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

Congxiao Wu; Fei Liu; Haixu Chen; Qin Liu; Chao Song; Kang Cheng; Zhiyong Gao; Cheng Fan

doi:10.1155/2022/7602482

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

J Oncol. 2022 Jul 20:2022:7602482. doi: 10.1155/2022/7602482. eCollection 2022.

Authors

Congxiao Wu¹, Fei Liu², Haixu Chen³, Qin Liu⁴, Chao Song², Kang Cheng², Zhiyong Gao⁵, Cheng Fan⁴

Affiliations

¹ Department of Plastic Surgery, Shenzhen Qianhai Taikang Hospital, Shenzhen 518000, Guangdong, China.
² Department of Orthopedics, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China.
³ Department of Basic Medicine, Sichuan Vocational College of Health and Rehabilitation, Zigong 643000, Sichuan, China.
⁴ Department of Neurosurgery, Anyue County People's Hospital, Ziyang 641300, Sichuan, China.
⁵ Department of Burn and Plastic Surgery, The First People's Hospital of Ziyang, Ziyang 641300, Sichuan, China.

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.