Department of Obstetrics and Gynecology, Donggang Branch, The First Hospital of Lanzhou University, Gansu Lanzhou, China.
Medical Security Service Center of Pingchuan District, Gansu Baiyin, China.
Medicine (Baltimore). 2023 Sep 1;102(35):e34851. doi: 10.1097/MD.0000000000034851.
Studies have shown that aging significantly impacts tumorigenesis, survival outcome, and treatment efficacy in various tumors, covering high-grade serous ovarian cancer (HGSOC). Therefore, the objective for this investigation is to construct an aging-relevant risk signature for the first time, which will help evaluate the immunogenicity and survival status for patients with HGSOC. Totaling 1727 patients with HGSOC, along with their mRNA genomic data and clinical survival data, were obtained based on 5 independent cohorts. The Lasso-Cox regression model was utilized to identify the aging genes that had the most significant impact on prognosis. The risk signature was developed by integrating the determined gene expression and accordant model weights. Additionally, immunocytes in the microenvironment, signaling pathways, and immune-relevant signatures were assessed based on distinct risk subgroups. Finally, 2 cohorts that underwent treatment with immune checkpoint inhibitor (ICI) were employed to confirm the effects of identified risk signature on ICI efficacy. An aging signature was constructed from 12 relevant genes, which showed improved survival outcomes in low-risk HGSOC patients across discovery and 4 validation cohorts (all P < .05). The low-risk subgroup showed better immunocyte infiltration and higher enrichment of immune pathways and ICI predictors based on further immunology analysis. Notably, in the immunotherapeutic cohorts, low-risk aging signature was observed to link to better immunotherapeutic outcomes and increased response rates. Together, our constructed signature of aging has the potential to assess not only the prognosis outcome and immunogenicity, but also, importantly, the efficacy of ICI treatment. This signature provides valuable insights for prognosis prediction and immunotherapeutic effect evaluation, ultimately promoting individualized treatment for HGSOC patients.
研究表明，衰老在多种肿瘤中显著影响肿瘤发生、生存结局和治疗效果，包括高级别浆液性卵巢癌（HGSOC）。因此，本研究旨在首次构建与衰老相关的风险特征，以帮助评估 HGSOC 患者的免疫原性和生存状况。共纳入了 1727 名 HGSOC 患者，以及他们的 mRNA 基因组数据和临床生存数据，这些数据来源于 5 个独立的队列。利用 Lasso-Cox 回归模型来确定对预后影响最大的衰老基因。通过整合确定的基因表达和一致的模型权重来开发风险特征。此外，根据不同的风险亚组评估了微环境中的免疫细胞、信号通路和免疫相关特征。最后，使用了 2 个接受免疫检查点抑制剂（ICI）治疗的队列来验证鉴定的风险特征对 ICI 疗效的影响。从 12 个相关基因中构建了一个衰老特征，该特征在发现和 4 个验证队列中显示出低风险 HGSOC 患者的生存结果得到改善（均 P<0.05）。进一步的免疫分析显示，低风险亚组的免疫细胞浸润更好，免疫途径和 ICI 预测因子的富集程度更高。值得注意的是，在免疫治疗队列中，低风险的衰老特征与更好的免疫治疗结果和更高的应答率相关。总之，我们构建的衰老特征不仅可以评估预后结果和免疫原性，还可以评估免疫检查点抑制剂治疗的效果。该特征为预后预测和免疫治疗效果评估提供了有价值的见解，最终为 HGSOC 患者的个体化治疗提供了帮助。
