Abstract
Tumor genotyping can provide a useful guide to drive clinical trials, inform treatment options, and predict patient outcomes1. This is due, in large part, to our understanding of major cancer pathways and their use in therapeutic strategies. EGFR mutation profiling assesses gefitinib or erlotinib efficacy in non-small cell lung cancer patients. Tumor genotyping of multiple genes and/or mutations, however, is not widely deployed due to the high cost of analyzing these regions via sequencing. In addition, detection of somatic mutations requires a higher level of sensitivity (<10%) than standard sequencing methods. Mutations are typically present in tumor cells that are heterogeneous and present in a high background of normal tissue making it challenging to detect early stage or conversely residual diseases. The MassARRAY® system* offers the ability to rapidly profile 10s to 100s of mutations in 10s to 1000s of samples with as little as 5% mutation abundance in fresh tissue and formalin fixed paraffin embedded (FFPE) samples. Optimized assays within the OncoCarta™ Panels can screen up to 600 mutations against 50 oncogenes and tumor suppressors, or custom de novo assays can easily be developed.
*Based on MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization – Time of Flight) mass spectrometry
Introduction Figure 1—Analytical sensitivity of the Sequenom MassARRAY® System Figure 2—Somatic Mutation in FFPE Tumor Sample detected at 15% Frequency. Figure 2 shows the MassARRAY® spectrum for a KIT mutation, V559del, for which there is either a wild-type allele (GTT) or deletion. Using MassARRAY® software, assays can easily be designed so that there is a clear distinction between the mutations and wild type. In this particular assay, the mass for the deletion is at 7764 Da, and the mass for the wild-type allele is at 7788 Da, resulting in a 24 Da separation. The intensity of the two alleles is compared to determine the relative frequency for each within the tumor sample. In the formalin-fixed paraffin embedded tissue (FFPE) analyzed, 15% of the tissue contained the V559del and 85% of tissue was wild-type. An unrelated mutation (grayed out) from a separate multiplex has been designed within the same mass window. Cancer is a disease of abnormal cell proliferation caused by mutations in genes that control proliferation and the cell cycle2. Cancers arise from mutations in a subset of genes that confer growth advantage. A survey of 200 cancers revealed 1,000 somatic mutations in roughly 500 protein kinase genes3. Genome-wide association studies and cancer genome sequencing have also identified mutations in more than 100 oncogenes and 30 tumor suppressor genes. Somatic mutations do not appear to occur randomly in cancer, and are found more frequently in certain genomic regions and/or cellular pathways than others. Mutation profiling has the potential to quickly identify which signaling pathway(s) have been co-opted to drive the proliferation of a specific human tumor type. On a patient specific basis, mutation profiling may thus be a useful tool in guiding therapeutic options. To advance clinical research, clinical trials and translational medicine, an approach for targeted mutation analysis across different tumor types and in statistically significant sample numbers is needed. It is currently too costly to routinely search for mutations in these genes by de novo sequencing. In any event not all mutations are equally likely to produce cancer phenotypes. Sanger sequencing has been effectively used for somatic mutation discovery. However, when there is a heterogeneous mixture of cancerous and normal tissue, Sanger sequencing may be unable to detect low frequency mutations. In one published study, Sequencing failed to detect EGFR (Epidermal Growth Factor Receptor) mutations in individuals with roughly 10% allele frequencies4. Next generation sequencing methods may hold promise for somatic mutation analysis. As yet, however the analytical sensitivity and quantitative performance of advanced sequencing methods for the detection of mutations in formalin fixed, paraffin-embedded solid tumor biopsies that include a mixture of neoplastic and non-neoplastic cells is unknown. In addition the current costs make focused second generation sequencing impractical. In contrast the high level of sensitivity and quantitative capability of the MassARRAY® System makes it ideal for analyzing somatic mutations in solid tumors or tumor cell lines. Analytical sensitivity and quantification Sequenom’s MassARRAY® system utilizes PCR amplification and single-base primer extension for mutation detection. The analytical sensitivity of the MassARRAY® system is demonstrated by titrating wild-type vs. mutant DNA. As an example, one assay to the EGFR T2582A mutation was analyzed (Figure 1). The sample consisted of 20 nanograms of total DNA comprising genomic DNA mixed with a synthetic oligonucleotide containing the mutation in amounts ranging from 0 to 100%. Excellent linearity was achieved. While the detection limit of the mutant allele varies between assays and samples, it is typically around ~5-10%. This is approximately 2.5-3.0-fold more sensitive than Sanger sequencing. Sensitive detection allows analysis of tumor samples that are limited in quantity or quality due to degradation and/or chemical modification. In one independent study (data not shown) the researchers were able to assess 3% mutant alleles5. High sensitivity demonstrated in tumor samples In a second experiment, the sensitivity and quantification was assessed. An FFPE sample of known mutation status was profiled with the MassARRAY® system, and compared against information previously obtained via sequencing analysis. Interestingly, we were able to confirm the previous mutation profile, but we also detected new mutations due to the higher level of sensitivity of the MassARRAY instrument, and lower mutation frequency within the sample. Somatic mutation analysis on the MassARRAY® System The MassARRAY® system offers a highly effective method for profiling hundreds of somatic mutations. Sequenom increases the speed and accessibility of mutation profiling with four optimized OncoCarta™ Panels (figure 3). The panels can be used to assess genetic changes associated with tumor initiation and progression, or for clinical research to evaluate therapies based on individual genotypes. Tens to hundreds of samples can be profiled in a single day. Figure 3—Oncogene mutations included in Sequenom’s OncoCarta™ Panels Panel Number of Genes Gene (# mutations) OncoCarta™ Panel 1.0 19 ABL1 (14); AKT1 (7); AKT2 (2); BRAF (28); CDK4 (2);EGFR (40); ERBB2 (8); FGFR1 (2); FGFR3 (9); FLT3(3); HRAS (12); JAK2 (1); KIT (32); KRAS (18); MET(5); NRAS (18); PDGFRA (11); PIK3CA (16); RET (6) OncoCarta™ Panel 2.0 18 AKT1 (1); BRAF (8); CTTNB1 (21); FBX4 (5); FBXW7(5); FGFR2 (2); FGFR3 (1); GNAQ (2); KIT (43); KRAS (6); MAP2K1 (6); MAP2K2 (5); NRAS (2);PDGFRA (4); PIK3CA (28); PTPN11 (1); SOS1 (3); P53(14) OncoCarta™ Panel 3.0 29 ABL1 (2); AKT1 (1); APC (12); BRAF (19); CDKN2A(7); CSF1R (6); CTTNB1 (28); EGFR (31); ERBB2 (1); ERBB3 (1); FLT3 (1); FLT4 (1); FLT5 (1); HRAS (2); JAK3 (3); KIT (3); KRAS (5); MET (5); MLH1 (1); MYC(6); PDGFRA (11); PIK3CA (5); PTEN (14); RB1 (11);RET (13); SRC (1); STK11 (12); P53 (7); VH1 (7) MelaCarta™ Panel 1.0 20 AKT1 (1); BRAF (20); CDK4 (2); CTNNB1 (5); CXCR4(1); EPHA 10 (1); EPHB6 (2); ERBB4 (2); GNA11(2); GNAQ (2); KIT (5); KRAS (9); MEK(2); MET(2); NEK10 (1); NRAS (11); PDGFRA (1); PIK3CA (1); PTK2B (2); ROR2 (1) *For a comprehensive list of mutations within each of the panels, visit www.sequenom.com/explore While the OncoCarta™ Panels feature a comprehensive set of mutations suitable for most research studies, research groups may want to profile other mutations. Researchers have the option to order custom assay design through Assays by Sequenom, a full service offering in which Sequenom designs and runs assays against your samples of interest. If researchers have access to a MassARRAY® system, they can also design their own assays using Sequenom’s TYPER™ Assay Designer software. A number of key cancer institutes have developed panels for their own utility 1, 4, 5, 6, and 7. Summary The MassARRAY® system has been demonstrated as an effective method for somatic mutation analysis due to its high level of sensitivity and quantitative ability. It offers flexibility in throughput, sample type, and assay format. The system is ideal for analyzing 10s to 100s of genetic targets across 100s to 1000s of samples. Cancer gene mutation profiling, with its select roster of candidate oncogenes and tumor suppressors, can be readily assessed on the MassARRAY® system. The MassARRAY® System is for research use only not for diagnostic use. References MacConaill, L. et al. Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples, PLoS ONE, (2009) 4(11) 1-7. Soto, A., et al. The somatic mutation theory of cancer: growing problems with the paradigm? BioEssays (2004) 26:1097–1107. Greenman, C., et al. Patterns of somatic mutation in human cancer genomes. Nature (2007) 446, 153-158. Thomas, R.K., et al. High-throughput oncogene mutation profiling in human cancer, Nature Genetics (2007), 39(3):283-4. Vivante, A., et al. High-throughput, sensitive and quantitative assay for the detection of BCR-ABL kinase domain mutations, Leukemia (2007) 21, 1318–1321. Dunlap, J. et al. Phosphatidylinositol-3-kinase and AKT1 mutations occur early in breast carcinoma, (2009) Breast Cancer Res Treat. Davies, M.A., et al. A novel AKT3 mutation in melanoma tumours and cell lines, British Journal of Cancer (2008), 1–4.
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