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KNTC1 和 PRC1 界定脂肪肉瘤的免疫抑制微环境与不良预后

英文原题:KNTC1 and PRC1 define an immunosuppressive microenvironment and poor prognosis in liposarcoma.

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KNTC1 and PRC1 define an immunosuppressive microenvironment and poor prognosis in liposarcoma.

PubMed 2026/01/09(内容时间) Eur J Med Res Q2 · IF 4.8(JCR 2025)

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研究概要

我们构建了一个稳健的双基因预后模型,可有效预测生存、反映肿瘤免疫微环境异质性,并区分 LPS 的病理亚型。

中文摘要

脂肪肉瘤(LPS)是一种高度异质性的恶性软组织肿瘤。肿瘤微环境免疫特征会显著影响癌症进展和治疗效果,但LPS中用于预后评估、反映肿瘤免疫微环境特征且具有诊断潜力的免疫相关生物标志物仍研究不足。

从GEO和TCGA数据库下载脂肪肉瘤患者RNA测序数据及临床信息。使用limma软件包进行差异表达基因(DEG)分析,并采用加权基因共表达网络分析(WGCNA)识别脂肪肉瘤相关模块。根据既往免疫特征,通过单样本基因集富集分析(ssGSEA)计算28种TIL(肿瘤浸润淋巴细胞)亚群富集评分;随后使用ConsensusClusterPlus进行一致性聚类,并结合LASSO和多变量Cox回归构建风险模型。还采用ESTIMATE算法评估免疫浸润、clusterProfiler进行功能富集分析、survival分析预后差异、timeROC进行受试者工作特征(ROC)分析,并开展划痕愈合和Transwell实验。

差异表达分析获得脂肪肉瘤与癌旁样本间852个DEG;WGCNA确定turquoise模块为脂肪肉瘤相关基因模块。基于免疫特征的一致性聚类将患者分为免疫高(H)和免疫低(L)亚型,生存结局存在显著差异。结合上述发现,通过LASSO和Cox回归构建由KNTC1和PRC1组成的稳健双基因预后特征,两种模型基因诊断表现突出(AUC>0.9)。高RiskScore与侵袭性病理亚型、转移和免疫抑制性微环境显著相关,整体免疫浸润较低;低危患者则免疫细胞丰度和活性较高。功能验证确认,沉默KNTC1可显著抑制LPS细胞迁移和侵袭,支持其参与肿瘤进展。

研究建立了稳健的双基因预后模型,可有效预测生存、反映肿瘤免疫微环境异质性并区分LPS病理亚型,为预后分层和个体化治疗策略提供了有价值的见解。

展开英文摘要原文

Liposarcomas (LPS) is a highly heterogeneous malignant soft tissue tumor. Tumor microenvironment immune traits critically affect cancer progression and treatment efficacy. However, immune-related biomarkers for prognostic assessment, reflecting tumor immune microenvironment features and with diagnostic potential, remain insufficiently explored in LPS.

The RNA-seq data and clinical information of patients with liposarcoma were downloaded from the GEO and TCGA database. The "limma" package performed the differential expression genes (DEGs) analysis, and the weighted gene co-expression network analysis (WGCNA) method was used to identify the liposarcoma-related module. We performed the single sample gene set enrichment analysis (ssGSEA) to calculate the enrichment scores for 28 tumor-infiltrating lymphocyte (TIL) subpopulations based on previously established immune signatures. Then, the consensus clustering was conducted using the "ConsensusClusterPlus" package. After that, the lasso and multivariate Cox regression analysis was applied for the risk model construction. The ESTIMATE algorithm for immune infiltration, "clusterProfiler" for function enrichment, "survival" for prognostic difference and "timeROC" for receiver operator characteristic curve (ROC) analysis were performed. The wound healing and transwell assay were conducted.

After differential expression analysis, 852 DEGs between liposarcoma and para-cancer samples were obtained, and the turquoise was the liposarcoma-related gene module through WGCNA analysis. Consensus clustering based on immune signatures stratified patients into immunity-high (H) and immunity-low (L) subtypes with significant survival differences. Integration of these findings led to a robust 2-gene prognostic signature (KNTC1 and PRC1) via LASSO and Cox regression. Both model genes exhibited outstanding diagnostic performance (AUC > 0.9). High RiskScore was significantly associated with aggressive pathological subtypes, metastasis, and an immunosuppressive microenvironment characterized by lower overall immune infiltration. Conversely, low-risk patients showed enhanced immune cell abundance and activity. In addition, functional validation confirmed that KNTC1 silencing significantly impaired LPS cell migration and invasion, underscoring its role in tumor progression.

We constructed a robust two-gene prognostic model that effectively predicts survival, reflects tumor immune microenvironment heterogeneity, and distinguishes pathological subtypes in LPS. Our findings provided valuable insights for prognostic stratification and personalized treatment strategies.

论文信息

作者
Zhang L、Fang X、Yang Z、Zhang M、Ma Y、Li P
第一作者单位
Department of Integrated Traditional and Western Medicine, The First Affiliated Hospital, College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003, China.China
通讯作者单位
Department of Gastrointestinal Surgery, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang, 471003, China. lph0819@163.com.China
期刊
European journal of medical research2026 Jan 9
原文标识
PubMed 41514406 · DOI 10.1186/s40001-025-03703-z