趋化因子表达谱预测胰腺腺癌患者的总生存期和免疫浸润情况

Xinyu Peng, Shengnan Lv, Yuxiang Fan, Jian Zhang, Huan Liu, Yan Liu, Feng Wei
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摘要

人类趋化因子与肿瘤存活有关,并在胰腺腺癌(PAAD)微环境中发挥关键作用。目前尚不清楚趋化因子的异常表达是否与 PAAD 的预后特征有关。因此,本研究探讨了趋化因子在 PAAD 中的基因改变谱,并构建了基于趋化因子家族的预后特征(CPS)。 研究人员从癌症基因组图谱(TCGA)数据库中获取了176例PAAD患者的RNA-Seq和临床数据。生物信息学分析工具用于评估趋化因子的表达和预后价值。利用无监督分层聚类获得了影响患者生存的概况,并构建了趋化因子相关基因的预后模型,以探索免疫格局。 29种趋化因子在PAAD组织中高表达,其中10种与预后不良显著相关。通过层次聚类,将 PAAD 患者分为两组。高水平的趋化因子表明预后较差(HR=5.4,CI=1.7-17,P=0.004)。使用最小绝对缩小和选择算子(LASSO)和逐步多变量 Cox 分析法构建了包含 7 个枢纽基因的 CPS。该特征将 PAAD 患者分为高危和低危两组,并被证实是一个独立的预后因素。ESTIMATE评分和TIMER2.0分析进一步反映了PAAD的免疫特征,即局部免疫细胞浸润的比例较高,以抑制性细胞为主。 这是首个基于趋化因子家族的 PAAD 患者预后预测模型。我们的工作强调了了解趋化因子对 PAAD 发生的作用机制的必要性。
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Chemokine expression profiles predict overall survival and immune infiltration in patients with pancreatic adenocarcinoma
Human chemokines are linked to tumour survival and perform a critical role in the pancreatic adenocarcinoma (PAAD) microenvironment. It is not known if abnormal expression of chemokines contributes to the prognostic features of PAAD. Therefore, this study explored gene alteration profiles of chemokines in PAAD and constructed a chemokine family-based prognosis signature (CPS). RNA-Seq and clinical data from 176 PAAD patients were obtained from The Cancer Genome Atlas (TCGA) database. Bioinformatics analysis tools were used to assess the expression and prognostic value of chemokines. A profile affecting patient survival was obtained using unsupervised hierarchical clustering and a prognostic model of chemokine-related genes was constructed to explore the immune landscape. 29 chemokines were highly expressed in PAAD tissues, and 10 were significantly associated with poor prognosis. Hierarchical clustering resulted in the classification of the PAAD cohort into 2 clusters. High levels of chemokines indicated a worse prognosis (for HR=5.4, CI=1.7-17, P=0.004). A CPS containing 7 hub genes was constructed using the least absolute shrinkage and selection operator (LASSO) and stepwise multivariable Cox analysis. This signature separated PAAD patients into high and low risk groups and was confirmed as an independent prognostic factor. An ESTIMATE score and TIMER2.0 analysis further reflected the immune profile of PAAD, which had a higher percentage of localized immune cell infiltration with predominantly suppressive cells. This is the first chemokine family-based model for predicting outcomes in PAAD patients. Our work highlights the need to understand the mechanism of chemokine contributions to PAAD occurrence.
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