Quintero et al. BMC Cancer (2017) 17:727 DOI 10.1186/s12885-017-3726-2 RESEARCH ARTICLE Open Access Guanylate-binding protein-1 is a potential new therapeutic target for triple-negative breast cancer Melissa Quintero1†, Douglas Adamoski1,3†, Larissa Menezes dos Reis1,3†, Carolline Fernanda Rodrigues Ascenção1,3, Krishina Ratna Sousa de Oliveira1,3, Kaliandra de Almeida Gonçalves1, Marília Meira Dias1, Marcelo Falsarella Carazzolle2 and Sandra Martha Gomes Dias1* Abstract Background: Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expression (ESR and PGR, respectively) and an absence of human epithelial growth factor receptor (ERBB2) amplification. Approximately 15–20% of breast malignancies are TNBC. Patients with TNBC often have an unfavorable prognosis. In addition, TNBC represents an important clinical challenge since it does not respond to hormone therapy. Methods: In this work, we integrated high-throughput mRNA sequencing (RNA-Seq) data from normal and tumor tissues (obtained from The Cancer Genome Atlas, TCGA) and cell lines obtained through in-house sequencing or available from the Gene Expression Omnibus (GEO) to generate a unified list of differentially expressed (DE) genes. Methylome and proteomic data were integrated to our analysis to give further support to our findings. Genes that were overexpressed in TNBC were then curated to retain new potentially druggable targets based on in silico analysis. Knocking-down was used to assess gene importance for TNBC cell proliferation. Results: Our pipeline analysis generated a list of 243 potential new targets for treating TNBC. We finally demonstrated that knock-down of Guanylate-Binding Protein 1 (GBP1 ), one of the candidate genes, selectively affected the growth of TNBC cell lines. Moreover, we showed that GBP1 expression was controlled by epidermal growth factor receptor (EGFR) in breast cancer cell lines. Conclusions: We propose that GBP1 is a new potential druggable therapeutic target for treating TNBC with enhanced EGFR expression. Keywords: Breast cancer, Triple-negative breast cancer, Gene expression, RNA-Seq, Transcriptomics, Therapeutic target Background the discovery of novel genes and transcripts. As such, The emergence of next-generation sequencing (NGS) RNA-Seq has become an important tool in cancer technology has provided a large amount of data, much studies [6], contributing to reduced costs and less time of which is publicly available [1, 2]. Specifically, RNA- being spent in benchtop experiments, thus speeding up Seq has been used for the estimation of RNA abun- the resolution of biological problems. However, a chal- dance [3, 4], alternative splicing detection [5–7], and lenge remains in achieving intelligible data analysis and efficient laboratory validation. Triple-negative breast cancer (TNBC) is characterized by a lack of estrogen and progesterone receptor expres- sion (ESR and PGR, respectively) and an absence of * Correspondence: [email protected] †Equal contributors human epithelial growth factor receptor (ERBB2)amp- 1Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research lification. Approximately to 15–20% of breast malig- in Energy and Materials (CNPEM), Campinas, São Paulo 13083-970, Brazil nancies are TNBC [8]. Patients with TNBC often Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Quintero et al. BMC Cancer (2017) 17:727 Page 2 of 16 exhibit unfavorable histopathologic features at diagno- RNA sample preparation kit v2 (Illumina) for samples se- sis, mainly consisting of a higher histologic grade, larger quenced at the High-Throughput Sequencing Facility tumor size, and frequent metastasis to the lymph nodes (HTSF) of the University of North Carolina at Chapel Hill [9]. As a consequence, TNBC is associated with a (UNC, USA) and the High-Performance Technologies shorter median time to relapse and death [10]. TNBC Central Laboratory (LaCTAD) of the University of Campi- represents an important clinical challenge since it does nas (UNICAMP, Brazil), respectively. After isolation, the not respond to hormone therapy, which targets the mRNAs were fragmented in the presence of divalent abovementioned receptors [11, 12]. Moreover, TNBC is cations and high temperatures and then employed for highly heterogeneous [13], indicating the necessity of cDNA synthesis with random primers using the Super- identifying unifying molecular targets, which may help script II Reverse Transcriptase (Life Technologies) kit. guide more efficient and less toxic therapeutic manage- The MDAMB231 and SKBR3 samples were sequenced at ment [14, 15]. HTSF, while the MDAMB436, MDAMB468, BT549 and Guanylate-Binding Protein-1 (GBP1) is a member of the MCF7 samples were sequenced at LaCTAD. All samples large GTPase family and is induced by interferons [16] were sequenced using the paired-end × 100 base pairs and inflammatory cytokines [17]. GBP1 is also transcrip- technique on the Hiseq2000 platform (Illumina). Level 3 tionally regulated by epidermal growth factor receptor TCGA RNA-Seq data (RNASeqV2 raw count estimates) (EGFR). In glioblastoma [18, 19] and esophageal squa- and related clinical data (immunohistochemical results for mous cell carcinoma [20], GBP1 upregulation via the ER, PR and HER2 TNBC markers) for 1093 tumor tissues EGFR signaling pathway contributes to tumor prolifera- from the Breast Invasive Carcinoma (BRCA) dataset, as tion and migration both in vitro and in vivo. Moreover, well as 112 normal breast tissue samples, were down- GBP1 is described as a component of the cytoskeletal loaded from the Genomic Data Commons Legacy Archive gateway of drug resistance in ovarian cancer [21, 22]. (National Cancer Institute) on November 10, 2016, from GBP1 expression is also linked to a lack of responsiveness legacy database. Cell line RNA-Seq data (accession codes to radiotherapy in some tumors [23], and GBP1 is overex- GSE58135 [25] and GSE48213 [26]) were obtained from pressed in pancreatic cancer that is refractory to oncolytic the Gene Expression Omnibus [27] by downloading raw virus therapy [24]. FASTQ files from the DDBJ Sequence Read Archive [28] In this work, we utilized RNA-Seq data obtained from (DRA) or NCBI Sequence Read Archive (SRA) [29]. TNBC tissues as well as cell lines that were publicly FastQC [30] was used to evaluate the quality of the available from The Cancer Genome Project (TCGA) reads. Reads presenting a mean quality score below 30 and the Gene Expression Omnibus Portal (GEO), were removed. Those that exhibited a quality score respectively, to search for new therapeutic targets for above this threshold but included bases at the extrem- TNBC. To complement our findings, we also per- ities with a quality score below 20 were trimmed using formed transcriptomics analyses of several TNBC cell Skewer [31] following guidelines published elsewhere lines. The obtained lists of overexpressed genes were [32], up to a minimum of 30 base pairs. The processed inter-crossed and compared with data from normal tis- reads were aligned against the hg19 genome using sues from the TCGA. Methylome and proteomic data STAR [33], and transcript abundance was estimated were integrated to our analysis to give further support with RNA-Seq by Expectation-Maximization (RSEM) to our findings. Using this approach, we identified 243 [34]. We applied upper-quantile normalization to per- genes, which were subsequently evaluated for their form batch effects adjustments and render dataset from druggability potential. GBP1 was the second gene on distinct sources comparable [35]. the list, and knock-down of GBP1 in TNBC and non- TNBC cell lines showed that its expression is important Assignment of breast cancer marker status in the TCGA for TNBC cell growth. In addition, we demonstrated cohort that GBP1 expression is controlled by EGFR signaling The TCGA normalized log2 RSEM values for the ESR1, in breast cancer cells. Thus, we present GBP1 as a new PGR and ERBB2 genes were adjusted to a bimodal potential druggable target for TNBC with enhanced curve using an approach published previously [36, 37]. EGFR expression. Briefly, for each gene, log2 + 1-transformed [38], upper quartile-normalized [35] gene expression was fitted for Methods a 2-component Gaussian mixture distribution model RNA sequencing and data processing with the R package mclust [39]. The highest match be- Total RNA extraction was performed using the RNeasy tween the assignment and clinical data (when available) kit (Qiagen) according to the manufacturer’s instructions. was the criterion for selecting equal or variable vari- Then, mRNA was isolated with either the Dynabeads ance between the two Gaussian fits. For the microarray mRNA purification kit (Life Technologies) or the TrueSeq validation datasets, the same approach was used, but Quintero et al. BMC Cancer (2017) 17:727 Page 3 of 16 log2 + 1-transformed