研究动态
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一个与细胞衰老相关的特征集能够预测宫颈癌患者的预后和免疫疗法敏感性。

A Cellular Senescence-Related Signature Predicts Cervical Cancer Patient Outcome and Immunotherapy Sensitivity.

发表日期:2023 Aug 14
作者: Huijing Shao, Xia Li, Pengfei Wu, Zixi Chen, Caihong Zhang, Hang Gu
来源: GENES & DEVELOPMENT

摘要:

宫颈癌(CC)是最常见的妇科恶性肿瘤之一。CC患者的死亡率和发病率很高。细胞衰老参与肿瘤发生和癌症进展的过程。然而,细胞衰老在CC发展中的作用仍不清楚,需要进一步研究。本研究从“CellAge”数据库中获取了与细胞衰老相关的基因(CSRGs)的数据。我们使用TCGA-CESC和CGCI-HTMCP-CC数据集作为训练集和验证集。最后,我们使用“单变量”和“最小绝对收缩和选择算子”(LASSO)Cox回归分析构建了一个包含八个CSRGs的签名。利用这个签名,我们计算了训练和验证队列中所有患者的风险评分,并将其分为低风险组(LR-G)和高风险组(HR-G)。结果显示,与HR-G中的患者相比,LR-G中的患者表现出更积极的临床预后、更丰富的免疫细胞浸润和更活跃的免疫反应。这个签名还可以调节SASP因子的表达。体外研究显示,CC细胞和组织中的签名包含的SERPINE1和IL-1α基因的表达增加。我们的研究结果有助于加深对CC发病机制的认识,对临床实践中的预后预测和免疫治疗有益。© 2023. 作者。
Cervical cancer (CC) is one of the most prevalent gynecological malignancies. The rate of mortality and morbidity among patients with CC is high. Cellular senescence is involved in tumorigenesis as well as in the cancer progression. However, the involvement of cellular senescence in CC development is still unclear and requires further investigation. In this study, we retrieved data on cellular senescence-related genes (CSRGs) from the "CellAge" Database. We used the TCGA-CESC and CGCI-HTMCP-CC datasets as the training and validation sets, respectively. Finally, a signature was constructed using "univariate" and "Least Absolute Shrinkage and Selection Operator" (LASSO) Cox regression analysis, which contains eight CSRGs. Using this signature, we calculated the risk scores of all patients in the training and validation cohorts and categorized them into the low-risk group (LR-G) and the high-risk group (HR-G). Results showed that, compared to patients in the HR-G, those in the LR-G demonstrated a more positive clinical prognosis, more abundant immune cell infiltrations, and a more active immune response. The signature could also modulate the expression of SASP factors. In vitro studies showed an increased expression of SERPINE1 and IL-1α genes included in the signature in CC cells and tissues. Our findings help to deepen our insights into the etiology of CC, which could be beneficial for prognostic prediction and immunotherapy in clinical practice.© 2023. The Author(s).