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生物信息学分析揭示了其在头颈部鳞状细胞癌中的预后意义及其与免疫细胞浸润的关联。

Bioinformatics analysis reveals 's prognostic significance in head and neck squamous cell carcinoma and its association with immune cell infiltration.

作者信息

Tang Yulian, Hu Ting, Yin Wenli, Huang Changqiao, Liu Dewen, Lai Fengming, Yang Chengliang, Tang Lizhu

机构信息

Modern Industrial College of Biomedicine and Great Health, Youjiang Medical University for Nationalities, Baise, China.

School of Laboratory Medicine, Youjiang Medical University for Nationalities, Baise, China.

出版信息

Transl Cancer Res. 2024 Nov 30;13(11):5953-5970. doi: 10.21037/tcr-24-834. Epub 2024 Nov 27.

DOI:10.21037/tcr-24-834
PMID:39697755
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11651743/
Abstract

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) has a poor prognosis due to late diagnosis and complex molecular mechanisms. Vascular endothelial growth factor C (VEGFC) is associated with angiogenesis and lymphangiogenesis. This study aimed to investigate 's prognostic value in HNSCC and its correlation with immune cell infiltration.

METHODS

gene expression was analyzed in HNSCC patients using Tumor Immune Estimation Resource 2.0 (TIMER2.0), Gene Expression Profiling Interactive Analysis (GEPIA), and University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) databases, focusing on differential expression and clinical-pathological correlations. The impact of on overall survival (OS) and disease-free survival (DFS) was assessed using GEPIA. RNA-seq profiles and clinical information from 503 HNSCC tumor tissues and 44 normal control tissues obtained from The Cancer Genome Atlas (TCGA) database were subjected to univariate and multivariate Cox regression analyses to develop a prognostic nomogram. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used for a protein-protein interaction (PPI) network, while the Tumor-Immune System Interaction Database (TISIDB) for immune-related associations. Expression was further validated with the Gene Expression Omnibus dataset (GSE6631) and reverse transcription quantitative polymerase chain reaction (RT-qPCR).

RESULTS

was significantly upregulated in HNSCC and closely correlated with age, gender, race, and tumor stage (P<0.05). PPI and co-expression gene analysis identified ITGA3, NT5E, and PXN as highly associated with VEGFC (R>0.6, P<0.05), which are mainly enriched in PI3K/Akt, MAPK signaling pathway, and cancer-associated glycoproteins. High expression predicted poor OS (P=0.003) and DFS (P=0.03). Univariate and multivariate Cox regression analyses confirmed as an independent prognostic factor for HNSCC. The prognostic nomogram accurately predicted 1-, 3-, and 5-year survival and calibration curve was very close to ideal 45-degree diagonal line. also correlated with immune cells infiltration, including B cells, CD4 T cells, CD8 T cells, as well as immune-related markers such as tumor-infiltrating lymphocytes (TILs) markers, immune modulators, and inflammatory chemokines (P<0.05).

CONCLUSIONS

may serve as an independent prognostic factor and potential immunotherapeutic target in HNSCC, offering insights into patient risk stratification and personalized treatment strategies.

摘要

背景

头颈部鳞状细胞癌(HNSCC)由于诊断较晚和分子机制复杂,预后较差。血管内皮生长因子C(VEGFC)与血管生成和淋巴管生成相关。本研究旨在探讨其在HNSCC中的预后价值及其与免疫细胞浸润的相关性。

方法

使用肿瘤免疫评估资源2.0(TIMER2.0)、基因表达谱交互分析(GEPIA)和阿拉巴马大学伯明翰分校癌症数据分析门户(UALCAN)数据库分析HNSCC患者的基因表达,重点关注差异表达和临床病理相关性。使用GEPIA评估其对总生存期(OS)和无病生存期(DFS)的影响。对从癌症基因组图谱(TCGA)数据库获得的503个HNSCC肿瘤组织和44个正常对照组织的RNA测序谱和临床信息进行单因素和多因素Cox回归分析,以建立预后列线图。使用检索相互作用基因/蛋白质的搜索工具(STRING)数据库构建蛋白质-蛋白质相互作用(PPI)网络,而使用肿瘤-免疫系统相互作用数据库(TISIDB)分析免疫相关关联。通过基因表达综合数据集(GSE6631)和逆转录定量聚合酶链反应(RT-qPCR)进一步验证表达情况。

结果

在HNSCC中显著上调,且与年龄、性别、种族和肿瘤分期密切相关(P<0.05)。PPI和共表达基因分析确定ITGA3、NT5E和PXN与VEGFC高度相关(R>0.6,P<0.05),它们主要富集于PI3K/Akt、MAPK信号通路和癌症相关糖蛋白。高表达预示着较差的OS(P=0.003)和DFS(P=0.03)。单因素和多因素Cox回归分析证实是HNSCC的独立预后因素。预后列线图准确预测了1年、3年和5年生存率,校准曲线非常接近理想的45度对角线。还与免疫细胞浸润相关,包括B细胞、CD4 T细胞、CD8 T细胞,以及免疫相关标志物,如肿瘤浸润淋巴细胞(TILs)标志物、免疫调节剂和炎性趋化因子(P<0.05)。

结论

在HNSCC中可能作为独立的预后因素和潜在的免疫治疗靶点,为患者风险分层和个性化治疗策略提供见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/efdcfaf31965/tcr-13-11-5953-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/3c39c1bb9f22/tcr-13-11-5953-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/9a9f100e7780/tcr-13-11-5953-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/4b20846f7a83/tcr-13-11-5953-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/3cd227234263/tcr-13-11-5953-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/dc12951b78e6/tcr-13-11-5953-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/7430318b7924/tcr-13-11-5953-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/842807247654/tcr-13-11-5953-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/efdcfaf31965/tcr-13-11-5953-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/3c39c1bb9f22/tcr-13-11-5953-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/9a9f100e7780/tcr-13-11-5953-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/4b20846f7a83/tcr-13-11-5953-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/3cd227234263/tcr-13-11-5953-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/dc12951b78e6/tcr-13-11-5953-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/7430318b7924/tcr-13-11-5953-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/842807247654/tcr-13-11-5953-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97a0/11651743/efdcfaf31965/tcr-13-11-5953-f8.jpg

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