Cuproptosis-related LINC02454 as a biomarker for laryngeal squamous cell carcinoma based on a novel risk model and in vitro and in vivo analyses

Author:

Zhu Qingwen1,Zhang Ruyue2,Lu Fei1,Zhang Xinyu1,Zhang Daidi2,Zhang Yaodong3,Chen Erfang1,Han Fugen3,Zha DingJun1

Affiliation:

1. The Air Force Military Medical University

2. The First Affiliated Hospital of Zhengzhou University

3. Children’s Hospital Affiliated to Zhengzhou University

Abstract

Abstract Purpose Laryngeal squamous cell carcinomas (LSCCs) are aggressive tumors with the second-highest morbidity rate in patients with head and neck squamous cell carcinoma. Cuproptosis is a type of programmed cell death that impacts tumor malignancy and progression. The purpose of this study was to investigate the relationship between cuproptosis-related long non-coding RNAs (crlncRNAs) and the tumor immune microenvironment and chemotherapeutic drug sensitivity in LSCC, and crlncRNA impact on LSCC malignancy. Materials and Methods Clinical and RNA-sequencing data from patients with LSCC were retrieved from The Cancer Genome Atlas. Differentially expressed prognosis-related crlncRNAs were identified based on univariate Cox regression analysis, a crlncRNA signature for LSCC was developed and validated using LASSO Cox regression. Finally, the effect of LINC02454, the core signature crlncRNA, on LSCC malignancy progression was evaluated in vitroand in vivo. Results We identified a four-crlncRNA signature (LINC02454, AC026310.1, AC090517.2, and AC000123.1), according to which we divided the patients into high- and low-risk groups. The crlncRNA signature risk score was an independent prognostic indicator for overall and progression-free survival, and displayed high predictive accuracy. Patients with a higher abundance of infiltrating dendritic cells, M0 macrophages, and neutrophils had worse prognoses and those in the high-risk group were highly sensitive to multiple chemotherapeutic drugs. Knockdown of LINC02454 caused tumor suppression, via cuproptosis induction. Conclusions A novel signature of four crlncRNAs was found to be highly accurate as a risk prediction model for patients with LSCC andto have potential for improving the diagnosis, prognosis, and treatment of LSCC.

Publisher

Research Square Platform LLC

Reference30 articles.

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