Identification of disulfidptosis-related lncRNA signature using RNA-Sequencing and Bioinformatics Analysis in Head and Neck Squamous Cell Carcinoma

Qi Chen,Xiao Shi, Yuanyuan Bao, Yue Chen

crossref(2024)

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摘要
Abstract As a novel form of regulated cell death, disulfidptosis generating a favorable opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells with combination of variable targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in head and neck squamous cell carcinoma (HNSC) remains largely unknown. Hence, we aimed to delve into the molecular characteristics of HNSC, focusing on disulfidptosis-related long non-coding RNAs (DRLs), and explore potential therapeutic strategies. We conducted lncRNA-mRNA RNA-Seq analyses on HNSC cell lines and utilized The Cancer Genome Atlas (TCGA) database, comprising RNA sequencing, clinical data, and gene mutation information from 522 HNSC tumors and 44 normal tissues. Bioinformatics analyses were employed to identify DRLs associated with disulfidptosis and assess their prognostic significance. Additionally, a risk model based on three selected DRLs was constructed to investigate its correlation with patient outcomes. Tumor mutation burden and chemotherapeutic responses were also explored in relation to the risk model. Our analysis pinpointed three DRLs (LINC02434, AC245041.2, and LINC02762) significantly correlated with HNSC prognosis. qRT-PCR results validated the consistency of LINC02434 and AC245041.2. The risk model, based on these DRLs, effectively stratified patients into high- and low-risk groups, revealing distinct survival patterns. Furthermore, the risk model demonstrated independent prognostic value in HNSC. Examination of the tumor microenvironment highlighted differences between high- and low-risk groups, suggesting potential implications for immunotherapeutic approaches. Specific chemotherapeutic agents with varying sensitivities across risk groups and molecular subtypes were identified. The identified three DRLs signature emerges as a novel biomarker with predictive value for HNSC prognosis. This study provides insights into potential therapeutic avenues and contributes to our understanding of the molecular landscape of HNSC.
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