A stratification model of hepatocellular carcinoma based on expression profiles of cells in the tumor microenvironment.
A stratification model of hepatocellular carcinoma based on expression profiles of cells in the tumor microenvironment.
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基于肿瘤微环境中细胞表达谱的肝细胞癌分层模型
DOI：
10.1186/s12885-022-09647-5
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发表时间：
2022-06-04
期刊：
影响因子：
3.8
通讯作者：
中科院分区：
文献类型：
--
作者：
肝细胞癌（HCC）是肝脏的恶性肿瘤，是全世界癌症相关死亡的最常见和第二大原因之一。一个可靠的预后模型，指导选择肝癌治疗尚未建立。使用一致聚类方法来确定癌症基因组图谱和肝癌-RIKEN，JP（LIRI_JP）数据集中的免疫簇的数量。根据RNA测序数据确定这些组之间的差异表达基因（DEG）。然后，为了识别标签基因中的枢纽基因，构建了共表达网络。同时探讨了免疫簇的临床特征和预后价值。最后，确定了免疫簇的潜在关键基因。在对DEG进行存活和相关性分析后，鉴定了三个免疫簇（C1、C2和C3）。C2患者的生存时间最长，肿瘤微环境（TME）细胞群丰度最高。成纤维细胞生长因子19（FGF 19）和连环蛋白（cadherin-associated protein）β1（CTNNB 1）基因突变主要见于C2和C3。C1、C2和C3的特征基因主要分别富集在5、23和26条途径中。本研究试图通过将来自公共数据集的患者表达谱分为三个簇并发现每个簇的独特分子特征来构建HCC预后的免疫分层模型。该分层模型提供了对HCC亚型的免疫和临床特征的见解，这有利于HCC的预后。在线版本包含补充材料，可通过10.1186/s12885-022-09647-5获得。
A malignancy of the liver, hepatocellular carcinoma (HCC) is among the most common and second-leading causes of cancer-related deaths worldwide. A reliable prognosis model for guidance in choosing HCC therapies has yet to be established. A consensus clustering approach was used to determine the number of immune clusters in the Cancer Genome Atlas and Liver Cancer-RIKEN, JP (LIRI_JP) datasets. The differentially expressed genes (DEGs) among these groups were identified based on RNA sequencing data. Then, to identify hub genes among signature genes, a co-expression network was constructed. The prognostic value and clinical characteristics of the immune clusters were also explored. Finally, the potential key genes for the immune clusters were determined. After conducting survival and correlation analyses of the DEGs, three immune clusters (C1, C2, and C3) were identified. Patients in C2 showed the longest survival time with the greatest abundance of tumor microenvironment (TME) cell populations. MGene mutations in Ffibroblast growth factor-19 (FGF19) and catenin (cadherin-associated protein),β1(CTNNB1) were mostly observed in C2 and C3, respectively. The signature genes of C1, C2, and C3 were primarily enriched in 5, 23, and 26 pathways, respectively. This study sought to construct an immune-stratification model for the prognosis of HCC by dividing the expression profiles of patients from public datasets into three clusters and discovering the unique molecular characteristics of each. This stratification model provides insights into the immune and clinical characteristics of HCC subtypes, which is beneficial for the prognosis of HCC. The online version contains supplementary material available at 10.1186/s12885-022-09647-5.
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影响因子：
3.4
作者：
Tang F;Tang S;Guo X;Yang C;Jia K
通讯作者：
Jia K
DOI：
10.1038/nrc3239
发表时间：
2012-03-22
期刊：
Nature reviews. Cancer
影响因子：
--
作者：
Pardoll DM
通讯作者：
Pardoll DM
影响因子：
64.5
作者：
Cancer Genome Atlas Research Network. Electronic address: wheeler@bcm.edu;Cancer Genome Atlas Research Network
通讯作者：
Cancer Genome Atlas Research Network
影响因子：
10.9
作者：
Vareki, Saman Maleki
通讯作者：
Vareki, Saman Maleki
影响因子：
29.4
作者：
Chiu, David Kung-Chun;Yuen, Vincent Wai-Hin;Wong, Carmen Chak-Lui
通讯作者：
Wong, Carmen Chak-Lui