Zhejiang Provincial Key Laboratory for Accurate Diagnosis and Treatment of Chronic Liver Diseases, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, No.2 Fuxue Lane, Wenzhou, Zhejiang, P.R. China.
BMC Cancer. 2023 Mar 28;23(1):284. doi: 10.1186/s12885-023-10766-w.
As a highly heterogeneous cancer, the prognostic stratification and personalized management of hepatocellular carcinoma (HCC) are still challenging. Recently, Antigen-presenting-cells (APCs) and T-cells-infiltration (TCI) have been reported to be implicated in modifying immunology in HCC. Nevertheless, the clinical value of APCs and TCI-related long non-coding RNAs (LncRNAs) in the clinical outcomes and precision treatment of HCC is still obscure. In this study, a total of 805 HCC patients were enrolled from three public datasets and an external clinical cohort. 5 machine learning (ML) algorithms were transformed into 15 kinds of ML integrations, which was used to construct the preliminary APC-TCI related LncRNA signature (ATLS). According to the criterion with the largest average C-index in the validation sets, the optimal ML integration was selected to construct the optimal ATLS. By incorporating several vital clinical characteristics and molecular features for comparison, ATLS was demonstrated to have a relatively more significantly superior predictive capacity. Additionally, it was found that the patients with high ATLS score had dismal prognosis, relatively high frequency of tumor mutation, remarkable immune activation, high expression levels of T cell proliferation regulators and anti-PD-L1 response as well as extraordinary sensitivity to Oxaliplatin/Fluorouracil/Lenvatinib. In conclusion, ATLS may serve as a robust and powerful biomarker for improving the clinical outcomes and precision treatment of HCC.
作为一种高度异质性的癌症，肝细胞癌（HCC）的预后分层和个体化管理仍然具有挑战性。最近，抗原呈递细胞（APCs）和 T 细胞浸润（TCI）被报道与改变 HCC 的免疫学有关。然而，APCs 和 TCI 相关长链非编码 RNA（LncRNA）在 HCC 的临床结局和精准治疗中的临床价值仍然不清楚。在这项研究中，总共从三个公共数据集和一个外部临床队列中招募了 805 名 HCC 患者。五种机器学习（ML）算法转化为 15 种 ML 集成，用于构建初步的 APC-TCI 相关 LncRNA 特征（ATLS）。根据验证集中平均 C 指数最大的标准，选择最佳 ML 集成来构建最佳 ATLS。通过纳入几个重要的临床特征和分子特征进行比较，ATLS 被证明具有相对更显著的预测能力。此外，还发现高 ATLS 评分的患者预后较差，肿瘤突变频率相对较高，免疫激活明显，T 细胞增殖调节剂和抗 PD-L1 反应表达水平较高，对奥沙利铂/氟尿嘧啶/仑伐替尼的敏感性极高。总之，ATLS 可能是改善 HCC 临床结局和精准治疗的有力且强大的生物标志物。
