Integrated scissor and CIBERSORTx analyses reveals fibroblast subpopulations and biomarkers in stomach adenocarcinoma.

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Siyi Wu, Manzhong Cai, Jiajia Cai, Yong'an Chen
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引用次数: 0

Abstract

Background: Stomach adenocarcinoma (STAD) represents a significant global health challenge, characterized by high heterogeneity in its tumor microenvironment. This study aimed to create a cell composition assessment tool and identify STAD-associated biomarkers by combined analysis of single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data.

Methods: A new signature matrix was constructed using CIBERSORTx for deconvolution analysis to gauge cell subpopulation proportions in bulk RNA-seq cohorts, followed by survival analysis to identify key cells. Weighted gene co-expression network analysis (WGCNA) was implemented to recognize key cell-related genes, which were further combined with differential expression analysis and survival analysis to determine biomarkers. Functional characterization was explored through enrichment analysis. The expression differences of biomarkers between STAD and normal groups were detected by quantitative real time polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC).

Results: Fibroblasts were identified as the cell type most associated with STAD survival, among which cell-substrate junction fibroblasts (SJFs) were identified as the key subpopulation using our custom CIBERSORTx signature matrix. In patients with STAD, low expression levels of cysteine and glycine-rich protein 1 (CSRP1), lipoma-preferred partner (LPP), Nexilin (NEXN), palladin cytoskeletal associated protein (PALLD), and transforming growth factor beta 1-induced transcript 1 (TGFB1I1) were significantly associated with higher survival rates, indicating that low expression of these biomarkers predicted favorable prognosis. Functional analysis revealed that these biomarkers were involved in oxidative phosphorylation and Wnt signaling pathways. Moreover, CSRP1, LPP, NEXN, PALLD and TGFB1I1 were significantly upregulated in STAD samples at both mRNA and protein levels.

Conclusion: Characterization of cellular composition via a custom signature matrix identified SJFs as a key subpopulation in the STAD tumor microenvironment. The identified biomarkers (CSRP1, LPP, NEXN, PALLD, and TGFB1I1) offered valuable insights into STAD microenvironment regulation. Trial registration Not applicable.

综合剪刀和CIBERSORTx分析揭示了胃腺癌中的成纤维细胞亚群和生物标志物。
背景:胃腺癌(STAD)是一项重大的全球健康挑战,其肿瘤微环境具有高度异质性。本研究旨在通过单细胞RNA测序(scRNA-seq)和大量RNA-seq数据的联合分析,建立一个细胞组成评估工具,并鉴定stad相关的生物标志物。方法:使用CIBERSORTx构建新的签名矩阵进行反卷积分析,以测量大量RNA-seq队列中的细胞亚群比例,然后进行生存分析以鉴定关键细胞。采用加权基因共表达网络分析(Weighted gene co-expression network analysis, WGCNA)识别关键细胞相关基因,并结合差异表达分析和生存分析确定生物标志物。通过富集分析探索功能表征。采用定量实时聚合酶链反应(RT-qPCR)和免疫组化(IHC)检测STAD组与正常组生物标志物的表达差异。结果:成纤维细胞被鉴定为与STAD存活最相关的细胞类型,其中细胞-基质连接成纤维细胞(SJFs)被鉴定为关键亚群,使用我们定制的CIBERSORTx签名矩阵。在STAD患者中,半胱氨酸和甘氨酸富蛋白1 (CSRP1)、脂肪瘤首选伴侣(LPP)、耐昔林(NEXN)、帕拉丁细胞骨架相关蛋白(PALLD)和转化生长因子β 1诱导转录物1 (TGFB1I1)的低表达水平与较高的生存率显著相关,表明这些生物标志物的低表达预示着良好的预后。功能分析显示,这些生物标志物参与氧化磷酸化和Wnt信号通路。此外,CSRP1、LPP、NEXN、PALLD和TGFB1I1在STAD样品中的mRNA和蛋白水平均显著上调。结论:通过定制特征矩阵表征细胞组成,确定SJFs是STAD肿瘤微环境中的关键亚群。鉴定的生物标志物(CSRP1, LPP, NEXN, pald和TGFB1I1)为STAD微环境调控提供了有价值的见解。试验注册不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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