Department of Pathology, the Second People's Hospital of Foshan, Affiliated Foshan Hospital of Southern Medical University, Foshan, China.
Department of Respiratory Medicine, Hainan Cancer Hospital, Hainan, China.
Front Immunol. 2023 Mar 17;14:1153423. doi: 10.3389/fimmu.2023.1153423. eCollection 2023.
Hepatocellular carcinoma (HCC) is a complex disease with a poor outlook for patients in advanced stages. Immune cells play an important role in the progression of HCC. The metabolism of sphingolipids functions in both tumor growth and immune infiltration. However, little research has focused on using sphingolipid factors to predict HCC prognosis. This study aimed to identify the key sphingolipids genes (SPGs) in HCC and develop a reliable prognostic model based on these genes.
The TCGA, GEO, and ICGC datasets were grouped using SPGs obtained from the InnateDB portal. A prognostic gene signature was created by applying LASSO-Cox analysis and evaluating it with Cox regression. The validity of the signature was verified using ICGC and GEO datasets. The tumor microenvironment (TME) was examined using ESTIMATE and CIBERSORT, and potential therapeutic targets were identified through machine learning. Single-cell sequencing was used to examine the distribution of signature genes in cells within the TME. Cell viability and migration were tested to confirm the role of the key SPGs.
We identified 28 SPGs that have an impact on survival. Using clinicopathological features and 6 genes, we developed a nomogram for HCC. The high- and low-risk groups were found to have distinct immune characteristics and response to drugs. Unlike CD8 T cells, M0 and M2 macrophages were found to be highly infiltrated in the TME of the high-risk subgroup. High levels of SPGs were found to be a good indicator of response to immunotherapy. In cell function experiments, SMPD2 and CSTA were found to enhance survival and migration of Huh7 cells, while silencing these genes increased the sensitivity of Huh7 cells to lapatinib.
The study presents a six-gene signature and a nomogram that can aid clinicians in choosing personalized treatments for HCC patients. Furthermore, it uncovers the connection between sphingolipid-related genes and the immune microenvironment, offering a novel approach for immunotherapy. By focusing on crucial sphingolipid genes like SMPD2 and CSTA, the efficacy of anti-tumor therapy can be increased in HCC cells.
肝细胞癌（HCC）是一种复杂的疾病，晚期患者预后较差。免疫细胞在 HCC 的进展中发挥着重要作用。鞘脂的代谢在肿瘤生长和免疫浸润中都有功能。然而，很少有研究关注利用鞘脂因子来预测 HCC 的预后。本研究旨在鉴定 HCC 中的关键鞘脂基因（SPGs），并基于这些基因构建一个可靠的预后模型。
使用 InnateDB 门户获取的 SPGs 将 TCGA、GEO 和 ICGC 数据集进行分组。通过 LASSO-Cox 分析创建预后基因特征，并使用 Cox 回归进行评估。使用 ICGC 和 GEO 数据集验证特征的有效性。使用 ESTIMATE 和 CIBERSORT 检查肿瘤微环境（TME），并通过机器学习识别潜在的治疗靶点。使用单细胞测序检查 TME 中细胞内特征基因的分布。通过细胞活力和迁移实验验证关键 SPGs 的作用。
我们鉴定了 28 个影响生存的 SPGs。使用临床病理特征和 6 个基因，我们为 HCC 开发了一个列线图。高风险和低风险组被发现具有不同的免疫特征和对药物的反应。与 CD8 T 细胞不同，M0 和 M2 巨噬细胞在高危亚组的 TME 中高度浸润。高水平的 SPGs 被发现是免疫治疗反应的良好指标。在细胞功能实验中，SMPD2 和 CSTA 被发现增强 Huh7 细胞的存活和迁移，而沉默这些基因则增加了 Huh7 细胞对拉帕替尼的敏感性。
本研究提出了一个六基因特征和一个列线图，可以帮助临床医生为 HCC 患者选择个性化治疗方案。此外，它揭示了鞘脂相关基因与免疫微环境之间的联系，为免疫治疗提供了新的思路。通过关注 SMPD2 和 CSTA 等关键鞘脂基因，可以提高 HCC 细胞中抗肿瘤治疗的疗效。
