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Prognostic model of patients with liver cancer based on tumor stem cell content and immune process

机译:基于肿瘤干细胞含量和免疫过程的肝癌患者的预后模型

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摘要

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.
机译:在全球范围内,肝脏肝细胞癌(LIHC)具有高死亡率和复发率,导致预后差。 LiHC的复发与两个方面密切相关:免疫渗透程度和肿瘤干细胞的含量。因此,本研究旨在使用来自癌症基因组地图集的RNA-SEQ和LIHC的临床资料,恶性肿瘤中的基质和免疫细胞的估计,mRNA茎秆指数评分和加权基因相关网络分析方法,找到与之明显相关的基因上述两个方面。主要基因和临床因素用作输入。进行套索回归和多元硬币回归,为肝癌患者构建有效的预后模型。最后,包括四种关键基因(0,和)和四种临床因素(亚洲,年龄,年龄和胆红素),包括预后模型,即免疫和癌症 - 细胞相关预后(ICRP)得分。 ICRP评分在测试集中实现了很大的性能。在测试组中的ICRP评分的曲线值下的区域分别为0.708,0.723和0.765,其优于LIHC的其他预测预测方法。 C折射率评估方法也得出相同的结论。

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