O-GlcNAcylation levels predict radiotherapy outcome in non-small cell lung cancer

Introduction

Lung cancer is the most commonly diagnosed malignancy and the leading cause of cancer-related mortality worldwide, accounting for about 12% of new cases annually (1,2). Non-small cell lung cancer (NSCLC) comprises 80–85% of cases and poses major therapeutic challenges due to its heterogeneity and frequent diagnosis at advanced stages (3). Radiotherapy (RT) is a key component of NSCLC management, applied with curative or palliative intent across disease stages (4). However, radioresistance remains a significant barrier, leading to recurrence and poor survival (5,6). Identifying molecular determinants of radioresponse is therefore critical to improving treatment outcomes.

O-GlcNAcylation (O-GlcNAc) is a dynamic post-translational modification (PTM) in which β-D-N-acetylglucosamine is attached to serine or threonine residues of nuclear and cytoplasmic proteins, regulated by O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA) (7,8). It influences diverse cellular processes including transcription, signaling, cell cycle regulation, and stress responses (9-11). Aberrant O-GlcNAc has been implicated in tumorigenesis by promoting metabolic reprogramming, invasion, metastasis, immune evasion, and resistance to standard therapies (12-14). Elevated O-GlcNAc has been reported in several cancers, including NSCLC, and is linked to aggressive behavior and poor prognosis (15). Emerging evidence suggests that O-GlcNAc also regulates DNA damage repair and survival pathways after irradiation, indicating a role in radioresistance (16).

Molecular imaging provides complementary information on tumor biology and treatment response. The glucose analog ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG), widely used in positron emission tomography-computed tomography (PET-CT), enables non-invasive assessment of glucose activity (17). The standardized uptake value (SUV) is a semi-quantitative index of glucose metabolism and is routinely used in staging, RT planning, response monitoring, and recurrence detection. Advances in radiomics and machine learning have further enhanced PET-based prognostic modeling and individualized treatment planning (18,19).

Given the links between O-GlcNAc, cancer metabolism, and therapeutic resistance, we hypothesized that O-GlcNAc expression may be associated with glycolytic phenotype and radioresponse in NSCLC. We retrospectively analyzed 216 NSCLC patients treated with RT. O-GlcNAc expression in tumor tissue was assessed by immunohistochemistry (IHC) and correlated with ¹⁸F-FDG uptake, baseline blood glucose, RT response, and survival outcomes. This study aimed to evaluate O-GlcNAc as a potential biomarker and therapeutic target in NSCLC. We present this article in accordance with the REMARK reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-998/rc).

Methods

Patients

This retrospective cohort study analyzed 216 patients in Shandong Cancer Hospital between 2014 and 2024. Clinical and treatment-related information—including age, gender, tumor stage, histology, radiation dose, chemotherapy use, and blood glucose levels—was systematically retrieved from the institutional electronic medical record system. Routine follow-up included contrast-enhanced computed tomography (CT) scans and clinical evaluations performed every 12 weeks (±2 weeks) after RT completion. The study protocol was reviewed and approved by the Ethics Committee of Shandong Cancer Hospital and Institute (ethics approval number: SDTHEC2023003058). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The patients were informed about the objective of the study and provided informed consent. Ultimately, a total of 216 patients meeting all eligibility criteria were included in the final analysis.

Inclusion criteria:

• Histologically confirmed NSCLC;
• Receipt of definitive or palliative RT at our institution;
• Availability of pretreatment ¹⁸F-FDG PET-CT imaging;
• Complete clinical, treatment, and follow-up records.

Exclusion criteria:

• Prior malignancy;
• Incomplete RT courses;
• Insufficient imaging or biomarker data.

RT response was evaluated according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 by an experienced radiologist unaware of O-GlcNAc status. Objective response was defined as complete or partial response (≥30% reduction in target lesions), while progressive disease indicated a ≥20% increase in lesion size or emergence of new metastases.

Survival outcomes included overall survival (OS) and progression-free survival (PFS). OS was calculated from the date of pathological diagnosis to death from any cause or last follow-up. PFS was defined as the time from RT initiation to radiologic progression or death.

O-GlcNAc IHC

Tumor tissue specimens were obtained from patients diagnosed with NSCLC who underwent RT at our institution. All samples were formalin-fixed and paraffin-embedded (FFPE) under standardized procedures in the Department of Pathology, Shandong Cancer Hospital. Sections of 4 µm thickness were prepared using a rotary microtome and mounted on poly-L-lysine-coated slides to enhance tissue adhesion.

For immunohistochemical staining, sections were initially deparaffinized in xylene and rehydrated through a graded ethanol series. Antigen retrieval was performed using EDTA buffer (pH 9.0) under high-pressure heating conditions. After cooling, slides were rinsed in phosphate-buffered saline (PBS, pH 7.4). To minimize non-specific binding, sections were incubated with normal goat serum for 30 minutes at room temperature. Endogenous peroxidase activity was blocked by treatment with 3% hydrogen peroxide for 15 minutes.

The sections were then incubated overnight at 4 ℃ with a mouse monoclonal anti-O-GlcNAc antibody (clone RL2, MA1-072; Invitrogen, Carlsbad, CA, USA) at a dilution of 1:200. Negative controls were prepared by omitting the primary antibody. Following primary antibody incubation, slides were washed and treated with biotin-labeled secondary antibody for 30 minutes at 37 ℃, followed by streptavidin-horseradish peroxidase conjugate (UltraSensitive™ S-P kit, KIT-9720; Maixin Biotech, Fuzhou, China). Immunoreactivity was visualized using 3,3'-diaminobenzidine (DAB) as the chromogen (DAB-1031; Maixin Biotech, Fuzhou, China), and sections were counterstained with hematoxylin. Finally, slides were dehydrated, cleared in xylene, and coverslipped with neutral balsam.

Slides were imaged using a BX53 light microscope (Olympus, Tokyo, Japan) under consistent bright-field settings. O-GlcNAc expression was evaluated by using a validated scoring system incorporating both staining intensity and the proportion of positive tumor cells. Staining intensity was graded as 0 (negative), 1 (weak), 2 (moderate), or 3 (strong). The percentage of positive cells was assigned a score of 1 (1–33%), 2 (34–66%), or 3 (67–100%). The final H-score, ranging from 0 to 9, was calculated by multiplying the intensity and proportion scores. All histological assessments were conducted independently by two board-certified pathologists who were blinded to clinical data. Discrepancies were resolved through concurrent re-evaluation using a multi-head microscope.

Statistical analysis

Statistical analyses were performed to evaluate associations between O-GlcNAc expression, clinicopathological variables, and treatment outcomes. Chi-squared test and Student’s t-test were performed to assess the statistical significance. Univariable and multivariable logistic regression models were employed to identify factors independently associated with high O-GlcNAc expression (dichotomized based on median H-score). Variables with P<0.10 in univariable analysis were included in the multivariable model. Results were reported as odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Survival curves were constructed using the Kaplan-Meier method and compared with the log-rank test. All analyses were conducted using SPSS version 25.0 (IBM Corp., Armonk, NY, USA) and GraphPad Prism version 7.0 (GraphPad Software, San Diego, CA, USA). A two-sided P value <0.05 was considered statistically significant.

Results

Clinical features

A total of 216 patients with pathologically confirmed NSCLC who underwent RT between 2014 and 2024 were included in this study. All patients had pretreatment ¹⁸F-FDG PET-CT imaging prior to initiation of RT. The baseline demographic and clinical characteristics of the study cohort are presented in Table 1.

The study population comprised 139 males (64.4%) and 77 females (35.6%), with a mean age of 66.3±10.9 years (range, 38–91 years). Patients were stratified into two groups according to age, with 128 individuals (59.3%) aged 65 years or older and 88 (40.7%) younger than 65 years. Histopathological classification showed that 162 patients (75.0%) had lung adenocarcinoma (LUAD) and 54 (25.0%) had lung squamous cell carcinoma (LUSC). Based on the 8th edition American Joint Committee on Cancer (AJCC) staging system, the distribution was as follows: 31 patients (14.4%) with stage I disease, 15 (6.9%) with stage II, 82 (38.0%) with stage III, and 88 (40.7%) with stage IV. At the time of diagnosis, 88 patients (40.7%) already had distant metastases.

All patients received RT, with a mean total dose of 54.7±8.8 Gy. Treatment response was assessed within 6 months of RT completion using RECIST 1.1 criteria. An objective radiological response was observed in 148 patients 68.5%), while 68 patients (31.5%) exhibited either stable disease or progression.

Pretreatment metabolic tumor activity, evaluated by ¹⁸F-FDG PET-CT, demonstrated a mean maximum standardized uptake value (SUVmax) of 11.3±6.7 in the primary tumor. The mean pretreatment blood glucose concentration was 5.6±1.3 mmol/L. The average Karnofsky Performance Status (KPS) score was 85.2±6.3, indicating generally preserved functional status at baseline.

With respect to systemic therapy, 198 patients (91.7%) received chemotherapy, 144 (66.7%) received targeted therapy—predominantly epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs)—and 91 (42.1%) received immune checkpoint inhibitors. The most common comorbidities were a history of smoking (44.0%), hypertension (26.9%), diabetes mellitus (20.4%), and heart disease (8.8%).

O-GlcNAc levels in NSCLC

The distribution of O-GlcNAc expression scores among all patients is summarized in Table S1. Specifically, the scores were distributed as follows: 0 (n=12), 1 (n=26), 2 (n=20), 3 (n=11), 4 (n=7), 5 (n=8), 6 (n=11), 7 (n=70), 8 (n=26), and 9 (n=25). Using the median score as the cutoff, patients were subsequently stratified into a low-expression group (scores 0–4) and a high-expression group (scores 5–9) for further analyses, as shown in Table 2. The proportion of RT responders was significantly lower in the low-expression group compared with the high-expression group (55.3% vs. 75.7%, P=0.002; Table 2, Figure 1A). IHC further confirmed higher O-GlcNAc expression in tumors from RT responders compared with non-responders (Figure 1B). No significant associations were observed between O-GlcNAc expression and baseline clinical variables, including sex, age, histology, stage, and KPS.

Figure 1 The association among the O-GlcNAc expression and radiotherapy outcome. (A) The O-GlcNAc expression was significantly correlated with the radiotherapy response. (B) Representative IHC staining images of responders and non-responders to RT and CT images of primary tumors. Scale bar =20 µm. The red arrows in CT reflected primary tumor. High O-GlcNAc expression was significantly associated with longer PFS (C) and OS (D) among patients undergoing RT. (E) No significant difference in PFS among the high, moderate, and low O-GlcNAc groups. (F) High O-GlcNAc expression was associated with longer OS compared to moderate/low expression groups. CT, computed tomography; IHC, immunohistochemistry; O-GlcNAc, O-GlcNAcylation; OS, overall survival; PFS, progression-free survival; RT, radiotherapy.

Further, we performed regression analysis to eliminate the interference of confounding factors and determine the factors associated with the expression of O-GlcNAc. Univariate and multivariate logistic regression analyses demonstrated that O-GlcNAc expression was independently associated with RT response (P=0.005; OR =2.47; 95% CI: 1.32–4.64; Table 3; Figure S1). Kaplan-Meier survival analyses further showed that high O-GlcNAc expression was significantly associated with longer PFS (log-rank P=0.049; Figure 1C) and OS (log-rank P=0.008; Figure 1D) among patients undergoing RT.

Recognizing that the relatively large patient cohort and the wide distribution of H-scores (ranging from 0 to 9) could make a simple dichotomization into high and low expression groups less rigorous, we further stratified patients into three categories based on O-GlcNAc expression: scores of 0–2 were defined as low expression, 3–6 as moderate expression, and 7–9 as high expression. Kaplan-Meier analyses across these three groups revealed no significant difference in PFS (Figure 1E), whereas patients in the high-expression group demonstrated significantly longer OS compared with those in the low- and moderate-expression groups (Figure 1F). These results provide additional evidence supporting our original conclusion that elevated O-GlcNAc expression is associated with a more favorable prognosis.

Given that LUAD accounted for 75% of our cohort, we examined whether the prognostic value of O-GlcNAc is dependent on histologic subtype. Accordingly, we analyzed the association between O-GlcNAc expression levels and survival outcomes separately in the LUAD and LUSC subgroups. Notably, we observed a clear histology-specific difference in the prognostic significance of O-GlcNAc. In patients with LUSC, O-GlcNAc expression levels showed no significant association with either PFS (log-rank P=0.76; Figure S2A) or OS (log-rank P=0.40; Figure S2B). In contrast, although there was no difference in PFS (log-rank P=0.051; Figure S2C), high O-GlcNAc still indicated a better OS (log-rank P=0.01; Figure S2D).

SUVmax levels and blood glucose in NSCLC

As glucose is the primary substrate for O-GlcNAc and SUVmax from ¹⁸F-FDG PET-CT reflects tumor glucose uptake, we further examined the associations between glucose metabolism indices and patient characteristics. Blood glucose, as an accessible clinical parameter, was also included.

Using the median SUVmax as the cutoff, patients were stratified into high- (n=108) and low-SUVmax (n=108) groups. As summarized in Table 4, univariate analysis revealed that the high-SUVmax group had significantly lower fasting blood glucose (P=0.009), a lower prevalence of diabetes (P=0.002), and a higher proportion of squamous cell carcinoma (LUSC) compared with adenocarcinoma (LUAD) (P=0.002). In addition, patients with high SUVmax presented with more advanced disease (P=0.02), lower prevalence of hypertension (P<0.001), increased use of chemotherapy (P=0.049) and of immunotherapy (P=0.04). However, SUVmax was not significantly associated with RT response (71.3% vs. 65.7%, P=0.38; Figure 2A,2B).

Figure 2 The association among the SUVmax, blood glucose and radiotherapy outcome. (A) The SUVmax was unrelated with the radiotherapy response. (B) Patients with higher SUVmax in tumors was not associated with RT response. The red arrows in PET-CT and CT reflected primary tumor. High SUVmax expression was not associated with PFS (C), but was significantly associated with shorter OS (D). (E) The blood glucose was unrelated with the radiotherapy response. Blood glucose was not associated with PFS (F) or OS (G). CT, computed tomography; OS, overall survival; PET-CT, positron emission tomography-computed tomography; PFS, progression-free survival; RT, radiotherapy; SUVmax, maximum standardized uptake value.

Multivariable logistic regression, adjusted for potential confounders including diabetes, chemotherapy, and stage, confirmed that low SUVmax was independently associated with LUAD (P=0.003; OR =2.96; 95% CI: 1.45–6.05) and inversely associated with hypertension (P=0.03; OR =0.40; 95% CI: 0.17–0.93). Survival analysis showed that SUVmax was not predictive of PFS (log-rank P=0.77; Figure 2C), but high SUVmax was significantly associated with shorter OS (log-rank P=0.03; Figure 2D).

Similarly, patients were stratified into high- and low-blood glucose groups using the median value. As summarized in Table 5, univariate comparisons showed that the high-glucose group was characterized by older age (P=0.007), higher prevalence of diabetes (P<0.001) and hypertension (P=0.001), and lower use of chemotherapy (P=0.04). No significant difference in RT response was observed between the groups (66.7% vs. 70.1%, P=0.59; Figure 2E).

Multivariable analysis confirmed that elevated blood glucose was independently associated only with pre-existing diabetes (P=0.02; OR =3.33; 95% CI: 1.21–9.14). Kaplan-Meier analyses demonstrated no significant associations between blood glucose levels and PFS (log-rank P=0.70; Figure 2F) or OS (log-rank P=0.08; Figure 2G).

Discussion

RT is widely applied as an effective treatment modality for various cancers, including NSCLC, melanoma, rectal cancer, etc. (20). However, tumor cells often develop radioresistance through mechanisms such as cell cycle arrest, enhanced DNA repair, and inhibition of apoptosis (21,22). Considerable research has focused on overcoming radioresistance, either by targeting key molecular pathways or by identifying predictive biomarkers that allow more precise patient stratification (23,24). Our study demonstrated that elevated O-GlcNAc expression in tumor tissues predicted improved RT response and was associated with longer PFS and OS, suggesting its potential as a clinically actionable biomarker.

From a mechanistic perspective, O-GlcNAc—a dynamic PTM regulated by OGT and OGA—has been implicated in diverse cellular processes relevant to radiosensitivity (25,26). Elevated O-GlcNAc can modify proteins involved in DNA repair pathways, such as ATM and H2AX, potentially enhancing repair capacity and promoting resistance. Conversely, excessive or dysregulated O-GlcNAc may impair DNA damage response fidelity, destabilize repair complexes, and sensitize tumor cells to radiation (27,28). In addition, O-GlcNAc modulates apoptosis regulators including p53 and Bcl-2 family proteins, and influences cell cycle progression through CDKs and checkpoint kinases (29-31). These multifaceted effects highlight why O-GlcNAc status may critically shape the outcome of RT, and may explain why patients with globally elevated O-GlcNAc derived greater benefit in our cohort. We hypothesize that RT may partially reverse the tumor-promoting functions of hyper-O-GlcNAc, thereby shifting the cellular balance toward growth inhibition and apoptosis.

Clinically, our findings emphasize the translational value of O-GlcNAc testing. Patients with higher O-GlcNAc expression appeared to derive greater therapeutic benefit from RT, suggesting that IHC-based assessment of O-GlcNAc could be incorporated into routine pathological evaluation. Such an approach may allow oncologists to identify patients who are more likely to respond favorably to standard radiation regimens, while guiding others toward alternative or combination strategies. Compared with genomic sequencing or complex molecular imaging, IHC-based assays for O-GlcNAc are relatively simple, cost-effective, and widely feasible, which enhances their clinical practicality.

We also examined the relationship between O-GlcNAc and clinical glucose-related indicators, given that glucose is a primary substrate for O-GlcNAc modification. Interestingly, neither pre-RT primary tumor SUVmax on PET-CT nor peripheral blood glucose levels predicted RT efficacy, and both parameters were unrelated to O-GlcNAc expression. These results imply that tumor cells may preferentially channel glucose into energy metabolism rather than PTM, and highlight the complexity of metabolic regulation in the tumor microenvironment (32,33). The lack of a direct correlation between systemic glucose indices and O-GlcNAc expression underscores the need for biomarker evaluation at the tissue level rather than relying on metabolic surrogates.

We note that among the 216 patients, the vast majority (n=198) received chemotherapy. Given the dynamic nature of most PTMs, chemotherapeutic agents may exert unanticipated effects on tumor O-GlcNAc levels. A retrospective review of medical records indicated that the most frequently administered regimens included pemetrexed, paclitaxel, and platinum-based agents.

Pemetrexed, a multi-target antifolate antimetabolite, exerts cytotoxic effects by inhibiting key enzymes in one-carbon metabolism and purine/pyrimidine synthesis, including thymidylate synthase (TS), dihydrofolate reductase (DHFR), and glycinamide ribonucleotide formyltransferase (GARFT). This inhibition induces replication stress, activates the DNA damage response (DDR), and remodels the metabolic network. By disrupting one-carbon metabolism and nucleotide synthesis, pemetrexed may impair the metabolic coupling of glucose and glutamine utilization, thereby reducing flux through the hexosamine biosynthesis pathway (HBP) and limiting the supply of UDP-GlcNAc (34). From this perspective, global O-GlcNAc levels may be downregulated due to substrate depletion.

In contrast, platinum-based agents induce tumor cell death by causing hypoxia, DNA damage, oxidative stress, and endoplasmic reticulum (ER) stress. These insults activate stress-adaptive response pathways (SARPs), in which O-GlcNAc functions as a critical modulator. Under such conditions, O-GlcNAc is often transiently or chronically upregulated, enhancing the stability, transcriptional activity, and protein-protein interactions of key survival factors. For example, O-GlcNAc can stabilize NRF2 through site-specific modification, thereby augmenting antioxidant and pro-survival signaling (35). Similarly, O-GlcNAc at the T346 site of calreticulin (CRT) maintains Ca²⁺ homeostasis and proteostatic capacity, promoting tumor cell survival and suppressing apoptosis (36).

Paclitaxel, which stabilizes microtubules, arrests mitosis, and induces oxidative and ER stress as well as proteostatic challenge, also engages this dynamic PTM. Under such stress conditions, O-GlcNAc is frequently elevated transiently, serving to stabilize and enhance the activity of transcription factors such as NF-κB, NRF2, and HIF-1α, optimize protein interactions and localization, buffer damage signals, and help maintain cellular homeostasis (8).

In summary, the impact of chemotherapy on O-GlcNAc is multifaceted and context-dependent. Although clinical diagnosis and treatment typically rely on pre-chemotherapy biopsies, and although our univariate and multivariable analyses statistically adjusted for chemotherapy administration, the timing of specimen collection in our study precludes definitive conclusions regarding the specific effects of these agents on tumor O-GlcNAc levels. Future mechanistic studies are warranted to elucidate how individual or combined chemotherapeutic agents modulate the O-GlcNAc landscape and to explore the potential of this pathway in overcoming chemotherapy resistance.

Several additional observations warrant further investigation. We found that patients with hypertension exhibited lower tumor SUVmax values, though the underlying mechanisms remain unclear. Furthermore, we observed that compared to LUAD, LUSC exhibited higher primary tumor SUVmax on PET-CT, which is consistent with the findings of Brooks et al., suggesting that LUSC is more dependent on glucose metabolism than LUAD (37). Moreover, while SUVmax was not associated with PFS, higher SUVmax predicted poorer OS, potentially reflecting its role as a surrogate for proliferative activity and tumor aggressiveness. These findings suggest that SUVmax retains prognostic value in NSCLC but may not reliably predict radiosensitivity, further supporting the clinical utility of O-GlcNAc as a biomarker.

Our study has certain limitations, including its relatively small sample size and potential selection bias, which may affect generalizability. Nevertheless, the consistent associations observed between O-GlcNAc expression and clinical outcomes highlight its potential value. Future multicenter studies with larger cohorts are warranted to validate these findings. Moreover, integrating O-GlcNAc evaluation with genomic profiling, proteomic and metabolomic analyses, and advanced molecular imaging may further refine patient selection and enable more precise RT strategies. Mechanistic studies are also required to clarify how O-GlcNAc regulates DNA repair, apoptosis, immune responses, and metabolic reprogramming under radiation exposure, and to identify key glycosylated proteins for precise therapeutic targeting. In summary, our findings identify O-GlcNAc as a promising predictive biomarker for RT response in NSCLC. The incorporation of O-GlcNAc testing into clinical workflows may enhance patient stratification and support individualized treatment planning. Further translational and mechanistic research will be essential to validate and expand upon these results, ultimately contributing to the development of integrated precision oncology strategies.

Conclusions

Our findings indicate that O-GlcNAc expression in tumor tissues is independently associated with RT response. Higher O-GlcNAc levels were associated with improved RT response and longer PFS and OS. In contrast, PET-derived SUVmax and blood glucose levels were not associated with RT response or PFS, but high SUVmax was predictive of shorter OS.

Acknowledgments

We would like to thank the patients and their families for participating in the study. We thank Dr. Juncai Lv, Dr. Xu Liu, and Dr. Weiwei Yan for their guidance on this study.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-998/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-998/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-998/prf

Funding: This work was supported by the foundation of National Natural Science Foundation of China (Nos. 82030082, 82172676, and 82373217); the foundation of Natural Science Foundation of Shandong (Nos. ZR2023ZD26, ZR2024JQ032, and ZR2021YQ52); Collaborative Academic Innovation Project of Shandong Cancer Hospital (GF001), and Noncommunicable Chronic Diseases-National Science and Technology Major Project (Nos. 2024ZD0519900 and 2024ZD0519902).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-998/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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The patients were informed about the objective of the study and provided informed consent. This study was approved by the Ethics Committee of Shandong Cancer Hospital and Institute (ethics approval number: SDTHEC2023003058).

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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