Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations.
Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations.
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通过追踪线粒体DNA突变的演变描绘卵巢癌的转移模式
DOI：
10.1038/s12276-023-01011-2
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发表时间：
2023-07
影响因子：
12.8
通讯作者：
Xing, Jinliang
中科院分区：
文献类型：
--
作者：
Xu, Zhiyang;Zhou, Kaixiang;Wang, Zhenni;Liu, Yang;Wang, Xingguo;Gao, Tian;Xie, Fanfan;Yuan, Qing;Gu, Xiwen;Liu, Shujuan;Xing, Jinliang
卵巢癌（OC）是最致命的妇科肿瘤，其特点是高转移率。准确描述转移模式的挑战极大地限制了OC患者治疗的改善。越来越多的研究利用线粒体DNA（mtDNA）突变作为肿瘤克隆性的有效谱系追踪标记。我们应用多区域采样和高深度mtDNA测序来确定晚期OC患者的转移模式。从35例OC患者的195例原发性和200例转移性肿瘤组织样本中分析了体细胞mtDNA突变。我们的研究结果显示了显着的样本水平和患者水平的异质性。此外，在原发性和转移性OC组织中观察到不同的mtDNA突变模式。进一步的分析确定了原发性和转移性OC组织中共享和私有突变之间的不同突变谱。基于mtDNA突变计算的克隆性指数分析支持16例双侧卵巢癌患者中14例的单克隆肿瘤起源。值得注意的是，基于mtDNA的空间系统发育分析揭示了OC转移的不同模式，其中线性转移模式表现出低程度的mtDNA突变异质性和短的进化距离，而平行转移模式则表现出相反的趋势。此外，定义了与不同转移模式相关的基于mtDNA的肿瘤进化评分（MTEs）。我们的数据显示，患有不同MTES的患者对减瘤手术和化疗的联合反应不同。最后，我们观察到肿瘤源性mtDNA突变在腹水中比在血浆样本中更容易检测到。我们的研究提出了一个明确的观点，OC转移模式，这揭示了有效的治疗OC患者。线粒体DNA的分析为癌症扩散（转移）提供了新的见解，这可能导致更准确的诊断，并为更好的治疗方案的选择提供信息。线粒体携带着自己的DNA，它以比染色体DNA高得多的速度积累突变。这些突变对于追踪细胞谱系非常有用。由中国西安第四军医大学的Jinliang Xing和Shujuan Liu领导的研究人员已经表明，这些变化也可以提供对肿瘤进展的见解。他们分析了35名卵巢癌患者的样本，揭示了原发性卵巢肿瘤和转移性肿瘤的突变谱之间的明显差异。与原发组织差异特别大的转移瘤对治疗的反应更差。未来的线粒体分析可以更好地了解转移性扩散和侵袭性癌症的治疗。
Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients. Analysis of mitochondrial DNA offers new insights into cancer spread (metastasis) that could lead to more accurate prognoses and inform selection of better treatment regimens. Mitochondria carry their own DNA, which accumulates mutations at a far higher rate than does chromosomal DNA. These mutations can be extremely useful for tracing cellular lineages. Researchers led by Jinliang Xing and Shujuan Liu at the Fourth Military Medical University in Xi’an, China, have shown that these changes can also provide insights on tumor progression. They analyzed samples from 35 patients with ovarian cancer, revealing distinct differences between the mutational profiles of primary ovarian tumors and metastatic growths. Metastases that differed especially strongly from primary tissue responded more poorly to treatment. Future mitochondrial analyses could yield a better understanding of metastatic spread and the treatment of aggressive cancers.
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影响因子：
30.8
作者：
Blakely CM;Watkins TBK;Wu W;Gini B;Chabon JJ;McCoach CE;McGranahan N;Wilson GA;Birkbak NJ;Olivas VR;Rotow J;Maynard A;Wang V;Gubens MA;Banks KC;Lanman RB;Caulin AF;St John J;Cordero AR;Giannikopoulos P;Simmons AD;Mack PC;Gandara DR;Husain H;Doebele RC;Riess JW;Diehn M;Swanton C;Bivona TG
通讯作者：
Bivona TG
影响因子：
7.7
作者：
Ju YS;Alexandrov LB;Gerstung M;Martincorena I;Nik-Zainal S;Ramakrishna M;Davies HR;Papaemmanuil E;Gundem G;Shlien A;Bolli N;Behjati S;Tarpey PS;Nangalia J;Massie CE;Butler AP;Teague JW;Vassiliou GS;Green AR;Du MQ;Unnikrishnan A;Pimanda JE;Teh BT;Munshi N;Greaves M;Vyas P;El-Naggar AK;Santarius T;Collins VP;Grundy R;Taylor JA;Hayes DN;Malkin D;ICGC Breast Cancer Group;ICGC Chronic Myeloid Disorders Group;ICGC Prostate Cancer Group;Foster CS;Warren AY;Whitaker HC;Brewer D;Eeles R;Cooper C;Neal D;Visakorpi T;Isaacs WB;Bova GS;Flanagan AM;Futreal PA;Lynch AG;Chinnery PF;McDermott U;Stratton MR;Campbell PJ
通讯作者：
Campbell PJ
影响因子：
14.9
作者：
Mikhailova, Alina G.;Mikhailova, Alina A.;Ushakova, Kristina;Tretiakov, Evgeny O.;Iliushchenko, Dmitrii;Shamansky, Victor;Lobanova, Valeria;Kozenkov, Ivan;Efimenko, Bogdan;Yurchenko, Andrey A.;Kozenkova, Elena;Zdobnov, Evgeny M.;Makeev, Vsevolod;Yurov, Valerian;Tanaka, Masashi;Gostimskaya, Irina;Fleischmann, Zoe;Annis, Sofia;Franco, Melissa;Wasko, Kevin;Denisov, Stepan;Kunz, Wolfram S.;Knorre, Dmitry;Mazunin, Ilya;Nikolaev, Sergey;Fellay, Jacques;Reymond, Alexandre;Khrapko, Konstantin;Gunbin, Konstantin;Popadin, Konstantin
通讯作者：
Popadin, Konstantin
影响因子：
7.3
作者：
Bashashati, Ali;Ha, Gavin;Tone, Alicia;Ding, Jiarui;Prentice, Leah M.;Roth, Andrew;Rosner, Jamie;Shumansky, Karey;Kalloger, Steve;Senz, Janine;Yang, Winnie;McConechy, Melissa;Melnyk, Nataliya;Anglesio, Michael;Luk, Margaret T. Y.;Tse, Kane;Zeng, Thomas;Moore, Richard;Zhao, Yongjun;Marra, Marco A.;Gilks, Blake;Yip, Stephen;Huntsman, David G.;McAlpine, Jessica N.;Shah, Sohrab P.
通讯作者：
Shah, Sohrab P.
影响因子：
6.4
作者：
Khalique, Lalarukh;Ayhan, Ayse;Ramus, Susan J.
通讯作者：
Ramus, Susan J.