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胃癌中与免疫图谱和临床结局相关的 SLC 转运体基因的共表达模式。

Co-expression pattern of SLC transporter genes associated with the immune landscape and clinical outcomes in gastric cancer.

机构信息

Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.

出版信息

J Cell Mol Med. 2023 Dec;27(24):4181-4194. doi: 10.1111/jcmm.18003. Epub 2023 Nov 1.

DOI:10.1111/jcmm.18003
PMID:37909856
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10746955/
Abstract

Solute carrier (SLC) transporters play a dual role in the occurrence and progression of tumours by acting as both suppressors and promoters. However, the overall impact of SLC transcriptome signatures on the tumour microenvironment, biological behaviour and clinical stratification of gastric cancer has not been thoroughly investigated. Therefore, we comprehensively analysed the expression profiles of the SLC transporter family members to identify novel molecular subtypes in gastric cancer. We identified two distinct SLC subtypes, SLC-S1 and SLC-S2, using non-negative matrix factorization. These subtypes were markedly linked with the tumour microenvironment landscape, biological pathway activation and distinct clinical features of gastric cancer. Furthermore, a new scoring model, the SLC score, was developed to quantify the SLC subtypes. High SLC scores indicated a pattern of 'SLC-S2', characterized by stromal infiltration and activation, poor prognosis and insensitivity to chemotherapy and immunotherapy, but high sensitivity to imatinib. The SLC score could serve as a supplement to the Tumour Node Metastasis (TNM) staging system to guide personalized treatment strategies and predict prognosis for patients with gastric cancer.

摘要

溶质载体 (SLC) 转运蛋白通过充当抑制剂和促进剂在肿瘤的发生和进展中发挥双重作用。然而,SLC 转录组特征对胃癌肿瘤微环境、生物学行为和临床分层的总体影响尚未得到彻底研究。因此,我们全面分析了 SLC 转运蛋白家族成员的表达谱,以确定胃癌中的新型分子亚型。我们使用非负矩阵分解鉴定了两种不同的 SLC 亚型,SLC-S1 和 SLC-S2。这些亚型与肿瘤微环境景观、生物途径激活和胃癌的独特临床特征明显相关。此外,开发了一种新的评分模型,即 SLC 评分,用于量化 SLC 亚型。高 SLC 评分表示“ SLC-S2”模式,其特征为基质浸润和激活、预后不良以及对化疗和免疫治疗不敏感,但对伊马替尼敏感。SLC 评分可以作为肿瘤淋巴结转移 (TNM) 分期系统的补充,以指导胃癌患者的个体化治疗策略和预测预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/f951b7d3b49b/JCMM-27-4181-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/33e628e7527f/JCMM-27-4181-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/fc0703e1c648/JCMM-27-4181-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/e1602bf6a5ab/JCMM-27-4181-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/c500e164e14e/JCMM-27-4181-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/94023ce4150a/JCMM-27-4181-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/f951b7d3b49b/JCMM-27-4181-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/33e628e7527f/JCMM-27-4181-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/fc0703e1c648/JCMM-27-4181-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/e1602bf6a5ab/JCMM-27-4181-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/c500e164e14e/JCMM-27-4181-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/94023ce4150a/JCMM-27-4181-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef4b/10746955/f951b7d3b49b/JCMM-27-4181-g004.jpg

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