肿瘤浸润免疫细胞对预测乙型肝炎病毒相关肝细胞癌预后的

StephenW

World J Gastroenterol. 2019 Sep 21;25(35):5266-5282. doi: 10.3748/wjg.v25.i35.5266.
Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma.
Chen QF1, Li W1, Wu PH1, Shen LJ1, Huang ZL2.
Author information

1
    Department of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China.
2
    Department of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China. [email protected].

Abstract
BACKGROUND:

Hepatitis B virus (HBV) has been recognized as a leading cause of hepatocellular carcinoma (HCC). Numerous reports suggest that immune infiltration can predict the prognosis of HCC. Nonetheless, no creditable markers for prognosis of HBV-related HCC have been established by systematically assessing the immune-related markers based on tumor transcriptomes.
AIM:

To establish an immune-related marker based on the cell compositions of immune infiltrate obtained based on tumor transcriptomes, so as to enhance the prediction accuracy of HBV-related HCC prognosis.
METHODS:

RNA expression patterns as well as the relevant clinical data of HCC patients were obtained from The Cancer Genome Atlas. Twenty-two immunocyte fraction types were estimated by cell type identification by estimating relative subsets of RNA transcripts. Subsequently, the least absolute shrinkage and selection operator (LASSO) Cox regression model was employed to construct an immunoscore based on the immunocyte fraction types. Afterwards, the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox analyses were performed. Additionally, a nomogram for prognosis that integrated the immunoscore as well as the clinical features was established. Meanwhile, the correlation of immunoscore with immune genes was also detected, and gene set enrichment analysis (GSEA) of the immunoscore was conducted.
RESULTS:

A total of 22 immunocyte fraction types were predicted and compared among the tumor as well as non-tumor samples. An immunoscore was constructed through adopting the LASSO model, which contained eight immunocyte fraction types. Meanwhile, the areas under the ROC curves for the immunoscore biomarker prognostic model were 0.971, 0.912, and 0.975 for 1-, 3-, and 5-year overall survival (OS), respectively. Difference in OS between the high-immunoscore group and the low-immunoscore group was statistically significant [hazard ratio (HR) = 66.007, 95% confidence interval (CI): 8.361-521.105; P < 0.0001]. Moreover, multivariable analysis showed that the immunoscore was an independent factor for predicting the prognosis (HR = 2.997, 95%CI: 1.737-5.170). A nomogram was established, and the C-index was 0.757 (95%CI: 0.648-0.866). The immunoscore showed a significant negative correlation with the expression of PD-1 (P = 0.024), PD-L1 (P = 0.026), PD-L2 (P = 0.029), and CD27 (P = 0.033). Eight pathways were confirmed by GSEA.
CONCLUSION:

The established immunoscore can potentially serve as a candidate marker to estimate the OS for HBV-related HCC cases.
KEYWORDS:

Cell type identification by estimating relative subsets of RNA transcripts; Hepatitis B virus; Hepatocellular carcinoma; Immune risk score; Prognostic signature

PMID:
    31558872
PMCID:
    PMC6761238
DOI:
    10.3748/wjg.v25.i35.526

StephenW

世界J胃肠病学杂志。 2019年9月21日; 25（35）：5266-5282。 doi：10.3748 / wjg.v25.i35.5266。
肿瘤浸润免疫细胞对预测乙型肝炎病毒相关肝细胞癌预后的意义。
陈QF1，李W1，吴PH1，沉LJ1，黄ZL2。
作者信息

1
    中山大学肿瘤防治中心医学影像与介入放射学系；华南肿瘤学国家重点实验室癌症医学协同创新中心，广东广州510060。
2
    中山大学肿瘤防治中心医学影像与介入放射学系；华南肿瘤学国家重点实验室癌症医学协同创新中心，广东广州510060。 [email protected]。

抽象
背景：

乙型肝炎病毒（HBV）已被认为是肝细胞癌（HCC）的主要原因。大量报道提示免疫浸润可以预测HCC的预后。但是，通过基于肿瘤转录组系统地评估免疫相关标志物，尚未建立可预见的HBV相关HCC标志物。
目标：

基于肿瘤转录组获得的免疫浸润细胞组成，建立免疫相关标记，以提高HBV相关HCC预后的预测准确性。
方法：

HCC患者的RNA表达模式和相关临床数据可从The Cancer Genome Atlas获得。通过估计RNA转录本的相对子集，通过细胞类型鉴定来评估22种免疫细胞级分类型。随后，使用最小绝对收缩和选择算子（LASSO）Cox回归模型来构建基于免疫细胞组分类型的免疫评分。之后，执行了接收器工作特性（ROC）曲线，Kaplan-Meier和多元Cox分析。此外，建立了将免疫评分和临床特征相结合的预后诺模图。同时，还检测了免疫分数与免疫基因的相关性，并进行了免疫分数的基因组富集分析。
结果：

预测了总共22种免疫细胞级分类型，并在肿瘤以及非肿瘤样品中进行了比较。通过采用包含八种免疫细胞级分类型的LASSO模型构建免疫评分。同时，免疫评分生物标志物预后模型的ROC曲线下面积分别为1年，3年和5年总生存期（OS）为0.971、0.912和0.975。高免疫评分组和低免疫评分组之间的OS差异具有统计学意义[危险比（HR）= 66.007，95％置信区间（CI）：8.361-521.105； P <0.0001]。此外，多变量分析显示免疫分数是预测预后的独立因素（HR = 2.997，95％CI：1.737-5.170）。建立了列线图，并且C指数为0.757（95％CI：0.648-0.866）。免疫评分与PD-1（P = 0.024），PD-L1（P = 0.026），PD-L2（P = 0.029）和CD27（P = 0.033）的表达呈显着负相关。 GSEA确认了八种途径。
结论：

建立的免疫评分可能会潜在地用作评估HBV相关HCC病例OS的候选标记。
关键词：

通过估计RNA转录本的相对亚群来鉴定细胞类型；乙型肝炎病毒；肝细胞癌；免疫风险评分；预后签名

结论：
    31558872
PMCID：
    PMC6761238
DOI：
    10.3748 / wjg.v25.i35.526