Ferroptosis-associated RNA-binding proteins predict clinical outcomes in head and neck squamous cell carcinoma

Introduction

Head and neck cancer (HNC) ranks as the sixth most prevalent malignancy globally, with an estimated annual incidence of 900,000 cases and 500,000 mortality events (1). Head and neck cancer quamous cell carcinoma (HNSCC) accounts for over 90% of all head and neck malignancies (2). The 5-year overall survival (OS) rate remains stagnant at 40–50% even with contemporary therapeutic regimens (3). This poor outcome reflects the asymptomatic nature of early-stage disease and the absence of validated screening biomarkers. Despite aggressive multimodal therapy, over 50% of patients experience disease recurrence or distant metastasis, driving substantial morbidity and mortality. Current diagnostic gold standards rely on histopathological assessment of biopsy specimens, often obtained at advanced stages (4). The Tumor-Node-Metastasis (TNM) staging system—evaluating primary tumor extent (T), lymph node involvement (N), and distant metastasis (M)—remains the cornerstone of prognostic stratification in clinical practice. However, TNM staging fails to account for intertumoral heterogeneity or predict therapeutic responsiveness, highlighting the need for molecular biomarkers (5).

Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation and reactive oxygen species (ROS) accumulation, has emerged as a critical modulator of oncogenesis (6). Unlike apoptosis or autophagy, ferroptosis is mechanistically distinct, involving dysregulated iron metabolism and glutathione peroxidase 4 (GPX4) inactivation. Malignant cells exhibit “iron addiction”, a metabolic dependency on iron to sustain proliferation and evade cell death, rendering ferroptosis a promising therapeutic target (7). Pharmacological induction of ferroptosis has thus garnered attention as a strategy to overcome therapy resistance.

RNA-binding proteins (RBPs) orchestrate post-transcriptional regulation—including RNA splicing, stability, and translation—to maintain cellular homeostasis, yet their role in ferroptosis remains underexplored. Emerging evidence implicates selected RBPs (e.g., ZFP36, ALKBH5) in ferroptosis regulation, but systematic investigations in HNSCC are lacking (8). For instance, ZFP36 (tristetraprolin) modulates ferroptosis in hepatic stellate cells by regulating iron-responsive element (IRE)-containing transcripts (9). Similarly, circular RNA cIARS promotes ferroptosis in hepatocellular carcinoma by sequestering ALKBH5, disrupting autophagic flux (10).

Despite these advances, the prognostic relevance of ferroptosis-associated RBPs—particularly in HNSCC—remains uncharacterized. To address this gap, we integrated multi-omics data from The Cancer Genome Atlas (TCGA) to identify ferroptosis-associated RBPs and construct a prognostic signature for HNSCC. Utilizing TCGA data, we created a new gene signature from differentially expressed ferroptosis-associated RBPs and examined its prognostic value. Additionally, we examined the potential role of immune responses in influencing the outcomes of HNSCC. Our findings unveil a novel ferroptosis-RBP axis in HNSCC pathogenesis and establish a translatable biomarker signature for precision oncology. We present this article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-733/rc).

Methods

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The transcriptomic and clinical data were retrieved from TCGA portal, comprising RNA-Seq profiles (FPKM normalized) of 504 HNSCC tumors and 44 matched adjacent normal tissues. Clinical metadata included age, sex, smoking history, HPV-16/18 status, alcohol use, tumor grade, TNM stage (AJCC 8th edition), and survival endpoints. Inclusion criteria required complete clinical and transcriptomic data. Patients with non-HNSCC-related mortality were excluded to minimize confounding. OS was defined as the interval from diagnosis to death from any cause or last follow-up (censored data). RBP genes were annotated using the Eukaryotic RNA-Binding Protein Database (EuRBPDB) (11).

Statistical analysis

The EdgeR package in R (Version 4.2.1) normalized RNA-Seq data and identified differentially expressed ferroptosis-associated genes (DE-FRGs) in HNSCC samples versus adjacent normal tissues, using a false discovery rate (FDR) threshold of <0.05.

To investigate the relationship between DE-FRGs and patient prognosis, a univariate Cox regression analysis was performed utilizing the survival package in R. Genes exhibiting a P value less than 0.05 were deemed statistically significant. Among these, genes with a hazard ratio (HR) greater than 1 were categorized as high-risk immune-related genes (IRGs), whereas the remaining genes were classified as low-risk. Additionally, Pearson correlation analysis was employed to evaluate the association between DE-FRGs and RBPs, applying a correlation coefficient threshold exceeding 0.6 and a P value less than 0.001, as determined by the cor.test function in R.

Patients in the TCGA cohort were categorized into high-risk and low-risk groups using median risk scores from the ferroptosis-associated gene signature. Kaplan-Meier analysis evaluated OS, while risk curves and scatter plots were created with the “pheatmap” R package. Principal component analysis (PCA) was used to visualize sample distribution. Time-dependent receiver operating characteristic (ROC) curves were generated using the “timeROC” R package to calculate area under the curve (AUC) values for 1-, 3-, and 5-year survival, assessing the model’s predictive performance. Univariate and multivariate Cox regression analyses evaluated the model’s risk score as an independent survival predictor, considering clinical factors like age, gender, grade, and TNM stage.

Ferroptosis-associated RBP genes underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis via the “clusterProfiler” R package, with P values adjusted using the Benjamini-Hochberg method. Additionally, Gene Set Enrichment Analysis (GSEA) was conducted to examine RBP signatures in the TCGA-HNSCC database.

Mutation profiles of the immune-related signature across all HNSCC samples were obtained through cBioPortal (http://www.cbioportal.org/). GSEA was utilized to identify pathways enriched in high-risk groups, applying a significance threshold of |FDR| <0.25 and a nominal P value <0.05. To explore the correlations between immune status and the ferroptosis-associated RBP gene signature, single-sample GSEA (ssGSEA) was employed to analyze immune cell infiltration patterns and to calculate enrichment scores for 16 immune cell types and 13 immune-related functions.

All statistical analyses were performed in R (v4.2.1), with data management assisted by Microsoft Excel (v16.38). Statistical significance was defined as two-tailed P<0.05 unless specified.

Results

Thirty-five ferroptosis-associated genes (FRGs) were identified as differentially expressed between HNSCC tumors and adjacent normal tissues (FDR <0.05, |log₂FC| >1). These DE-FRGs were defined by stringent thresholds: Benjamini-Hochberg adjusted FDR <0.05 and |log₂ fold-change| >1. Among 495 candidate FRGs, 15 ferroptosis-associated RBPs emerged as independent prognostic markers via univariate Cox regression (P<0.01). These RBPs included ribosomal proteins (RPL31, RPL27, RPL30, RPL12, RPL39), translation initiation factors (EIF3E, EIF3H), and redox regulators (NQO1, TXNRD1), as shown in Figure 1. Utilizing these findings, we subsequently calculated risk scores and formulated a prognostic signature specifically tailored to the identified ferroptosis-associated ribosomal protein genes (RPGs).

Figure 1 Univariate Cox analysis of ferroptosis-associated RBPs in HNSCC. Fifteen ferroptosis-associated RBPs were significantly associated with overall survival in HNSCC patients (P<0.01). All RBPs showed hazard ratios >1.0, indicating that higher expression of these genes is associated with worse prognosis in HNSCC patients. CI, confidence interval; HNSCC, head and neck squamous cell carcinoma; RBP, RNA-binding protein.

Functional annotation of ferroptosis-associated RBPs

To systematically characterize the biological roles of ferroptosis-linked RBPs, we conducted comprehensive enrichment analyses using GO and KEGG databases. The top 10 significantly enriched GO terms and KEGG pathways (FDR <0.05) are depicted in Figure 2. Functional annotation revealed three principal GO categories: (I) biological processes (BP), notably cellular oxidant detoxification; (II) molecular functions (MF), including iron ion binding; and (III) cellular components (CC), such as mitochondrial matrix. KEGG pathway analysis highlighted eight pathways, including arachidonic acid metabolism, chemical carcinogenesis-ROS, and ferroptosis, with direct relevance to lipid peroxidation regulation and HNSCC progression.

Figure 2 (A) GO and (B) KEGG analyses of differentially expressed genes related to ferroptosis. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.

Prognostic signature of ferroptosis-associated RBPs in HNSCC

Kaplan-Meier analysis demonstrated significantly reduced OS in high-risk patients stratified by the ferroptosis-RBP signature (log-rank P<0.001; Figure 3A). The RPG signature’s prognostic AUC was 0.688, outperforming traditional clinical features (Figure 3B). The risk survival status plot showed that higher risk scores are linked to lower survival rates in HNSCC patients. Time-dependent ROC analysis revealed increasing predictive accuracy of the RBP signature over time, with AUC values of 0.602 (1-year), 0.688 (3-year), and 0.669 (5-year) (Figure 3C). Heatmap analysis revealed most new RPGs negatively correlated with the risk model, suggesting further study is needed (Figure 3D).

Figure 3 Prognostic performance of ferroptosis-associated RBP signature in HNSCC. (A) Kaplan-Meier survival curves depict the association between high-risk RBPs signatures and overall survival in patients with HNSCC. (B) The AUC values indicate the predictive efficacy of the identified risk factors. (C) AUC values are provided for the prediction of 1-, 3-, and 5-year survival rates in HNSCC patients. (D) The risk survival status plot illustrates the correlation between patients’ risk scores and their survival outcomes. AUC, area under the curve; HNSCC, head and neck squamous cell carcinoma; RBP, RNA-binding protein.

Furthermore, PCA was performed to illustrate the significant differences in risk score distributions between the low-risk and high-risk patient cohorts, as depicted in Figure 4.

Figure 4 PCA of risk gene signatures in HNSCC. (A) Risk RBP genes. (B) Ferroptosis-associated RBP genes. (C) Ferroptosis-associated genes. (D) All genes. HNSCC, head and neck squamous cell carcinoma; PCA, principal component analysis; RBP, RNA-binding protein.

Independent prognostic validation

Univariate Cox regression analysis showed that the risk score (HR =2.205; Figure 5A) and clinical stage (HR =1.419; Figure 5A) were significantly linked to OS in HNSCC patients (P<0.001; Figure 5A). Multivariate Cox regression analysis showed that the ferroptosis-associated RBPs signature is an independent predictor of HNSCC survival (HR =2.144, 95% CI: 1.645–2.718, P<0.001; Figure 5B). We also evaluated the risk models against clinical characteristics to confirm our results.

Figure 5 Cox analysis of ferroptosis-associated RBPs. (A) Univariate analysis shows the link between these genes’ expression and overall survival in HNSCC patients. (B) Multivariate analysis confirms their independent prognostic value. CI, confidence interval; HNSCC, head and neck squamous cell carcinoma; RBP, RNA-binding protein.

Immune landscape and ferroptosis-RBP interactions

Distinct immune infiltration profiles were observed between low- and high-risk subgroups, reflecting differential remodeling of the tumor microenvironment (TME). As illustrated in Figure 6A,6B, a diverse array of immune cell types—including B cells, mast cells, plasmacytoid dendritic cells (pDCs), T follicular helper cells (Tfh), Th1 cells, Th2 cells, tumor-infiltrating lymphocytes (TILs), regulatory T cells (Tregs), T cell co-inhibition responses, chemokine receptors (CCRs), and human leukocyte antigen (HLA) molecules involved in antigen presentation—were observed to be more actively expressed in low-risk samples, with statistical significance (P<0.001).

Figure 6 Boxplots of immune-related cell scores and functions. (A) Boxplots representing the scores of various immune-related cell types across distinct risk groups. (B) Boxplots of immune-related function scores in the context of risk stratification. *, P<0.05; **, P<0.01; ***, P<0.001; ns, not significant.

In contrast, immune effector cells, including CD8⁺ T cells, natural killer (NK) cells, and TILs, exhibited diminished expression levels in the high-risk cohort. Furthermore, the scores for T helper cells, Th2 cells, and Treg demonstrated analogous patterns of downregulation. These observations imply that an elevated ferroptosis-associated RBPs risk score may be associated with an immunosuppressive state within the TME.

GSEA

GSEA identified that the new ferroptosis-associated RBPs signature significantly influences immune pathways, especially the T/B cell receptor signaling pathway, which is vital for immune cell activation and tumor response (Figure 7).

Figure 7 GSEA enrichment of immune pathways mediated by ferroptosis-associated RBP signature. GSEA, Gene Set Enrichment Analysis; RBP, RNA-binding protein.

This pathway’s enrichment indicates that ferroptosis-associated RBPs may affect the TME by altering immune cell interactions, suggesting their role in immune evasion in HNSCC. These findings highlight the significance of studying the relationship between ferroptosis and immune responses for cancer prognosis and treatment.

Discussion

HNSCC is a growing global health issue, with a 5-year survival rate of under 50% (12). This bleak outlook is mainly due to the lack of reliable biomarkers and increasing tumor resistance to standard treatments (13). A recent study has underscored the significance of molecular markers, particularly those related to autophagy, immune response, and long noncoding RNAs (lncRNAs), in forecasting clinical outcomes in HNSCC (14). Emerging evidence highlights ferroptosis, an iron-dependent regulated cell death, as crucial in cancer development and treatment response (15). The incorporation of prognostic models developed from next-generation sequencing (NGS) data, in conjunction with publicly available databases, is advancing our comprehension of the clinical-genetic landscape. This integration is consequently establishing ferroptosis as a central focus of research for predicting OS across diverse malignancies (16).

This study investigated ferroptosis-associated genes and RBPs in HNSCC progression. Analysis of TCGA data identified differentially expressed genes between tumor and normal tissues. Univariate Cox regression (P<0.01) revealed 15 ferroptosis-associated RBPs significantly linked to prognosis.

Ribosome dysregulation is a hallmark of HNSCC, characterized by rRNA gene downregulation and promoter hypermethylation (17). RPL22 regulates the CDK4-cyclin D complex, impacting cell cycle and chemotherapy response (18). In laryngeal squamous cell carcinoma, overexpression of RPS10, RPL24, and RPS26 correlates with lymph node metastasis. Inhibition of ribosome synthesis by CX-5461 reduces expression of these proteins and suppresses LSCC cell invasion and migration (19).

EIF3E and EIF3H, eIF3 complex subunits crucial for translation initiation, exhibit aberrant expression across cancers. EIF3H promotes tumorigenesis; its upregulation in gastric cancer promotes proliferation and induces apoptosis (20), while downregulation in osteosarcoma suppresses proliferation and tumor growth (21).

Redox regulators NQO1 and TXNRD1 are pivotal in HNSCC (22). NQO1 enhances radiosensitivity by inducing programmed necrosis via ROS release and regulates G2/M phase progression (23). TXNRD1 overexpression correlates with poor anti-PD-1 immunotherapy response. Its inhibition promotes ferroptosis and improves anti-PD-1 efficacy. TXNRD1 also modulates PD-L1 transcription and redox balance to facilitate immune evasion (24). Collectively, NQO1 influences proliferation and radiosensitivity through redox activity and cell cycle control, while TXNRD1 modulates immunotherapy response via immune evasion and redox mechanisms (24). providing a foundation for targeted therapies.

We developed a prognostic model using identified RBPs and performed pathway enrichment analysis. The enrichment map from KEGG and GO analyses showed the links between enriched pathways. Our prognostic signature, based on TCGA data, revealed that high-risk patients had notably shorter survival times.

The 5-year survival AUC of the ROC curve was 0.669, indicating strong sensitivity and specificity of our prognostic model. We also explored the link between the ferroptosis-associated RBP signature and immune profiles in HNSCC using PCA and gene set enrichment analyses.

Research indicates that RBPs play a crucial role in regulating ferroptosis, thereby influencing immune responses. For instance, RBM24 modulates iron death and inflammatory responses by affecting the stability of SLC7A11 mRNA, demonstrating that RBPs hold significant roles in both cell death and immune regulation (25). Recent literature has identified SLC7A11 as a crucial biomarker in both the diagnosis and prognosis of HNSCC (26), with particular associations noted with human papillomavirus (HPV) (27).

In the tumor immune microenvironment, the expression of ferroptosis-related genes is closely associated with immune cell infiltration. For instance, a study has shown that elevated expression of transferrin receptor 1 (TFRC) correlates with poor prognosis and abnormal immune cell infiltration in cervical cancer patients, further highlighting the potential role of ferroptosis in tumor immune regulation (28). Additionally, DAZAP1, as an RBP, regulates ferroptosis processes in hepatocellular carcinoma by interacting with SLC7A11 mRNA, revealing the critical role of RBPs in tumor progression and immune responses (29).

In gliomas, ferroptosis-associated lncRNAs have been shown to correlate with immune landscape and radiotherapy response. A prognostic model of ferroptosis-related lncRNAs was established in the study, revealing that high-risk patients exhibited higher levels of immunosuppressive cell infiltration and increased immune checkpoint expression. This indicates that ferroptosis-associated lncRNAs play a significant regulatory role in the tumor’s immune microenvironment (30).

Furthermore, a correlation has been identified between ferroptosis and the response to immune checkpoint inhibitors. In HNCs, the positive correlation between ferroptosis characteristics and immune activity suggests that ferroptosis-inducing agents could enhance the antitumor efficacy of immune checkpoint inhibitors (31). This discovery provides new insights into the application of ferroptosis in tumor immunotherapy.

Our research, based on transcriptome profiling and clinical data from 504 HNSCC cases in TCGA, reveals new insights into the role of ferroptosis-associated RNA binding proteins in HNSCC prognosis, paving the way for future studies on tumor progression mechanisms.

Research on the molecular regulatory mechanisms of ferroptosis and its therapeutic implications is on the cusp of substantial advancements. Future investigations will seek to further elucidate the complex regulatory frameworks that govern ferroptosis in tumor cells, incorporating insights from metabolism, epigenetics, gene mutations, and tumor immunity. The application of high-throughput technologies, such as single-cell sequencing, will facilitate the development of novel strategies for the treatment of HNSCC.

In summary, this study highlights the prognostic importance of certain ferroptosis-associated RBPs in HNSCC, which may inform future therapeutic approaches. Nonetheless, it is crucial to recognize that the identified gene signature profiles require validation in diverse patient populations. The absence of clinical sample validation in our research calls into question the robustness of our conclusions. Furthermore, the constraints of the available clinical data warrant a cautious interpretation of our findings.

Conclusions

This study identifies specific RBP genes associated with ferroptosis as prognostic indicators for HNSCC, thereby providing valuable insights for the development of targeted therapeutic interventions.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-733/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-733/prf

Funding: This work was supported by the Shandong Provincial Natural Science Foundation (No. ZR2022QH360).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-733/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 was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

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/.

References

1. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394-424. [Crossref] [PubMed]
2. Xu L, Li YY, Zhang YC, et al. A Novel Ferroptosis-Related Gene Signature to Predict Prognosis in Patients with Head and Neck Squamous Cell Carcinoma. Dis Markers 2021;2021:5759927. [Crossref] [PubMed]
3. Kumpitsch C, Moissl-Eichinger C, Pock J, et al. Preliminary insights into the impact of primary radiochemotherapy on the salivary microbiome in head and neck squamous cell carcinoma. Sci Rep 2020;10:16582. [Crossref] [PubMed]
4. Johnson DE, Burtness B, Leemans CR, et al. Head and neck squamous cell carcinoma. Nat Rev Dis Primers 2020;6:92. [Crossref] [PubMed]
5. Fang R, Iqbal M, Chen L, et al. A novel comprehensive immune-related gene signature as a promising survival predictor for the patients with head and neck squamous cell carcinoma. Aging (Albany NY) 2021;13:11507-27. [Crossref] [PubMed]
6. Huang L, McClatchy DB, Maher P, et al. Intracellular amyloid toxicity induces oxytosis/ferroptosis regulated cell death. Cell Death Dis 2020;11:828. [Crossref] [PubMed]
7. Manz DH, Blanchette NL, Paul BT, et al. Iron and cancer: recent insights. Ann N Y Acad Sci 2016;1368:149-61. [Crossref] [PubMed]
8. Qin H, Ni H, Liu Y, et al. RNA-binding proteins in tumor progression. J Hematol Oncol 2020;13:90. [Crossref] [PubMed]
9. Zhang Z, Guo M, Li Y, et al. RNA-binding protein ZFP36/TTP protects against ferroptosis by regulating autophagy signaling pathway in hepatic stellate cells. Autophagy 2020;16:1482-505. [Crossref] [PubMed]
10. Liu Z, Wang Q, Wang X, et al. Circular RNA cIARS regulates ferroptosis in HCC cells through interacting with RNA binding protein ALKBH5. Cell Death Discov 2020;6:72. [Crossref] [PubMed]
11. Liao JY, Yang B, Zhang YC, et al. EuRBPDB: a comprehensive resource for annotation, functional and oncological investigation of eukaryotic RNA binding proteins (RBPs). Nucleic Acids Res 2020;48:D307-13. [Crossref] [PubMed]
12. Leemans CR, Braakhuis BJ, Brakenhoff RH. The molecular biology of head and neck cancer. Nat Rev Cancer 2011;11:9-22. [Crossref] [PubMed]
13. Chow LQM. Head and Neck Cancer. N Engl J Med 2020;382:60-72. [Crossref] [PubMed]
14. Chen Y, Luo TQ, Xu SS, et al. An immune-related seven-lncRNA signature for head and neck squamous cell carcinoma. Cancer Med 2021;10:2268-85. [Crossref] [PubMed]
15. Li J, Cao F, Yin HL, et al. Ferroptosis: past, present and future. Cell Death Dis 2020;11:88. [Crossref] [PubMed]
16. Lin R, Fogarty CE, Ma B, et al. Identification of ferroptosis genes in immune infiltration and prognosis in thyroid papillary carcinoma using network analysis. BMC Genomics 2021;22:576. [Crossref] [PubMed]
17. Priyadarshini N, Venkatarama Puppala N, Jayaprakash JP, et al. Downregulation of ribosomal RNA (rRNA) genes in human head and neck squamous cell carcinoma (HNSCC) cells correlates with rDNA promoter hypermethylation. Gene 2023;888:147793. [Crossref] [PubMed]
18. Del Toro N, Fernandez-Ruiz A, Mignacca L, et al. Ribosomal protein RPL22/eL22 regulates the cell cycle by acting as an inhibitor of the CDK4-cyclin D complex. Cell Cycle 2019;18:759-70. [Crossref] [PubMed]
19. Gao M, Liu T, Hu K, et al. Ribosomal Dysregulation in Metastatic Laryngeal Squamous Cell Carcinoma: Proteomic Insights and CX-5461's Therapeutic Promise. Toxics 2024;12:363. [Crossref] [PubMed]
20. Wang X, Wang H, Zhao S, et al. Eukaryotic translation initiation factor EIF3H potentiates gastric carcinoma cell proliferation. Tissue Cell 2018;53:23-9. [Crossref] [PubMed]
21. Hong S, Liu Y, Xiong H, et al. Eukaryotic translation initiation factor 3H suppression inhibits osteocarcinoma cell growth and tumorigenesis. Exp Ther Med 2018;15:4925-31. [Crossref] [PubMed]
22. Chen J, Zhang S, Zhang S, et al. Mesoporous Silica Nanoparticle-Based Combination of NQO1 Inhibitor and 5-Fluorouracil for Potent Antitumor Effect Against Head and Neck Squamous Cell Carcinoma (HNSCC). Nanoscale Res Lett 2019;14:387. [Crossref] [PubMed]
23. Oh ET, Kim HG, Kim CH, et al. NQO1 regulates cell cycle progression at the G2/M phase. Theranostics 2023;13:873-95. [Crossref] [PubMed]
24. Hsieh MS, Ling HH, Setiawan SA, et al. Therapeutic targeting of thioredoxin reductase 1 causes ferroptosis while potentiating anti-PD-1 efficacy in head and neck cancer. Chem Biol Interact 2024;395:111004. [Crossref] [PubMed]
25. Zhang J, Kong X, Sun W, et al. The RNA-binding protein RBM24 regulates lipid metabolism and SLC7A11 mRNA stability to modulate ferroptosis and inflammatory response. Front Cell Dev Biol 2022;10:1008576. [Crossref] [PubMed]
26. Jiang Y, Sun M. SLC7A11: the Achilles heel of tumor? Front Immunol 2024;15:1438807. [Crossref] [PubMed]
27. Hémon A, Louandre C, Lailler C, et al. SLC7A11 as a biomarker and therapeutic target in HPV-positive head and neck Squamous Cell Carcinoma. Biochem Biophys Res Commun 2020;533:1083-7. [Crossref] [PubMed]
28. Shang X, Wang H, Gu J, et al. Ferroptosis-related gene transferrin receptor protein 1 expression correlates with the prognosis and tumor immune microenvironment in cervical cancer. PeerJ 2024;12:e17842. [Crossref] [PubMed]
29. Wang Q, Guo Y, Wang W, et al. RNA binding protein DAZAP1 promotes HCC progression and regulates ferroptosis by interacting with SLC7A11 mRNA. Exp Cell Res 2021;399:112453. [Crossref] [PubMed]
30. Zheng J, Zhou Z, Qiu Y, et al. A Prognostic Ferroptosis-Related lncRNAs Signature Associated With Immune Landscape and Radiotherapy Response in Glioma. Front Cell Dev Biol 2021;9:675555. [Crossref] [PubMed]
31. Chung CH, Lin CY, Chen CY, et al. Ferroptosis Signature Shapes the Immune Profiles to Enhance the Response to Immune Checkpoint Inhibitors in Head and Neck Cancer. Adv Sci (Weinh) 2023;10:e2204514. [Crossref] [PubMed]