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与肝细胞癌免疫浸润相关的关键候选预后生物标志物

Key Candidate Prognostic Biomarkers Correlated with Immune Infiltration in Hepatocellular Carcinoma.

作者信息

Deng Zenghua, Huang Kanghua, Liu Dongfang, Luo Nan, Liu Tingting, Han Long, Du Dexiao, Lian Dongbo, Zhong Zhaohui, Peng Jirun

机构信息

Department of Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.

Ninth School of Clinical Medicine, Peking University, Beijing, 100038, People's Republic of China.

出版信息

J Hepatocell Carcinoma. 2021 Dec 18;8:1607-1622. doi: 10.2147/JHC.S337067. eCollection 2021.

DOI:10.2147/JHC.S337067
PMID:34956967
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8694277/
Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, which causes ~800,000 deaths annually world-wide. Immune checkpoint inhibitor (ICI) has reformed cancer therapy and achieved unprecedented results in various malignancies, including HCC. However, the response rate of immunotherapy is very low in HCC. Considereing the complicated and unique immune status in liver, we hypothesize that critical molecules will affect prognosis and correlate with immune context in the tumor microenvironment of HCC.

METHODS

Using Kaplan-Meier plotter, GEPIA2 and Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB), survival genes and their prognostic value were estimated in HCC. Based on Tumor Immune Estimation Resource (TIMER), association between survival genes and immune infiltration was examined in HCC. FunRich and STRING were used to analyze gene ontology and protein-protein interaction (PPI) Network, qRT-PCR was used to measure mRNA level of candidates; and a Cell Counting Kit-8 was used to measure proliferation of HCC cell line.

RESULTS

Using multiple databases, we identified 36 key prognostic genes highly expressed in HCC and associated with poor survival of patients. Meanwhile, the 36 gene signatures correlated with immune infiltration in HCC. Moreover, these genes were significantly associated with exhausted T cells and polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) in HCC. Among the 36 key genes, SKA3, SGOL2, SPINDOC, TEDC2, TMCO3 and NUP205 were highly expressed in tumor samples compared with adjacent normal tissues in our HCC cohort (n=22). Additionally, proliferation of SMMC7721 cell line was inhibited when it interfered with SiRNA of each gene.

CONCLUSION

The 36 genes may serve as potential prognostic biomarkers and molecular targets to ameliorate tumor immune microenvironment (TIME) in HCC and therefore represent a novel avenue for individualized immunotherapy in HCC.

摘要

背景

肝细胞癌(HCC)是原发性肝癌最常见的亚型,全球每年约有80万人死于该病。免疫检查点抑制剂(ICI)革新了癌症治疗,并在包括HCC在内的各种恶性肿瘤中取得了前所未有的成果。然而,HCC免疫治疗的有效率非常低。鉴于肝脏复杂且独特的免疫状态,我们推测关键分子会影响HCC患者的预后,并与肿瘤微环境中的免疫背景相关。

方法

使用Kaplan-Meier Plotter、GEPIA2和肝细胞癌综合分子数据库(HCCDB),评估HCC中的生存基因及其预后价值。基于肿瘤免疫评估资源(TIMER),研究HCC中生存基因与免疫浸润之间的关联。使用FunRich和STRING分析基因本体和蛋白质-蛋白质相互作用(PPI)网络,采用qRT-PCR检测候选基因的mRNA水平;使用细胞计数试剂盒-8检测HCC细胞系的增殖情况。

结果

通过多个数据库,我们鉴定出36个在HCC中高表达且与患者不良生存相关的关键预后基因。同时,这36个基因特征与HCC中的免疫浸润相关。此外,这些基因与HCC中耗竭的T细胞和多形核髓源性抑制细胞(PMN-MDSC)显著相关。在我们的HCC队列(n = 22)中,与相邻正常组织相比,36个关键基因中的SKA3、SGOL2、SPINDOC、TEDC2、TMCO3和NUP205在肿瘤样本中高表达。此外,当干扰每个基因的SiRNA时,SMMC7721细胞系的增殖受到抑制。

结论

这36个基因可能作为潜在的预后生物标志物和分子靶点,以改善HCC的肿瘤免疫微环境(TIME),因此代表了HCC个体化免疫治疗的新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/ebaf07c4acae/JHC-8-1607-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/dc7afb9c928f/JHC-8-1607-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/f17be0695c00/JHC-8-1607-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/0f3ae27892bb/JHC-8-1607-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/8112fbf319c2/JHC-8-1607-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/d4b5a477ed56/JHC-8-1607-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/a5ca8241c95d/JHC-8-1607-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/ebaf07c4acae/JHC-8-1607-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/dc7afb9c928f/JHC-8-1607-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/f17be0695c00/JHC-8-1607-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/0f3ae27892bb/JHC-8-1607-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/8112fbf319c2/JHC-8-1607-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/d4b5a477ed56/JHC-8-1607-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/a5ca8241c95d/JHC-8-1607-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff15/8694277/ebaf07c4acae/JHC-8-1607-g0007.jpg

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