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内质网应激模式与肝细胞癌免疫微环境的相关性:预后特征分析。

Correlation of endoplasmic reticulum stress patterns with the immune microenvironment in hepatocellular carcinoma: a prognostic signature analysis.

机构信息

Department of Gastroenterology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Department of Gastrointestinal Surgery, Jinshan Hospital, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

出版信息

Front Immunol. 2023 Dec 8;14:1270774. doi: 10.3389/fimmu.2023.1270774. eCollection 2023.

DOI:10.3389/fimmu.2023.1270774
PMID:38143739
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10748430/
Abstract

BACKGROUNDS

The extended duration of endoplasmic reticulum stress (ERS) can impact the progression of hepatocellular carcinoma (HCC) and the efficacy of immunotherapies by interacting with immune cells that have infiltrated the tumor microenvironment (TME).

METHODS AND RESULTS

The study utilized a training cohort of 364 HCC patients with complete information from The Cancer Genome Atlas Program (TCGA) database, and a validation cohort of 231 HCC patients from the International Cancer Genome Consortium (ICGC) database. The genes related to ERS exhibiting a strong correlation with overall survival (OS) were identified using univariate Cox regression analysis. A 13-gene predictive signature was then produced through the least absolute shrinkage and selection operator (LASSO) regression approach. The data revealed that the ERS-associated gene signature effectively stratified patients into high- or low-risk groups regarding OS in both the training and validation cohorts (P < 0.0001 and P = 0.00029, respectively). Using the multivariate method, it is still an independent prognostic factor in both the training and validation cohorts (P < 0.001 and P = 0.008, respectively). Moreover, several metabolic pathways were identified to be enriched among the 13 genes in the predictive signature. When the ERS-associated gene signature was combined with the tumor-node-metastasis (TNM) stage, the ERS nomogram performed better than either the gene signature or the TNM stage alone (C-index values: 0.731, 0.729, and 0.573, respectively). Further analysis revealed that patients in the high-risk group exhibited increased infiltration of immune cells. Additionally, GP6 was downregulated in HCC tissues among these signature genes (P < 0.05), which was related to poor OS.

CONCLUSIONS

The data suggest that this novel ERS-associated gene signature could contribute to personalized cancer management for HCC. Moreover, targeting GP6 inhibition might be a potential method for HCC therapy.

摘要

背景

内质网应激(ERS)的持续时间延长会通过与浸润肿瘤微环境(TME)的免疫细胞相互作用,影响肝细胞癌(HCC)的进展和免疫疗法的疗效。

方法和结果

该研究利用了来自癌症基因组图谱计划(TCGA)数据库的 364 名 HCC 患者的完整信息的训练队列,以及来自国际癌症基因组联盟(ICGC)数据库的 231 名 HCC 患者的验证队列。通过单因素 Cox 回归分析,确定了与总生存期(OS)具有强相关性的 ERS 相关基因。然后,通过最小绝对收缩和选择算子(LASSO)回归方法生成了一个 13 基因预测特征。数据表明,该 ERS 相关基因特征在训练和验证队列中都能有效地将患者分为高或低 OS 风险组(P < 0.0001 和 P = 0.00029,分别)。使用多变量方法,该特征在训练和验证队列中仍然是独立的预后因素(P < 0.001 和 P = 0.008,分别)。此外,在预测特征的 13 个基因中鉴定出几种代谢途径富集。当将 ERS 相关基因特征与肿瘤-淋巴结-转移(TNM)分期结合使用时,与基因特征或 TNM 分期单独使用相比,ERS 列线图表现更好(C 指数值分别为 0.731、0.729 和 0.573)。进一步分析表明,高危组患者的免疫细胞浸润增加。此外,在这些特征基因中,GP6 在 HCC 组织中下调(P < 0.05),与 OS 不良相关。

结论

该数据表明,这种新的 ERS 相关基因特征可能有助于 HCC 的个体化癌症管理。此外,靶向 GP6 抑制可能是 HCC 治疗的一种潜在方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/ab33c045c264/fimmu-14-1270774-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/61d778344c6b/fimmu-14-1270774-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/bc1e91b1eabc/fimmu-14-1270774-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/eabd06f4dd9a/fimmu-14-1270774-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/1163857addd5/fimmu-14-1270774-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/ab33c045c264/fimmu-14-1270774-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/61d778344c6b/fimmu-14-1270774-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/28d74e0264c8/fimmu-14-1270774-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/7ac067cfb3c7/fimmu-14-1270774-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/b39cb907239f/fimmu-14-1270774-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/bc1e91b1eabc/fimmu-14-1270774-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8a/10748430/eabd06f4dd9a/fimmu-14-1270774-g007.jpg
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