Department of Oncology, Third Xiangya Hospital of Central South University, Changsha, China.
Department of Radiation Oncology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
Cancer Med. 2021 Dec;10(23):8693-8707. doi: 10.1002/cam4.4341. Epub 2021 Oct 20.
Tongue squamous cell carcinoma (TSCC) is characterized by aggressive invasion and poor prognosis. Currently, immune checkpoint inhibitors may prolong overall survival compared with conventional treatments. However, PD1/PDL1 remain inapplicable in predicting the prognosis of TSCC; thus, it is urgent to explore the genetic characteristics of TSCC.
We utilized single-sample gene set enrichment analysis (ssGSEA) to classify TSCC patients from the TCGA database into clusters with different immune cell infiltrations. ESTIMATE (immune-related scores) and CIBERSORT (immune cell distribution) analyses were used to evaluate the immune landscape among clusters. GO, KEGG, and GSEA analyses were performed to analyze the different underlying molecular mechanisms in the clusters. Based on the immune characteristics, we applied the LASSO Cox regression to select hub genes and construct a prognostic risk model. Finally, we established an interactive network among these hub genes by using Cytoscape, and a pan-cancer analysis to further verify and decipher the innate function of these genes.
Using ssGSEA, we constructed three functional clusters with different overall survival and immune-cell infiltration. ESTIMATE and CIBERSORT analyses revealed the different distributions of immune cells (T cells, B cells, and macrophages) with diverse immune-related scores (ESTIMATE, immune, stromal, and tumor purity scores). Moreover, pathways including those of the interferon-gamma response, hypoxia, and glycolysis of the different subtypes were investigated to elucidate their involvement in mediating the heterogeneous immune characteristics. Subsequently, after LASSO Cox regression, a signature of 15 immune-related genes was established that is more prognostically effective than the TNM stage. Furthermore, three hub genes-PGK1, GPI, and RPE-were selected using Cytoscape evaluation and verified by immunohistochemistry. PGK1, the foremost regulator, was a comprehensively profiled pan-cancer, and a PGK1-based interactive network was established.
Our results suggest that immune-related genes and clusters in TSCC have the potential to guide individualized treatments.
舌鳞状细胞癌（TSCC）具有侵袭性强、预后差的特点。目前，免疫检查点抑制剂与传统治疗相比可能延长总生存期。然而，PD1/PDL1 在预测 TSCC 预后方面仍然不适用；因此，迫切需要探索 TSCC 的遗传特征。
我们利用单样本基因集富集分析（ssGSEA）将 TCGA 数据库中的 TSCC 患者分为具有不同免疫细胞浸润的聚类。ESTIMATE（免疫相关评分）和 CIBERSORT（免疫细胞分布）分析用于评估聚类之间的免疫景观。GO、KEGG 和 GSEA 分析用于分析聚类中不同的潜在分子机制。基于免疫特征，我们应用 LASSO Cox 回归选择枢纽基因并构建预后风险模型。最后，我们使用 Cytoscape 构建了这些枢纽基因之间的交互网络，并进行了泛癌分析以进一步验证和解析这些基因的内在功能。
使用 ssGSEA，我们构建了具有不同总生存期和免疫细胞浸润的三个功能聚类。ESTIMATE 和 CIBERSORT 分析揭示了不同免疫细胞（T 细胞、B 细胞和巨噬细胞）的不同分布以及具有不同免疫相关评分（ESTIMATE、免疫、基质和肿瘤纯度评分）的不同免疫细胞。此外，研究了不同亚型的干扰素-γ反应、缺氧和糖酵解等途径，以阐明它们在介导异质免疫特征中的作用。随后，经过 LASSO Cox 回归，建立了一个由 15 个免疫相关基因组成的signature，比 TNM 分期更具有预后效果。此外，使用 Cytoscape 评估选择了三个枢纽基因-PGK1、GPI 和 RPE-并通过免疫组织化学验证。PGK1 作为最重要的调节剂，是一个全面分析的泛癌，建立了一个基于 PGK1 的交互网络。
我们的研究结果表明，TSCC 中的免疫相关基因和聚类具有指导个体化治疗的潜力。
