Dataset Information

Identification of Ferroptosis-Related lncRNA Pairs for Predicting the Prognosis of Head and Neck Squamous Cell Carcinoma

ABSTRACT:

Background

Ferrogenesis was strongly associated with tumorigenesis and development, and activating the ferrogenic process was a novel regimen in treating cancer, especially conventional treatment-resistant cancers. The purpose of the article was to construct a ferroptosis-related long noncoding RNAs (FRlncRNAs) signature, regardless of expression levels to effectively predict prognosis and immunotherapeutic response for head and neck squamous cell carcinoma (HNSCC).

Methods

The RNA-seq data for HNSCC and corresponding clinical information were obtained in the TCGA database, and ferroptosis-related genes (FRGs) were extracted in the ferroptosis database. On this basis, differentially expressed FRlncRNAs (DEFRlncRNAs) pairs were identified through coexpression analysis, differential expression analysis, and a fresh pairing algorithm. Then, a risk assessment model was established with univariate Cox, LASSO, and multivariate Cox regression analysis. Finally, we evaluated the model from various aspects, including survival status, clinicopathological characteristics, infiltration status of immune cells, immune functions, chemotherapeutic sensitivity, immune checkpoint inhibitors (ICIs)-related molecules, and N6-methyladenosine (m6A) mRNA status.

Result

We established a signature of 11-DEFRlncRNA pairs related to the prognosis of HNSCC that had AUC values above 0.75 in the one-, three-, and five-year ROC curves, underscoring the high susceptibility and specifiability of predicting HNSCC prognosis. Survival rates were remarkably higher for the low-risk patients than for the high-risk patients, and the signature was significantly correlated with survival, clinical, T, and N stages. Finally, immune cell infiltration status, immune functions, chemotherapeutic sensitivity, and expression levels of ICIs-related and m6A-related molecules were statistically different among different groups.

Conclusion

Our study established a novel lncRNA signature, which is independent of specific expression levels, could predict patient prognosis, and might have promising clinical applications in HNCSS.

SUBMITTER: Wu C

PROVIDER: S-EPMC9328971 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeImmunotherapy is changing head and neck squamous cell carcinoma (HNSCC) treatment pattern. According to the Chinese Society of Clinical Oncology (CSCO) guidelines, immunotherapy has been deemed as first-line recommendation for recurrent/metastatic HNSCC, marking that advanced HNSCC has officially entered the era of immunotherapy. Long non-coding RNAs (lncRNAs) impact every step of cancer immunity. Therefore, reliable immune-lncRNAs able to accurately predict the immune landscape and survival of HNSCC are crucial to clinical management.MethodsIn the current study, we downloaded the transcriptomic and clinical data of HNSCC from The Cancer Genome Atlas and identified differentially expressed immune-related lncRNAs (DEir-lncRNAs). Further then, Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify proper DEir-lncRNAs to construct optimal risk model. Low-risk and high-risk groups were classified based on the optimal cut-off value generated by the areas under curve for receiver operating characteristic curves (AUC), and Kaplan-Meier survival curves were utilized to validate the prediction model. We then evaluated the model based on the clinical factors, immune cell infiltration, and chemotherapeutic and immunotherapeutic efficacy between two groups.ResultsIn our study, we identified 256 Deir-lncRNAs in HNSCC. A total of 18 Deir-lncRNA pairs (consisting of 35 Deir-lncRNAs) were used to construct a risk model significantly associated with survival of HNSCC. Cox proportional hazard regression analysis confirmed that our risk model could be served as an independent prognostic indicator. Besides, HNSCC patients with low-risk score significantly enriched of CD8+ T cell, and corelated with high chemosensitivity and immunotherapeutic sensitivity.ConclusionOur risk model could be served as a promising clinical prediction indicator, effective discoursing of the immune cell infiltration of HNSCC patients, and distinguishing patients who could benefit from chemotherapy and immunotherapy.

Project description:Squamous cell carcinoma of the head and neck (HNSCC) is one of the six most common malignancies. HNSCC has both a high incidence and poor prognosis, and its prognostic factors remain unclear. Ferroptosis is a newly discovered form of programmed cell death that is iron-dependent. Increasing evidence indicates that targeting ferroptosis may present a new form of anti-tumor treatment. However, the prognostic value of ferroptosis-related genes (FRGs) in HNSCC is unclear. This study was designed to identify molecular markers associated with ferroptosis that influence prognosis in patients with HNSCC. We used HNSCC tumor and normal data from The Cancer Genome Atlas (TCGA) to identify prognosis-related FRGs. An FRG-based prognostic risk score was constructed, and its prognostic value for patients with HNSCC was evaluated using receiver operating characteristic curve (ROC) and nomogram analyses. The model was validated using the Gene Expression Omnibus (GEO) database. Univariate Cox regression analysis in patients with HNSCC revealed 11 FRGs that were significantly associated with overall survival (OS). We constructed a ferroptosis risk score model based on five genes and divided the patients into different risk groups based on its median value. Kaplan-Meier curve analysis showed that patients with a higher ferroptosis risk score had shorter OS (TCGA training set: P < 0.001, TCGA validation set: P < 0.05,GEO validation set: P < 0.001), and Gene Expression Profiling Interactive Analysis (GEPIA) further verified the relationships between these five genes and prognosis in patients with HNSCC. Multivariate Cox regression analysis showed that the risk score remained an independent predictor of OS after the exclusion of clinical confounders (HR > 1, P < 0.01). Significant differences in gene function enrichment analysis and immune cell infiltration status were identified between the two groups. The prognostic model can be used to predict the prognosis of patients with HNSCC. Moreover, the five FRGs may affect ferroptosis in HNSCC and thereby represent potential treatment targets. These results provide new directions for HNSCC treatment.