Inhibition of radiotherapy sensitivity in nasopharyngeal carcinoma via the long non-coding RNA RHPN1-AS1

Introduction

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy originating from the mucosal epithelium of the nasopharynx and is one of the most common head and neck cancers in China (1). Over 70% of new cases occur in East and Southeast Asia, indicating distinct geographical predominance (2), and the most prevalent pathological type is squamous cell carcinoma (3). Due to the occult anatomical location of the primary tumor and the atypical nature of early symptoms, NPC often evades early detection. Consequently, diagnosis is frequently made at the advanced stages, with metastasis occasionally being present, leading to an overall poor prognosis. Furthermore, the complex anatomy of the nasopharynx makes radical surgical resection challenging; thus, radiotherapy is the preferred primary treatment (4).

Despite the significant advancements made in radiotherapy techniques over recent decades, approximately 15% of patients with NPC still experience recurrence after initial radiotherapy (5), indicating that local control rates and long-term survival remain suboptimal. A radiobiological study suggested that the intrinsic radioresistance or low radiosensitivity of NPC cells is a major cause of radiotherapy failure (manifesting as residual tumor or recurrence) (6). Therefore, in-depth research into the mechanisms governing radiosensitivity in NPC is crucial for improving radiotherapeutic outcomes.

Recent studies have revealed that approximately 93% of the human genome is transcribed into RNA, yet only about 2% encodes proteins. Long non-coding RNAs (lncRNAs) are a class of RNA transcripts longer than 200 nucleotides (7) that are not translated into proteins. They were once considered to be “transcriptional noise” or part of the “DNA junk” (8); however, a growing body of evidence suggests that lncRNAs influence tumor cell radiosensitivity by regulating processes such as DNA damage repair, cell cycle progression, and apoptosis (9-11). Within this context, we conducted this study to identify potential radiosensitivity-associated molecules in NPC using bioinformatics approaches and to further clarify the mechanisms underlying the potential regulatory effect of lncRNAs on NPC cell radiosensitivity. We present this article in accordance with the ARRIVE and MDAR reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2852/rc).

Methods

Data acquisition and preprocessing

Given that NPC samples are integrated within the head-and-neck squamous cell carcinoma (HNSCC) cohort in The Cancer Genome Atlas (TCGA), transcriptome profiling data and corresponding clinical information from 109 HNSCC patients who received radiotherapy were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Among these patients, 39 were classified as complete response (CR) patients and 70 as incomplete response (IR) according to clinical response records. Radiotherapy response status was used to reflect intrinsic radiosensitivity.

Identification of differentially expressed lncRNAs (DElncRNAs)

DElncRNAs between CR and IR groups were identified using the “limma” package in R (The R Foundation for Statistical Computing, Vienna, Austria). The screening criteria were set as |log₂ fold change| ≥1 and P<0.05. Heatmaps and volcano plots were generated via the “Pheatmap” and “ggplot2” R packages, respectively.

Weighted gene co-expression network analysis (WGCNA)

WGCNA was performed using the “WGCNA” R package (R Foundation for Statistical Computing, Vienna, Austria) to identify gene modules associated with radiotherapy sensitivity. Briefly, transcriptomic data from HNSCC samples were first subjected to hierarchical clustering to detect and remove outlier samples. A soft-thresholding power was then selected to achieve approximate scale-free topology. Pairwise gene similarities were calculated based on adjacency, and a topological overlap measure was used to assess network connectivity. Gene modules were identified using the dynamic tree cut algorithm, with a minimum module size of 30 genes and a module merge threshold (MEDissThres) of 0.25 to combine similar modules.

Radiotherapy response, categorized as CR or non-CR (NR), was used as the representative phenotypic trait to identify clinically relevant modules. Module-trait correlations were calculated, and genes with module membership (correlation with the module eigengene) >0.3 and gene significance (correlation with radiotherapy response) P≤0.05 were considered candidate hub genes. Finally, these hub genes were intersected with DElncRNAs identified from differential expression analysis to prioritize lncRNAs potentially associated with NPC radiosensitivity.

Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis

KEGG (https://www.genome.jp/kegg/) enrichment analysis, a vital method in bioinformatics, was used to determine the characteristics and functional significance of genes. Visualization of related graphs were conducted with the “ggplot2” R package. A significance threshold of P<0.05 was applied for enrichment analysis.

Clinical sample collection

Forty patients with pathologically confirmed NPC who received radical radiotherapy were prospectively enrolled and were recruited from The First Affiliated Hospital of Anhui Medical University. Inclusion criteria were: age 18–70 years, no prior anticancer treatment, measurable lesions, and a Karnofsky performance status score >70. Tumor biopsy specimens and paired adjacent normal tissues (>5 cm from the tumor margin) were collected before radiotherapy and stored at −80 °C. Therapeutic response was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) and categorized as CR or NR, including partial response, stable disease, and progressive disease. These clinical samples were used to validate the association between candidate lncRNAs and radiotherapy sensitivity identified from bioinformatics analyses. The study protocol was approved by the institutional ethics committee of The First Affiliated Hospital of Anhui Medical University (No. Quick-PJ 2023-10-16) and written informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. A protocol detailing the research question, key design features, and analysis plan was prepared before the study but was not registered in a publicly accessible repository.

Cell culture and transfection

Human NPC cell lines C666-1 and HONE1 (Mingzhou Biotechnology, Ningbo, China) were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum and antibiotics at 37 °C with 5% CO₂. Small interfering RNAs (siRNAs) targeting RHPN1-AS1 and CELF2, overexpression plasmids (pcDNA3.1-CELF2), and controls were obtained from GenePharma (Shanghai, China). Transfections were performed with Lipofectamine 3000 (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol.

Cell irradiation conditions

Cells were exposed to ionizing radiation using an X-ray irradiator at room temperature at a dose rate of 2 Gy/min. Following irradiation, cells were immediately returned to the incubator for further culture. Unless otherwise specified, downstream functional assays were performed 24 h after irradiation.

RNA extraction and quantitative polymerase chain reaction (qPCR)

Total RNA was extracted with TRIzol reagent (Tiangen Biotech, Beijing, China) and reverse-transcribed via the lnRcute lncRNA cDNA synthesis kit or HiScript II RT SuperMix (Novogene, Beijing, China). qPCR was performed with SYBR Green Master Mix on a LightCycler system (Roche, Basel, Switzerland). GAPDH served as the internal control, and the relative expression was calculated via the 2^-ΔΔCt method. The primer sequences are provided in Table S1.

Cell viability and colony formation assays

Cell viability was measured with Cell Counting Kit-8 (CCK-8; 6,000 cells/well in 96-well plates). For colony formation, 500 cells were seeded in six-well plates, irradiated, and cultured for 14 days. Colonies (≥50 cells) were fixed with 4% paraformaldehyde, stained with crystal violet, and counted.

Flow cytometry analysis

For cell cycle analysis, cells were irradiated, incubated for 24 hours, and stained with propidium iodide (PI). Apoptosis was assessed with annexin V/PI double staining. Flow cytometry was performed on a BD FACSCalibur instrument (BD Biosciences, Franklin Lakes, NJ, USA), with 10,000–20,000 events per sample being collected.

Caspase 3/7 activity assay

Cells were incubated with caspase 3/7 fluorescent probe for 30 min and imaged via fluorescence microscopy. Fluorescence intensity was quantified with ImageJ software (US National Institutes of Health, Bethesda, MD, USA).

Western blot analysis

Cells were lysed in RIPA buffer with protease inhibitors. Equal amount of protein was separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred to polyvinylidene fluoride membranes, and probed with primary antibodies overnight at 4 °C and then with horseradish peroxidase-conjugated secondary antibodies. Signals were detected with an enhanced chemiluminescence substrate.

Enzyme-linked immunosorbent assay (ELISA)

The secretion levels of MMP-2 and MMP-9 in cell culture supernatants were determined using specific sandwich ELISA kits from Elabscience Biotechnology Co., Ltd. (Wuhan, China), specifically the Human MMP-2 ELISA Kit (Cat. No. E-EL-H1445) and Human MMP-9 ELISA Kit (Cat. No. E-EL-H6075). The assays were performed strictly following the manufacturer’s protocols. Briefly, supernatants were incubated in the pre-coated microplates, followed by the addition of biotinylated detection antibodies and HRP conjugates. The absorbance was measured at 450 nm using a microplate reader. The concentrations of MMP-2 and MMP-9 were calculated by comparing the optical density (OD) values of the samples to the standard curves.

Immunofluorescence staining

Cells grown on glass-bottom dishes were fixed with cold methanol, permeabilized, blocked, and incubated with primary antibodies (γH2AX and 53BP1) for overnight at 4 °C and then with fluorescent secondary antibodies. Images were acquired via confocal microscopy and analyzed with ImageJ software.

Wound-healing assay

Cells were grown to 70–80% confluence in six-well plates, scratched with pipette tips, and cultured for 24 hours. Migration distance was measured and the migration rate was calculated.

RNA immunoprecipitation (RIP)

RIP assays were performed with the Magna RIP kit (MilliporeSigma, Burlington, MA, USA) according to manufacturer’s protocol. Cell lysates were immunoprecipitated with CELF2 antibody or IgG control for overnight at 4 °C. Co-precipitated RNA was extracted and analyzed by quantitative real-time polymerase chain reaction (RT-qPCR).

Xenograft mouse model

Animal experiments were performed under a project license (No. DWLLPF-2024102801) granted by the Animal Ethics Committee of Hefei Institutes of Physical Science, Chinese Academy of Sciences, in compliance with Chinese Academy of Sciences guidelines for the care and use of animals. C57BL/6 mice were obtained from University of Science and Technology of China (USTC) and housed at 22 °C and 50%±5% relative humidity with 12-hour day-light cycles. Both male and female mice were included in the study. The mice were fed ad libitum with a commercial diet acquired from Suzhou Shuangshi Laboratory Animal Feed Science Co., Ltd. (Suzhou, China) and water.

Nude mice (4–6 weeks old; n=16) were randomly divided into four groups and subcutaneously injected with 3×10⁶ HONE1 cells. When tumors grew to ~100 mm³, mice received 8 Gy of irradiation or sham treatment. The irradiation dose was selected to induce measurable tumor growth delay without excessive toxicity, consistent with previous NPC radiotherapy studies. Tumor volume was measured with calipers (volume =1/2 × length × width²). Mice were euthanized at day 25, and tumors were excised and weighed.

Statistical analysis

All data were presented as the mean ± standard deviation (SD) from at least three independent experiments. Statistical analyses were performed with SPSS 24.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism 9 (Dotmatics, Boston, MA, USA). Student’s t-test or one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was applied as appropriate. A P value <0.05 was considered to indicate statistical significance.

Results

Screening of radiotherapy-sensitive differential genes and WGCNA

Differential expression analysis (NR/CR) was performed with the “limma” R package and the TCGA-HNSCC gene expression matrix. A volcano plot was generated based on the analysis results, as shown in Figure 1A. The differential expression analysis identified a total of 916 significantly DElncRNAs, with 849 being upregulated and 67 downregulated. Meanwhile, an expression heatmap of selected differentially expressed genes was generated with the “pheatmap” R package, as shown in Figure 1B. The differentially expressed genes overall showed significant expression differences between the non-sensitive and sensitive groups.

Figure 1 Differential gene selection and WGCNA. (A) Volcano map of lncRNA gene expression. In this figure, the red dots represent upregulated differentially expressed genes, the blue dots represent downregulated differentially expressed genes, and the gray dots represent nonsignificantly differentially expressed genes. (B) Heatmap of differential lncRNA gene expression. The red color indicates high expression, while the blue color indicates low expression. (C) Nonscaleable soft threshold distribution. (D) Cluster dendrogram, where genes with similar expression patterns are clustered, with each color representing a module. (E) Heatmap of correlation between modules and clinical features. The red color indicates high expression, while the blue color indicates low expression. (F) Venn diagram of differential lncRNA and hub genes. DEG, differentially expressed genes; DElnc, differentially expressed long noncoding RNA; lncRNA, long noncoding RNA; RE, radiotherapy effective; WGCNA, weighted gene coexpression network analysis.

Sample clustering was performed, and then outlier samples were excluded to ensure analytical accuracy. The results showed no significant outlier samples, and all samples were retained. When R² reached 0.9, the soft threshold stabilized and was closest to the cutoff line of 0.9. Meanwhile, when the mean connectivity approached 0, the soft threshold was also 7. Therefore, the optimal soft threshold was selected as 7, as shown in Figure 1C. The adjacency between genes was calculated, and gene similarity was derived from the adjacency, followed by determination of the dissimilarity measure. A hierarchical clustering tree of genes was generated accordingly. Subsequently, based on the hybrid dynamic tree cut standard, the minimum number of genes per module was set to 30. The MEDissThres was set to 0.25 to merge similar modules identified by the dynamic tree cut algorithm. After the merging, a total of 35 modules remained, as shown in Figure 1D.

Correlation analysis was performed between gene modules and clinical traits (NR/CR). The phenotypic traits were converted into quantitative traits, with 0 representing NR and 1 representing CR. Among the 35 co-expression modules, key module genes were screened according to a threshold of Cor >0.3 and P≤0.05. Three key modules were identified: MEroyalblue, MEgrey60, and MEpaleturquoise (Figure 1E). To further identify hub genes, module hub genes were obtained through threshold filtering. MEroyalblue, MEpaleturquoise, and MEgrey60 yielded 12, 25, and 9 hub genes, respectively. The intersection of module genes and radiotherapy sensitivity-related differentially expressed genes yielded a total of 5 DElncRNAs, as shown in Figure 1F.

Preliminary validation of radiotherapy sensitivity-associated lncRNAs and messenger RNA (mRNA)

After the therapeutic efficacy in 40 patients with NPC after radiotherapy was evaluated, 15 cases were classified into the CR group and 25 cases into the NR group, with representative images shown in Figure 2A,2B. Compared to that in the CR group, the expression of RHPN1-AS1 was significantly upregulated in the NR group (P<0.05). In contrast, the expressions of EXTL3-AS1, MAP3K5-AS1, LINC01409, and AC010210.1 were not significantly different between the two groups, as illustrated in Figure 2C.

Figure 2 Expression levels of lncRNA in biopsy samples and their differential expression compared to adjacent noncancerous tissues. (A) Typical magnetic resonance images of the CR group. (B) Typical magnetic resonance images of the NR group. (C) Differential expression analysis of relative lncRNA levels. (D) Differential expression of RHPN1-AS1 in NPC tissues and adjacent noncancerous tissues. ***, P<0.001. CR, complete response; lncRNA, long noncoding RNA; NPC, nasopharyngeal carcinoma; NR, non-complete response; ns, not significant.

To determine whether RHPN1-AS1 expression differs between NPC tissues and adjacent nontumor tissues, we extracted RNA from both cancerous and adjacent tissues of 40 NPC specimens and performed qPCR validation. The analysis revealed that the expression level of RHPN1-AS1 was significantly higher in NPC tissues than in adjacent nontumor tissues (P<0.05) (Figure 2D). These findings further support the presence of an association between RHPN1-AS1 and radiotherapy sensitivity in patients with NPC.

si-RHPN1-AS1 inhibited the proliferative capacity of NPC cells under irradiation

A long-term clonogenic survival assay was performed via the colony formation method to evaluate the proliferative potential of C666-1 and HONE1 NPC cells after irradiation. As shown in Figure 3A, the clonogenic formation of both C666-1 and HONE1 NPC cells was significantly inhibited with an increasing irradiation dose. Notably, the colony-forming capacity of the cells in the si-RHPN1-AS1 treatment group was significantly lower than that in the negative control group (Figure 3B). Furthermore, we conducted a short-term cell proliferation inhibition assay within 24 hours. As the irradiation dose increased, the colony formation in the si-RHPN1-AS1 treated group was significantly reduced as compared to that in negative control group (Figure 3C). These results strongly suggest that under long-term post-irradiation conditions, si-RHPN1-AS1 effectively inhibits the clonogenic survival and proliferative capacity of NPC cells.

Figure 3 Knockdown of RHPN1-AS1 inhibited proliferation in NPC cells. (A) Proliferation ability of C666-1 and HONE1 cells as detected by colony formation assay (crystal violet stained). (B) Proliferation ability was significantly inhibited in the si-RHPN1-AS1 group. (C) Cell viability of C666-1 and HONE1 cells as evaluated by CCK-8 assay. *, P<0.05; **, P<0.01. CCK-8, Cell Counting Kit-8; NPC, nasopharyngeal carcinoma; ns, not significant; si-NC, siRNA negative control; si-RHPN1-AS1, siRNA targeting RHPN1-AS1; siRNA, small interfering RNA.

si-RHPN1-AS1 promoted the apoptosis of NPC cells under irradiation

Upon further examination of apoptosis levels, we found that cell apoptosis significantly increased after silencing of RHPN1-AS1. Under 2 Gy of irradiation, apoptosis was further enhanced, as shown in Figure 4A,4B. Additionally, cell cycle analysis was performed, and after RHPN1-AS1 was silenced, the number of cells in the G2/M phase significantly increased, while the number of cells in the G1 phase significantly decreased (Figure 4C). Under irradiation conditions, a similar phenomenon was observed, indicating that silencing RHPN1-AS1 can arrest cells in the G2/M phase. These results collectively demonstrate that under irradiation conditions, si-RHPN1-AS1 can promote apoptosis in NPC cells.

Figure 4 Knockdown of RHPN1-AS1 induced apoptosis in NPC cells. (A) Flow cytometry detection of apoptotic cells in C666-1 and HONE1 cells. (B) Percentage of apoptotic cells. (C) Percentage of cells in different cell cycle phases as detected by flow cytometry. *, P<0.05; **, P<0.01; ***, P<0.001. EGFP, enhanced green fluorescent protein; NPC, nasopharyngeal carcinoma; si-NC, siRNA negative control; si-RHPN1-AS1, siRNA targeting RHPN1-AS1; siRNA, small interfering RNA.

si-RHPN1-AS1 inhibited the migration and invasion capabilities of NPC under irradiation

In addition to investigating the proapoptotic and antiproliferative effects of si-RHPN1-AS1 on C666-1 and HONE1 NPC cells under irradiation, we examined whether it influences the migration and invasion capabilities of these cells. To this end, we used a wound-healing assay to assess the migration and invasion abilities of C666-1 and HONE1 cells. As shown in Figure 5A, silencing RHPN1-AS1 significantly reduced the migration rate of NPC cells. Under irradiation, the number of migrating and invading cells in the si-RHPN1-AS1 treatment group was markedly decreased (Figure 5B). MMP-2 and MMP-9 belong to a class of enzymes known as matrix metalloproteinases, which play a crucial role in cell migration and invasion by degrading the extracellular matrix, thereby facilitating cellular penetration and movement. To investigate the role of these enzymes, we used Western blotting to detect and analyze MMP-2 and MMP-9. As shown in Figure 5C-5E, under irradiation, the protein levels of MMP-2 and MMP-9 in the si-RHPN1-AS1 treatment group were significantly lower than those in the negative control group. These results indicate that the application of si-RHPN1-AS1 can effectively inhibit the migration and invasion of NPC cells, partially by reducing the expression of MMP-2 and MMP-9.

Figure 5 Knockdown of RHPN1-AS1 inhibited the migration and invasion of NPC cells. (A) The migration rates of C666-1 and HONE1 cells were determined via wound-healing assay (scale bar =100 µm; visualized with phase contrast). (B) Statistical results for the migration ability of C666-1 and HONE1 cells. (C) Western blotting was employed to detect the protein expression levels of MMP-2 and MMP-9. (D) ELISA was used to assess the expression levels of MMP-2 protein. (E) ELISA was used to assess the expression levels of MMP-9 protein. *, P<0.05; **, P<0.01; ***, P<0.001. ELISA, enzyme-linked immunosorbent assay; NPC, nasopharyngeal carcinoma; si-RHPN1-AS1, siRNA targeting RHPN1-AS1; siRNA, small interfering RNA.

Overexpression of RHPN1-AS1 promoted the proliferation and migration of NPC under irradiation while inhibiting apoptosis

We successfully achieved overexpression of RHPN1-AS1 by transfecting the pc-RHPN1-AS1 plasmid into NPC cells. Under irradiation, the proliferative capacity of C666-1 and HONE1 NPC cells was evaluated via colony formation assay. As shown in Figure 6A, the colony-forming ability of cells in the RHPN1-AS1-overexpression group was significantly higher than that in the control group. Similarly, the colony-forming ability in the 2 Gy + RHPN1-AS1-overexpression group was also significantly higher than that in the irradiation-only group. Furthermore, we assessed cell viability within 48 hours using the CCK-8 assay, measuring the absorbance at an OD of 450 nm to determine the cell viability level. As shown in Figure 6B, cell viability in the RHPN1-AS1-overexpression group was significantly higher than that in the control group. Similarly, the cell viability in the group with RHPN1-AS1 overexpression and 2 Gy of irradiation was significantly higher than that in the irradiation-only group.

Figure 6 Overexpression of RHPN1-AS1 promoted the proliferation and migration of NPC cells while inhibiting their apoptosis. (A) Colony formation assay was used to detect the proliferation ability of C666-1 and HONE1 cells (crystal violet stained). (B) Cell viability was assessed with the CCK-8 method. (C) Wound-healing assay was used to determine the migration rate of C666-1 and HONE1 cells (scale bar =100 µm; visualized with phase contrast). (D) Apoptosis level changes were detected via the caspase 3/7 fluorescence method (scale bar =10 µm). *, P<0.05; **, P<0.01; ***, P<0.001. CCK-8, Cell Counting Kit-8; MFI, median fluorescence intensity; NPC, nasopharyngeal carcinoma.

Additionally, we employed wound-healing assays to evaluate the migration and invasion capabilities of RHPN1-AS1-overexpressing cells. As shown in Figure 6C, the migration rate of NPC cells significantly increased after RHPN1-AS1 overexpression. Under irradiation, the number of migrating cells in the RHPN1-AS1-overexpression treatment group was also significantly increased. When further examining the apoptosis levels, we found that under both 0 and 2 Gy of irradiation, apoptosis was significantly reduced after RHPN1-AS1 overexpression (Figure 6D). Therefore, under irradiation, overexpression of RHPN1-AS1 promoted the proliferation and migration of NPC cells and inhibited apoptosis.

si-RHPN1-AS1 increased DNA damage in NPC cells under irradiation conditions

To further evaluate the effect of si-RHPN1-AS1 on cellular DNA damage repair, we examined the expression levels of the DNA double-strand break (DSB) markers, γ-H2AX and 53BP1, in si-RHPN1-AS1-treated NPC cells under irradiation using immunofluorescence and laser scanning confocal microscopy. The results showed a notable increase in positive signals for both γ-H2AX and 53BP1 in the si-RHPN1-AS1 group as compared to the control group, as illustrated in Figure 7A. Further quantitative analysis revealed that after irradiation treatment, the foci count of γ-H2AX and 53BP1 in the si-RHPN1-AS1 group was significantly higher than that in the control group, as shown in Figure 7B,7C. These findings suggest that silencing RHPN1-AS1 may inhibit DNA damage repair and increase DNA damage in NPC cells.

Figure 7 Knockdown of RHPN1-AS1 inhibited DNA damage repair in NPC cells after irradiation. (A) Changes in γ-H2AX and 53BP1 foci in NPC cells were observed under laser confocal microscopy (scale bar =10 µm; DAPI, γ-H2AX and 53BP1 antibody stained). (B) Quantification of γ-H2AX foci. (C) Quantification of 53BP1 foci. ***, P<0.001. ns, not significant; NPC, nasopharyngeal carcinoma.

Validation of si-RHPN1-AS1’s ability to enhance the radiosensitivity of NPC cells in an animal model

We sought to confirm whether si-RHPN1-AS1 can enhance the radiosensitivity of NPC cells through in vivo experiments. By comparing images of subcutaneous xenograft tumors, we observed that the tumor volume in the RHPN1-AS1-silenced group was smaller than that in the control group, while the irradiated groups showed significantly smaller tumor volumes than did the nonirradiated groups (Figure 8A). Furthermore, the growth rate of subcutaneous xenograft tumors in the HONE1-sh-RHPN1 group was slower than that in the HONE1-NC group. After 8 Gy of irradiation, the growth rate of subcutaneous tumors in both groups slowed down, and the average tumor weight was lower than that in the no-irradiated groups, as shown in Figure 8B,8C. Of particular note, the xenograft models in the HONE1-sh-RHPN1 + IR group exhibited the smallest tumor volume, slowest tumor growth rate, and the lowest tumor weight. Therefore, the in vivo experiments confirmed that silencing RHPN1-AS1 enhances the radiosensitivity of NPC cells.

Figure 8 RHPN1-AS1 regulated the radiosensitivity of NPC cells was verified in vivo. (A) Comparison of subcutaneously transplanted tumor images of nude mice between the different treatment groups. (B) Changes in tumor volume in the subcutaneous transplantation of nude mice in the different treatment groups. (C) Comparison of weight of the subcutaneously transplanted tumor of nude mice between the different treatment groups. *, P<0.05; **, P<0.01; ***, P<0.001. IR, ionizing radiation; NC, negative control; NPC, nasopharyngeal carcinoma.

lncRNA RHPN1-AS1 negatively regulated CELF2 expression

A previous study has suggested that lncRNA RHPN1-AS1 may regulate the expression of CELF2 mRNA (12). Therefore, we used the online Gene Expression Profiling Interactive Analysis (GEPIA) with the TCGA database data for correlation analysis and found a negative correlation between RHPN1-AS1 and CELF2 expressions, which prompted further investigation (Figure 9A). To verify whether RHPN1-AS1 negatively regulates CELF2, we employed siRNA interference technology and successfully reduced the expression level of RHPN1-AS1 in C666-1 and HONE1 cells, providing an experimental foundation for further research (Figure 9B). Detection by qPCR showed that after downregulation of RHPN1-AS1 expression, the expression level of CELF2 significantly increased, further supporting our hypothesis that RHPN1-AS1 regulates CELF2 (Figure 9C). Additionally, RIP experiments indicated that both CELF2 protein and RHPN1-AS1 were significantly enriched in the anti-CELF2 antibody pull-down group compared to the IgG control group in C666-1 and HONE1 cells, confirming a direct interaction between RHPN1-AS1 and CELF2 (Figure 9D,9E). To further confirm this finding, we performed Western blot experiments, and the results indicated that after the silencing of RHPN1-AS1, the expression of CELF2 protein was significantly enhanced in C666-1 and HONE1 cells, further confirming that RHPN1-AS1 negatively regulates CELF2 (Figure 9F,9G). In summary, we preliminarily verified that RHPN1-AS1 can negatively regulate the expression of CELF2.

Figure 9 lncRNA RHPN1-AS1 negatively regulated the expression of CELF2. (A) Correlation between RHPN1-AS1 and CELF2 expression in NPC. (B) Downregulation of RHPN1-AS1 expression levels via siRNA technology. (C) Detection of CELF2 expression levels after silencing of RHPN1-AS1. (D,E) Detection of the interaction between RHPN1-AS1 and CELF2 in C666-1 and HONE1 cells via RNA immunoprecipitation. (F,G) Detection of CELF2 protein expression levels in C666-1 and HONE1 cells after silencing RHPN1-AS1. ***, P<0.001. lncRNA, long noncoding RNA; NC, negative control; NPC, nasopharyngeal carcinoma; si-NC, siRNA negative control; si-RHPN1-AS1, siRNA targeting RHPN1-AS1; siRNA, small interfering RNA; TPM, transcripts per million.

Silencing CELF2 reversed the inhibitory effects of si-RHPN1-AS1 on NPC cells

To validate the regulatory role of CELF2 in RHPN1-AS1-mediated processes in NPC, we sequentially transfected RHPN1-AS1 siRNA and CELF2 siRNA into C666-1 and HONE1 NPC cells and assessed their biological functions. The results from the colony formation assay showed that silencing RHPN1-AS1 reduced the proliferative capacity of NPC cells, while silencing CELF2 enhanced it, as shown in Figure 10A. Compared to the si-RHPN1-AS1 group, the si-RHPN1-AS1 + si-CELF2 group exhibited a significant increase in the number of colonies, indicating that silencing CELF2 abolished the inhibitory effect of si-RHPN1-AS1 on clonal proliferation (Figure 10B). Similarly, CCK-8 assay results demonstrated that silencing CELF2 reversed the suppressive effect of si-RHPN1-AS1 on cell viability (Figure 10C). Flow cytometry analysis of apoptosis in NPC cells revealed that the si-RHPN1-AS1 group showed a significant increase in apoptosis, while silencing CELF2 inhibited NPC cell apoptosis. Compared to the si-RHPN1-AS1 group, the si-RHPN1-AS1 + si-CELF2 group exhibited a significant reduction in apoptosis, indicating that silencing CELF2 counteracted the proapoptotic effect of si-RHPN1-AS1 (Figure 10D). Additionally, we observed that silencing CELF2 partially reversed the inhibitory effect of si-RHPN1-AS1 on the invasive capacity of NPC cells, further underscoring the importance of CELF2 in mediating the functions of RHPN1-AS1 (Figure 10E).

Figure 10 Silencing of CELF2 reversed the inhibitory effect of RHPN1-AS1 silencing on NPC cells. (A) Evaluation of the proliferation capacity of C666-1 and HONE1 cells via colony formation assay (crystal violet stained). (B) Statistical comparison of colony numbers. (C) Assessment of cell viability in C666-1 and HONE1 cells via CCK-8 assay. (D) Detection of apoptosis in C666-1 and HONE1 cells via flow cytometry. (E) Wound-healing assay was used to determine the migration rate of C666-1 and HONE1 cells (scale bar =100 µm; visualized with phase contrast). *, P<0.05; **, P<0.01; ***, P<0.001. CCK-8, Cell Counting Kit-8; EGFP, enhanced green fluorescent protein; NC, negative control; NPC, nasopharyngeal carcinoma; ns, not significant; PI, propidium iodide; si-RHPN1-AS1, siRNA targeting RHPN1-AS1.

Effect of CELF2 expression on the MAPK signaling pathway

Using KEGG enrichment analysis, we found that the network genes were involved in MAPK signaling pathway (the MAPK pathway), as shown in Figure 11A. To further clarify the mechanism underlying the effect of CELF2 on NPC, we performed gene set enrichment analyses on the downstream signaling pathways of CELF2. The results indicated that CELF2 expression significantly influenced the MAPK signaling pathway, as detailed in Figure 11B. To further examine the impact of CELF2 on the MAPK signaling pathway, we employed multiple experimental approaches. First, we transfected CELF2 siRNA (siRNA#1, #2, and #3) and a CELF2-overexpression plasmid (pc-CELF2) into C666-1 and HONE1 NPC cells. The qPCR data showed that siRNA significantly reduced CELF2 expression levels, while pc-CELF2 notably increased CELF2 expression levels, as shown in Figure 11C,11D. Considering the close association of the MAPK/p38 and MAPK/JNK pathways with apoptosis, we further examined the protein expression levels of phosphorylation of p38 (p-p38) and p-JNK in the MAPK signaling pathway after CELF2 overexpression or silencing using Western blotting. The experimental results demonstrated that high levels of CELF2 promoted the activation of the MAPK signaling pathway and increased the protein expression levels of p-p38 and p-JNK. Conversely, silencing CELF2 led to reduced protein expression levels of p-p38 and p-JNK in the MAPK pathway (Figure 11E,11F).

Figure 11 CELF2 expression modulated the MAPK signaling pathway. (A) Bubble plot of KEGG enrichment analysis. (B) GSEA plot. (C) Expression levels of the CELF2 gene after transfection with CELF2 siRNAs (siRNA#1, #2, and #3). (D) Expression levels of the CELF2 gene after transfection with pc-CELF2. (E) Western blot analysis of p-p38 and p-JNK protein expression in the MAPK pathway. (F) Expression levels of p-p38 and p-JNK proteins in the MAPK pathway. **, P<0.01; ***, P<0.001. GSEA, Gene Set Enrichment Analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; NC, negative control; ns, not significant; pc-NC, pcDNA negative control plasmid for overexpression; pc-CELF2, pcDNA CELF2 plasmid for overexpression; siRNA, small interfering RNA.

Regulatory effect of lncRNA RHPN1-AS1 on the MAPK pathway via the targeting of CELF2

To further investigate whether RHPN1-AS1 affects CELF2 in the MAPK signaling pathway, we co-transfected RHPN1-AS1 siRNA and CELF2 siRNA into C666-1 and HONE1 NPC cells. The results showed that RHPN1-AS1 siRNA upregulated CELF2 protein expression, while CELF2 siRNA downregulated CELF2 protein expression. Compared to the group treated with RHPN1-AS1 siRNA alone, the group treated with si-RHPN1-AS1 and si-CELF2 exhibited a significant reduction in CELF2 protein expression, as shown in Figure 12A,12B. Western blot analysis revealed that CELF2 silencing reduced the protein expression levels of p-p38 and p-JNK in the MAPK signaling pathway. In contrast, silencing RHPN1-AS1 increased the protein expression levels of p-p38 and p-JNK and abolished the inhibitory effect of CELF2 silencing on the MAPK pathway (Figure 12C-12F). These findings suggest that RHPN1-AS1 may influence the MAPK signaling pathway by regulating CELF2 expression.

Figure 12 Silencing of RHPN1-AS1 activated the MAPK signaling pathway by promoting CELF2 expression. (A) Expression levels of CELF2 protein in C666-1 and HONE1 cells cotransfected with RHPN1-AS1 siRNA and CELF2 siRNA. (B) Statistical analysis of band grayscale values from the results shown in (A). (C,D) Expression levels of p-p38 and p-JNK proteins in the MAPK pathway in C666-1 and HONE1 cells cotransfected with RHPN1-AS1 siRNA and CELF2 siRNA. (E,F) Grayscale analysis of the expression levels of p-p38 and p-JNK, respectively. *, P<0.05; **, P<0.01; ***, P<0.001. NC, negative control; ns, not significant.

Discussion

In recent years, with advancements in gene sequencing technology, numerous molecular markers have become available for predicting tumor radiosensitivity. These molecular markers encompass a variety of entities, including gene expression, protein expression, and metabolic pathways in tumor cells. By detecting the expression levels or mutation status of these molecular markers, the radiosensitivity of tumor cells can be predicted, thereby guiding the formulation of radiotherapy regimens.

This study used HNSCC transcriptome data from the TCGA database. Through differential expression analysis and WGCNA, a total of 1,485 relevant differentially expressed genes were screened out, including 916 lncRNAs. To characterize the differential expression of genes within modules and examine their relationship with radiosensitivity, five DElncRNAs were ultimately selected as candidate radiosensitivity genes. Validation with endoscopic biopsy specimens from 40 patients with NPC who received radical radiotherapy at our hospital revealed that RHPN1-AS1 expression was significantly upregulated in the NR group, and its expression was significantly higher in cancer tissues than in adjacent noncancerous tissues. RHPN1-AS1 is a 2030-bp transcript derived from chromosome 8q24.3 in humans and is an antisense lncRNA originating from the promoter region of RHPN1 (13). Studies have found that RHPN1-AS1 is significantly overexpressed in HNSCC tissues. Inhibition of RHPN1-AS1 in Cal-27 and Tca8113 cell lines was found to reduce cell migration, invasion, and viability. In a large-sample analysis of RNA-sequencing data, aberrant expression levels of RHPN1-AS1 in HNSCC were identified, strongly suggesting that RHPN1-AS1 may function as an oncogene (14). Furthermore, in the RHPN1-AS1 knockdown groups of Cal-27 and Tca8113 cells, the expression of proteins related to epithelial-mesenchymal transition (EMT), including β-catenin, claudin-1, and vimentin, decreased. Given that EMT is associated with tumor radioresistance (15,16), these results suggest that RHPN1-AS1, acting as an oncogene, may be related to radiosensitivity in HNSCC.

We employed human NPC cell lines C666-1 and HONE1 to investigate the role of RHPN1-AS1 in NPC cell radiosensitivity under radiation conditions by silencing and overexpressing RHPN1-AS1. The study found that under irradiation, si-RHPN1-AS1 not only significantly inhibited NPC cell proliferation, arrested the cell cycle at the G2/M phase, and promoted apoptosis, but also markedly suppressed NPC cell migration, reduced the expression of invasion-related proteins such as MMP-2 and MMP-9, and inhibited invasive ability. The repair capacity for radiation-induced DNA DSBs is closely related to radiosensitivity. Upon DSB formation, the phosphorylation of serine 139 on histone H2AX, resulting in γ-H2AX, is one of the earliest events in the DNA damage response. Specific antibody staining allows for the visualization of corresponding foci under a fluorescence microscope, making γ-H2AX a recognized marker of DSBs (17). 53BP1 is recruited to DSB sites and participates in the nonhomologous end joining (NHEJ) repair process, also serving as a widely used indicator for DSB damage and repair (18). γ-H2AX and 53BP1 show high consistency (similar in number and capable of colocalization), both peaking at 1-hour post-irradiation, and thus are ideal markers for accurately reflecting the repair process of ionizing irradiation-induced DSBs (19-21). Detecting the levels of γ-H2AX and 53BP1 proteins after irradiation can provide insights into the extent of DNA damage and repair and is thus valuable for assessing radiosensitivity. Therefore, under irradiation, we used immunofluorescence and confocal laser scanning microscopy to observe the expression levels of the DSB markers γ-H2AX and 53BP1 in si-RHPN1-AS1-treated NPC cells. The results showed that compared with the control group, the si-RHPN1-AS1 group exhibited significantly increased positive signals for both γ-H2AX and 53BP1. Further quantitative analysis revealed that after radiation treatment, the foci count of γ-H2AX and 53BP1 in the si-RHPN1-AS1 group was significantly higher than that in the control group, suggesting that silencing RHPN1-AS1 inhibits DNA damage repair. Finally, we further validated whether si-RHPN1-AS1 can enhance the radiosensitivity of NPC cells through in vivo experiments. Analysis of subcutaneous xenograft tumor growth in mice demonstrated that silencing RHPN1-AS1 increased the radiosensitivity of NPC cells in vivo.

Through a review of related studies, we identified a potential correlation between RHPN1-AS1 and CELF2. Using the online tool GEPIA with TCGA database data for correlation analysis, we found that their expressions were indeed negatively correlated, which prompted further investigation. Silencing RHPN1-AS1 resulted in upregulated CELF2 expression. RIP experiments confirmed that CELF2 is a regulatory target of RHPN1-AS1. To further investigate the regulatory roles of RHPN1-AS1 and CELF2 in NPC cells, we examined the biological functions of NPC cells after sequential transfection with RHPN1-AS1 siRNA and CELF2 siRNA. The results showed that the cell viability and proliferation capacity in the si-RHPN1-AS1 group were significantly lower than those in the control group, whereas the si-CELF2 group exhibited significantly higher cell viability and proliferation capacity. Silencing CELF2 abolished the inhibitory effects of RHPN1-AS1 silencing on cell viability and proliferation. RHPN1-AS1 silencing accelerated apoptosis in NPC cells, while CELF2 silencing inhibited NPC cell apoptosis and reversed the proapoptotic effect induced by RHPN1-AS1 silencing. Furthermore, we observed that CELF2 silencing partially reversed the inhibitory effect of si-RHPN1-AS1 on the invasive capacity of NPC cells, further confirming the significance of CELF2 in mediating the effects of RHPN1-AS1.

CELF proteins are a class of shuttling nucleocytoplasmic RNA-binding proteins possessing three RNA recognition motifs. In humans, the CELF family includes six known isoforms, from CELF1 to CELF6 (22). Based on the similarity of the amino acid sequence, they can be further divided into two subfamilies: one consisting of CELF3-6, primarily confined to neurons and a few other tissues; and the other consisting of CELF1 and CELF2, which are generally expressed in most tissues but exhibit differential expression during development and differentiation (23). CELF proteins have distinct functions within the nucleus and the cytoplasm. Their primary nuclear function involves regulating alternative splicing, as CELF proteins can directly bind to introns of pre-mRNA and promote the formation of normal splicing patterns. Additionally, in the nucleus, they are associated with RNA editing involving the conversion of cytosine to uracil. In the cytoplasm, they can regulate deadenylation, mRNA stability, and translation by binding to the 5' and 3' untranslated regions of mature mRNAs (24). CELF2 acts as a tumor suppressor in various cancers (25-27). Downregulation of CELF2 expression is significantly associated with poor prognosis in patients with malignant tumors, while elevated CELF2 expression is significantly correlated with prolonged survival across multiple cancers, suggesting its potential as a biomarker for predicting cancer prognosis (28). lncRNAs typically regulate CELF2 expression through various mechanisms, including interactions with RNA-binding proteins, to influence mRNA stability, translation, or localization (29). Research by Zhao et al. (30) demonstrated that CELF2 expression increases under ionizing radiation, leading to apoptosis in colon cancer cells. Therefore, as a tumor-suppressor gene, CELF2 can inhibit cancer cell proliferation and invasion, promote apoptosis, and enhance radiosensitivity. Overall, CELF2 and its regulatory network hold potential clinical value in modulating tumor cell radiosensitivity.

To further clarify the function and mechanism of CELF2, we applied KEGG and gene set enrichment analyses and found that CELF2 expression significantly affects the MAPK signaling pathway. The MAPK signaling pathway is a crucial cellular signal transduction pathway involved in regulating cell growth, proliferation, apoptosis, differentiation, and other physiological processes (31). To investigate the impact of CELF2 expression on the MAPK pathway, we transfected CELF2 siRNA and CELF2-overexpression plasmids into NPC cells. The results showed that si-CELF2 significantly reduced CELF2 expression levels, whereas pc-CELF2 notably increased them. High levels of CELF2 promoted the activation of the MAPK signaling pathway and increased the protein expression levels of p-p38 and p-JNK. Conversely, silencing CELF2 led to reduced protein levels of p-p38 and p-JNK in the MAPK pathway. We conducted co-transfection experiments with RHPN1-AS1 and CELF2 and found that upregulation via RHPN1-AS1 siRNA significantly increased CELF2 protein expression levels, while downregulation via CELF2 siRNA decreased CELF2 protein levels. Notably, the CELF2 protein expression level in the si-RHPN1-AS1 + si-CELF2 group was significantly lower than that in the si-RHPN1-AS1 group. Furthermore, we observed that silencing RHPN1-AS1 significantly increased the protein expression of p-p38 and p-JNK in the MAPK pathway and abolished the inhibitory effect of CELF2 silencing on the MAPK pathway. These results suggest that RHPN1-AS1 may regulate the radiosensitivity of NPC by modulating the effect of CELF2 on the MAPK signaling pathway.

Radiotherapy remains the cornerstone of NPC treatment owing to the intrinsic radiosensitivity of this malignancy, as comprehensively summarized by Jicman et al. (32). Despite substantial advances such as intensity-modulated radiotherapy (IMRT) and combined chemoradiotherapy, which have significantly improved local–regional tumor control, a considerable proportion of NPC patients still develop radioresistance. This resistance ultimately leads to treatment failure, local recurrence and distant metastasis, representing a major unmet clinical challenge. These observations underscore the urgent need to elucidate the molecular determinants underlying heterogeneous radiotherapy responses in NPC. However, the contribution of intrinsic biological regulators—particularly lncRNAs—to radiotherapy sensitivity remains insufficiently characterized.

Herein, we identify the lncRNA RHPN1-AS1 as a negative regulator of NPC radiosensitivity. We demonstrate that RHPN1-AS1 expression correlates with radiotherapy response in clinical specimens and validate its function in vitro and in vivo. RHPN1-AS1 silencing significantly enhances radiation-induced DNA DSBs (indicated by γ-H2AX and 53BP1 foci), suppresses tumor aggression, and promotes apoptosis. Mechanistically, we establish a novel RHPN1-AS1–CELF2 regulatory axis. By targeting CELF2, RHPN1-AS1 modulates MAPK signaling (specifically p38 and JNK pathways), thereby facilitating DNA damage tolerance and survival signaling.

Several limitations warrant attention. First, while validated in clinical biopsies, our cohort was relatively small; future multicenter studies are needed to confirm these findings across diverse disease stages. Second, although we utilized TCGA datasets for screening, integrating longitudinal survival data would further refine clinical relevance. Third, while we confirmed the RHPN1-AS1-CELF2-MAPK axis, the precise molecular interactions (e.g., direct RNA-protein binding) and the specific contributions of individual MAPK components require further dissection.

In summary, our study provides compelling evidence that RHPN1-AS1 functions as a negative regulator of NPC radiosensitivity by targeting CELF2 and modulating MAPK signaling pathways. This work not only advances the mechanistic understanding of intrinsic radiosensitivity heterogeneity in NPC but also highlights the translational potential of lncRNA-based biomarkers and therapeutic targets for overcoming radioresistance and improving the precision of radiotherapy in NPC.

Conclusions

This study demonstrated that lncRNA RHPN1-AS1 negatively regulates the radiosensitivity of NPC cells. lncRNA RHPN1-AS1 likely modulates NPC radiosensitivity by targeting CELF2 and affecting the p-p38 MAPK and p-JNK proteins within the MAPK signaling pathway. The specific regulatory mechanisms underlying the interactions between RHPN1-AS1, CELF2, and MAPK should be further investigated. Overall, our findings constitute insights that can aid in identifying potential targets for enhancing NPC radiosensitivity, improving therapeutic efficacy, and predicting prognosis.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the ARRIVE and MDAR reporting checklists. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2852/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2852/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2852/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2852/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol was approved by the institutional ethics committee of The First Affiliated Hospital of Anhui Medical University (No. Quick-PJ 2023-10-16) and written informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Animal experiments were performed under a project license (No. DWLLPF-2024102801) granted by the Animal Ethics Committee of Hefei Institutes of Physical Science, Chinese Academy of Sciences, in compliance with Chinese Academy of Sciences guidelines for the care and use of animals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Gray)