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开发和验证与凝血相关基因的肝细胞癌预后模型。

Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma.

机构信息

Laboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou, China.

Anesthesiology Department, Lanzhou University Second Hospital, Lanzhou, China.

出版信息

BMC Bioinformatics. 2023 Mar 9;24(1):89. doi: 10.1186/s12859-023-05220-4.

DOI:10.1186/s12859-023-05220-4
PMID:36894886
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9996845/
Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated.

METHODS

Firstly, we identified differentially expressed coagulation-related genes of HCC and control samples in the datasets GSE54236, GSE102079, TCGA-LIHC, and Genecards database. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to determine the key CRGs and establish the coagulation-related risk score (CRRS) prognostic model in the TCGA-LIHC dataset. The predictive capability of the CRRS model was evaluated by Kaplan-Meier survival analysis and ROC analysis. External validation was performed in the ICGC-LIRI-JP dataset. Besides, combining risk score and age, gender, grade, and stage, a nomogram was constructed to quantify the survival probability. We further analyzed the correlation between risk score and functional enrichment, pathway, and tumor immune microenvironment.

RESULTS

We identified 5 key CRGs (FLVCR1, CENPE, LCAT, CYP2C9, and NQO1) and constructed the CRRS prognostic model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group. The AUC values for 1 -, 3 -, and 5-year OS in the TCGA dataset were 0.769, 0.691, and 0.674, respectively. The Cox analysis showed that CRRS was an independent prognostic factor for HCC. A nomogram established with risk score, age, gender, grade, and stage, has a better prognostic value for HCC patients. In the high-risk group, CD4T cells memory resting, NK cells activated, and B cells naive were significantly lower. The expression levels of immune checkpoint genes in the high-risk group were generally higher than that in the low-risk group.

CONCLUSIONS

The CRRS model has reliable predictive value for the prognosis of HCC patients.

摘要

背景

肝细胞癌(HCC)在全球范围内具有较高的发病率和死亡率,严重威胁着人们的身心健康。凝血与 HCC 的发生和发展密切相关。凝血相关基因(CRGs)是否可作为 HCC 的预后标志物仍有待研究。

方法

首先,我们在数据集 GSE54236、GSE102079、TCGA-LIHC 和 Genecards 数据库中鉴定 HCC 和对照样本中差异表达的凝血相关基因。然后,使用单变量 Cox 回归分析、LASSO 回归分析和多变量 Cox 回归分析确定关键 CRGs,并在 TCGA-LIHC 数据集建立凝血相关风险评分(CRRS)预后模型。通过 Kaplan-Meier 生存分析和 ROC 分析评估 CRRS 模型的预测能力。在 ICGC-LIRI-JP 数据集进行外部验证。此外,通过结合风险评分和年龄、性别、分级和分期,构建列线图来量化生存概率。我们进一步分析了风险评分与功能富集、通路和肿瘤免疫微环境之间的相关性。

结果

我们确定了 5 个关键 CRGs(FLVCR1、CENPE、LCAT、CYP2C9 和 NQO1)并构建了 CRRS 预后模型。高风险组的总生存期(OS)更短。在 TCGA 数据集的 1 年、3 年和 5 年 OS 的 AUC 值分别为 0.769、0.691 和 0.674。Cox 分析表明,CRRS 是 HCC 的独立预后因素。基于风险评分、年龄、性别、分级和分期建立的列线图对 HCC 患者具有更好的预后价值。在高危组中,CD4T 细胞记忆静止、NK 细胞激活和 B 细胞幼稚明显较低。高危组免疫检查点基因的表达水平普遍高于低危组。

结论

CRRS 模型对 HCC 患者的预后具有可靠的预测价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/d772ae7b270f/12859_2023_5220_Fig9_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/d772ae7b270f/12859_2023_5220_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/e04879e56607/12859_2023_5220_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/c5f3b2f2c69e/12859_2023_5220_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/43520010f2ae/12859_2023_5220_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/bffed62160c5/12859_2023_5220_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/3a596199b1d9/12859_2023_5220_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/30d78b36c81e/12859_2023_5220_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/8bc0ff806aef/12859_2023_5220_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/c621de443ae5/12859_2023_5220_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/9996845/d772ae7b270f/12859_2023_5220_Fig9_HTML.jpg

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