidence intervals (CIs). Methylation tests were performed once for each sample, and the data are presented as the mean and standard deviations of all test results for the samples. P<0.05 was considered to indicate a statistically significant difference.

To calculate sensitivity and specificity in BW samples, test results were categorized as follows: Methylation-positive as ‘1’ and methylation-negative as ‘0’. A binary logistic regression analysis was used to determine the best performing marker combination for detecting LC in BW samples. To describe demographic and other clinical characteristics, frequency and percent were used. The negative predictive value (NPV) and positive predictive value (PPV) were also calculated.

The paired t test was conducted to compare differences in methylation levels of each gene between tumor and paired adjacent non-tumor tissue. The Kruskal Wallis test was used to analyze differences in methylation levels between patients with LC and individuals with benign diseases in BW samples. Spearman's correlation analysis was performed to investigate the correlation between methylation levels of genes in BW specimens. The difference in the sensitivity and specificity between the methylation testing and cytology examination for LC diagnosis was analyzed using McNemar test. Fisher's exact test was utilized to examine the relationship between clinicopathological parameters and methylation status in BW samples.

To investigate a subset of hypermethylated candidate genes for detecting LC, CpG methylation patterns were compared between primary lung tumors and corresponding adjacent non-tumor tissues using CpG methylation microarray analyses (Fig. S1). The initial hypothesis was that candidate genes should be unmethylated in non-tumor tissues and frequently hypermethylated in tumor tissues. A total of 18,585 unmethylated CpG probes across all 13 non-tumor tissues were selected. Subsequent statistical analysis (ANOVA) identified 2,844 CpG probes differentially hypermethylated in primary tumor tissue. Methylation candidate numbers were then narrowed to 516 CpG probes representing 65 annotated genes that showed consistent hypermethylation in at least two adjacent CpG probes (Table SIII). Among the 65 candidate genes, the analysis focused on 10 hypermethylated genes, apoptosis antagonizing transcription factor, ATP-binding cassette subfamily C member 9, ADAM metallopeptidase with thrombospondin type 1 motif 20 (ADAMTS20), forkhead box C2 (mesenchyme forkhead 1) (FOXC2), hey-like transcriptional repressor, NK2 transcription factor-related locus 5 (Drosophila) (NKX2-5), oligodendrocyte transcription factor 3 (OLIG3), one cut domain family member 1, protocadherin γ subfamily A 12 (PCDHGA12) and paired-related homeobox 1 (PRRX1), exhibiting a positive call for methylation in their 5′ regulatory regions (promoter or 5′ untranslated region) and had not been previously reported as aberrantly hypermethylated in primary lung tumor tissue.

To verify the methylation status of 10 candidate genes, a pyrosequencing-based methylation assessment was performed in four representative LC cell lines, A549, NCI-H358, SK-MES-1 and NCI-H146, and their status was compared with that of NHBE cells. Results revealed that all 10 genes were hypermethylated in LC cell lines but methylated at a low level in NHBE cells (Fig. 1). In verification analysis using a pyrosequencing assay to confirm whether these candidate genes were aberrantly hypermethylated in primary lung tumors examined in CpG microarray analysis, all candidate genes except HELT exhibited a significantly high level of methylation in primary tumor tissues compared with their corresponding non-tumor tissues (Fig. 2). The mean MtIs of all candidate genes were high in lung tumors (range, 25.1–60.4%), but relatively low in non-tumor tissues (range, 5.6–40.7%; Table II). Among these genes, six (ADAMTS20, FOXC2, NKX2-5, OLIG3, PCDHGA12 and PRRX1) were chosen for further validation because of their consistently high (100%) methylation positivity across all tumor tissues.

A highly sensitive and accurate 3-plex LTE-qMSP in a single closed tube was developed to measure the methylation of target genes in BW samples. Methylation levels were determined using DNA from 68 patients with LC and 33 individuals with benign diseases. Results of the 3-plex LTE-qMSP showed that the methylation levels of all six genes were significantly higher in patients with LC than in individuals with benign diseases (Fig. 3). To determine sensitivity and specificity of individual genes for LC detection, ROC analysis was performed (Fig. 4). Given the optimal cut-off values, the sensitivity range of each gene was 52.9–80.9% and the specificity range was 81.8–97.0% for LC; AUC range was 0.696–0.859. The PPV range was 86.7–97.9% and NPV range was 48.2–69.8%. Cytology results of BW specimens showed a sensitivity of 50.0%, with a specificity of 100% (Table III).

In single marker analysis, PCDHGA12 showed the highest sensitivity of 80.9% (55/68 patients with LC) and PRRX1 achieved the highest specificity of 97.0% (32/33 individuals with benign diseases). PCDHGA12 and PRRX1 had relatively high diagnostic accuracies with AUCs of 0.859 and 0.830, respectively (Table III). A binary logistic regression analysis was conducted using all six markers to identify the best-performing biomarker combination in 36 splits (6 genes by 6 genes) of the dataset. PCDHGA12 and PRRX1 biomarkers were significantly associated with LC. These genes were highly co-methylated according to the correlation analysis (Spearman's correlation coefficient, 0.74). The overall sensitivity of the two-marker combination was 82.4% (56/68 patients with LC; 95% CI, 71.2–90.2%) with a specificity of 87.9% (29/33 individuals with benign diseases; 95% CI, 71.8–96.6%) and AUC of 0.891 (95% CI, 0.813–0.944; Table III). PPV was 93.3% (95% CI, 84.7–97.2%) and NPV was 70.7% (95% CI, 58.7–80.4%). The sensitivities for stage I, II, III and IV LC were 61.5% (8/13), 83.3% (5/6), 92.9% (13/14) and 85.7% (30/35), respectively (Table IV). For detecting LC, sensitivity of this two-marker combination outperformed cytology (McNemar test). When combined with cytology results, its sensitivity was slightly increased to 85.3% (58/68 patients with LC; 95% CI, 74.6–92.7%), maintaining specificity, showing an AUC of 0.866 (95% CI, 0.784–0.926). PPV was 93.6% (95% CI, 85.2–97.3%) and the NPV was 74.4% (95% CI, 61.7–83.9%; Table III).

Subgroup analysis revealed that the methylation status of the two-marker combination was not associated with sex, age or stage (Fisher's exact test). However, it was associated with tumor location and histology (Fisher's exact test) (Table IV). Notably, the sensitivity for SCLC was 100% (19/19 patients with SCLC; Table IV). Specificity was not significantly affected by sex or age (Fisher's exact test).