Department of Otolaryngology, The First Hospital of Hebei Medical University, Hebei ProvinceChina.
Otorhinolaryngology Surgery, The Fourth Hospital of Hebei Medical University, Hebei ProvinceChina.
Medicine (Baltimore). 2022 Aug 5;101(31):e29555. doi: 10.1097/MD.0000000000029555.
Laryngeal squamous cell carcinoma (LSCC) is one of the most common forms of head and neck cancers. However, few studies have focused on the correlation between competing endogenous RNA (ceRNAs) and immune cells in LSCC.
RNAseq expression of LSCC and adjacent tissues were downloaded from The Cancer Genome Atlas to establish a ceRNA network. The key gene in ceRNA was screened by the cox regression analysis to establish a prognostic risk assessment model. The CIBERSORT algorithm was then used to screen important tumor-infiltrating cells related to LSCC. Finally, co-expression analysis was applied to explore the relationship between key genes in the ceRNA network and tumor-infiltrating cells. The external datasets were used to validate critical biomarkers.
We constructed a prognostic risk assessment model of key genes in the ceRNA network. As it turned out, Kaplan-Meier survival analysis showed significant differences in overall survival rates between high-risk and low-risk groups (P < .001). The survival rate of the high-risk group was drastically lower than that of the low-risk group, and the AUC of 1 year, 3 years, and 5 years were all above 0.7. In addition, some immune infiltrating cells were also found to be related to LSCC. In the co-expression analysis, there is a negative correlation between plasma cells and TUBB3 (r = -0.33, P = .0013). External dataset validation also supports this result.
In this study, we found that some key genes (SLC35C1, CLDN23, HOXB7, STC2, TMEM158, TNFRSF4, TUBB3) and immune cells (plasma cells) may correspond to the prognosis of LSCC.
喉鳞状细胞癌(LSCC)是头颈部癌症中最常见的形式之一。然而,很少有研究关注 LSCC 中竞争内源性 RNA(ceRNA)与免疫细胞的相关性。
从癌症基因组图谱下载 LSCC 和相邻组织的 RNAseq 表达谱,构建 ceRNA 网络。通过 Cox 回归分析筛选 ceRNA 中的关键基因,建立预后风险评估模型。然后应用 CIBERSORT 算法筛选与 LSCC 相关的重要肿瘤浸润细胞。最后,进行共表达分析,探讨 ceRNA 网络中关键基因与肿瘤浸润细胞的关系。使用外部数据集验证关键生物标志物。
构建了 ceRNA 网络中关键基因的预后风险评估模型。Kaplan-Meier 生存分析表明,高低风险组之间的总生存率存在显著差异(P<0.001)。高风险组的生存率明显低于低风险组,1 年、3 年和 5 年的 AUC 均高于 0.7。此外,还发现一些免疫浸润细胞与 LSCC 相关。在共表达分析中,浆细胞与 TUBB3 呈负相关(r=-0.33,P=0.0013)。外部数据集验证也支持这一结果。
本研究发现,一些关键基因(SLC35C1、CLDN23、HOXB7、STC2、TMEM158、TNFRSF4、TUBB3)和免疫细胞(浆细胞)可能与 LSCC 的预后相关。