Abstract
Fusion genes have pivotal roles in the development and progression of human cancer and offer potential for rational drug design. Massively parallel sequencing has identified a panoply of in-frame expressed fusion genes, but early reports suggest that the majority of these are present at very low prevalence or are private events. Conventional methods for the identification of recurrent expressed fusion genes in large cohorts of cancers (eg fluorescence in situ hybridization (FISH) and reverse transcriptase PCR (RT–PCR)) are time consuming and prone to artifacts. Here, we describe a novel high-throughput strategy for the detection of recurrent fusion genes in cancer based on the Sequenom MassARRAY platform. Fusion genes were initially identified by massively parallel sequencing of breast cancer cell lines. For each fusion gene, two Sequenom probes were designed. Primary human breast cancers and cancer cell lines were interrogated for 10 fusion genes. Sensitivity, specificity, and predictive values of the MassARRAY method were then determined using FISH and qRT–PCR as the ‘gold standard.’ By combining two probes per fusion gene, the negative and positive predictive values were 100 and 71.4%, respectively. All fusion genes identified by massively parallel sequencing were accurately detected. No recurrent fusion genes were found. The MassARRAY-based approach described here may, therefore, be employed as a high-throughput screening tool for known fusion genes in human cancer. In keeping with other highly sensitive assays, further refinement of this technique is necessary to reduce the number of false-positive results.
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Main
The identification of oncogenic fusion genes in cancer provides an opportunity for rational drug design, and is exemplified by chronic myeloid leukemia, where neoplastic cells expressing the BCR-ABL fusion gene are specifically sensitive to imatinib.1 With the advent of massively parallel sequencing, it has become apparent that chromosomal rearrangements are not limited to hematological malignancies and sarcomas, but are in fact common events in carcinomas.2, 3, 4, 5, 6, 7, 8, 9, 10 For example, fusion genes involving ETS-family members, such as ERG (SLC45A3-ERG), ETV1 (TMPRSS2-ETV1), ETV4 (TMPRSS2-ETV4), and ETV5 (SLC45A3-ETV5), have been shown to be common in prostate carcinomas.2, 6, 11, 12, 13, 14, 15, 16 Some special types of breast cancer have recently been shown to be characterized by the presence of recurrent fusion genes resulting from chromosomal translocations, including ETV6-NTRK3 in secretory carcinomas5, 17, 18, 19, 20, 21 and MYB-NFIB in adenoid cystic carcinomas.4, 22, 23, 24 The majority of fusion genes identified by massively parallel sequencing, however, appear to exist at very low prevalence or represent private events (ie identified only in the index case).7, 9, 10, 14, 15 This observation and the fact that chromosomal rearrangements are more frequently identified within amplified regions of the genome have led some to conclude that the majority of these rearrangements are likely to constitute passenger events.7, 8
The probability of a given expressed fusion gene to constitute an oncogenic driver is higher if it is recurrently found in cancers.7 Traditionally, testing the recurrence of known expressed fusion genes was based on a combination of fluorescence in situ hybridization (FISH) and reverse transcription PCR (RT–PCR). In comparison to contemporary analytical studies, these techniques are labor intensive, time consuming (eg FISH on tissue microarrays, including probe design and validation, and scoring) and/or prone to false-positive results (eg mis-priming and amplification of intronic sequences with RT–PCR, particularly when using DNA extracted from formalin-fixed paraffin-embedded (FFPE) material).
MassARRAY technology (iPLEX®) constitutes a highly sensitive, high-throughput tool for the genotyping of single-nucleotide polymorphisms25, 26, 27, 28, 29, 30 and for mutation screening.31, 32, 33 To detect nucleic acid changes, target regions are initially amplified using multiplex PCR and subsequently hybridized to custom-designed primers, then subjected to a single base extension reaction using single mass-modified nucleotides. Spotting of the products onto a matrix chip and subsequent ionization then enables real-time detection by the MassARRAY mass spectrometer (Sequenom, San Diego, CA, USA). This process is based on the principle of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Briefly, laser energy is absorbed by the matrix, resulting in partial vaporization of the illuminated substrate, with minimal damage or fragmentation. Ionized samples are then transferred electrostatically into the mass spectrometer, which enables detection by mass-to-charge ratio. This platform has some advantages over conventional detection systems. Product mass is directly determined with high analytical accuracy (0.1–0.01%), without reliance upon the indirect analysis of fluorescent or radioactive reporters. The high-throughput nature of the technology is due to a combination of the ability to multiplex PCR reactions (up to 36-plex, with as little as 10 ng per multiplex), and rapid analysis. Furthermore, small PCR amplicons (70–120 bp) are suitable for the assessment of FFPE tissue, facilitating the identification of recurrent fusion genes in large annotated cohorts.
Given the versatility of the MassARRAY technology, we have successfully developed a protocol for the detection of known, expressed fusion genes. The aims of this proof-of-principle study were (i) to develop a robust strategy for the high-throughput detection of known, expressed fusion genes, (ii) to test this protocol in a cohort of 10 cancer cell lines known to harbor fusion genes previously detected by massively parallel sequencing, and (iii) to apply these techniques to detect fusion genes in a cohort of FFPE breast cancers.
MATERIALS AND METHODS
Cancer Cell Lines and Human Breast Cancer Tissues
Nine breast cancer cell lines (HCC1143, HCC1187, HCC1395, HCC1599, HCC1937, HCC1954, HCC2157, HCC2218, and HCC38) and HeLa cells, which were used as a negative control for the known fusion genes, were obtained from ATCC (see Stephens et al7 for phenotypic characteristics and growth conditions). DNA samples from these cell lines were previously subjected to massively parallel paired-end DNA sequencing.7 Ten fusion genes were identified among five breast cancer cell lines (HCC1187, HCC1395, HCC1599, HCC1937, and HCC38) and validated using RT–PCR and FISH (Table 1). Cell pellets of two cell lines (HCC38 and HCC1937) were formalin fixed overnight and embedded in paraffin following routine protocols to simulate the same sample preparation that FFPE human breast cancer tissues undergo.
To evaluate this novel assay in primary human breast cancers, 125 FFPE invasive breast cancer samples were randomly selected from a cohort of 245 cases that have been previously described.34 These samples were predominantly estrogen and progesterone receptor positive (86 and 78%, respectively), did not express HER2 (89%), and were of high histological grade (61% grade III; Supplementary Table 1). Two of the 10 fusion genes examined (NFIA-EHF and SLC26A6-PRKAR2A) were previously investigated in the 125 samples assessed by MassARRAY in this study by FISH and RT–PCR.7 They were, therefore, included in the assessment of the performance of this assay along with the detection of all 10 fusion genes in the panel of 10 cancer cell lines (nine breast cancer and HeLa cells). The study design, including the cell lines used for each aspect of the assessment of probe performance, is illustrated in Figure 1. This study is compliant with the required sections of the REMARK guidelines.35
RNA Extraction and RT
Representative 8 μm thick FFPE sections of the breast tumor samples were microdissected to ensure >70% tumor cell content as previously described.36 Total RNA was extracted from breast cancer tissues using the RNeasy FFPE RNA Isolation Kit (Qiagen) followed by an additional DNase treatment as previously described.37 RNA quantification was performed using the Ribogreen Quant-iT reagent (Invitrogen, UK) according to the manufacturer's instructions. Total RNA was extracted from breast cancer cell lines using the RNAeasy kit (Invitrogen) according to the manufacturer's instructions. RT was performed using Superscript III (Invitrogen) converting 500 ng of total RNA, with triplicate reactions undertaken for each sample as previously described.37 In addition, in all cases of primary breast cancer where MassARRAY analysis yielded positive results, validation of the presence of the fusion gene was performed using not only the RNA sample subjected to MassARRAY analysis, but also with RNA obtained from a re-microdissected sample.
To assess the performance of this assay in a biologically relevant scenario, where the fusion gene is harbored by a non-modal tumor cell population within a heterogeneous tumor, cDNA from HCC1937 (known to harbor the NFIA-EHF fusion gene) was pooled with HCC1954 (devoid of this fusion gene) in serial dilutions of 0, 10, 25, 50, 75, 90, and 100%.
PCR Primer and Extension Probe Design
Five PCR multiplexes were designed using Sequenom's Assay Designer software (available from https://www.mysequenom.com/Home), two multiplexes for probe 1 and three for probe 2. Sequences for initial PCR primers and extension primers for each fusion gene assessed in this study are shown in Table 2, and details of multiplexes, unextended and extended primer masses are detailed in Supplementary Table 2. Amplification primer pairs were designed so the forward and reverse primers hybridize to each partner of the fusion gene (Figure 2). Therefore, in the absence of a fusion gene, no PCR product is available for the single base extension step. Two single base extension probes were designed to detect the presence of each of 10 previously characterized fusion genes. In each case, probe 1 was designed to specifically amplify the region of the breakpoint with an extension primer upstream and downstream, extending a single base beyond the breakpoint to the partner gene (Figure 2). Probe 2 (consisting of a single primer) was designed to hybridize to the breakpoint region, spanning 5–6 bases on either side of the fused genes, and extend to the 3′-end of the fusion gene (Figure 2).
Sequenom MassARRAY Protocol
Initial amplification PCR multiplex reactions were performed in 384-well plates using 2.5 ng of cDNA, 100 nM PCR primers, 2.75 mM MgCl2, 200 μM dNTP, and 0.1 U of hot-start enzyme (PCR enzyme Kit, Sequenom) per reaction, under the following conditions: 94°C for 5 min, followed by 45 cycles of 94°C (30 s), 56°C (30 s), 72°C (60 s), and a final extension step at 72°C for 3 min. Samples were kept at 4°C until further analysis. Shrimp alkaline phosphatase (SAP) dephosphorylates unincorporated dNTPs by cleaving phosphate groups from the 5′-termini, removing all excess dNTPs. A 2μl mixture, comprising 0.3 μl SAP (1 U/μl), 0.17 μl SAP buffer (10 × ) and 1.53 μl H2O, was added to the PCR products, which were then subjected to the following conditions: 37°C for 40 min, followed by 85°C for 10 min. Samples were kept at 4°C until further analysis.
Samples were then subjected to the iPLEX extension reaction, during which the primers hybridize to their target regions, which are extended by a single mass-modified nucleotide. Extension primers and multiplexes are detailed in Supplementary Table 2. The final extension reaction contains 0.222 μl iPLEX buffer (10 × ), 0.2 μl iPLEX termination mix, 0.041 μl iPLEX enzyme, 0.4926 μl H2O, and 1.0444 μl of the extension primers at their optimized concentrations (Sequenom). The extension reaction conditions were as follows: 94°C for 30 s, followed by 40 cycles of 94°C for 5 s, followed by 5 cycles of 52°C for 5 s, and 80°C for 5 s and a final step of 72°C for 3 min. The iPLEX reaction products were then treated with a cationic exchange resin for 30 min to remove salts, such as Na+, K+, and Mg+ ions, to minimize background noise. In all, 15 nl of the resulting products were spotted onto the MassARRAY SpectroCHIP II with a nano-dispenser (Sequenom), followed by insertion into the mass spectrometer of the MassARRAY System (Sequenom).
Data Analysis
MassARRAY results were analyzed with the SpectroTYPER 4.0. software. Design information was used to calculate the expected position of the correct analyte in the spectra. In the presence of a targeted fusion gene, PCR products are generated and single base extension will result in an allele-specific peak (Figure 2). The accurate detection of a fusion gene by MassARRAY using this assay requires both the forward and reverse primers of probe 1, and a single primer for probe 2 to detect the expected allele (according to primer design), whereas a negative MassARRAY result is recorded if either primer of probe 1 and/or the single primer of probe 2 fail to detect an allele. True positive results were defined as samples classified as positive by MassARRAY that were previously determined to harbor the same fusion genes by massively parallel sequencing, FISH or RT–PCR. The results of the MassARRAY analysis were interpreted by two observers (MBK and SM) blinded to the results of FISH and RT–PCR.
Sensitivity was defined as the proportion of FISH/RT–PCR positive tests, which were identified as positive by Sequenom MassARRAY. Specificity was defined as the proportion of FISH/RT–PCR negative tests, which were identified as negative by Sequenom MassARRAY. Negative predictive value was defined as the proportion of negative tests by Sequenom MassARRAY that were negative by FISH/RT–PCR. Positive predictive value was defined as the proportion of positive tests by Sequenom MassARRAY that were positive by FISH/RT–PCR.
The sensitivity, specificity, and negative and positive predictive values of this assay were determined by combining the results from MassARRAY analysis of all 10 fusion genes in the 10 cancer cell lines (nine breast cancer cell lines and HeLa cells) and of two fusion genes (ie NFIA-EHF and SLC26A6-PRKAR2A) in 125 breast cancer samples. These results were compared with the previously determined fusion gene status of these samples by massively parallel sequencing and RT–PCR in the cell lines, or RT–PCR and FISH in the series of primary breast cancers (Figure 1).
RESULTS
MassARRAY analysis identified all known fusion genes correctly (ie 100% sensitivity and negative predictive value) with either probe 1 or probe 2 (Table 3). Importantly, when samples were evaluated with either probe independently, the performance of this assay was suboptimal, given the high number of false-positive results and the limited specificity (95.0 and 94.4% for probe 1 and probe 2, respectively) and positive predictive value (37 and 34.5% for probe 1 and probe 2, respectively; Table 3 and Supplementary Table 3).
When the results of the two probes were combined, the specificity (98.8%) and positive predictive value (71.4%) were both increased, without a reduction in sensitivity (100%) or negative predictive value (100%; Table 3).
Given the high sensitivity and negative predictive value of the MassARRAY assay to detect expressed fusion genes, we sought to determine if any of the 10 fusion genes identified in the cell lines by massively parallel sequencing would be present in any of the breast cancers included in this study. First, to ascertain the efficacy of the assay to detect expressed fusion genes in FFPE samples, cDNA derived from FFPE pellets of two breast cancer cell lines harboring three fusion genes (HCC38 harboring MBOAT2-PRKCE and SLC26A6-PRKCE fusion genes, and HCC1937 harboring the NFIA-EHF fusion gene) were used as positive controls. Among the 10 fusion genes assessed, three were present in one of the cell lines, one of which was a false positive (ie HCC1937 does not harbor the PLXND1-TMCC1 fusion gene; Table 4 and Supplementary Table 4). We next investigated the presence of the remaining eight fusion genes in the series of 125 primary breast cancers. Of these eight fusion genes, seven were not detected in any of the 125 breast tumor samples. The remaining fusion gene (CYP39A1-EIF3K) was positive in four cases using this MassARRAY fusion assay. Independent validation with RT–PCR using custom-designed primers, the same RNA subjected to Sequenom MassARRAY assay, and RNA extracted from independent samples of the same cancers failed to validate any of the results as true positives, demonstrating that no primary breast cancer tested harbored any of the fusion genes evaluated (Figure 3; Supplementary Table 5). These observations lend further support to the suggestion that the majority of expressed fusion genes in usual types of breast cancer are private.
To determine if the assay described here could detect a fusion gene expressed by a non-modal cancer cell population, we performed spiking experiments by mixing cDNA from HCC1937 cells, which express the NFIA-EHF fusion gene, with cDNA from HCC1954 cells, which do not harbor this fusion gene. The Sequenom MassARRAY assay was able to detect a fusion gene expressed by the equivalent of as little as 10% of the cancer cells within a tumor population, in agreement with the results obtained by RT–PCR analysis of the same mixtures of cDNA samples (Figure 4).
This novel fusion gene detection assay has favorable sensitivity and negative predictive value in both cell lines and FFPE breast cancer samples and is able to detect fusion genes in non-modal clonal populations of cancers. Its specificity and positive predictive value, however, are suboptimal.
DISCUSSION
In this proof-of-principle study, we describe a novel application of the Sequenom MassARRAY platform as a robust high-throughput screening tool for the detection of known expressed fusion genes. Probes were designed to specifically target the breakpoint of the fusion transcript. Unlike the DNA breakpoint of recurrent fusion genes, which is specific to each sample, the breakpoint at the transcript level is identical in recurrent expressed fusion genes (eg ETV6-NTRK3 in secretory carcinomas of the breast38). The use of two probes per fusion gene enabled the sensitivity and negative predictive value to be maximized (both 100%), with acceptable specificity (98.8%), but suboptimal positive predictive value (71.4%). We have also used the assay we developed to investigate the presence of eight fusion genes detected in breast cancer cell lines in a cohort of 125 FFPE primary breast cancers. Although four cases were considered to harbor a fusion gene using either of the two MassARRAY probes described here, they were proven to be false-positive results using an orthogonal method (ie RT–PCR) in two biological replicates of the samples.
One source of artifacts when these assays are applied to RNA extracted from FFPE tissues is the degraded nature of RNA extracted. In fact, one could expect a higher proportion of false-positive results if degraded RNA rather than RNA extracted from cell lines or fresh frozen tissues was used. This hypothesis was not confirmed. Out of 200 assays (with both probes) performed on RNA extracted from all cell lines, 26 were false-positive results (13%), whereas out of the 2500 assays performed on RNA extracted from FFPE samples, only 14 were false-positive results (0.6%), less than would have been expected given the source of the RNA. To confirm that the performance of this assay was not adversely affected by tissue fixation and sample preparation, two breast cancer cell lines known to harbor some of the fusion genes evaluated were subjected to formalin fixation and paraffin embedding. RNA was extracted from these cell lines and subjected to the MassARRAY assay. Both fusion genes were accurately detected. These observations suggest that the assay described here is unlikely to be compromised by tissue fixation and sample preparation.
Although the sensitivity and negative predictive value of the MassARRAY assay developed were optimal (ie no false-negative results), false-positive results were observed. The source of the false-positive results is yet to be fully elucidated. It is perhaps surprising that a greater number of false-positive tests were found when RNA extracted from cell lines was assessed. Possible explanations for this observation include (i) incomplete removal of DNA from the RNA samples, (ii) the iPLEX reactions may have been saturated with cDNA from the cell lines, and (iii) formation of primer dimers or hairpin formation, particularly in the absence of the target fusion gene. Importantly, though, despite the suboptimal specificity and positive predictive value, the high sensitivity and negative predictive value render the MassARRAY assay described here as a useful screening tool for the identification of expressed fusion genes. Hence, this assay allows large collections of cancer samples to be rapidly and efficiently screened for the presence of multiple expressed fusion genes in a single experiment. Cases without the target fusion gene can be confidently excluded, therefore, leading to a substantial reduction in the workload for the subsequent validation steps, should the entire screening process be undertaken by RT–PCR or FISH.
The limitations of the present study reflect those inherent to the MassARRAY platform, and, for that matter, any platform that does not allow for de novo sequencing for the detection of fusion transcripts. First, the approach described is not suitable for the identification of novel fusion genes and is of limited utility for discovery studies. Second, using the probes described, MassARRAY can only be employed to detect expressed fusion genes that lead to the formation of chimeric transcripts with recurrent breakpoints at the RNA level; fusion genes resulting from promoter swapping events cannot be identified. Third, in common with other highly sensitive assays, false positives can occur with appreciable frequency. In fact, even by combining the results of probes 1 and 2, the positive predictive value was still 71.4%. Therefore, in the presence of a positive result by the MassARRAY method described here, validation with orthogonal methods (ie RT–PCR and FISH) remains necessary. Finally, we did not detect any of the 10 fusion genes identified in the cell line panel in any of the 125 primary breast cancers screened using the MassARRAY fusion assay. This may be due to the fact that the expressed fusion genes identified in cancer cell lines may have arisen as artifacts of in vitro culturing, and do not readily recapitulate the changes seen in primary tumors. It is conceivable that if fusion genes were detected by massively parallel sequencing of primary breast cancers, and their recurrence interrogated by the MassARRAY methodology described here in a large cohort of phenotypically matched primary breast cancers, recurrent events would have been identified.
In conclusion, we have extended the repertoire of existing applications of the MassARRAY platform by designing an assay that has optimal sensitivity and negative predictive value, and would constitute a useful screening method for expressed fusion genes. The increasing numbers of genomes subjected to massively parallel sequencing will undoubtedly require scalable platforms for the validation of fusion genes identified; the method described here may provide a solution for this need. Importantly, the limited specificity and positive predictive values of the Sequenom MassARRAY assay described here do not allow for its use as a stand-alone diagnostic test for the detection of expressed fusion genes. Confirmation of the results with established ‘gold standards,’ such as FISH and RT–PCR, remains necessary.
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Acknowledgements
This project was funded in part by Breakthrough Breast Cancer. PW is funded by a Wellcome Trust Clinical Fellowship grant. NP is supported in part by a Royal College of Surgeons of England Clinical Research Fellowship. VP and JSRF are funded in part by European Community's Seventh Framework Programme (FP7/2010-2014) under the Grant agreement number 242006. JSR-F is a recipient of the 2010 CRUK Future Leaders Prize. We acknowledge NHS funding to the NIHR Biomedical Research Centre.
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Supplementary Information accompanies the paper on the Laboratory Investigation website
Identification of recurrent expressed fusion genes through FISH and RT-PCR are time-consuming and prone to artefacts. A novel high-throughput strategy for the detection of recurrent fusion genes based on the Sequenom MassARRAY platform is described, and shows promise as a high-throughput screening tool for these genes in human cancer.
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Lambros, M., Wilkerson, P., Natrajan, R. et al. High-throughput detection of fusion genes in cancer using the Sequenom MassARRAY platform. Lab Invest 91, 1491–1501 (2011). https://doi.org/10.1038/labinvest.2011.110
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DOI: https://doi.org/10.1038/labinvest.2011.110