Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients
Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients
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DOI：
10.1186/s12920-019-0530-7
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发表时间：
2019-05-30
影响因子：
2.7
通讯作者：
Chen, Xian
中科院分区：
文献类型：
--
作者：
Ankney, J. Astor;Xie, Ling;Chen, Xian
背景：目前，50基因表达模型(PAM50)作为乳腺癌(BC)亚型的分类器，不足以在PAM50分类的每个亚型中区分具有不同预后的患者亚群。迫切需要廉价和微创的生物标记物测试，以方便和准确地预测个人的临床结果和对治疗的反应。虽然已经开发了定量蛋白质组学方法来在体外识别/分析不同癌细胞株分泌的蛋白质(分泌组)，但缺乏这些分泌组鉴定的临床病理相关性和相关的预后价值。方法：为了寻找预测个体化预后的生物标记物，我们引入了一种新的多组学(分泌-转录组学)方法，在其癌基因分泌状态下识别BC亚型的候选标记物，其基因具有患者特有的具有预后意义的mRNA表达变化。首先，我们使用无标记定量(LFQ)蛋白质组学方法从代表主要BC亚型的一系列BC细胞系中鉴定显示BC亚型分泌的蛋白质。为了确定和外部验证这些分泌蛋白的预后价值，我们发展了一种分泌-转录方法，发现了PAM50亚型分泌相关mRNA表达模式(SeCEP)，其中在对应PAM50亚型的患者中，精选蛋白的PAM50亚型分泌与其编码基因的顺式mRNA表达统计相关。SeCEP基因的Kaplan-Meier分析用于寻找新的液体活检生物标志物来预测个体化预后。结果：mRNA表达与分泌相关(SeCEP)以PAM50亚型的方式准确地定位了多个基因，这些基因完全翻译成肿瘤活性分泌体。此外，多个SeCEP基因的不同组合或组合中的多个SeCEP基因被鉴定为“系统预后标记物”，表明在预后不良或复发风险高的PAM50亚型患者的不同亚群中，mRNA共表达模式。因此，我们的分泌转录组方法在统计上将BC亚型分泌组基因与患者特定的关于其mRNA表达变化的信息联系起来，并显著提高了临床结果或预后背景下患者分层的敏感性和特异性。结论：通过将LFQ分泌组筛选与患者数据的蛋白质转录组回顾分析相结合，我们的集成多组学方法绕过了昂贵、繁琐的全基因组钓鱼和预测建模，这通常需要将少数预后改变的基因与基因组中数千个其他非BC相关基因区分开来。
Background: Presently, a 50-gene expression model (PAM50) serves as a breast cancer (BC) subtype classifier that is insufficient to distinguish, within each single PAM50-classified subtype, patient subpopulations having different prognosis. There is a pressing need for inexpensive and minimally invasive biomarker tests to easily and accurately predict individuals' clinical outcomes and response to treatments. Although quantitative proteomic approaches have been developed to identify/profile proteins secreted (secretome) from various cancer cell lines in vitro, missing are the clinicopathological relevance and the associated prognostic value of these secretomic identifications.Methods: To discover biomarkers to predict individualized prognosis we introduce a new multi-omics (secreto-transcriptomics) method that identifies, in their oncogenically secreted states, candidate markers of BC subtypes whose genes bear patient-specific mRNA expression alterations of prognostic significance. First, we used label-free quantitative (LFQ) proteomics to identify the proteins showing BC-subtypic secretion from a series of BC cell lines representing major BC-subtypes. To determine and externally validate the prognostic value of these secreted proteins, we developed a secreto-transcriptomic approach that discovered a PAM50-subtypic Secretion-Correlated mRNA Expression Pattern (SeCEP) wherein the PAM50-subtypic secretion of select proteins statistically correlated with cis-mRNA expression of their encoding genes in patients of the corresponding PAM50-subtypes. Kaplan-Meier analysis of SeCEP genes was used to identify new liquid biopsy biomarkers for predicting individualized prognosis.Results: The mRNA expression-to-secretion correlation (SeCEP) pinpointed multiple genes that are fully translated into the oncogenically active secretome in a PAM50-subtypic manner. Further, multiple SeCEP genes in distinct combinations or panels of multiple SeCEP genes were identified as 'systems prognostic markers' that showed mRNA co-overexpression patterns in the distinct subpopulations of PAM50-subtypic patients with poor prognosis or high-risk of relapse. Thus, our secreto-transcriptomic approach statistically linked BC subtypic secretome genes with patient-specific information about their mRNA expression alterations and significantly improved the sensitivity and specificity in patient stratification in the context of clinical outcomes or prognosis.Conclusions: By combining LFQ secretome screening with proteo-transcriptomic retrospective analysis of patient data our integrated multi-omics approach bypasses costly, tedious, genome-wide fishing and predictive modeling that are commonly required to distinguish a few prognostically altered genes from thousands of other non-BC related genes in a genome.