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Dualistic classification of high grade serous ovarian carcinoma has its root in spatial heterogeneity
Journal of Advanced Research ( IF 10.7 ) Pub Date : 2022-08-28 , DOI: 10.1016/j.jare.2022.08.014
Tingting Sun 1 , Zuwei Zhang 1 , Liming Tian 1 , Yu Zheng 1 , Linxiang Wu 1 , Yunyun Guo 1 , Xiaohui Li 1 , Yuanyuan Li 1 , Hongwei Shen 1 , Yingrong Lai 2 , Junfeng Liu 2 , Huanhuan Cui 3 , Shasha He 4 , Yufeng Ren 4 , Guofen Yang 1
Affiliation  

Introduction

Widespread intra-peritoneal metastases is a main feature of high grade serous ovarian carcinoma (HGSOC). Recently, the extent of tumour heterogeneity was used to evaluate the cancer genomes among multi-regions in HGSOC. However, there is no consensus on the effect of tumour heterogeneity on the evolution of the tumour metastasis process in HGSOC.

Objectives

We performed whole-exome sequencing in multiple regions of matched primary and metastatic HGSOC specimens to reveal the genetic mechanisms of ovarian tumourigenesis and malignant progression.

Methods

63 samples (including ovarian carcinoma, omentum metastasis, and normal tissues) were used. We analyzed the genomic heterogeneity, traced the subclone dissemination and establishment history and compared the different genetic characters of cancer evolutionary models in HGSOC.

Results

We found that HGSOC had substantial intra-tumour heterogeneity (median 54.2, range 0 ∼ 106.7), high inter-patient heterogeneity (P < 0.001), but relatively limited intra-patient heterogeneity (P = 0.949). Two COSMIC mutational signatures were identified in HGSOCs: signature 3 was related to homologous recombination, and signature 1 was associated with aging. Two scenarios were identified by phylogenetic reconstruction in our study: 3 cases (33.3 %) showed star topology, and the other 6 cases (66.7 %) displayed tree topology. Compared with star topology group, more driver events were identified in tree topology group (P < 0.001), and occurred more frequently in early stage than in late stage of clonal evolution (P < 0.001). Moreover, compared with the star topology group, the tree topology group showed higher rate of intra-tumour heterogeneity (P = 0.045).

Conclusion

A dualistic classification model was proposed for the classification of HGSOC based on spatial heterogeneity, which may contribute to better managing patients and providing individual treatment for HGSOC patients.



中文翻译:

高级别浆液性卵巢癌的二元分类源于空间异质性

介绍

广泛的腹膜内转移是高级别浆液性卵巢癌 (HGSOC) 的主要特征。最近,肿瘤异质性的程度被用来评估 HGSOC 中多区域的癌症基因组。然而,对于肿瘤异质性对 HGSOC 肿瘤转移过程演变的影响,目前还没有达成共识。

目标

我们对匹配的原发性和转移性 HGSOC 标本的多个区域进行了全外显子组测序,以揭示卵巢肿瘤发生和恶性进展的遗传机制。

方法

使用了 63 个样本(包括卵巢癌、网膜转移和正常组织)。我们分析了基因组异质性,追踪了亚克隆的传播和建立历史,并比较了 HGSOC 癌症进化模型的不同遗传特征。

结果

我们发现 HGSOC 具有显着的肿瘤内异质性(中位数 54.2,范围 0 ∼ 106.7),患者间异质性高(P < 0.001),但患者内异质性相对有限(P = 0.949)。在 HGSOC 中发现了两个 COSMIC 突变特征:特征 3 与同源重组相关,特征 1 与衰老相关。在我们的研究中,通过系统发育重建确定了两种情况:3 例 (33.3%) 显示星形拓扑,其他 6 例 (66.7%) 显示树形拓扑。与星形拓扑组相比,树形拓扑组识别出更多的驱动事件(P < 0.001),并且在克隆进化早期发生的频率高于克隆进化晚期(P < 0.001)。而且,与星型拓扑组相比,

结论

提出了一种基于空间异质性的 HGSOC 分类的二元分类模型,这可能有助于更好地管理患者并为 HGSOC 患者提供个体化治疗。

更新日期:2022-08-28
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