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牛津经典链接上皮间质转化至免疫抑制与不良预后卵巢癌。

The Oxford Classic Links Epithelial-to-Mesenchymal Transition to Immunosuppression in Poor Prognosis Ovarian Cancers.

机构信息

MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, England, United Kingdom.

Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, England, United Kingdom.

出版信息

Clin Cancer Res. 2021 Mar 1;27(5):1570-1579. doi: 10.1158/1078-0432.CCR-20-2782. Epub 2021 Jan 14.

Abstract

PURPOSE

Using RNA sequencing, we recently developed the 52-gene-based Oxford classifier of carcinoma of the ovary (Oxford Classic, OxC) for molecular stratification of serous ovarian cancers (SOCs) based on the molecular profiles of their cell of origin in the fallopian tube epithelium. Here, we developed a 52-gene NanoString panel for the OxC to test the robustness of the classifier.

EXPERIMENTAL DESIGN

We measured the expression of the 52 genes in an independent cohort of prospectively collected SOC samples ( = 150) from a homogenous cohort who were treated with maximal debulking surgery and chemotherapy. We performed data mining of published expression profiles of SOCs and validated the classifier results on tissue arrays comprising 137 SOCs.

RESULTS

We found evidence of profound nongenetic heterogeneity in SOCs. Approximately 20% of SOCs were classified as epithelial-to-mesenchymal transition-high (EMT-high) tumors, which were associated with poor survival. This was independent of established prognostic factors, such as tumor stage, tumor grade, and residual disease after surgery (HR, 3.3; = 0.02). Mining expression data of 593 patients revealed a significant association between the EMT scores of tumors and the estimated fraction of alternatively activated macrophages (M2; < 0.0001), suggesting a mechanistic link between immunosuppression and poor prognosis in EMT-high tumors.

CONCLUSIONS

The OxC-defined EMT-high SOCs carry particularly poor prognosis independent of established clinical parameters. These tumors are associated with high frequency of immunosuppressive macrophages, suggesting a potential therapeutic target to improve clinical outcome.

摘要

目的

我们最近使用 RNA 测序开发了基于 52 个基因的卵巢癌牛津分类器(Oxford Classic,OxC),用于基于输卵管上皮细胞起源的分子特征对浆液性卵巢癌(SOC)进行分子分层。在这里,我们开发了一种用于 OxC 的 52 基因 NanoString 面板,以测试分类器的稳健性。

实验设计

我们在一个同质队列中前瞻性收集 SOC 样本(n=150)的独立队列中测量了 52 个基因的表达,这些患者接受了最大程度的减瘤手术和化疗。我们对 SOC 的已发表表达谱进行了数据挖掘,并在包含 137 个 SOC 的组织阵列上验证了分类器结果。

结果

我们发现 SOC 中存在明显的非遗传异质性。大约 20%的 SOC 被归类为上皮-间充质转化高(EMT-high)肿瘤,与不良预后相关。这与既定的预后因素无关,如肿瘤分期、肿瘤分级和手术后的残留疾病(HR,3.3;=0.02)。对 593 名患者的表达数据进行挖掘发现,肿瘤的 EMT 评分与估计的激活型巨噬细胞(M2)分数之间存在显著关联(<0.0001),这表明 EMT-high 肿瘤中免疫抑制与不良预后之间存在机制联系。

结论

OxC 定义的 EMT-high SOC 具有独立于既定临床参数的特别不良预后。这些肿瘤与高频率的免疫抑制性巨噬细胞相关,提示可能有治疗靶点可以改善临床结局。

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