Department of Molecular and Cellular Pharmacology, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing, China.
Peking University International Cancer Institute and Department of Pharmacology, School of Basic Medical Sciences, Peking University, Beijing, China.
Aging (Albany NY). 2020 Aug 27;12(16):16555-16578. doi: 10.18632/aging.103832.
Globally, liver hepatocellular carcinoma (LIHC) has a high mortality and recurrence rate, leading to poor prognosis. The recurrence of LIHC is closely related to two aspects: degree of immune infiltration and content of tumor stem cells. Hence, this study aimed to used RNA-seq and clinical data of LIHC from The Cancer Genome Atlas, Estimation of Stromal and Immune cells in Malignant Tumours, mRNA stemness index score, and weighted gene correlation network analysis methods to find genes significantly linked to the aforementioned two aspects. Key genes and clinical factors were used as input. Lasso regression and multivariate Cox regression were conducted to build an effective prognostic model for patients with liver cancer. Finally, four key genes (0, , , and ) and four clinical factors (Asian, age, grade, and bilirubin) were included in the prognostic model, namely Immunity and Cancer-stem-cell Related Prognosis (ICRP) score. The ICRP score achieved a great performance in test set. The area under the curve value of the ICRP score in test set for 1, 3, and 5 years was 0.708, 0.723, and 0.765, respectively, which was better than that of other prognostic prediction methods for LIHC. The C-index evaluation method also reached the same conclusion.
全球范围内，肝癌（LIHC）的死亡率和复发率都很高，导致预后不良。LIHC 的复发与两个方面密切相关：免疫浸润程度和肿瘤干细胞含量。因此，本研究旨在使用来自癌症基因组图谱的 LIHC 的 RNA-seq 和临床数据、基质和免疫细胞估计恶性肿瘤、mRNA 干性指数评分和加权基因相关网络分析方法，找到与上述两个方面显著相关的基因。将关键基因和临床因素作为输入。使用 Lasso 回归和多变量 Cox 回归构建肝癌患者的有效预后模型。最后，将四个关键基因（、、、）和四个临床因素（亚洲人、年龄、分级和胆红素）纳入预后模型，即免疫和癌症干细胞相关预后（ICRP）评分。ICRP 评分在测试集中表现出色。ICRP 评分在测试集中的 1、3 和 5 年 AUC 值分别为 0.708、0.723 和 0.765，优于其他 LIHC 预后预测方法。C 指数评估方法也得出了相同的结论。
