Multiplex Mutation Screening by Mass Spectrometry
2011; Elsevier BV; Volume: 13; Issue: 5 Linguagem: Inglês
10.1016/j.jmoldx.2011.04.003
ISSN1943-7811
AutoresCarol Beadling, Michael C. Heinrich, Andrea Warrick, Erin M. Forbes, Dylan Nelson, Emily Justusson, Judith Levine, Tanaya Neff, Janice Patterson, Ajia Presnell, Arin McKinley, Laura J. Winter, Christie Dewey, Amy Harlow, Oscar Barney, Brian J. Druker, Kathryn G. Schuff, Christopher L. Corless,
Tópico(s)Lung Cancer Treatments and Mutations
ResumoThere is an immediate and critical need for a rapid, broad-based genotyping method that can evaluate multiple mutations simultaneously in clinical cancer specimens and identify patients most likely to benefit from targeted agents now in use or in late-stage clinical development. We have implemented a prospective genotyping approach to characterize the frequency and spectrum of mutations amenable to drug targeting present in urothelial, colorectal, endometrioid, and thyroid carcinomas and in melanoma. Cancer patients were enrolled in a Personalized Cancer Medicine Registry that houses both clinical information and genotyping data, and mutation screening was performed using a multiplexed assay panel with mass spectrometry–based analysis to detect 390 mutations across 30 cancer genes. Formalin fixed, paraffin-embedded specimens were evaluated from 820 Registry patients. The genes most frequently mutated across multiple cancer types were BRAF, PIK3CA, KRAS, and NRAS. Less common mutations were also observed in AKT1, CTNNB1, FGFR2, FGFR3, GNAQ, HRAS, and MAP2K1. Notably, 48 of 77 PIK3CA-mutant cases (62%) harbored at least one additional mutation in another gene, most often KRAS. Among melanomas, only 54 of 73 BRAF mutations (74%) were the V600E substitution. These findings demonstrate the diversity and complexity of mutations in druggable targets among the different cancer types and underscore the need for a broad-spectrum, prospective genotyping approach to personalized cancer medicine. There is an immediate and critical need for a rapid, broad-based genotyping method that can evaluate multiple mutations simultaneously in clinical cancer specimens and identify patients most likely to benefit from targeted agents now in use or in late-stage clinical development. We have implemented a prospective genotyping approach to characterize the frequency and spectrum of mutations amenable to drug targeting present in urothelial, colorectal, endometrioid, and thyroid carcinomas and in melanoma. Cancer patients were enrolled in a Personalized Cancer Medicine Registry that houses both clinical information and genotyping data, and mutation screening was performed using a multiplexed assay panel with mass spectrometry–based analysis to detect 390 mutations across 30 cancer genes. Formalin fixed, paraffin-embedded specimens were evaluated from 820 Registry patients. The genes most frequently mutated across multiple cancer types were BRAF, PIK3CA, KRAS, and NRAS. Less common mutations were also observed in AKT1, CTNNB1, FGFR2, FGFR3, GNAQ, HRAS, and MAP2K1. Notably, 48 of 77 PIK3CA-mutant cases (62%) harbored at least one additional mutation in another gene, most often KRAS. Among melanomas, only 54 of 73 BRAF mutations (74%) were the V600E substitution. These findings demonstrate the diversity and complexity of mutations in druggable targets among the different cancer types and underscore the need for a broad-spectrum, prospective genotyping approach to personalized cancer medicine. The identification of somatic mutations that cause aberrant activation of intracellular signaling pathways has transformed the diagnosis and treatment of cancer. Mutations in specific genes define distinct subtypes of cancer, and provide invaluable markers for disease diagnosis and prognosis. Many of the mutated proteins also represent targets for novel therapeutic agents that are more specific, more efficacious, and less toxic than broad-based chemotherapeutic regimens.1Druker B.J. Translation of the Philadelphia chromosome into therapy for CML.Blood. 2008; 112: 4808-4817Crossref PubMed Scopus (576) Google Scholar, 2Heinrich M.C. Corless C.L. Demetri G.D. Blanke C.D. von Mehren M. Joensuu H. McGreevey L.S. Chen C.J. Van den Abbeele A.D. Druker B.J. 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Antonescu C.R. Schwartz G.K. A phase II study of imatinib mesylate (IM) for patients with advanced melanoma harboring somatic alterations of KIT.J Clin Oncol. 2009; 27 (abstr 9001 27 (No 15S):9001)Google Scholar Using genomic mutation signatures predictive of sensitivity to targeted therapies is the most effective way to identify patients most likely to benefit. Moreover, because many of the compelling cancer drug targets are shared across several tumor types, new drug trials are likely to be most efficient when patient populations are recruited on the basis of genotype, as opposed to solely on the basis of cellular tumor type. A transformative approach to drug development and routine clinical management of cancer patients would be to use broad-based prospective genotyping of clinical tumor specimens to identify relevant drug targets in individual patients. To this end, we have established a Personalized Cancer Medicine Registry (PCMR) with the goal of integrating prospective tumor genotyping into the care of cancer patients. The PCMR serves as a repository of both clinical information and genotyping data and is the focal point for the application of genotyping technologies that work on formalin-fixed, paraffin-embedded (FFPE) clinical material. Herein, we describe a mass spectrometry–based panel of multiplexed assays that can detect 390 mutations across 30 cancer genes. Evaluation of tumor specimens from 820 registry patients with urothelial, colorectal, endometrioid, or thyroid carcinoma, or melanoma using this approach yielded a previously unappreciated complexity and diversity of mutations in some cancers, particularly in regard to the druggable targets BRAF and PIK3CA. The patterns of oncogenic mutations emerging from these analyses have significant implications for the use of targeted therapeutics that are currently in clinical trials, and the methods described herein provide a robust means to identify these mutations in clinical specimens. Participants were selected from patients receiving clinical care at Oregon Health & Science University for one of five cancer types, with an emphasis on late-stage disease: colorectal adenocarcinoma, endometrioid carcinoma of the uterus or ovary, thyroid carcinoma, urothelial (transitional cell) carcinoma of the bladder or kidney, and malignant melanoma. The study was conducted under full institutional review board approval, with consent or waiver of written documentation of consent per federal and institutional guidelines. Blocks of FFPE tumor tissue, or unstained sections of FFPE tissue, were obtained from the pathology archives of Oregon Health & Science University, or from 115 other health care institutions across 26 US states; one case was obtained from Korea. The diagnosis in each case was confirmed by a single pathologist (C.L.C.). Tumor-rich areas (>75%) were dissected from 5-μm unstained sections by comparison with a hematoxylin and eosin–stained slide, and genomic DNA was extracted using a QIAamp DNA Mini kit (Qiagen, Valencia, CA) in accordance with the manufacturer's instructions. In addition, buccal swabs or saliva samples were collected as a source of germline DNA from the majority of patients. Mutation screening was primarily performed using a panel of 324 assays interrogating 390 mutations in 30 genes analyzed on a MassARRAY platform (Sequenom, San Diego, CA). A total of 500 ng FFPE-derived DNA was required to screen the 36-multiplex panel. This Solid Tumor Panel includes all of the assays that are part of the commercially available OncoCarta v01 panel (Sequenom), as well as 136 custom-designed assays that are now also commercially available (OncoCarta v02, Sequenom). Amplification primers and extension oligo sequences for the 136 custom-designed assays are available upon request. Assay Designer 3.1 software (Sequenom) was used to design assay multiplexes targeting mutations in known cancer genes, and assays were performed using TypePLEX (Sequenom) chemistry. Initial PCR reactions were set up with an EpMotion 5075 liquid handler (Eppendorf), and used 10 ng DNA per multiplex in a total volume of 5 μl, with 100 nmol/L primers, 2 mmol/L MgCl2, 500 μmol/L dNTPs, and 0.1 units Taq polymerase. Amplification included one cycle of 94°C for 4 minutes, followed by 45 cycles of 94°C for 20 seconds, 56°C for 30 seconds, and 72°C for 1 minute, and one final cycle of 72°C for 3 minutes. Unincorporated nucleotides were inactivated by addition of 0.3 units shrimp alkaline phosphatase and incubation at 37°C for 40 minutes, followed by heat inactivation of shrimp alkaline phosphatase at 85°C for 5 minutes. Single base primer extension reactions were performed with 0.625 to 1.25 μmol/L extension primer and 1.35 units TypePLEX thermosequenase DNA polymerase. Extension cycling included one cycle of 94°C for 30 seconds, 40 cycles of 94°C for 5 seconds, five cycles of 52°C for 5 seconds and 80°C for 5 seconds, followed by one cycle of 72°C for 3 minutes. Extension products were purified by incubation for 30 minutes with an ion exchange resin (SpectroCLEAN, Sequenom), and approximately 10 nl of purified product was spotted onto SpectroChip II matrices. A Bruker matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometer (MassARRAY Compact, Sequenom) was used to resolve extension products. MassARRAY Typer Analyzer software (Sequenom) was used for automated data analysis, accompanied by visual inspection of extension products. Examples of all detected mutations were confirmed by standard, bidirectional Sanger sequencing. To determine assay sensitivity, FFPE-derived samples with known mutations were diluted into FFPE-derived wild-type DNA at defined ratios. A total of 10 ng DNA was used per assay multiplex. In separate dilutions, the total amount of DNA in a multiplex was titrated from 20 ng to 0.312 ng. Mutant allelic ratios were determined from the peak area of each allele using Sequenom Typer Analyzer software. Because the Solid Tumor Panel is incomplete for some genes, additional mutation screening was performed for FGFR3 exon 7, and KIT exons 11, 13 and 17 by high-resolution melting curve analyses on a Roche LightCycler 480. The primers used were FGFR3 exon 7 forward 5′-TGGCCCCTGAGCGTCATCTGC-3′, FGFR3 exon 7 reverse 5′-TCTGGTTGGCCGGCAGCCCC-3′, KIT exon 11 forward 5′-CCAGAGTGCTCTAATGACTG-3′, KIT exon 11 reverse 5′-CTCAGCCTGTTTCTGGGAAA-3′, KIT exon 13 forward 5′-GGAAGCCCTCATGTCTGAAC-3′, KIT exon 13 reverse 5′-ACACGGCTTTACCTCCAATG-3′, KIT exon 17 forward 5′-TCGGATCACAAAGATTTGTG-3′, and KIT exon 17 reverse 5′-GCAGGACTGTCAAGCAGAGA-3′. Reactions were performed with 100 ng DNA template in a total volume of 20 μl, with LC480 High Resolution Melting Master Mix (Roche) supplemented with 3 mmol/L MgCl2. FGFR3 primers were used at a final concentration of 200 nmol/L, and KIT primers were used at 500 nmol/L. The amplification conditions included one cycle of 95°C for 8 minutes, followed by 40 cycles of 95°C for 20 seconds, 58°C for 2 seconds, and 72°C for 10 seconds. Melt analysis was performed in one cycle of 95°C for 1 minute, 40°C for 1 minute, 65°C for 1 second, followed by continuous heating to 95°C, with fluorescence measured at 25 acquisitions per degree Celsius (°C). RET-PTC1/PTC3 translocations were detected in cDNA samples from papillary thyroid carcinomas using hydrolysis probes as described previously.30Sadow P.M. Heinrich M.C. Corless C.L. Fletcher J.A. Nose V. Absence of BRAF NRAS, KRAS, HRAS mutations, and RET/PTC gene rearrangements distinguishes dominant nodules in Hashimoto thyroiditis from papillary thyroid carcinomas.Endocr Pathol. 2009; 21: 73-79Crossref Scopus (30) Google Scholar Briefly, RET-PTC1 and RET-PTC3 translocation products were detected in a multiplexed two-color RT-PCR assay with GAPDH as an internal positive control. PTC1- and PTC3-specific forward PCR primers were used with a common RET reverse primer and FAM-labeled Taqman probe, whereas GAPDH was detected with a Texas Red–labeled probe. The primer and probe sequences included H4 (PTC1) forward primer 5′-AAAGCCAGCGTGACCATC-3′, ELE1 (PTC3) forward primer 5′-TGGCTTACCCAAAAGCAGAC-3′, RET reverse primer 5′-GTTGCCTTGACCACTTTTC-3′, RET probe 5′-FAM-CCAAAGTGGGAATTCCCTCGGA-3′IABlkFQ, GAPDH forward primer 5′-AGCCGCATCTTCTTTTGC-3′, GAPDH reverse primer 5′-GCCCAATACGACCAAATCC-3′, and GAPDH probe 5′-/5TexRd-XN/TGG GGA AGG TGA AGG TCG GA/3IAbRQSp/−3′. PCR reactions were performed in a Roche LightCycler 480 instrument using a 20-μl reaction volume, with LightCycler 480 Probes Master reaction mix (Roche), and random-primed cDNA template derived from 40 to 200 ng total RNA. The GAPDH probe was used at 0.15 μmol/L, and all other primers and probes were used at a final concentration of 0.3 μmol/L each. Cycling conditions included an initial 10 minutes denaturing step at 95°C, followed by 40 cycles of 95°C for 10 seconds and 60°C for 20 seconds. Samples that scored positive for the RET-PTC1 and RET-PTC3 multiplex were re-tested with each primer pair individually to determine the RET fusion partner. The mass spectrometry–based assays consist of multiplexed single nucleotide primer extension reactions across known mutation sites, generating extension products that differ by the added mass of a wild-type or mutant nucleotide.31Oeth P. del Mistro G. Marnellos G. Shi T. van den Boom D. Qualitative and quantitative genotyping using single base primer extension coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MassARRAY).Methods Mol Biol. 2009; 578: 307-343Crossref PubMed Scopus (78) Google Scholar, 32van den Boom D. Ehrich M. Discovery and identification of sequence polymorphisms and mutations with MALDI-TOF MS.Methods Mol Biol. 2007; 366: 287-306Crossref PubMed Google Scholar The Solid Tumor Panel consists of 324 assays covering 390 mutations across 30 cancer genes (see Supplemental Table S1 at http://jmd.amjpathol.org). The panel is necessarily biased toward activating mutations in oncogenes, as the design of MassARRAY assays requires foreknowledge of the mutations to be detected. For this reason, the MassARRAY approach is less suitable for screening inactivating mutations in tumor suppressor genes. As detailed in Table 1, the panel covers a substantial portion of the mutations reported in the Catalogue of Somatic Mutations in Cancer (COSMIC) database (http://www.sanger.ac.uk/genetics/CGP/cosmic; v48, released July 27, 2010) for these 30 genes, although rare mutations will still be missed by this approach. For example, in the case of BRAF, the Solid Tumor Panel covers 31 of the 131 distinct solid tumor amino acid mutations listed in the COSMIC database. Owing to the high frequency of specific mutations such as V600E, these 31 amino acid mutations account for 98% of the reported solid tumor BRAF mutations.Table 1Mutations Covered in the Solid Tumor PanelGeneNo. of annotated mutant solid tumor cases in COSMICPercentage of COSMIC solid tumor cases covered in Solid Tumor Panel⁎Proportion of solid tumor cases in COSMIC with a mutation that would be detected by the Solid Tumor Panel.ABL150%AKT111595%AKT20NAAKT320%BRAF1287098%CDK40NACTNNB1266776%EGFR529280%ERBB211633%FBX40NAFBXW714631%FGFR11020%FGFR26227%FGFR3201228%FLT320%GNAQ13996%HRAS62691%JAK250%KIT260148%KRAS1423599%MAP2K10NAMAP2K20NAMET14051%NRAS135398%PDGFRA54072%PIK3CA277289%PTPN11157%RET36978%SOS120%TP531158421%COSMIC, Catalogue of Somatic Mutations in Cancer (http://www.sanger.ac.uk/genetics/CGP/cosmic).NA, not available. Proportion of solid tumor cases in COSMIC with a mutation that would be detected by the Solid Tumor Panel. Open table in a new tab COSMIC, Catalogue of Somatic Mutations in Cancer (http://www.sanger.ac.uk/genetics/CGP/cosmic). NA, not available. We performed dilution series for six different mutations from FFPE-der
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