DDX18 Facilitates the Tumorigenesis of Lung Adenocarcinoma by Promoting Cell Cycle Progression through the Upregulation of CDK4

Abstract

Lung adenocarcinoma (LUAD) is the most prevalent and aggressive subtype of lung cancer, exhibiting a dismal prognosis with a five-year survival rate below 5%. DEAD-box RNA helicase 18 (DDX18, gene symbol DDX18), a crucial regulator of RNA metabolism, has been implicated in various cellular processes, including cell cycle control and tumorigenesis. However, its role in LUAD pathogenesis remains elusive. This study demonstrates the significant upregulation of DDX18 in LUAD tissues and its association with poor patient survival (from public databases). Functional in vivo and in vitro assays revealed that DDX18 knockdown potently suppresses LUAD progression. RNA sequencing and chromatin immunoprecipitation experiments identified cyclin-dependent kinase 4 (CDK4), a cell cycle regulator, as a direct transcriptional target of DDX18. Notably, DDX18 depletion induced G1 cell cycle arrest, while its overexpression promoted cell cycle progression even in normal lung cells. Interestingly, while the oncogenic protein c-Myc bound to the DDX18 promoter, it did not influence its expression. Collectively, these findings establish DDX18 as a potential oncogene in LUAD, functioning through the CDK4-mediated cell cycle pathway. DDX18 may represent a promising therapeutic target for LUAD intervention.

1. Introduction

Lung cancer remains a significant global health burden. In 2022, an estimated 20 million new cancer diagnoses were reported, alongside 9.7 million cancer-related deaths [1]. Lung cancer emerged as the most prevalent malignancy, accounting for nearly 2.5 million new cases (12.4% of all cancers). Furthermore, lung cancer held the dubious distinction of being the leading cause of cancer mortality, responsible for an estimated 1.8 million deaths (18.7% of all cancer deaths) [1]. Lung cancers can be classified into small cell lung carcinoma and non-small cell lung carcinoma (NSCLC), with the latter accounting for approximately 85% of all cases [2]. Recent breakthroughs in pathway understanding, detection technologies, and targeted therapies have revolutionized treatment for lung adenocarcinoma [3]. Identification of actionable mutations, such as those in EGFR, PI3K/AKT/mTOR, RAS–MAPK, and NTRK/ROS1 pathways, has led to the development of highly effective drugs [4]. These include EGFR inhibitors (erlotinib, gefitinib) and targeted therapies for other pathways (everolimus, entrectinib), some of which now surpass chemotherapy as first-line treatment [4]. However, survival in NSCLC patients remains poor due to early metastases and the development of targeted therapy resistance [5].

Tightly regulated cell cycle progression is essential for maintaining cellular homeostasis. The four distinct stages (G1, S, G2, and M) are governed by the coordinated activity of cyclin-dependent kinases (CDKs) and cyclin proteins [6,7,8,9]. Cell cycle-specific transcriptional control and protein degradation mechanisms further ensure the precise temporal regulation of these proteins [10]. During the G1 phase, in response to mitotic signals, D-type cyclins (D1, D2, and D3) bind and activate CDK4/6, leading to retinoblastoma protein (RB) phosphorylation [11,12]. This phosphorylation disrupts the E2F–RB complex, releasing the E2F transcription factor and promoting the expression of E-type cyclins (E1, E2). Subsequently, cyclin E–CDK2 complex formation drives the G1/S transition in concert with cyclin D-CDK4/6 [11,13,14,15]. The S/G2 transition is facilitated by cyclin A-CDK2-mediated phosphorylation of DNA replication machinery components [16,17]. Finally, B-type cyclins and CDK1 orchestrate the G2/M phase transition [7,18,19]. Disruptions in cell cycle control mechanisms are a hallmark of cancer, including lung adenocarcinoma. Targeting these pathways offers a promising therapeutic strategy [8,11,12,17] (Figure 1). Besides cell biological factors, external mechanical stimulation, such as local nanomechanical forces prevalent within the soft matter environment [20] of the tumor extracellular matrix, is regulated by matrix stiffness and modulates PD-L1 expression through the activation of the Yes-associated proteins to contribute to tumor cell proliferation [21].

RNA helicases are a diverse group of enzymes essential for RNA metabolism, influencing various cellular processes such as translation, splicing, and RNA decay [22]. Notably, the DEAD-box RNA helicase (DDX) family represents the largest class of RNA helicases, with over 40 members, and plays roles in various cellular processes, mainly involving RNA but sometimes other nucleic acids [23]. Growing evidence implicates their involvement in tumorigenesis [24,25]. For example, MTR4 selectively cleaves mRNAs for glycolytic enzymes PKM2 and GLUT1, thereby regulating their expression and contributing to tumor development [26]. In breast cancer, DDX21 promotes tumorigenesis through distinct mechanisms, including the activation of the AP-1 signaling pathway and the modulation of rRNA processing [27]. Likewise, DDX17 functions as a transcriptional regulator, driving the binding of the nuclear Y-box binding protein 1 (YB1) to the epidermal growth factor receptor (EGFR) gene and promoting its transcription, ultimately facilitating liver cancer metastasis [28]. These findings collectively highlight the DDX family as a promising target for cancer therapy.

DDX18, a member of DEAD-box RNA helicases, is also involved in a broad range of functions associated with RNA. Similar to other DDX family members such as DDX5 and DDX10, DDX18 also possesses a modular architecture with N- and C-terminal domains flanking a conserved helicase core composed of two RecA-like domains [29]. Emerging evidence suggests a multifaceted role for DDX18 in cancer progression. Studies have demonstrated its upregulation and association with poor patient survival in pancreatic ductal adenocarcinoma (PDA) [30]. Mechanistically, DDX18 promotes tumor immune escape in PDA by transcriptionally activating STAT1 expression [30]. Conversely, in gastric cancer, DDX18 promotes tumorigenesis through a distinct pathway. Here, it facilitates the maturation of microRNA-21 via the activation of the AKT signaling pathway [31]. Interestingly, a recent report highlights a protective role for DDX18. It prevents R-loop-induced DNA damage and genome instability through its interaction with PARP-1 [32]. These findings collectively suggest that DDX18 exerts context-dependent effects on cancer development.

To investigate the role of DDX18 in lung adenocarcinoma (LUAD) development, we employed a multifaceted approach. Initially, gene chip technology was utilized to identify DDX18 upregulation in LUAD tissues. Subsequently, functional assays were conducted to evaluate the impact of DDX18 on LUAD cell behavior. Finally, transcriptome sequencing and in vitro experiments were employed to elucidate the underlying regulatory mechanisms by which DDX18 contributes to LUAD progression.

2. Results

2.1. DDX18 Is Upregulated in the LUAD Tissue and Is Required for LUAD Cells Proliferation

To evaluate the clinical significance of DDX18 expression in LUAD, we analyzed publicly available datasets. DDX18 mRNA levels were significantly higher in LUAD tissues compared to adjacent normal tissues in both the GSE75037 dataset (Figure 2a,c) and The Cancer Genome Atlas (TCGA) data (Figure 2b,d). Additionally, high DDX18 expression correlated with poor prognosis in LUAD patients (Figure 2e).

To investigate the functional role of DDX18 in LUAD cells, we generated DDX18 knockdown H157 and H460 cell lines using lentiviral vectors expressing two distinct DDX18-specific shRNAs. Control cells were infected with a lentivirus containing a scramble shRNA. RT-PCR and Western blot analyses confirmed efficient DDX18 knockdown in both cell lines (Figure 2f,g). Functional assays revealed that DDX18 depletion significantly inhibited cell proliferation compared to the control (Figure 2h). Consistent with this finding, colony formation assays demonstrated a reduction in colony numbers in DDX18 knockdown H460 and H157 cells compared to the control (Figure 2i). Furthermore, DDX18 knockdown significantly impaired cell migration in both H460 and H157 cells (Figure 2j).

2.2. DDX18 Overexpression Promotes Tumor Cell Proliferation and Migration

Building on the observation that DDX18 silencing suppressed proliferation and migration of LUAD cells, suggesting its oncogenic role in LUAD, we hypothesized that DDX18 overexpression might promote proliferation in non-malignant lung cells. Beas-2B cells were stably transduced with lentiviral vectors expressing DDX18. RT-PCR and Western blot analyses confirmed efficient DDX18 overexpression at both mRNA and protein levels (Figure 3a,b). Notably, DDX18 overexpression significantly enhanced Beas-2B cell proliferation as measured by the CCK8 assay (Figure 3c). However, colony formation assays revealed no significant difference in clonogenic survival between control and DDX18-overexpressing Beas-2B cells (Figure 3d). Conversely, DDX18 overexpression demonstrably increased the migratory capacity of Beas-2B cells (Figure 3e).

2.3. DDX18 Knockdown Inhibits LUAD Tumorigenesis In Vivo

To evaluate the in vivo role of DDX18 in LUAD tumorigenesis, H460 cells expressing either scramble shRNA (control) or DDX18 shRNA were injected subcutaneously into the left and right flanks, respectively, of nude mice. Representative images of tumor-bearing mice were captured at 4 and 16 days post-injection (Figure 4a,b). Compared to control tumors, DDX18 knockdown significantly suppressed LUAD tumor growth, as evidenced by reduced tumor volume (Figure 4c) and weight (Figure 4d). Hematoxylin and eosin (H&E) staining revealed a looser cell organization in DDX18 knockdown tumor sections compared to controls (Figure 4e). These findings demonstrate that DDX18 is essential for LUAD tumorigenesis.

2.4. Screening for Candidate Targets for DDX18 through RNA-Seq and GO Enrichment Analysis

RNA sequencing analysis was performed to comprehensively identify genes regulated by DDX18 in H460 LUAD cells. Compared to scramble control cells, DDX18 knockdown resulted in differential expression of over 2507 genes (fold change > 2.0) (Figure 5a). Functional enrichment analysis using KEGG pathways and Gene Ontology (GO) terms revealed a significant enrichment of differentially expressed genes (DEGs) in cell cycle-associated pathways. The top 10 enriched GO terms for upregulated and downregulated genes are presented in Figure 5b. Gene Set Enrichment Analysis (GSEA) further confirmed that the cell cycle pathway was significantly deregulated in DDX18-depleted LUAD cells (Figure 5c). Within the biological process (BP) category, GO enrichment analysis identified the most significant enrichments in categories related to “cell cycle,” “mitotic cell cycle,” and “cell cycle checkpoints” (Figure 5d). These findings suggest that DDX18 plays a critical role in regulating cell cycle progression in LUAD cells.

2.5. DDX18 Knockdown Induces G1 Cell Cycle Arrest in LUAD Cells

RNA-seq analysis identified CDK4, a key cell cycle regulator, as downregulated upon DDX18 knockdown in H460 cells (Figure 6a). CDK4 deregulation is a well-established hallmark of various cancers. Interestingly, CDK6 and CCND1, both associated with G1-S phase transition, were upregulated in the absence of DDX18 (Figure 6b). This suggests that DDX18 might regulate cell proliferation by specifically targeting CDK4, a critical G1 phase checkpoint protein. Western blot analysis confirmed that protein levels of CDK4 mirrored the RNA-seq data, whereas CDK6 and CCND1 were upregulated following DDX18 knockdown (Figure 6b). Flow cytometry analysis revealed a significant G1 arrest in H460 and H157 cells with DDX18 knockdown, as evidenced by the increased G1 cell population (Figure 6c,d). Conversely, DDX18 overexpression in Beas-2B cells led to increased protein levels of CDK4, CDK6, and CCND1 (Figure 6e) and altered cell cycle distribution with changes observed across G1, S, and G2/M phases (Figure 6f). Notably, protein levels of CDK4, CDK6, and CCND1 in nude mice xenografts mirrored those observed in cell lines (Figure 6g). These findings collectively suggest that DDX18 regulates cell cycle progression, potentially through CDK4 modulation.

2.6. DDX18 Knockdown Induces Apoptosis in LUAD Cells

RNA-seq analysis revealed upregulation of apoptosis-related genes CDKN1A (P21) and BAX upon DDX18 knockdown in H460 cells (Figure 7a). Western blot analysis confirmed these findings, demonstrating increased protein levels of P21 and BAX following DDX18 knockdown (Figure 7b). To investigate whether apoptosis contributes to the growth inhibition observed in DDX18-depleted H460 and H157 cells, we performed flow cytometry analysis with Annexin V/PI double staining. This analysis revealed a significant increase in the total apoptotic cell population following DDX18 knockdown (Figure 7c,d). Collectively, these results suggest that DDX18 knockdown promotes apoptosis in LUAD cells.

2.7. DDX18 Regulates the Cell Cycle through Transcriptional Regulation of CDK4

We identified a potential E-box element (GTCACGTGCC) located 251 bp upstream of the CDK4 transcriptional start site (TSS) (Figure 8a, left panel) based on the previous literature [33]. To investigate DDX18 interaction with this E-box in H460 cells, we constructed an overexpression vector expressing HA-tagged DDX18 and established H460 cells stably expressing this construct. Chromatin immunoprecipitation (ChIP) assay using an anti-HA antibody revealed enrichment of the CDK4 promoter E-box region compared to a non-binding region 1798 bp upstream of the TSS (Figure 8a, right panel). These findings suggest that DDX18 potentially binds to the CDK4 promoter.

To further establish CDK4 as a functional downstream target of DDX18 in cell cycle regulation, we rescued CDK4 expression in DDX18 knockdown LUAD cells. Western blot analysis confirmed restoration of CDK4 protein levels upon CDK4 rescue (Figure 8b). Notably, CDK4 rescue restored the proliferation capacity (Figure 8c) and colony formation ability (Figure 8d) of DDX18-depleted LUAD cells. Furthermore, CDK4 rescue significantly reduced the G1-arrested cell population as measured by flow cytometry (Figure 8f,g) and restored the migratory capacity of these cells (Figure 9a,b). Collectively, these data strongly suggest that CDK4 is a critical downstream effector of DDX18-mediated cell cycle regulation in LUAD.

2.8. c-Myc Does Not Regulate DDX18 Expression

c-Myc, a well-characterized oncogenic transcription factor known to regulate a vast array of genes, has been proposed to regulate DDX18 expression through promoter binding [34]. To investigate this, we analyzed ChIP-seq data for c-Myc in publicly available ENCODE database cell lines. While the analysis predicted c-Myc binding to the DDX18 promoter region (Figure 9c), c-Myc knockdown in LUAD cells did not affect DDX18 protein levels (Figure 9d). These findings suggest that c-Myc may not be a functional regulator of DDX18 expression in LUAD cells.

3. Discussion

While DDX18 has been implicated in pancreatic and gastric cancers [30,31], its function in lung cancer and its contribution to lung cancer cell biology were unclear. In the present study, we demonstrate that DDX18 expression is upregulated in lung cancer and correlates with poor prognosis. Furthermore, DDX18 depletion significantly inhibits the proliferation, invasion, and migration of lung cancer cells in both in vitro and in vivo models. Mechanistically, we revealed that DDX18 promotes lung cancer cell cycle progression through transcriptional activation of CDK4. Collectively, our findings unveil a novel oncogenic role for DDX18 in lung cancer.

Limited research has previously explored the function of DDX18. Our findings regarding DDX18’s role in lung cancer progression enrich its multifaceted contributions in cancer biology. While previous work showed DDX18’s involvement in tumorigenesis across various cancers, the mechanisms appear to be highly context-dependent. In pancreatic cancer, DDX18 promotes immune escape through STAT1 activation, shielding cancer cells from immune surveillance [30]. Conversely, in gastric cancer, DDX18 fosters tumor development by impacting microRNA-21 maturation [31]. Interestingly, a separate study revealed a contrasting protective function for DDX18, where it interacts with PARP-1 to prevent R-loop formation and DNA damage, thereby safeguarding genome stability [32]. These seemingly disparate findings underscore the complex and context-dependent nature of DDX18’s influence on tumorigenesis. It is likely that DDX18 exerts its effects through distinct regulatory pathways depending on the cellular context and specific tumor type. Further investigation into the precise mechanisms underlying DDX18’s context-specific functions in different cancers is warranted to elucidate its full oncogenic potential.

CDK4, a well-characterized cyclin-dependent kinase essential for G1/S phase transition, is frequently dysregulated in various cancers [35]. Studies have demonstrated that CDK4 deficiency impedes S phase entry, leading to cell cycle arrest in G1 [36]. Our findings provide compelling evidence that DDX18 depletion induces G1 phase arrest in lung cancer cells, coinciding with a decrease in CDK4 protein expression. Conversely, DDX18 overexpression accelerates cell cycle progression in normal lung cells. Mechanistically, we identified DDX18 enrichment at the CDK4 promoter region, suggesting its role as a transcriptional activator of CDK4. This finding establishes a novel regulatory mechanism by which DDX18 promotes cell cycle progression of lung adenocarcinoma through CDK4 upregulation. By targeting DDX18 and its ability to regulate CDK4 expression and influence cell cycle progression, we can potentially develop novel therapeutic strategies to impede lung cancer growth.

c-Myc, a well-established oncogene frequently dysregulated in cancer [37], has been reported to bind the DDX18 promoter [34], implying that it may potentially activate DDX18 transcription. However, our findings suggest a disconnect between c-Myc expression and DDX18 levels in lung cancer, highlighting the possibility of cell type-specific regulatory mechanisms or the existence of alternative upstream regulators of DDX18. This discrepancy underscores the need for further investigation into the upstream transcriptional control of DDX18. The main limitation of our present study is the lack of identification of the potential factor that regulates the transcription of DDX18. Identifying the key transcription factors involved in DDX18-CDK4 axis regulation is critical to fully elucidate the molecular mechanisms governing DDX18 function in lung carcinogenesis.

Lung cancer development is a complex process driven by genetic alterations. Mutations in tumor suppressor genes, like TP53, and oncogenes, such as KRAS, play a key role in initiating uncontrolled proliferation of lung epithelial cells [38]. These mutations can be caused by exposure to carcinogens like tobacco smoke, which damages DNA and disrupts cell cycle regulation [38]. Additionally, chronic inflammation triggered by smoking or other factors can create a microenvironment promoting tumor growth and survival by releasing pro-inflammatory mediators and growth factors [39]. Furthermore, metabolic reprogramming is a hallmark of cancer, and lung tumors often exhibit increased glucose uptake and aerobic glycolysis, even in the presence of oxygen, to support their growth [40].

The expanding repertoire of RNA helicases implicated in tumorigenesis highlights their potential as therapeutic targets. Despite the lack of clinically validated drug targets within this family, ongoing research actively explores their therapeutic potential. Our findings on the significant role of DDX18 in lung cancer progression warrant further investigation of its underlying molecular mechanisms. This will involve recruiting patients for clinical lung cancer sample collection and the development of primary mouse lung cancer models to dissect the impact of DDX18 on the immune response. Our future endeavors will focus on the development or identification of potent and selective small-molecule inhibitors for DDX18. Employing these inhibitors for in vivo mouse lung cancer models will provide insights to inform the design of future clinical translation strategies.

4. Materials and Methods

4.1. Cell Culture

Human embryonic kidney 293 cells (HEK293 FT), bronchial epithelial cells (Beas-2B), and two non-small cell lung cancer cell lines (H460 and H157) were obtained from ATCC (American Type Culture Collection, Rockville, MD, USA). HEK293 FT and Beas-2b were cultured in Dulbecco’s Modified Eagle Medium (DMEM) containing 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. H460 and H157 cells were cultured in RPMI-1640 media (Invitrogen, Carlsbad, CA, USA) containing 10% FBS and 1% penicillin/streptomycin. All cell lines were incubated in a humidified chamber at 37 °C with 5% CO₂.

4.2. Cell Viability Assay

The effects of DDX18 depletion on the cell growth of three cell lines were measured by the Cell Counting Kit-8 (CCK-8) assay (Dojindo, Kumamoto, Japan). Cells were plated in 96-well plates at 3 × 10³ cells/well in 200 μL. After being cultured for 24, 48, 72, or 96 h, the medium was replaced with a mixture of 100 μL of the CCK-8 reagent diluted with RPMI-1640 (1:10). The plate was incubated for an additional 60 min, and then measured at 450 nm with a microplate reader. Independent experiments were repeated at least three times.

4.3. Colony Formation Assay

H460 and H157 cells were seeded onto 6-well plates with a density of 500 cells per well and cultured for about 1 week. Subsequently, the cells were fixed with methanol for 30 min and stained with crystal violet (Beyotime Biotechnology, Shanghai, China) for 30 min. Colonies were counted using ImageJ 1.8.0 software after washing and drying.

4.4. Cell Migration Assay

Culture medium containing 10% FBS (500 μL) was added to the wells of a 24-well plate, and 1 × 10⁵ cells were cultured with FBS-free medium in the inner cavity of the Transwell insert. After the incubation for 36 h, cells adhering to the Transwell insert membrane were fixed and were stained with crystal violet.

4.5. Cell Cycle Analysis

The cell cycle was quantified using the manufacturer’s instructions for the cell cycle analysis kit (Multi Science, Hangzhou, China). A single-cell suspension of H460 and H157 cells was prepared by trypsinization and washed once with phosphate-buffered saline (PBS). Subsequently, the cells were centrifuged (1000× g rpm, 5 min) and resuspended in 300 μL PI containing 3 μL immobilization in a dark place for 30 min. The samples were immediately analyzed by flow cytometry (Thermo Fisher Scientific, Waltham, MA, USA).

4.6. Apoptosis Assays

Apoptosis was quantified by using the Annexin V/propidium iodide (PI) kit (BD Biosciences, Franklin Lakes, NJ, USA). A single-cell suspension of H460 and H157 cells was prepared by trypsinization and washed once with PBS. After centrifugation (1000× g rpm, 5 min), cells were resuspended in 1× annexin V binding buffer 80 µL containing 1 µL Annexin V-FITC and 1 µL PI at 37 °C for 20 min. Cell apoptosis was evaluated by flow cytometry.

4.7. Real-time (RT) Quantitative PCR

Total RNA of cells and tumors was extracted through TRIZOL reagent (Invitrogen, Carlsbad, CA, USA), and 500 ng of the RNA was used with the reverse transcriptase (Accurate Biology, Hunan, China) to produce cDNA. Real-time qPCR was performed with an Applied Biosystems^TM QuantStudio^TM 3&5 (Thermo Fisher Scientific) using FastStart Universal SYBR Green Master (Takara, Otsu, Shiga, Japan). PCR conditions were the following: 3 min at 95 °C, 40 cycles of 10 s at 95 °C, and 30 s at 60 °C. The average Ct value for each gene was determined from triplicate reactions and normalized with mRNA levels of GAPDH. Specificity of the PCR products was confirmed by the presence of a single, well-defined melt peak following each PCR run.

Primer sequences were as follows:

DDX18-Forward: 5′-GTGGATGGTCTTGAACAGGGAT-3′

DDX18-Reverse: 5′-TCCATGAATGGCCAAGACGG-3′

GAPDH-Forward: 5′-TTCACCACCATGGAGAAGGC-3′

GAPDH-Reverse: 5′-GGCATGGACTGTGGTCATGA-3′

4.8. Chromatin Immunoprecipitation (CHIP)

Chromatin immunoprecipitation (ChIP) assays were performed using a SimpleChIP Enzymatic Chromatin IP kit (Cell Signaling Technologies, Danvers, MA, USA). Cells were fixed with 1% formaldehyde for 10 min, and glycine with 0.125 M was added to stop the fixation. Chromatin was treated with micrococcal nuclease, sonicated, and immunoprecipitated with normal rabbit IgG (negative control) or anti-HA antibody (Proteintech, Rosemont, IL, USA) overnight at 4 °C. After the reverse cross-linking and DNA purification, immunoprecipitated DNA was quantified by qPCR.

Primer sequences were as follows:

CDK4#1-Forward: 5′-GGACCCAAGCAGACAGAGAG-3′

CDK4#1-Reverse: 5′-GGTGGGTGCTTTGTAAGCCT-3′

CDK4#E-box-Forward: 5′-GTGGCCTAGGTTGCCATGGCAC-3′

CDK4#E-box-Reverse: 5′-CTCACCATGTGACCAGCTGCC-3′

4.9. Construct and Lentivirus Production

For DDX18 knockdown, two different DDX18 shRNA target sequences were synthesized and inserted into pLKO.1-puro vector (Plasmid #8453, Addgene, Watertown, MA, USA). To overexpress DDX18, full-length DDX18 cDNA was inserted into pLenti-CMV GFP vector (Plasmid #17448, Addgene) linearized by BamHl/Sall digestion. For lentivirus production, package plasmid psPAX2 (Plasmid #12260, Addgene), envelop plasmid pMD2.G (Plasmid #12259, Addgene), and vectors were co-transfected into HEK 293FT cells. Then, 72 h after transfection, the supernatant was harvested and concentrated with Lenti-X concentrator (ECOTOP, Guangzhou, China). One day before the viral infection, cells were plated into a 6-well plate at a density of 1 × 10⁵ cells/well and transduced in the presence of 5 μg/mL polybrene for 24 h. The cells were selected for puromycin resistance (1.5 μg/mL) for 48 h.

4.10. Western Blotting

Western blotting was performed as previously described [23]. Membranes were probed with the following antibodies: DDX18 (DF9258, Affinity Biosciences, Changzhou, China), CDK4 (AF2515, Beyotime, Shanghai, China), CDK6 (AG1575, Beyotime), CyclinD1 (ab32053, Abcam, Cambridge, MA, USA), BAX (ab32503, Abcam), P21 (ab109520, Abcam). All primary antibodies were diluted in Tris-buffered saline containing Tween 20 and 3% bovine serum albumin (BSA), and a peroxidase conjugate (Bioworld, Saint Louis Park, MN, USA) was used as the secondary antibody. GAPDH (60004-1-Ig, Proteintech, Rosemont, IL, USA) and β-ACTIN (20536-I, Proteintech) were used as a loading control. Immunoreactive bands were visualized using an enhanced chemo-luminescence kit (Thermo Fisher Scientific), and images were captured using a Amersham^TM ImageQuant^TM 800 molecular imager (Cytiva, Washington, DC, USA).

4.11. Establishment of the Xenograft Mouse Model

All work with the xenograft mouse model was conducted following the guidelines of the Ministry of Science and Technology of China and was approved by the Animal Ethics Committee of Sun Yat-sen University. Six-week-old NU/NU mice were obtained from the Guangdong Experimental Animal Center. Animals were maintained under a 12 h light/dark cycle in a specific pathogen-free (SPF) facility with ad libitum access to standard laboratory chow and water. To assess the tumor growth, 5 × 10⁶ H460 cells were injected subcutaneously into the left (control group) and right (DDX18 knockdown group) flanks of each mouse. Tumor sizes were measured with a caliper and recorded every day. Tumor volume was calculated as follows: tumor volume = (length × width²) × 0.5, and when the size reached ~1.5 cm³, mice were euthanized, and tumor weight was measured after removing the tumors.

4.12. RNA Sequencing and Bioinformatics Analysis

RNA isolation for RNA sequencing (RNA-seq) analyses was performed using TRIZOL reagent (Invitrogen). The whole transcriptome libraries for costunolide and DMSO-treated cells (n = 3) were prepared with the SOLiD TM Whole Transcriptome Analysis Kit (Applied Biosystems, Carlsbad, CA, USA) and paired-end sequencing was conducted on an Illumina HiSeq system using PE150 strategy. The reads were aligned against the human reference genome (H. sapiens, GRCh38) and TMM normalization method was used for data normalization (R/Bioconductor package edgeR). Limma package and Student’s t-test were used for statistical analysis of the mean expression values between costunolide and DMSO-treated lung cancer cell lines (n = 3). KEGG and Reactome analysis were conducted by KOBAS3.0 (kobas.cbi.pku.edu.cn/kobas3 (accessed on 13 July 2023)) [41], and pathways with p-value < 0.05 were considered to be significantly enriched in the annotation categories.

4.13. Statistical Analysis

All experimental data in the figures are shown as the mean ± SD. The statistical significance of Kaplan–Meier survival plot was determined by log-rank analysis. The other statistical significance was detected by t-test. All of the statistical analyses were performed in GraphPad Prism 8.3.0. * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001; ns means non-significant. All experiments were repeated at least three times.

5. Conclusions

Our findings demonstrate a potential oncogenic role for DDX18 in LUAD. Analysis of TCGA and GEO databases revealed significant upregulation of DDX18 in LUAD tissues, and this upregulation correlated with poor patient survival. Functional studies confirmed that DDX18 knockdown in LUAD cells impedes cell growth, while overexpression in Beas-2B cells promotes proliferation. RNA-seq identified the cell cycle pathway as significantly dysregulated upon DDX18 depletion. Flow cytometry analysis further revealed G1 cell cycle arrest in DDX18 knockdown cells, accompanied by downregulation of the key G1 regulator CDK4. CHIP experiments confirmed DDX18 binding to the CDK4 promoter region. Rescue of CDK4 expression after DDX18 knockdown abrogated the cell cycle arrest phenotype, suggesting DDX18 regulates cell cycle progression via CDK4 expression. Collectively, these data strongly support the potential of DDX18 as a therapeutic target for lung cancer.