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单细胞和批量 RNA 测序揭示 SPINK1 和 TIMP1 作为上皮细胞标记基因与结直肠癌生存和肿瘤免疫微环境特征相关

英文原题:Single-Cell and Bulk RNA Sequencing Reveal SPINK1 and TIMP1 as Epithelial Cell Marker Genes Linked to Colorectal Cancer Survival and Tumor Immune Microenvironment Profiles.

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Single-Cell and Bulk RNA Sequencing Reveal SPINK1 and TIMP1 as Epithelial Cell Marker Genes Linked to Colorectal Cancer Survival and Tumor Immune Microenvironment Profiles.

PubMed 2025/12/11(内容时间) Int J Mol Sci Q1 · IF 5.6(JCR 2025)

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中文摘要

结直肠癌(CRC)是癌症死亡的主要原因,肿瘤微环境和基因表达影响预后。识别与生存相关的上皮标志基因(EMG)可能改善预后评估并指导治疗。

我们从TISCH数据库获取了CRC患者的单细胞RNA测序(scRNA-seq)数据(n = 23,176个细胞),通过差异表达分析识别EMG。这些EMG与恶性细胞标志物取交集。

我们使用TCGA-COAD的bulk RNA-seq数据(n = 375)通过单因素Cox分析评估EMG的预后价值,随后进行LASSO回归。显著基因通过多因素Cox模型进行评估。开发了基于EMG的风险评分,并使用GSE39582(n = 585)和GSE17536(n = 177)进行验证。使用xCELL和TIMER算法评估免疫浸润。共识别出107个EMG并在TCGA数据中进行评估。Cox分析识别出18个与生存相关的EMG,经LASSO缩小至SPINK1和TIMP1。

多因素分析证实SPINK1(HR: 0.88, 95% CI: 0.79-0.97, p = 0.009)和TIMP1(HR: 1.66, 95% CI: 1.29-2.13, p < 0.001)为独立生存预测因子。患者被分为高风险组(n = 187)和低风险组(n = 188)。低风险组的总生存期和无病生存期均显著更优。免疫谱分析揭示了不同的模式,高风险组显示更高的树突状细胞、记忆T细胞、巨噬细胞和免疫检查点表达,而低风险组显示NK细胞、浆细胞和CD4+ T辅助细胞的富集。这些发现在GSE39582和GSE17536队列中得到验证。EMG在CRC中具有预后价值,SPINK1和TIMP1为独立生存预测因子。不同的免疫模式支持将EMG与免疫谱分析整合,以改善风险分层和个性化治疗。

展开英文摘要原文

Colorectal cancer (CRC) is a major cause of cancer death, with the tumor microenvironment and gene expression influencing outcomes. Identifying survival-associated epithelial marker genes (EMGs) may improve prognosis and guide therapy.

We obtained single-cell RNA-sequencing (scRNA-seq) data from CRC patients ( n = 23,176 cells) from the TISCH database to identify EMGs through differential expression analysis. These were intersected with malignant cell markers.

We used bulk RNA-seq data from TCGA-COAD ( n = 375) to assess EMG prognostic value via univariable Cox analysis, followed by LASSO regression. Significant genes were evaluated using multivariable Cox models. An EMGs-based risk score was developed and validated using GSE39582 ( n = 585) and GSE17536 ( n = 177). Immune infiltration was assessed using xCELL and TIMER algorithms. A total of 107 EMGs were identified and assessed in TCGA data. Cox analysis identified 18 survival-related EMGs, which were narrowed by LASSO to SPINK1 and TIMP1. Multivariable analysis confirmed SPINK1 (HR: 0.

88, 95% CI: 0. 79-0. 97, p = 0. 009) and TIMP1 (HR: 1. 66, 95% CI: 1. 29-2. 13, p < 0. 001) as independent survival predictors. Patients were classified into high- ( n = 187) and low-risk ( n = 188) groups. The low-risk group had significantly better overall and disease-free survival. Immune profiling revealed distinct patterns, where the high-risk group showed higher dendritic cells, memory T-cells, macrophages, and immune checkpoint expression, while the low-risk group showed enrichment of NK cells, plasma cells, and CD4+ T-helper cells.

These findings were validated in the GSE39582 and GSE17536 cohorts. EMGs have prognostic value in CRC, with SPINK1 and TIMP1 as independent survival predictors. Distinct immune patterns support integrating EMGs with immune profiling for improved risk stratification and personalized treatment.

论文信息

作者
Al-Bzour NN、Abu-Rjai' ZN、Al-Bzour AN、Qasaymeh A、Saeed A、Saeed A
第一作者单位
Department of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.Jordan
通讯作者单位
Department of Pathology and Laboratory Medicine, University of Vermont Medical Center, Burlington, VT 05401, USA.United States
期刊
International journal of molecular sciences2025 Dec 11
原文标识
PubMed 41465391 · DOI 10.3390/ijms262411964