Li Jiang, Tao Haisu, Wang Wenqiang, Li Jian, Zhang Erlei
Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095, Jiefang Avenue, Wuhan 430030, Hubei, China.
Department of Hepatobiliary Surgery, College of Medicine, First Affiliated Hospital of Shihezi University Medical College, North 2nd Road, Shihezi, Xinjiang Uygur Autonomous Region, China.
J Oncol. 2022 Mar 12;2022:1182383. doi: 10.1155/2022/1182383. eCollection 2022.
. Because of the heterogeneity of hepatocellular carcinoma (HCC) and the complex nature of the tumor microenvironment (TME), the long-term efficacy of therapy continues to be a clinical challenge. It is necessary to classify and refine the appropriate treatment intervention decision-making in this kind of tumor. . We used "ConsensusClusterPlus" to establish a stable molecular classification based on the ferroptosis-related genes (FRGs) expression obtained from FerrDb. The clinical features, immune infiltration, DNA damage, and genomic changes of different subclasses were evaluated. The least absolute shrinkage and selection operator regression (LASSO) method and univariate Cox regression were utilized to construct the ferroptosis-related prognosis risk score (FPRS) model, and the association between the FPRS model and HCC molecular characteristics, immune features, and immunotherapy was studied. . We identified two ferroptosis subclasses, C1 with poor prognosis and a higher proportion of patients in the middle and late stages infected with HBV and HCV, having higher DNA damage including aneuploidy, HRD, fraction altered, and the number of segments, and higher probability of gene mutation and copy number mutation. FPRS model was constructed on the basis of differentially expressed genes (DEGs) between C1 and C2, which showed a higher area under the curve (AUC) in predicting overall survival rate in the training set and independent verification cohort and could reflect the clinical characteristics and response to immunotherapy of different patients, being an independent prognostic factor of HCC. . Here, we revealed two novel molecular subgroups based on FRGs and develop an FPRS model consisting of six genes that can help predict prognosis and select patients suitable for immunotherapy.
由于肝细胞癌（HCC）的异质性以及肿瘤微环境（TME）的复杂性质，治疗的长期疗效仍然是一项临床挑战。对这类肿瘤进行分类并完善适当的治疗干预决策是必要的。我们使用“ConsensusClusterPlus”基于从FerrDb获得的铁死亡相关基因（FRGs）表达建立了一种稳定的分子分类。评估了不同亚类的临床特征、免疫浸润、DNA损伤和基因组变化。利用最小绝对收缩和选择算子回归（LASSO）方法和单变量Cox回归构建铁死亡相关预后风险评分（FPRS）模型，并研究FPRS模型与HCC分子特征、免疫特征和免疫治疗之间的关联。我们确定了两个铁死亡亚类，C1预后较差，中晚期感染HBV和HCV的患者比例较高，具有更高的DNA损伤，包括非整倍体、HRD、改变分数和片段数量，以及更高的基因突变和拷贝数突变概率。FPRS模型基于C1和C2之间的差异表达基因（DEGs）构建，在训练集和独立验证队列中预测总生存率时显示出更高的曲线下面积（AUC），并且可以反映不同患者的临床特征和对免疫治疗的反应，是HCC的独立预后因素。在此，我们基于FRGs揭示了两个新的分子亚组，并开发了一个由六个基因组成的FPRS模型，该模型有助于预测预后并选择适合免疫治疗的患者。
