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线粒体标志物可预测乳腺癌患者的复发、转移及他莫昔芬耐药性:通过伴随诊断早期发现治疗失败情况。

Mitochondrial markers predict recurrence, metastasis and tamoxifen-resistance in breast cancer patients: Early detection of treatment failure with companion diagnostics.

作者信息

Sotgia Federica, Fiorillo Marco, Lisanti Michael P

机构信息

Translational Medicine, School of Environment & Life Sciences, University of Salford, Greater Manchester, United Kingdom.

The Department of Pharmacy, Health and Nutritional Sciences, The University of Calabria, Cosenza, Italy.

出版信息

Oncotarget. 2017 Jul 27;8(40):68730-68745. doi: 10.18632/oncotarget.19612. eCollection 2017 Sep 15.

Abstract

Here, we used a data-mining and informatics approach to discover new biomarkers of resistance to hormonal therapy in breast cancer. More specifically, we investigated whether nuclear-encoded genes associated with mitochondrial biogenesis can be used to predict tumor recurrence, distant metastasis and treatment failure in high-risk breast cancer patients. Overall, this strategy allowed us to directly provide validation of the prognostic value of these mitochondrial components in large and clinically relevant patient populations, with >15 years of follow-up data. For this purpose, we employed a group of 145 ER(+) luminal A breast cancer patients, with lymph-node (LN) metastasis at diagnosis, that were treated with tamoxifen, but not any chemotherapy agents. Using this approach, we identified >60 new individual mitochondrial biomarkers that predicted treatment failure and tumor recurrence, with hazard-ratios (HR) of up to 4.17 (=2.2e-07). These include mitochondrial chaperones (HSPD1, HSPA9), membrane proteins (VDAC2, TOMM70A) and anti-oxidants (SOD2), as well as 18 different mitochondrial ribosomal proteins (MRPs) and >20 distinct components of the OXPHOS complexes. In addition, we combined 4 mitochondrial proteins (HSPD1, UQCRB, MRPL15, COX17), to generate a compact mitochondrial gene signature, associated with a HR of 5.34 (=1e-09). This signature also successfully predicted distant metastasis and was effective in larger groups of ER(+) (=2,447), basal (=540) and HER2(+) (=193) breast cancers. It was also effective in all breast cancers (=3,180), if considered together as a single group. Based on this analysis, we conclude that mitochondrial biogenesis should be considered as a new therapeutic target for overcoming tumor recurrence, distant metastasis and treatment failure in patients with breast cancer. In summary, we identified individual mitochondrial biomarkers and 2 compact mitochondrial gene signatures that can be used to predict tamoxifen-resistance and tumor recurrence, at their initial diagnosis, in patients with advanced breast cancer. In the long-term, these mitochondrial biomarkers could provide a new companion diagnostics platform to help clinicians to accurately predict the response to hormonal therapy in ER(+) breast cancer patients, facilitating more personalized and effective treatment. Similarly, these mitochondrial markers could be used as companion diagnostics, to determine which breast cancer patients would benefit most from clinical treatments with mitochondrially-targeted anti-cancer therapeutics. Finally, we also showed that these mitochondrial markers are superior when directly compared with conventional biomarkers, such as Ki67 and PCNA.

摘要

在此,我们采用数据挖掘和信息学方法来发现乳腺癌激素治疗耐药的新生物标志物。更具体地说,我们研究了与线粒体生物发生相关的核编码基因是否可用于预测高危乳腺癌患者的肿瘤复发、远处转移和治疗失败。总体而言,这一策略使我们能够在具有超过15年随访数据的大量且具有临床相关性的患者群体中,直接验证这些线粒体成分的预后价值。为此,我们选取了145例ER(+) 腔面A型乳腺癌患者,这些患者在诊断时伴有淋巴结(LN)转移,接受了他莫昔芬治疗,但未接受任何化疗药物。通过这种方法,我们鉴定出60多种新的个体线粒体生物标志物,它们可预测治疗失败和肿瘤复发,风险比(HR)高达4.17(=2.2e - 07)。这些标志物包括线粒体伴侣蛋白(HSPD1、HSPA9)、膜蛋白(VDAC2、TOMM70A)和抗氧化剂(SOD2),以及18种不同的线粒体核糖体蛋白(MRP)和20多种不同的氧化磷酸化复合物成分。此外,我们将4种线粒体蛋白(HSPD1、UQCRB、MRPL15、COX17)组合起来,生成了一个紧密的线粒体基因特征,其风险比为5.34(=1e - 09)。这一特征还成功预测了远处转移,并且在更大规模的ER(+)(=2447例)、基底样(=540例)和HER2(+)(=193例)乳腺癌患者群体中有效。如果将所有乳腺癌患者(=3180例)视为一个单一群体,它同样有效。基于这一分析,我们得出结论,线粒体生物发生应被视为克服乳腺癌患者肿瘤复发、远处转移和治疗失败的新治疗靶点。总之,我们鉴定出了个体线粒体生物标志物和2个紧密的线粒体基因特征,可用于在晚期乳腺癌患者初次诊断时预测他莫昔芬耐药和肿瘤复发。从长远来看,这些线粒体生物标志物可为临床医生提供一个新的伴随诊断平台,以帮助他们准确预测ER(+)乳腺癌患者对激素治疗的反应,从而促进更个性化和有效的治疗。同样,这些线粒体标志物可作为伴随诊断工具,以确定哪些乳腺癌患者将从线粒体靶向抗癌治疗的临床治疗中获益最大。最后,我们还表明,与传统生物标志物如Ki67和PCNA直接比较时,这些线粒体标志物更具优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47e6/5620292/7fd9346b7c53/oncotarget-08-68730-g001.jpg

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