Accurate and sensitive mutation detection and quantitation using TaqMan Mutation Detection Assays for disease research



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PPLICTION NOTE Mutation Detection ssays ccurate and sensitive mutation detection and quantitation using Mutation Detection ssays for disease research In this research study, we addressed the feasibility of obtaining sensitive, accurate, and reproducible mutation detection results in synthetic templates, cell lines, and FFPE tissue samples using Mutation Detection ssays. nalytical performance assessed with synthetic templates and genomic DN (gdn) extracted from cell lines or model FFPE cell lines indicates that Mutation Detection ssays have a minimum of 0.1% sensitivity and can detect fewer than 10 copies of mutant DN sequence in a background of wild type gdn. Our data indicate that Mutation Detection ssays can accurately detect mutation status and quantify the percent mutation with a relative standard deviation (CV) <20%. dditionally, benchmarking to an established qpcr assay technology for mutation detection demonstrates that the Mutation Detection ssays have a wider detection range and superior limit of detection. Introduction Somatic mutations can be present in low abundance within a very high background of wild type sequences. Many mutation detection methods compatible with tumor specimens have been reported in the literature and/or are commercially available. Methods that are commonly used are gene sequencing (including pyrosequencing and traditional Sanger sequencing) and real-time PCR. Realtime PCR based technologies include high-resolution melt curve analysis, peptide nucleic acid (PN) clamping, and allele-specific amplification with bifunctional fluorescent primer/probe detection (RMS/Scorpion). However, these commercially available kits have various limitations in terms of sensitivity, specificity, cost, workflow, and turnaround time. lso, there is a need for the technology to be able to accurately quantify the percent mutation within a sample. We developed sensitive and quantitative Mutation Detection ssays to help accurately assess mutation status and percentage in research samples. Mutation Detection ssays were designed based on novel competitive allele specific (castpcr ) technology, which combines allele-specific qpcr with allele-specific MGB blocker oligonucleotides to effectively suppress nonspecific amplification of the off-target allele (Figure 1).

3 5 3 5 SP SB G SP llele-specific primer SB llele-specific blocker (MGB) LST Locus-specific probe LSP Locus-specific primer LST LSP 5 3 5 3 Figure 1. Schematic of a Mutation Detection ssay. mutant allele assay or wild type allele assay is composed of an allele-specific primer (SP), locus-specific primer (LSP), locus-specific probe (LST), and allele-specific blocker (SB). The % mutation present in the sample is calculated based on the ΔC t value between amplification reactions for a mutant allele assay and the corresponding wild type allele assay or a gene-specific reference assay. Materials and methods DN samples Twelve cell lines (from TCC or other sources; Table 1) were cultured according to the suppliers recommendations, and gdn was isolated using the PureLink Genomic DN Mini Kit (Life Technologies) or the QIamp gdn Mini Kit (Qiagen). gdn from mutant cell lines was diluted into gdn from wild type cell lines at various percentages. The total gdn sample input in each reaction was 10 ng or 30 ng. Eight model FFPE cell line specimens were prepared by crometrix, part of Life Technologies (Table 1). gdn was extracted from 20 µm slices with the Recoverll Nucleic cid Extraction Kit (mbion, part of Life Technologies) or QIamp DN FFPE Kit (Qiagen). gdn from mutant cell lines was diluted into gdn from FFPE wild type cell lines at various percentages. The total FFPE sample input in each reaction was 30 ng. FFPE or fresh frozen tumor specimens (colorectal and lung cancer) were collected and gdn was extracted by an independent laboratory using their own validated method. Synthetic plasmid constructs for seven KRS mutant alleles and corresponding wild type alleles were each designed with 600 bp of genomic context sequence surrounding the mutant base. Gene synthesis, plasmid construction, and plasmid preparation were performed by Genert, part of Life Technologies (Regensburg, Germany), and all sequences were verified by Sanger sequencing prior to use. ll DN samples were quantified using a NanoDrop ND1000 (NanoDrop Technologies) or RNase P Detection Reagents Kit. DN Template Reagents Kit were used to create a standard curve. Mutation Detection ssays Mutation detection experiments were performed by running 10 µl or 20 μl reactions comprising DN template, 1X Genotyping Master Mix, and 1X Mutation Detection ssay (containing allele-specific forward primer, locus-specific probe, locus-specific reverse primer, and allele-specific MGB blocker). qpcr was run on an pplied Biosystems Vii 7 or 7900HT Real-Time PCR System in 96-well or 384-well plates with the following conditions: 95 C for 10 min; 5 cycles: 92 C for 15 sec and 58 C for 1 min; 45 cycles: 92 C for 15 sec and 60 C for 1 min. ll samples were run in quadruplicates or triplicates. C t values were obtained from the instrument s real-time PCR data collection software using auto baseline and 0.2 manual threshold. The mutation status and percent mutation were analyzed using Mutation Detector software.

Table 1. Cell lines used in this study and their corresponding mutations. Cell line Sample type Mutation description mutation ID SW1463 Fresh/FFPE KRS G12C 516 549 Fresh/FFPE KRS G12S 517 PSN-1 Fresh/FFPE KRS G12R 518 SW480 Fresh/FFPE KRS G12V 520 PNC-1 Fresh/FFPE KRS G12D 521 NCI-H2009 Fresh/FFPE KRS G12 522 DLD-1 Fresh/FFPE KRS G13D 532 H460 Fresh EGFR L858R 6224 H1975 Fresh EGFR T790M 6240 Table 2. KRS gene mutations in the benchmarking study. mutation ID Nucleotide change mino acid change 516 c.34g>t p.g12c 517 c.34g> p.g12s 518 c.34g>c p.g12r 520 c.35g>t p.g12v 521 c.35g> p.g12d 522 c.35g>c p.g12 532 c.38g> p.g13d H1650 Fresh EGFR Exon19 Del 6223 Colo 201 Fresh BRF V600E 476 Jurkat Fresh/FFPE Wild type Benchmarking of the Mutation Detection ssays to another commercially available qpcr technology for mutation detection was performed for seven KRS gene mutation targets (Table 2). The other commercially available assays, or assays, were purchased as a kit and the assay reactions were performed according to the protocol. The benchmarking experiments were performed on the pplied Biosystems 7500 Real-Time PCR System in 96-well reaction plates. The Mutation Detection ssays were used with the following thermal cycling conditions: 95 C for 10 min; 5 cycles: 92 C for 15 sec and 58 C for 1 min; 40 cycles: 92 C for 15 sec and 60 C for 1 min; with the analysis settings described above. The mutation detection assays were run in 25 μl reaction volume with the following thermal cycling conditions: 95 C for 4 min; 40 cycles: 95 C for 30 sec and 60 C for 1 min. nalysis of assays was performed according to the vendor s protocol. Results ssay sensitivity, selectivity, and linearity To evaluate assay sensitivity, selectivity, and linearity, gdn from each of the mutant cell lines (fresh or FFPE cell line) was serially diluted into a background of wild type cell line gdn of the same sample type. For fresh cell lines, the mutant allele percentage ranged from 100% to 0.1%. For FFPE cell lines, the mutant allele percentage ranged from 50% to 0.1%. The results show that assays can detect mutations at various percentages with excellent linearity (R 2 >0.990) and PCR efficiency (100 ± 10%) (Figure 2). In addition, assays can clearly detect 0.1% mutation (equivalent to 10 copies of mutant allele) in a background of 30 ng wild type gdn (Figure 2B). Some of the assays have been shown to detect down to a single copy of the mutant allele in a background of 100 ng wild type gdn (data not shown). ssay accuracy and reproducibility To assess the detection accuracy and reproducibility of the Mutation Detection ssays, three independent experiments were performed to measure the mutation percentage of model samples prepared in the above-mentioned cell line titration study. Both mutant allele assays and the corresponding wild type allele assays were run with each sample. The percent mutation present in the sample was calculated based on the ΔC t value between amplification reactions for the mutant allele assay and corresponding wild type allele assay. Run-to-run variation was analyzed for detection precision. The data show that these research assays can precisely quantify the percent mutation with CV<20% when the target allele copy number is >30 (Table 3).

KRS mutation detection in FFPE colorectal tumor research specimens Seven KRS Mutation Detection ssays were further tested with biological samples by an independent laboratory using a total of 31 gdn samples from FFPE colon tissue research specimens. mong those 31 samples, 10 were non-tumor colon specimens and 21 were colorectal tumor specimens. The KRS mutation status of these samples was validated by three different methods ( allelic discrimination (D) probe assay (custom SNP assay), D probe assay + peptide nucleic acid (PN) wild type allele blocker, and Sanger sequencing) (Table 4). Ten gdn samples extracted from normal FFPE tissues were examined for KRS mutation status using Mutation Detection ssays. No positive samples were found in the 10 nontumor tissues. The results obtained by KRS Mutation Detection ssays for those tumor samples were concordant with previously reported results (Table 4). KRS, BRF, and EGFR mutation detection in cell line and tumor biopsy research samples Mutation Detection ssays were evaluated using a total of 33 gdn samples from cell lines and tumor biopsy research samples (fresh frozen and FFPE tissues) by an independent laboratory. Mutation status of these samples was initially assessed by two different methods (amplification refractory mutation system (RMS ) technology and Sanger sequencing). RMS technology for mutation detection discriminates between the mutation and wild type DN by selectively amplifying the target sequence. The results from the Mutation Detection ssays demonstrated complete concordance. B. C t 31 29 27 25 23 21 0.1% G12R FFPE cell titration 0.5% y = -3.3345x + 25.632 R 2 = 0.99897 1% 19-1.50-1.00-0.50 0.00 0.50 1.00 1.50 2.00 10 1 1 10-1 10-2 10-3 10-4 log % mutation 5% mplification plot 0.1% Mutation sample Wild type gdn sample 12.5% 25% 50% Figure 2. Mutation Detection ssays can detect mutations at various percentages with excellent linearity and PCR efficiency. The FFPE mutant cell line PSN-1 was serially titrated into the FFPE wild type Jurkat cell line from 50% to 0.1%. The total gdn sample input was 30 ng. The KRS_518_mu mutant allele assay was used to detect mutations in these model FFPE samples. () The KRS_518_mu assay demonstrated excellent linearity (R 2 = 0.999) and PCR efficiency (99.5%). (B) The amplification plot shows the C t difference between 0.1% mutation sample (10 copies mutant allele in 30 ng wild type gdn and wild type gdn sample (30 ng) for the KRS_518_mu assay.

Table 3. KRS G12C percent mutation measurement in cell line titration research samples from run to run. In this experiment, the total genomic DN input was 10 ng. G12C mutant cell line gdn titrated into wild type cell line gdn Target mutant allele copy number 3000 1500 750 375 188 90 30 15 3 Expected (%) 100 50 25 12.5 6.3 3 1 0.5 0.1 Measured (%), average 100 48.9 23.3 11.2 5.7 2.6 0.8 0.4 0.1 CV (%) from run-to-run 0 2.2 3.8 7.8 7.5 9 17 26 23 Table 4. KRS mutation detection in FFPE colorectal tumor research specimens using different mutation detection technologies. G12 G12C G12D G12R G12S G12V G13D WT Mutation Detection ssays 2 1 4 0 0 4 8 2 D assay 2 1 4 0 0 4 8 2 D assay + PN blocker 2 1 4 0 0 4 8 2 n = 21 Sequencing 2 1 4 0 0 4 8 2 Table 5. Mutation detection in cell lines and tumor biopsy research samples. The same samples were tested independently at different sites. EGFR_L858R EGFR_2235_2249del15 KRS_G12C KRS_G12R KRS_G12V KRS_G12D Mutation Detection ssay (data from an independent laboratory) Mutation Detection ssay (internal testing data) 2 2 4 1 6 3 2 2 4 1 6 3 RMS 2 2 4 1 6 3 Sanger sequencing 2 2 4 1 6 3 to those previously reported results. Eighteen of the 33 gdn samples were then independently tested at Life Technologies to determine the robustness and reproducibility of the assays in biological samples. Results from this independent testing showed that Mutation Detection ssays are highly accurate and reproducible (Table 5). Benchmarking to other commercially available mutation detection kits Specificity and sensitivity of the Mutation Detection ssays compared to s product for mutation detection were evaluated with synthetic plasmid DN targets containing either the mutant allele or wild type allele. The seven KRS mutant allele assays from each company were run with 10,000 copies (equivalent to 30 ng gdn) of both target alleles. Three replicates were performed for each target, and the average C t values were determined (Figures 3 and 3B). Mutation Detection ssays generated significantly lower C t values compared to s assays, indicating that the Mutation Detection ssays have greater sensitivity. In addition, the mutant allele assays did not amplify the wild type allele target, with the exception of one Mutation Detection ssay that resulted in minimal amplification for mutation target KRS 521. The mutant allele assay on wild type allele target C t value minus the mutant allele assay on mutant allele target C t value provides a ΔC t value for each target assessed. This ΔC t correlates to the sensitivity capabilities of the assay. larger ΔC t value indicates the assay can detect a lower percent mutation in a larger quantity of sample. The Mutation Detection ssays provided significantly larger ΔC t values than s assays did, demonstrating the greater sensitivity of the Mutation Detection ssays.

The limit of detection for each of the seven assays for both technologies was evaluated with a dilution range of mutant allele targets, each combined with a constant 30 ng of wild type gdn. Two replicates were performed for each mutant allele target input quantity from 10,000 copies down to 1 2 copies per reaction. The number of reactions that amplified and reached the cycle threshold value before cycle 40 was counted (Table 6). The Mutation Detection ssays detected down to 1 copy of mutant allele sequence in a background of 10,000 copies of wild type gdn. s mutation detection assays reproducibly detected 50 copies for all seven mutations; however, detection was inconsistent below this input quantity. These results demonstrate the superior limit of detection of Mutation Detection ssays compared to this current commercial qpcr technology. Conclusions This study demonstrates that Mutation Detection ssays can accurately detect mutation status and quantify percent mutation in research samples with a relative standard deviation (CV) <20% in fresh and FFPE cell line samples containing a high background of gdn. The research assays demonstrate a minimum sensitivity of 0.1% mutation, and can detect down to a single copy of mutated DN sequence in a background of wild type gdn. dditionally, benchmarking to an established qpcr mutation detection technology shows that Mutation Detection ssays have a wider detection range and superior limit of detection.. Mutant allele DN target verage C t 40 35 30 25 20 15 10 5 0 516 517 518 520 521 522 532 mutation B. Wild type allele DN target verage C t 40 35 30 25 20 15 10 5 0 516 517 518 520 521 522 532 mutation Figure 3. Comparison of Mutation Detection ssays with s mutant allele assays. C t values of Mutation Detection ssays (blue) versus the C t values of s mutant allele assays (grey) run on 10,000 copies of () mutant allele DN target or (B) wild type allele DN target. The data demonstrate that Mutation Detection ssays have higher sensitivity and equivalent specificity compared to s assays.

Table 6. Limit of detection evaluation across a dynamic range of mutant allele DN target inputs in a background of wild type allele DN for and s mutation detection assays (n = 2 per input quantity). Red indicates that less than two replicates were detected; gray indicates that no replicates were detected. Mutant allele target input mutation 516 mutation 517 mutation 518 mutation 520 mutation 521 mutation 522 mutation 532 10,000 copies 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1,000 copies 2 2 2 2 2 2 2 2 2 2 2 2 2 2 100 copies 2 2 2 2 2 2 2 2 2 2 2 2 2 2 50 copies 2 2 2 2 2 2 2 2 2 2 2 2 2 2 25 copies 2 2 2 0 2 2 2 2 2 2 2 2 2 2 10 copies 2 1 2 0 2 1 2 2 2 1 2 2 2 0 5 copies 2 2 2 0 2 1 2 1 2 0 2 1 2 1 ~1 to 2 copies 1 0 1 0 1 0 1 0 1 0 2 0 0 0 Mutation Detection ssays have the following features: 1. ssays can detect less than 0.1% mutation in a background of wild type gdn. The limit of detection is down to 1 copy of mutant allele. 2. ssays have excellent linearity and PCR efficiency. 3. ssays are highly reproducible and can precisely quantify percent mutation. 4. ssays are highly accurate and highly concordant with other technologies. 5. ssays are compatible with multiple sample types including FFPE tissues, fresh frozen tissues, and cell lines. 6. ssays have superior detection range and sensitivity compared to current commercially available qpcr assays.

For Research Use Only. Not intended for any animal or human therapeutic or diagnostic use. 2011 Life Technologies Corporation. ll rights reserved. The trademarks mentioned herein are the property of Life Technologies Corporation or their respective owners. is a registered trademark of Roche Molecular Systems Inc., used under permission and license. Printed in the US. CO31540 01011 Headquarters 5791 Van llen Way Carlsbad, C 92008 US Phone +1.760.603.7200 Toll Free in the US 800.955.6288 www.lifetechnologies.com