基于失巢凋亡相关长非编码 RNA 的新型风险模型预测头颈部鳞状细胞癌的预后、免疫反应和免疫治疗。

Predicting the prognosis, immune response, and immunotherapy in head and neck squamous cell carcinoma using a novel risk model based on anoikis-related lncRNAs.

机构信息

Department of Otolaryngology-Head and Neck Surgery, Ningbo Medical Center Lihuili Hospital, Ningbo University, NingboZhejiang, 315040, China.

Health Science Center, Ningbo University, Ningbo, 315211, Zhejiang, China.

出版信息

Eur J Med Res. 2023 Nov 28;28(1):548. doi: 10.1186/s40001-023-01521-9.

DOI:10.1186/s40001-023-01521-9

PMID:38017579

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10683111/

Abstract

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is an extremely heterogeneous and metastatic disease. Anoikis, which is a specific type of programmed apoptosis, is involved in tumor metastasis, tissue homeostasis, and development. Herein, we constructed an anoikis-related long non-coding RNA (lncRNA) signature to predict the prognosis, immune responses, and therapeutic effects in HNSCC patients.

METHODS

A total of 501 HNSCC samples were acquired from the TCGA database and randomly classified into the training and validation groups (1:1 ratio). Thereafter, the results derived from the training set were analyzed with the LASSO regression analysis, and a novel anoikis-related lncRNA risk model was constructed. Time-dependent ROC curves and Kaplan-Meier analysis were carried out to assess the diagnostic value and survival outcomes. A nomogram was utilized to predict the prognostic accuracy. Furthermore, we studied the tumor microenvironment, tumor mutation burden, enrichment pathways, and the response to chemotherapy and immunotherapy.

RESULTS

Seven anoikis-related lncRNAs (AC015878.1, CYTOR, EMSLR, LINC01503, LINC02084, RAB11B-AS1, Z97200.1) were screened to design a novel risk model, which was recognized as the independent prognostic factor for HNSCC patients. The findings implied that low-risk patients showed significantly longer OS, PFS, and DSS compared to those high-risk patients. The two groups that were classified using the risk model showed significant differences in their immune landscape. The risk model also predicted that low-risk HNSCC patients could attain a better response to immunotherapy, while high-risk patients would be more sensitive to gemcitabine, docetaxel, and cisplatin.

CONCLUSIONS

We constructed a novel risk model that could be employed for effectively predicting patient prognosis with a good independent prognostic value for HNSCC patients. Furthermore, this model could be used for designing new immunotherapeutic and chemotherapeutic strategies, and it helps clinicians establish personalized and detailed strategies for HNSCC patients.

摘要

背景

头颈部鳞状细胞癌（HNSCC）是一种极具异质性和转移性的疾病。细胞凋亡是一种特定类型的程序性细胞死亡，它参与肿瘤转移、组织内稳态和发育。在此，我们构建了一个与细胞凋亡相关的长非编码 RNA（lncRNA）特征，以预测 HNSCC 患者的预后、免疫反应和治疗效果。

方法

从 TCGA 数据库中获取了 501 例 HNSCC 样本，并将其随机分为训练组和验证组（1:1 比例）。然后，利用 LASSO 回归分析对训练集的结果进行分析，构建了一个新的与细胞凋亡相关的 lncRNA 风险模型。采用时间依赖性 ROC 曲线和 Kaplan-Meier 分析评估诊断价值和生存结局。使用列线图预测预后准确性。此外，我们还研究了肿瘤微环境、肿瘤突变负荷、富集途径以及对化疗和免疫治疗的反应。

结果

筛选出 7 个与细胞凋亡相关的 lncRNA（AC015878.1、CYTOR、EMSLR、LINC01503、LINC02084、RAB11B-AS1、Z97200.1）用于设计一个新的风险模型，该模型被认为是 HNSCC 患者的独立预后因素。结果表明，低风险患者的总生存期（OS）、无进展生存期（PFS）和疾病特异性生存期（DSS）明显长于高风险患者。使用风险模型分类的两组患者在免疫景观方面存在显著差异。该模型还预测低风险 HNSCC 患者对免疫治疗的反应更好，而高风险患者对吉西他滨、多西他赛和顺铂更敏感。