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. 2013 Dec 31;37(1):41–52. doi: 10.1007/s13402-013-0162-4

High-level copy number gains of established and potential drug target genes in gastric cancer as a lead for treatment development and selection

Mariette Labots 1, Tineke E Buffart 1, Josien C Haan 2, Nicole C T van Grieken 2, Marianne Tijssen 2, Cornelis J H van de Velde 3, Heike I Grabsch 4, Bauke Ylstra 2, Beatriz Carvalho 2, Remond J A Fijneman 2, Henk M W Verheul 1, Gerrit A Meijer 2,✉
PMCID: PMC13004447  PMID: 24379144

Abstract

Purpose

The overall survival rate of patients with advanced gastric cancer is poor. Therefore, there is an urgent need for new treatment options for these patients. The identification of drug target genes located on DNA regions exhibiting high-level copy number gains (CNG) may be an effective approach, as has e.g. previously been shown for HER2. The aim of the present study was to identify putative drug targets in patients with gastric cancer by applying this strategy.

Methods

Genome-wide array comparative genomic hybridization (array CGH) data available from 183 primary gastric cancer samples were analyzed through Ingenuity Pathway Analysis (IPA) to assess whether any established or potential anticancer drug target genes showed high-level CNG, including focal amplifications.

Results

A total of 147 high-level gained regions were identified in the gastric cancer samples, harboring 167 genes that had previously been annotated as drug target genes. Thirty (18 %) of these genes showed high-level gains in at least 2 % of the tumors. The identified drug target genes included those for drugs known to be active in advanced (gastric) cancer, targets for targeted therapies in clinical development, as well as targets for drugs currently used for other indications but of potential interest for anticancer treatment. In addition, 12 potential drug target genes were identified, including genes involved in growth factor signaling and cell cycle regulation.

Conclusion

The majority of gastric cancers carried one or more high-level CNGs or focal amplifications encompassing putative drug target genes. A number of the associated drugs are currently not being considered for treatment of gastric cancer. Based on these results we hypothesize that DNA copy number profiling may be a useful tool to identify new drug targets and to guide individualized treatment strategies in patients with gastric cancer.

Electronic supplementary material

The online version of this article (doi:10.1007/s13402-013-0162-4) contains supplementary material, which is available to authorized users.

Keywords: Gastric cancer, DNA copy number changes, Drug target gene, Treatment selection, Personalized medicine, Drug repositioning

Introduction

There is an urgent clinical need to improve the outcome of patients with advanced gastric cancer, as the median overall survival (OS) rarely exceeds 1 year [1, 2]. The current first-line systemic treatment for locally advanced or metastatic disease is based on a combination of fluoropyrimidine and platinum chemotherapy regimens [3, 4]. The potential benefit of second-line chemotherapy as compared to best-supportive-care (BSC) has been debated [5]. Recently, irinotecan as second-line treatment has been shown to improve OS compared to BSC [6]. Although other chemotherapeutic agents, including taxanes, are being used for the treatment of gastric cancer, most recent developments focus on combination treatment with molecular targeting agents.

Several preclinical studies have reported the activity of the HER2-neu (HER2) targeting monoclonal antibody trastuzumab in HER2-overexpressing gastric cancer cell lines and xenograft models [7]. Synergistic antitumor activity has been demonstrated for the combination of trastuzumab with several cytotoxic agents [8]. HER2 is over-expressed or amplified in 5–23 % of gastric adenocarcinomas, predominantly in cancers of the intestinal subtype [9–11]. In 2010, trastuzumab was approved for the treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancers in combination with chemotherapy. This approval was based on the outcome of a randomized clinical trial (ToGA) in which the addition of trastuzumab to combination chemotherapy, consisting of capecitabine or 5-fluorouracil (5-FU) plus cisplatin, increased the median OS from 11.1 months to 13.8 months [12]. Other combination treatment strategies, including the dual EGFR/HER2-tyrosine kinase inhibitor lapatinib, are currently being explored (http://clinicaltrials.gov/show/NCT00680901 and /NCT00486954).

The poor outcome of advanced gastric cancer patients emphasizes the urgent need for improved treatment options, either through the identification of more active agents or through a better selection of treatment options for individual patients. DNA copy number changes may, due to gene-dosage effects, lead to mRNA over-expression and consequently protein over-expression. This may also occur with genes coding for proteins that serve as drug targets. The aim of the present study, therefore, was to establish the prevalence of DNA high-level copy number gains, including amplifications of potential drug target genes, in a large cohort of patients with gastric cancer.

Materials and methods

Sample selection and array comparative genomic hybridization (array CGH)

Genome-wide array comparative genomic hybridization (array CGH) data available from 183 primary gastric cancer samples, previously selected from a set of 206 tumor samples derived from the Dutch D1D2 trial [13] and from the archives of the Academic Department of Surgery, Leeds General Infirmary (UK), were analyzed in the present study. Details of this patient series and its corresponding array CGH copy number data have been reported previously [14]. DNA isolation and array CGH using bacterial artificial chromosome (BAC) arrays were performed as previously described [15]. The array CGH data can be accessed using the Gene Expression Omnibus (GEO) via http://www.ncbi.nlm.nih.gov/geo/, accession number GSE26389. High-level copy number gains (CNGs) were defined as a minimum of 2 consecutive BAC clones showing a log2 ratio of ≥1, matching at least 4 gene copies. These gains can be broad or focal, i.e., smaller than 3 Mb [16]. The sizes (Mb) and chromosomal bands on which the high-level CNGs were located are listed per tumor in Supplementary Table 1.

Identification of drug target genes

The frequency of high-level CNGs was calculated for each BAC clone. Genes located within loci covered by high-level CNG BACs were identified using the RefSeq genes in the May 2004 human reference sequence (NCBI Build 35/hg17) of the UCSC Genome Browser (http://genome.ucsc.edu/cgi-bin/hgGateway) [17]. Putative drug target genes were identified using Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com/) considering all drug target genes irrespective of drug class. The position of the high-level CNGs and the overlap with the genes were confirmed by using the USCS Genome Browser Convert utility (http://genome-euro.ucsc.edu/cgi-bin/hgConvert) to convert corresponding CNG coordinates to the February 2009 assembly (GRCh37/hg19) (Supplementary Table 2). Drug target genes that were located within high-level CGN regions in at least 4 patients (2 %) were ordered according to the indication and mechanism of action of the drug associated with a particular gene. Additional information on IPA-identified drugs targeting high-level gained genes was searched for via PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) and throughout the world-wide web. In case multiple drugs were listed by IPA for targeting a specific gene, 3 representative drugs are shown in the corresponding tables of this manuscript. In addition to the above described selection methods, potential target genes for drugs interfering with signal transduction pathways were selected by searching for kinases in the original gene list, and for known receptors and ligands in the Database of Interacting Proteins (http://dip.doe-mbi.ucla.edu/dip/).

HER2 expression analysis

To assess the correlation of high-level gene CNG with protein expression, HER2 immunohistochemistry using tissue microarray sections was performed on a subset of 62 tumors from the Leeds General Infirmary, UK, as previously described [9].

Results

Identification of high-level copy number gains and its frequencies

In 183 gastric cancers, 147 high-level copy number gains (CNG) were identified by array CGH with a mean number of 2.25 and median of 1 high-level CNG per tumor (range 0–21), in total harboring more than 6,400 genes. The frequencies of the high-level CNGs across the chromosomes are shown in Fig. 1. At least one high-level CNG was observed in 118 (64.5 %) tumors, while no high-level CNGs were observed in 65 tumors (35.5 %). The most frequent high-level CNG regions were located on chromosomes 6p21, 8q24, 11p13, 16q24, 17q21 and 20q13. Examples of array CGH profiles with numerous high-level CNGs are shown in Fig. 2a and b.

Fig. 1.

Fig. 1

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Frequency plots of high-level copy number gains in 183 gastric tumors. The x-axis displays BACs spotted on the array sorted by chromosomal position. The y-axis displays the percentage of tumors with high-level copy number gains. Boundaries of chromosomes are indicated by vertical dotted lines

Fig. 2.

Fig. 2

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DNA copy number profiles of two patients containing high-level copy number gains on which several drug target genes are located. The x-axis displays BACs spotted on the array sorted by chromosomal position from chromosome 1 to chromosome 22 and X. The y-axis displays the log2 ratios of the clones

Identification of gastric cancer drug target genes

Seventy-eight regions (53 %) of the 147 high-level CNG regions were found to contain a total of 167 genes that have been annotated as drug targets by IPA. Thirty of these genes occurred in at least 2 % of the tumors and were ordered according to evidence of antitumor activity, mechanism of action and indication of the drugs associated with the genes (Table 1, n = 13; Table 2, n = 5; Supplementary Table 3, n = 12). Twelve additional genes were identified in at least 2 % of the tumors by specifically searching the aforementioned regions for genes coding for kinases, receptors and ligands (Table 2, n = 11; Supplementary Table 3, n = 1). In Fig. 3 a heatmap depicting the number of these identified drug target genes per tumor is shown, sorted per category as discussed below.

Table 1.

Target genes of (a) cytotoxic drugs, (b) clinically available targeted anticancer drugs and (c) drugs with potential for repositioning as anticancer drug showing high-level copy number gain in at least 2 % of the samples

Gene ID Chromosome Maximum frequency (%) IPA-reported drugs Drug class
a
TUBB3 16 14 (7.7) Docetaxel, epothilone B, vinorelbine Taxane; vinca-alkaloid
TOP2A 17 9 (4.9) Doxorubicin, etoposide, mitoxantrone Anthracyclin; plant-alkaloid; anthracenedione
TUBG1 17 6 (3.3) Docetaxel, epothilone B, vinorelbine Taxane; vinca-alkaloid
TUBG2 17 6 (3.3) Docetaxel, epothilone B, vinorelbine Taxane; vinca-alkaloid
ADA 20 4 (2.2) Pentostatin, vidarabine Antimetabolite
b
VEGFA 6 12 (6.6) Bevacizumab, aflibercept, pegaptanib Anti-VEGF MAb; VEGF receptor decoy; anti-VEGF aptamer
ERBB2 17 11 (6.0) Trastuzumab, lapatinib, erlotinib HER2-neu MAb and TKI
RARA 17 9 (4.9) Etretinate, acitretin, retinoic acid Aromatic retinoid
EGFR 7 7 (3.8) Cetuximab, lapatinib, erlotinib Anti-EGFR MAb and TKI
c
HRH3 20 19 (10.4) Tesmilifene, triprolidine, buclizine Antihistamine/anticholinergic
DGAT1 8 17 (9.3) Omacor Antilipemic
FDFT1 8 8 (4.4) TAK-475, zoledronic acid Antilipemic; bisphosphonate
CYP3A4 7 7 (3.8) Ketoconazole Anti-androgen, antifungal
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IPA ingenuity pathway analysis; MAb monoclonal antibody; TKI tyrosine kinase inhibitor

Table 2.

Target genes of agents under (pre)clinical evaluation and potential drug targets for anticancer treatment showing high-level copy number gain in at least 2 % of the samples

Gene ID Chromosome Maximum frequency (%) Source IPA-reported drugs Drug class
HSP90AB1 6 10 (5.5) IPA 17-DMAG, IPI-504 (retaspimycin) HSP90 inhibitor
EPHB4 7 8 (4.4) IPA XL647 Anti-HER2, EGFR, VEGFR and EphB4 TKI
CDK6 7 7 (3.8) IPA PD-0332991; flavopiridol Selective CDK4/6 inhibitor; anti-CDK flavonoid
CDK10 16 7 (3.8) IPA Flavopiridol Anti-CDK flavonoid
FGFR2 10 4 (2.2) IPA Palifermin Recombinant human KGF; anti-FGFR TKI
MAPK15 8 17 (9.3) Gene list
TNFRSF6B 20 13 (7.1) DIP; (transmembrane) receptor
PTK6 20 13 (7.1) Gene list
SRMS 20 13 (7.1) Gene list
CCR7 17 9 (4.9) DIP; (G-protein coupled) receptor
BMP7 20 9 (4.9) DIP; ligand (growth factor)
PTK7 6 9 (4.9) Gene list
KRAS 12 8 (4.4) Gene list
CDK12 17 8 (4.4) Gene list
PTK2 8 7 (3.8) Gene list
CDK14 7 4 (2.2) Gene list
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TKI tyrosine kinase inhibitor; IPA ingenuity pathway analysis; DIP database of interacting proteins; Gene list kinases identified by searching the original data for genes coding for kinases

Fig. 3.

Fig. 3

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Heatmap based on unsupervised hierarchical clustering of 118 gastric tumors containing at least one high-level copy number gain. Samples on the horizontal axis and genes on the vertical axis, ordered by drug target category. “Cytotoxic agents” in red, “Clinically available targeted anticancer agents” in blue, “Non-anticancer agents” in yellow, “Agents under (pre)clinical evaluation and potential new anticancer drug targets” in green and “Agents without apparent anticancer activity” in purple. Within the heatmap, green blocks depict presence and black blocks absence of high-level copy number gain

Identification of cytotoxic drug-related genes

Five of 30 IPA-identified drug target genes were found to be related to the mechanism of action of cytotoxic agents (Table 1a). Three of these genes, involved in the regulation of microtubule assembly, the target of taxanes, were located within regions exhibiting high-level CNG, i.e., tubulin-beta 3 (TUBB3, 16q24.1-q24.3), tubulin-gamma1 and tubulin-gamma 2 (TUBG1 and TUBG2, 17q12-q21.31), in 14 (7.7 %), 6 (3.3 %) and 6 (3.3 %) tumors, respectively. A fourth gene coding for topoisomerase (DNA) II alpha (TOP2A, 17q12-q21.31), a drug target of anthracyclines such as epirubicin and doxorubucin, showed high-level CNG in 9 tumors (4.9 %). The fifth high-level CNG cytotoxic drug target gene, ADA (20q12-q13.13), coding for adenosine deaminase, showed CNG in 4 (2.2 %) tumors. The protein product of the latter is an enzyme involved in purine metabolism and, thereby, serves as a target for antimetabolites such as 5-FU and its prodrug capecitabine.

Identification of available targeted anticancer agent-related genes

Four high-level CNG genes were found that are associated with targeted anticancer agents that are currently available for clinical application (Table 1b). One of these genes, coding for vascular endothelial growth factor A (VEGFA, 6p21.2-p12.3), which is implicated in tumor angiogenesis, showed high-level CNG in 12 (6.6 %) tumors. The gene coding for HER2/neu (17q12-21.31), which is a member of the EGFR family and the target of trastuzumab, showed high-level CNG in 11 (6.0 %) tumors. In 62 of 183 tumors (see section 2), the relation between HER2 high-level CNG and protein expression was determined by additional immunohistochemistry. By doing so, we found that 57 of these tumors did not show HER2 over-expression. In 4 out of the remaining 5 HER2 over-expressing tumors (2 classified as +, 3 classified as +++), HER2 high-level CNG was indeed observed (80 %). Representative examples of HER2 over-expressing tumors are shown in Supplementary Fig. 1. The gene coding for the epidermal growth factor receptor (EGFR, 7p11.2), a transmembrane tyrosine kinase receptor, another member of the EGFR family and target of panitumumab and cetuximab, was amplified in 7 (3.8 %) tumors. The gene coding for the retinoic acid receptor alpha (RARA, 17q12-21.31), involved in transcription regulation of multiple genes, was amplified in 9 (4.9 %) tumors. In acute promyelocytic leukemia (APL) the RARA gene is fused to the PML gene on chromosome 15. APL is responsive to treatment with the vitamin A derivative all-trans retinoic acid (ATRA) [18].

Identification of target genes associated with drugs not primarily used against cancer

Targets for drugs that are clinically used for other indications than cancer, but which could be applied for anticancer purposes (i.e., drug repositioning candidates), included the two most frequency amplified genes, i.e. HRH3 and DGAT1, with a frequencies of 19 (10.4 %) and 17 (9.3 %), respectively (Table 1c). HRH3 (20q13.13-33), codes for histamine receptor 3, which is involved in the regulation of histamine release and is a target of tesmilifene and buclizine. DGAT1 (8q24.23-24.3) codes for diacylglycerol O-acyltransferase 1, which is important for the formation of adipose tissue and is a target of omega 3-fatty acid. The gene coding for farnesyl-diphosphate farnesyltransferase 1 (FDFT1, 8p23.2-p22), which is known to convert two units of farnesyl pyrophosphate into squalene and is involved in cholesterol synthesis, was located on a high-level CNG in 8 (4.4 %) tumors. This enzyme is a target of zoledronic acid and TAK-475. The gene coding for cytochrome P450, family 3, subfamily A, polypeptide 4 (CYP3A4, 7q21.3-22.1), which is of critical importance for the metabolism of drugs and the synthesis of cholesterol, steroids, and other lipids, was found to be amplified in 7 (3.8 %) tumors. Ketoconazole is a potent inhibitor of CYP3A4.

Identification of potential new drug targets for anticancer treatment

Five genes were identified as IPA-annotated targets of agents under (pre)clinical investigation for cancer, and 12 potential drug target genes were identified by searching the original gene list for kinases, ligands and receptors (Table 2; Supplementary Table 3). The gene coding for mitogen-activated protein kinase 15 (MAPK15, 8q24.23-24.3), was located on a high-level CNG in 17 (9.3 %) tumors. MAPK15 is a member of seronine/threonine super family and is involved in cell proliferation, differentiation, apoptosis and stress responses. The gene encoding the tumor necrosis factor receptor super family, member 6b, decoy (TNFRSF6B, 20q13.13-33), was located on a high-level CNG in 13 (7.1 %) tumors. TNFRSF6B is thought to play a role in FasL- and LIGHT-mediated cell death. The gene encoding the src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristylation sites (SRMS, 20q13.13-33) was found to be located on a high-level CNG in 13 (7.1 %) tumors. The genes encoding protein tyrosine kinase 2 (PTK2, 8q24.23-q24.3), PTK6 (20q13.13-33) and PTK7 (6p21.2-p12.3) were located on a high-level CNGs in 7 (3.8 %), 13 (7.1 %) and 9 (4.9 %) tumors, respectively. PTKs have specific functions in cell signaling pathways. PTK2 is also known as Focal Adhesion Kinase (FAK) and plays a role in cell-cell interactions and intracellular signaling. Although not identified by IPA, several FAK inhibitors are currently under investigation in phase I clinical studies. PTK 6 and 7 also play specific roles in intracellular signaling. The gene encoding the heat shock protein 90 kDa alpha (cytosolic), class B member 1 (HSP90AB1, 6p21.2-p12.3) was located on a high-level CNGs in 10 (5.5 %) tumors. Hsp90 is a molecular chaperone and is believed to play a role in the prevention of apoptosis and in the processes of angiogenesis and metastasis. Several Hsp90 inhibitors are under investigation in phase 2 clinical trials, such as AUY922 in gastrointestinal stromal tumors and, combined with trastuzumab, in gastric cancer. The gene encoding the C-C chemokine receptor type 7 (CCR7, 17q12-21.31) was located on a high-level GNGs in 9 (4.9 %) tumors. CCR7 is involved in leukocyte adhesion and chemotaxis. The gene encoding the bone morphogenetic protein 7 (BMP7, 20q13.13-33) was located on a high-level CNG in 9 (4.9 %) tumors. BMP7 is a signaling molecule belonging to the transforming growth factor-beta super family and is considered to play a role in bone metastases. The gene coding for the ephrin type B-receptor 4 (EPHB4, 7q21.3-22.1), a transmembrane receptor tyrosine kinase, is involved in tumor-induced angiogenesis and was located on a high-level CNG in 8 (4.4 %) tumors. XL647, an inhibitor of the tyrosine kinases EphB4, HER2, VEGFR and EGFR, has shown antitumor activity in patients with advanced non-small cell lung cancer. The Kirsten rat sarcoma oncogene (KRAS, 12p12.1), was located on a high-level CNG in 8 (4.4 %) tumors. This gene encodes a GTPase protein, which plays an important role in cell signaling and, if mutated, often plays an essential role in cancer progression. Although at present KRAS is not a drug target, the protein is an important determinant of response to the anti-EGFR antibodies cetuximab and panitumumab in colorectal cancer, as patients with mutated KRAS will not respond to these agents. The genes encoding the cyclin dependent kinases 6 (CDK6, 7q21.13-21.3), CDK10 (16q24.1-3), CDK12 (17q12-21.31) and CDK14 (7q21.13-21.3) were located on a high-level CNGs in 7 (3.8 %), 7 (3.8 %), 8 (4.4 %) and 4 (2.2 %) tumors, respectively. CDKs are important regulators of cell cycle progression, promoting cell division and cancer progression. Flavopiridol is a CDK inhibitor under investigation in a number of phase I and II clinical studies, predominantly in combination with chemotherapy. The gene encoding the fibroblast growth factor receptor 2 (FGFR2, 10q26.12-13), a transmembrane tyrosine kinase receptor involved in angiogenesis, was located on a high-level CNG in 4 (2.2 %) tumors. Dovitinib (TKI-258) is a multi-targeted inhibitor of receptor tyrosine kinases, including FGFR1-3, and is furthest advanced in clinical development in renal cell carcinoma. Furthermore, 13 genes were considered as targets for drugs without known apparent anticancer effects (Supplementary Table 3), such as diuretics and analgesics, as well as the erythropoiesis-stimulating hormone erythropoietin (EPO, 7q21.3-22.1), which was located on a high-level CNG in 8 (4.4 %) tumors. The normal function of EPO is to stimulate erythrocyte formation, but-in addition to its identification in this study as a potential drug target-it has been shown to play a role in angiogenesis and, therefore, may stimulate tumor growth as well.

Discussion

With the current first-line chemotherapy regimens for advanced gastric cancer, median survival rates remain poor and improvement of treatment strategies are urgently warranted. In the present study, we set out to establish the frequency of high-level DNA copy number gains (CNG) of drug targets as a screen for potential alternative, individualized treatment options for patients with gastric cancer, as has previously e.g. been performed for small cell lung cancer and bronchial carcinoids [19]. Recently, genomic alterations related to FGFR2, KRAS, EGFR, ERBB2 and cMET were identified in 37 % of patients with gastric cancer, suggestive for potential targeted treatment options. In this study 22 recurrent alterations were identified through genomic identification of significant targets in cancer (GISTIC), 13 of which were amplifications [20]. Twenty out of 25 amplified genes located on narrow regions were found to overlap with genes identified in regions exhibiting high-level CNG in the present study. In a similar way, 14 out of 15 (candidate) drug targets located on 13 recurrent amplifications in another study [21], were found to overlap with genes identified in the present study.

The drug target genes found to be located on high-level CNGs included targets of cytoxic agents (5) and targeted agents (4) that are currently being used clinically. In addition, 4 high-level CNG genes are known as drug targets for other indications, but these could be of interest for anticancer treatment as well (drug repositioning candidates). Other high-level CNG genes (16) included molecular targets that are either under (pre)clinical evaluation or are new targets that might potentially be druggable.

Among genes known as targets for chemotherapeutic agents, we found high-level CNGs of microtubule function related genes (TUBB3, TUBG1 and TUBG2) and high-level CNGs of the TOP2A gene. Although TUBB3 over-expression has been associated with low response rates to taxane-based chemotherapy, and with poor outcomes in advanced (serous) ovarian cancer, non-small cell lung cancer and breast cancer [22–25], in docetaxel-treated patients with gastric cancer a higher response rate for TUBB3 expressing versus non-expressing tumors has been reported [26]. In advanced gastric cancer, the addition of docetaxel to the combination cisplatin and 5-FU has been found to improve anticancer activity, but also to increase toxicity [2]. Taken together, over-expression of TUBB3 may be associated with resistance to taxane therapy for some tumors, but for gastric cancer it seems to be associated with higher response rates. Further studies should be designed to determine to what extent this relation in gastric cancer can be used as a biomarker for taxane sensitivity or resistance. For TUBG1 and TUBG2 no data are currently available in relation to taxane treatment, but these genes should similarly be evaluated for their potential relation to taxane sensitivity.

High-level CNG of TOP2A in 4.9 % of the current set of gastric tumors is comparable to that observed in previous studies [27, 28]. No consistent data are available for TOP2A expression in relation to anthracyclin sensitivity, while epirubicin in combination with cisplatin and 5-fluorouracil (ECF) or capecitabine (ECC) is currently employed as an active regimen for the treatment of advanced (esophago)gastric cancer [29, 30].

High-level CNG targets for anticancer agents include HER2, present in 6 % of our cases. Trastuzumab is a clinically available antibody against the HER2 protein, and is approved for the treatment of advanced gastric cancer. Earlier reports have indicated that HER2 amplification is present in approximately 15 % of gastric tumors, and that it is highly concordant between primary tumors and metastatic lesions [11, 31, 32]. Besides high-level CNG of drug target genes, expression at the protein level is essential for its therapeutic consequences. In gastric cancer, concordance percentages between HER2 over-expression and gene amplification range between 87 and 96 % [33]. Our current series revealed a correlation of approximately 80 % (see Supplementary Fig. 1). In addition, HER2 high-level CNG was found to be associated with TOP2A high-level CNG in 7 of these tumors (64 %). Conversely, 7 of 9 tumors with TOP2A high-level CNG also showed HER2 high-level CNG (78 %). These findings are consistent with previous reports [11, 34]. Interestingly, increased sensitivity to anthracycline-based chemotherapy has been reported in patients with TOP2A co-amplified HER2-positive breast cancers [35, 36]. Although HER2-amplification alone was not found predictive for response to peri-operative ECF treatment in patients with early gastric cancer, it would be of interest to investigate TOP2A co-amplification as a predictive biomarker in both early and advanced gastric cancers [37].

Four genes were identified as targets for which drugs are available to treat diseases other than cancer, but which may be of interest to explore their potential in cancer treatment as well. These genes include HRH3 and DGAT1. Tesmilifene, a tamoxifen analogue originally developed as an antihistamine targeting HRH3, has been shown to inhibit tumor initiating cells in breast cancer models, in particular of HER2-positive tumors, and to exhibit synergistic activity with doxorubicin [38]. A phase III randomized trial in metastatic breast cancer patients comparing doxorubicin with either tesmilifene or a placebo showed a significantly improved OS for the combination with tesmilifene [39]. Based on the high frequency of high-level CNGs of HRH3 in the present series of gastric cancers, the activity of tesmilifene as monotherapy and/or in combination with doxorubicin warrants further preclinical evaluation in gastric cancer patients selected for HRH3 high-level CNGs.

Overt expression of DGAT1 activity can be inhibited by simvastatin, a drug commonly used to treat dyslipidemia [40]. Based on previous reports on antitumor activity of statins through inhibition of the mevalonate pathway, currently a randomized phase III trial is ongoing in which the addition of simvastatin to combination cisplatin and 5-FU chemotherapy in advanced gastric cancer is being studied (http://clinicaltrials.gov/show/NCT01099085). However, in a small randomized phase II clinical trial, pravastatin, a cholesterol-lowering agent similar to simvastatin, did not improve the outcome in advanced gastric cancer when combined with ECC chemotherapy [41]. One could speculate that this disappointing result may largely be due to the “one size fits all” (non-selection) treatment strategy used, while proper treatment selection based on gene amplification could have resulted in a significantly better outcome.

FDFT1, located on high-level CNGs in 4.4 % of the patients, has been associated with the bisphosphonate zoledronate, based on its inhibition of farnesyl pyrophosphate synthase in the mevalonate pathway [42]. Zoledronic acid is commonly used to prevent fractures in patients with bone metastases from prostate cancer, but also cytostatic activity of this drug by induction of apoptosis in gastric cancer cells has been reported (Yamada et al., Proc Am Assoc Cancer Res 47(2006), [Abstract# 3806]). Based on our data, further investigation of zoledronic acid in advanced gastric cancer should be considered upon selection of patients with tumors carrying FDFT1 high-level CNGs.

Potential (new) targets for treatment that were identified in the current study included several growth factor signaling genes (MAPK15, HSP90, SRM, KRAS, PTK6 and 7), cell cycle regulating genes (CDK6, 10, 12 and 14) and genes involved in cell-cell interactions (EPHBH4, CCR7, BMP7 and PTK2 (FAK)). For some of these genes, new agents are already being explored in preclinical and clinical settings. For the others it might be of interest to do so as well. In addition, TNFRSF6B, involved in apoptosis-regulated cell death, was located on high-level CNGs in 7.1 % of the tumors. Since a neutralizing antibody against TNFRSF6B showed cytostatic activity and induction of apoptosis in a hepatocellular carcinoma cell line [43], it could also be considered as a therapeutic option for this category of gastric cancers.

Targets that interfere with cell-cell interactions such as CCR7 and PTK2 (FAK) constitute interesting new drug targets. For example, preclinical evidence is accumulating in predominantly T cells that fingolimod (FTY720), an oral drug in development for the treatment of multiple sclerosis, may indirectly target CCR7. After phosphorylation, it binds to S1P1 receptors and causes aberrant internalization of the CCR7 receptor [44]. In addition, very recently triptolide, a new agent under preclinical evaluation that interferes with PTK2 was found to show antitumor activity against a breast cancer cell line (MCF7) predominantly by causing cell detachment [45].

Various CDK inhibitors have been designed and are being explored in preclinical and clinical studies, including flavopiridol, ALX-270-442-M001 and PD-0332991 (palbociclib) [46]. The latter agent has shown promising results in combination with letrozole in a randomized phase II trial in patients with ER-positive, HER2-negative breast cancer; a phase III clinical trial is currently ongoing (Finn RS. Abstract #S1-6. Presented at: San Antonio Breast Cancer Symposium; Dec. 4–8, 2012; San Antonio). To what extent these inhibitors are specific for a certain type of CDK at the tumor cell level in vivo is as yet unknown and needs further exploration in order to determine whether they can be used for treatment selection as well.

VEGFA and HSP90AB1 were found to show high-level CNG in 6.6 % and 5.5 % of gastric cancers, respectively. Both genes are located on chromosome 6p and co-occurrence of high-level CNGs of these loci was observed in 10 of 12 tumors (83 %; their loci were covered by different BAC clones). To our knowledge, co-amplification of these genes has not been reported previously. The monoclonal antibody bevacizumab binds to VEGFA and is clinically used mostly in combination with chemotherapy. In the AVAGAST trial, bevacizumab improved PFS and response rates, but failed to improve OS when added to combination chemotherapy in patients with advanced gastric cancer [47]. This disappointing result may be due to the fact that bevacizumab was administered to all patients, regardless whether their tumors showed VEGFA high-level CNG. Treatment selection based on high-level CNGs of drug target genes might be worthwhile in these patients to determine its value for bevacizumab treatment selection. We realize that VEGF over-expression may be present independent of DNA copy number. However, in a recently published AVAGAST biomarker analysis, a high baseline plasma VEGFA concentration was identified as a potential predictor for bevacizumab efficacy [48].

The geldanamycin derivate 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG) is a heat shock protein inhibitor that has been shown to disrupt multiple pro-angiogenic signaling pathways in gastric cancer cells and to inhibit xenograft tumor growth in vivo [49]. Currently, several heat shock protein inhibitors are in early clinical development. Ganetespib (STA-9090) elicited one complete and two minor responses in 26 previously treated, unselected patients with advanced esophagogastric cancer (J Clin Oncol 31, 2013 (suppl; abstr 4090)), underscoring the need for molecular profiling to identify a potential subgroup of patients that might benefit from this treatment. Based on our observation of HSP90 and VEGA co-amplification, one could consider combined VEGF- and HSP90-targeted therapy in gastric cancer to synergistically increase their individual antitumor activity.

FGFR2, showing high-level CNGs in 2.2 % of the tumors, is currently being evaluated for its clinical value as a drug target in renal cell cancer with the agent dovitinib (http://clinicaltrials.gov/show/NCT01223027). This agent is also being investigated in a phase II trial in patients with metastatic or unresectable gastric cancer carrying a FGFR2 amplification (http://clinicaltrials.gov/show/NCT01719549). AZD4547, an investigational receptor tyrosine kinase inhibitor targeting FGFR1-3, has recently been shown to inhibit tumor growth in FGFR2-amplified xenograft and patient-derived gastric cancer xenograft models, but not in non-amplified models, suggesting the selection of FGFR2-amplified patients for FGFR inhibitor therapy [50].

In contrast to sensitivity, some genes with high-level CNG are associated with absolute or relative resistance in this group. Upstream of MAPK15 and KRAS, inhibitors are available in the clinic or under investigation such as sorafenib (for MAPK15) and cetuximab or panitumumab for KRAS, while direct inhibitors of MAPK15 and KRAS are of interest as well.

Remarkable is the absence of cMET in our list of 30 drug target genes, because amplification of this gene has previously been reported in 10–25 % of gastric adenocarcinomas [51, 52]. cMET high-level CNG was not observed in any of our 183 gastric cancer cases. A possible explanation might be that cMET amplification is associated with more advanced disease or that cMET driven cancers are rare in Western patients, as recently suggested by Janjigian et al. referring to absent cMET amplification in a cohort of 38 patients with localized gastric cancer [53].

The analysis of array CGH profiles for potential drug targets in gastric cancer was aimed at copy number gains of druggable targets, mainly receptor and non-receptor kinases. Potential overlap of identified targets may be caused by co-localization of the genes on the same highly-gained BAC clone. For example, TNSFRSF6B on chromosome 20 may co-localize with PTK6, SRMS and CHRNA4 on the same BAC clone. Therefore, it remains difficult to determine which is the driver gene in this case. Investigating antitumor activity of different drugs that inhibit these four targets may be worthwhile, but determination of its corresponding protein expression profiles may be more appropriate for evaluation of specific genes in this high-level CNG.

The fact that we evaluated high-level CNGs of drug-related genes in resectable gastric cancers may have influenced our detection of druggable target genes. One can speculate whether the number of potential target genes may be higher in more advanced disease. Although the identified drug targets may be particularly relevant for patients with advanced tumors, it will be of interest to investigate whether new combination treatment strategies with targeted agents could be evaluated in the neoadjuvant setting for response.

As pointed out previously, the effect of high-level CNGs of drug target genes on protein expression remains to be resolved for most genes, and this is critical for the therapeutic relevance of these findings. The aim of the present study was merely to identify potential drug targets that may be considered of interest for further investigation in gastric cancer.

In conclusion, the present analysis of an existing dataset revealed many genes of potential therapeutic interest in a large series of primary gastric cancer samples from Western European patients. These include known substrates for systemic therapies used in advanced gastric cancer, as well as new targets for treatment that are of interest for evaluation of antitumor activity in tumors carrying high-level CNGs. The presence of such high-level CNGs may be used to individualize anticancer therapy by selecting drugs against amplified target genes. In contrast, amplifications of drug pathway-associated genes may indicate resistance to therapy, as has been shown for KRAS in anti-EGFR therapy. The present study provides a potential clinically applicable method for the identification of new treatment strategies in advanced gastric cancer, which may be used for other tumor types as well. Proof of concept studies should be performed to further determine the efficacy of this approach.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary table 1 (38KB, docx)

Overview of all high-level copy number gains observed in 183 gastric cancers including the chromosomal position and size (Mb). (DOCX 38 kb)

Supplementary table 2 (24.4KB, docx)

Chromosomal start and end positions of the high-level copy number gains containing the putative drug target genes. Positions are represented according to the NCBI Build 35/hg17 and, after conversion, the GRCh37/hg19 assembly of the UCSC Genome Browser. Chr, chromosome; Start resp End, genome position in basepairs. (DOCX 24.4 kb)

Supplementary table 3 (23.5KB, docx)

Target genes of drugs without apparent anticancer effect showing high-level copy number gain in at least 2 % of the samples. IPA, Ingenuity Pathway Analysis; DIP, Database of Interacting Proteins; NA, not applicable. (DOCX 23.4 kb)

Supplementary figure 1 (14.2MB, docx)

Two examples of HER2 protein expression in tissue microarray cores of gastric tumors with HER2 amplification showing over-expression (40×). (DOCX 14.2 MB)

Acknowledgments

We thank the Mapping Core and Map Finishing groups of the Wellcome Trust Sanger Institute for initial clone supply and verification. This work was financially supported by the AEGON International Scholarship in Oncology.

Conflict of interest

The authors declare that they have no conflict of interest.

Footnotes

Tineke E. Buffart and Josien C. Haan contributed equally

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary table 1 (38KB, docx)

Overview of all high-level copy number gains observed in 183 gastric cancers including the chromosomal position and size (Mb). (DOCX 38 kb)

Supplementary table 2 (24.4KB, docx)

Chromosomal start and end positions of the high-level copy number gains containing the putative drug target genes. Positions are represented according to the NCBI Build 35/hg17 and, after conversion, the GRCh37/hg19 assembly of the UCSC Genome Browser. Chr, chromosome; Start resp End, genome position in basepairs. (DOCX 24.4 kb)

Supplementary table 3 (23.5KB, docx)

Target genes of drugs without apparent anticancer effect showing high-level copy number gain in at least 2 % of the samples. IPA, Ingenuity Pathway Analysis; DIP, Database of Interacting Proteins; NA, not applicable. (DOCX 23.4 kb)

Supplementary figure 1 (14.2MB, docx)

Two examples of HER2 protein expression in tissue microarray cores of gastric tumors with HER2 amplification showing over-expression (40×). (DOCX 14.2 MB)

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