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胃癌中基底膜相关特征的鉴定

Identification of Basement Membrane-Related Signatures in Gastric Cancer.

作者信息

Wang Jinyun, Liu Dingwei, Wang Qixuan, Xie Yong

机构信息

Department of Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital of Nanchang University, Nanchang 330006, China.

Queen Mary School, Medical College of Nanchang University, Nanchang 330006, China.

出版信息

Diagnostics (Basel). 2023 May 25;13(11):1844. doi: 10.3390/diagnostics13111844.

DOI:10.3390/diagnostics13111844
PMID:37296697
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10252969/
Abstract

BACKGROUND

The basement membrane (BM) serves as a major barrier to impede tumor cell invasion and extravasation during metastasis. However, the associations between BM-related genes and GC remain unclear.

METHODS

RNA expression data and corresponding clinical information of STAD samples were downloaded from the TCGA database. We identified BM-related subtypes and constructed a BM-related gene prognostic model using lasso-Cox regression analysis. We also investigated the single-cell properties of prognostic-related genes and the TME characteristic, TMB status, and chemotherapy response in high- and low-risk groups. Finally, we verified our results in the GEPIA database and human tissue specimens.

RESULTS

A six-gene lasso regression model (APOD, CAPN6, GPC3, PDK4, SLC7A2, SVEP1) was developed. Activated CD4+ T cells and follicular T cells were shown to infiltrate more widely in the low-risk group. The low-risk group harbored significantly higher TMB and better prognosis, favoring immunotherapy.

CONCLUSIONS

We constructed a six-gene BM-related prognostic model for predicting GC prognosis, immune cell infiltration, TMB status, and chemotherapy response. This research provides new ideas for developing more effective individualized treatment of GC patients.

摘要

背景

基底膜(BM)是转移过程中阻碍肿瘤细胞侵袭和外渗的主要屏障。然而,BM相关基因与胃癌(GC)之间的关联仍不清楚。

方法

从TCGA数据库下载STAD样本的RNA表达数据及相应临床信息。我们鉴定了BM相关亚型,并使用套索-考克斯回归分析构建了BM相关基因预后模型。我们还研究了预后相关基因的单细胞特性以及高、低风险组中的肿瘤微环境特征、肿瘤突变负荷(TMB)状态和化疗反应。最后,我们在GEPIA数据库和人体组织标本中验证了我们的结果。

结果

建立了一个六基因套索回归模型(载脂蛋白D(APOD)、钙蛋白酶6(CAPN6)、磷脂酰肌醇蛋白聚糖3(GPC3)、丙酮酸脱氢酶激酶4(PDK4)、溶质载体家族7成员2(SLC7A2)、腱生蛋白C(SVEP1))。结果显示,活化的CD4+T细胞和滤泡性T细胞在低风险组中浸润更广泛。低风险组的TMB显著更高,预后更好,更适合免疫治疗。

结论

我们构建了一个六基因BM相关预后模型,用于预测GC的预后、免疫细胞浸润、TMB状态和化疗反应。本研究为开发更有效的GC患者个体化治疗提供了新思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca3/10252969/b3af000054c2/diagnostics-13-01844-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca3/10252969/88637897abf7/diagnostics-13-01844-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca3/10252969/5486a361c8cb/diagnostics-13-01844-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca3/10252969/8bd9d4708dd3/diagnostics-13-01844-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca3/10252969/85c05598a183/diagnostics-13-01844-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ca3/10252969/b3af000054c2/diagnostics-13-01844-g010.jpg

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Single-cell sequencing analysis reveals gastric cancer microenvironment cells respond vastly different to oxidative stress.单细胞测序分析揭示了胃癌微环境细胞对氧化应激的反应有很大的不同。
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Medicine (Baltimore). 2023 Sep 29;102(39):e35027. doi: 10.1097/MD.0000000000035027.
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