卵巢癌(OC)是世界上最致命的妇科恶性肿瘤，免疫疗法正成为一种有前景的治疗方法。免疫表型得分(IPS)是一种强大的生物标记，可以区分对免疫疗法敏感的患者。本研究旨在构建一个预后模型，用于预测全身生存率(OS)并鉴定可能从免疫疗法中获益的患者。首先，我们合并了癌症基因组图谱(TCGA)和癌症免疫图谱(TCIA)数据集，并将229个OC样本纳入训练队列。验证队列包括来自基因表达库(GEO)队列的240个OC样本。训练队列被分成高和低IPS亚组，以获得差异表达基因(DEGs)。通过单变量Cox回归分析鉴定了与OS相关的DEGs。Least absolute shrinkage and selection operator(LASSO)Cox回归被用于构建预后模型。然后，进行免疫和突变分析，探索模型与肿瘤微环境(TME)和肿瘤突变负担(TMB)之间的关系。在高和低IPS亚组之间获得了83个DEGs，在其中17个DEGs与OS相关。选择了五个关键基因建立预后模型，该模型对预测OS具有较高的准确性，可作为独立的生存指标。通过风险评分将OC样本分为不同的组，显示出不同的免疫状态、TME、TMB、免疫疗法反应和化疗敏感性。在GEO队列中验证了类似的结果。我们开发了与TME相关的免疫表型得分签名，用于预测OC的OS和对免疫疗法的反应。© 2023年作者。由美国化学学会出版。

Ovarian cancer (OC) is the deadliest gynecological malignancy in the world, and immunotherapy is emerging as a promising treatment. Immunophenoscore (IPS) is a robust biomarker distinguishing sensitive responders from immunotherapy. In this study, we aimed to construct a prognostic model for predicting overall survival (OS) and identifying patients who would benefit from immunotherapy. First, we combined The Cancer Genome Atlas (TCGA) and The Cancer Immune Atlas (TCIA) data sets and incorporated 229 OC samples into a training cohort. The validation cohort included 240 OC samples from the Gene Expression Omnibus (GEO) cohort. The training cohort was divided into high- and low-IPS subgroups to obtain differentially expressed genes (DEGs). DEGs with OS were identified by Univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the prognostic model. Then, immune and mutation analyses were performed to explore the relationship between the model and the tumor microenvironment (TME) and tumor mutation burden (TMB). Eighty-three DEGs were obtained between the high-and low-IPS subgroups, where 17 DEGs were associated with OS. The five essential genes were selected to establish the prognostic model, which showed high accuracy for predicting OS and could be an independent survival indicator. OC samples that were divided by risk scores showed distinguished immune status, TME, TMB, immunotherapy response, and chemotherapy sensitivity. Similar results were validated in the GEO cohort. We developed an immunophenoscore-related signature associated with the TME to predict OS and response to immunotherapy in OC.© 2023 The Authors. Published by American Chemical Society.