Shin et al. Clin Proteom (2020) 17:16 https://doi.org/10.1186/s12014-020-09280-z Clinical Proteomics RESEARCH Open Access Identifcation of TUBB2A by quantitative proteomic analysis as a novel biomarker for the prediction of distant metastatic breast cancer Dongyoon Shin1†, Joonho Park2†, Dohyun Han3, Ji Hye Moon4, Han Suk Ryu4* and Youngsoo Kim1,2* Abstract Background: Metastasis of breast cancer to distal organs is fatal. However, few studies have identifed biomarkers that are associated with distant metastatic breast cancer. Furthermore, the inability of current biomarkers, such as HER2, ER, and PR, to diferentiate between distant and nondistant metastatic breast cancers accurately has necessi- tated the development of novel biomarker candidates. Methods: An integrated proteomics approach that combined flter-aided sample preparation, tandem mass tag labeling (TMT), high pH fractionation, and high-resolution MS was applied to acquire in-depth proteomic data from FFPE distant metastatic breast cancer tissues. A bioinformatics analysis was performed with regard to gene ontology and signaling pathways using diferentially expressed proteins (DEPs) to examine the molecular characteristics of dis- tant metastatic breast cancer. In addition, real-time polymerase chain reaction (RT-PCR) and invasion/migration assays were performed to validate the diferential regulation and function of our protein targets. Results: A total of 9441 and 8746 proteins were identifed from the pooled and individual sample sets, respectively. Based on our criteria, TUBB2A was selected as a novel biomarker candidate. The metastatic activities of TUBB2A were subsequently validated. In our bioinformatics analysis using DEPs, we characterized the overall molecular features of distant metastasis and measured diferences in the molecular functions of distant metastatic breast cancer between breast cancer subtypes. Conclusions: Our report is the frst study to examine the distant metastatic breast cancer proteome using FFPE tis- sues. The depth of our dataset allowed us to discover a novel biomarker candidate and a proteomic characteristics of distant metastatic breast cancer. Distinct molecular features of various breast cancer subtypes were also established. Our proteomic data constitute a valuable resource for research on distant metastatic breast cancer. Keywords: Distant metastatic breast cancer, Formalin-fxed parafn-embedded (FFPE) tissue, Biomarkers, Tandem mass tag (TMT), Quantitative proteomics Background *Correspondence: [email protected]; [email protected] Breast cancer is one of the most prevalent and lethal can- †Dongyoon Shin and Joonho Park contributed equally to this work 1 Department of Biomedical Sciences, Seoul National University College cers in women worldwide [1]. In particular, its annual of Medicine, 103 Daehakro, Seoul 30380, Korea incidence—currently 17 million cases—is increasing at 4 Department of Pathology, Seoul National University Hospital, 101 an alarming rate [2, 3]. Tere are approximately 232,000 Daehakro, Seoul 03080, Korea Full list of author information is available at the end of the article new cases of invasive breast cancer each year in the US, © The Author(s) 2020. 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The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Shin et al. Clin Proteom (2020) 17:16 Page 2 of 19 and approximately 40,000 women die each year from recent report has described a low correlation between the disease; furthermore, roughly 90% of these deaths proteomes and transcriptomes in human breast cancer are caused by the most malignant form of breast cancer: tissues, suggesting that a proteomic approach to human distant metastatic breast cancer [2, 4]. Distant metastatic BC tissues could complement a transcriptomic method breast cancer, which preferentially metastasizes to distal [29]. organs, such as the bone, liver, lung, and brain, has a poor Although proteomic studies have been performed for prognosis [5, 6]. In addition, this type of breast cancer various diseases, including breast cancer, none has inves- causes various complications at the afected sites, such tigated the overall characteristics of distant metastatic as pericardial efusion, pleural efusion, bone fracture, breast cancer [29–37, 44]. Proteomic research is expected hypercalcemia, and red blood cell anemia, which worsens to provide greater insight into the pathogenesis of distant survival outcomes [7–9]. metastatic breast cancer, generating novel information Distant metastatic breast cancer is assessed, based on about the molecular features of distant metastasis—for various factors, such as tumor size, lymphovascular inva- example, by discovering novel protein biomarkers for the sion, histological grade, nodal involvement, and hormone prediction or diagnosis of distant metastatic breast can- receptor status—all of which are independent risk fac- cer. Tus, an in-depth proteomic analysis is important for tors for distant metastatic breast cancer [10–13]. Among yielding valuable resources in distant metastatic breast these factors, breast cancer molecular subtypes are asso- cancer—data that have not been found in genomic and ciated with various patterns of distant metastatic spread transcriptomic analyses. and related to diferences in survival outcomes [10, 14]. Recent advances in mass spectrometry (MS)-based For instance, the most widely known molecular subtypes, proteomics have accelerated the development of high- such as the luminal A, luminal B, HER2, and basal-like throughput techniques for proteomic quantifcation [38, (triple-negative) groups, have site-specifc, cumulative 39]. In addition, a tandem mass tag (TMT)-based strat- metastatic incidence rates, demonstrating substantial dif- egy has facilitated relative protein quantifcation by com- ferences in the distant metastatic behavior of and overall paring the reporter ion intensities that are obtained by survival between breast cancer subtypes [10]. MS/MS. Because this approach can quantify thousands Although various risks and molecular characteristics of proteins precisely with high sensitivity, TMT-based of distant metastatic breast cancer have been established, techniques have been used widely to generate substan- the prediction and diagnosis of distant metastasis in tial datasets [40–43]. With a 6-plex TMT quantifcation breast cancer with molecular biomarkers remain largely technique, in combination with high-resolution MS, we unexamined [4–6, 10–13]. Tus, characterizing the constructed an in-depth proteomic map of distant meta- molecular signatures that are associated with distant static breast cancer. metastasis using omics-based approaches, such as In this study, we hypothesized that in-depth proteomic genomics, transcriptomics, and proteomics, might iden- data would supply important proteins to profle the tify previously overlooked biomarker candidates. molecular signatures of distant metastatic breast cancer. Many genomic or transcriptomic studies have exam- Using our proteomic techniques, we identifed by far the ined the molecular characteristics of distant meta- largest number of proteins from FFPE distant and non- static breast cancer—for instance, genes that are distant metastatic breast cancer tissues. Furthermore, we associated with lung, brain, and bone metastasis from determined important protein targets to validate distant breast tumor [15–18, 20, 21]. In addition, genetic sig- metastatic potential of breast cancer. Te function of natures that predict distant metastasis in breast cancer these targets was determined using several approaches, have been established through genomic profling [19]. including RT-PCR and invasion/migration assays. However, given the relatively low correlation between Trough our criteria to narrow down the important gene expression and protein expression, it is difcult to proteins, we discovered a novel protein biomarker can- assume that the tendencies in genomic data will trans- didate diferentially expressed in distant metastatic breast late fully to proteomic data without verifcation [22, cancer. Furthermore, we examined the distinct biologi- 23]. Similarly, considering that transcriptomic and pro- cal functions of distant metastatic breast cancer between teomic data have a moderate correlation, the molecular molecular subtypes. In summary, we have proposed the characteristics of the transcriptome could not perfectly frst protein biomarker candidate that potentially be able represent those of the proteome [24–26]. In the case to distinguish distant metastasis, derived from primary of breast cancer,