Multi-Purpose Utility of Circulating Plasma DNA Testing
`in Patients with Advanced Cancers
`
`Geraldine Perkins1, Timothy A. Yap1,2, Lorna Pope1, Amy M. Cassidy1, Juliet P. Dukes1, Ruth Riisnaes1,
`Christophe Massard1,2, Philippe A. Cassier2, Susana Miranda1, Jeremy Clark1, Katie A. Denholm2,
`Khin Thway1, David Gonzalez De Castro1, Gerhardt Attard1,2, L. Rhoda Molife2, Stan B. Kaye1,2,
`Udai Banerji1,2, Johann S. de Bono1,2*
`
`1 Division of Clinical Studies, The Institute of Cancer Research, Sutton, Surrey, United Kingdom, 2 Drug Development Unit, Royal Marsden NHS Foundation Trust, Sutton,
`Surrey, United Kingdom
`
`Abstract
`
`Tumor genomic instability and selective treatment pressures result in clonal disease evolution; molecular stratification for
`molecularly targeted drug administration requires repeated access to tumor DNA. We hypothesized that circulating plasma
`DNA (cpDNA) in advanced cancer patients is largely derived from tumor, has prognostic utility, and can be utilized for
`multiplex tumor mutation sequencing when repeat biopsy is not feasible. We utilized the Sequenom MassArray System and
`OncoCarta panel for somatic mutation profiling. Matched samples, acquired from the same patient but at different time
`points were evaluated; these comprised formalin-fixed paraffin-embedded (FFPE) archival tumor tissue (primary and/or
`metastatic) and cpDNA. The feasibility, sensitivity, and specificity of this high-throughput, multiplex mutation detection
`approach was tested utilizing specimens acquired from 105 patients with solid tumors referred for participation in Phase I
`trials of molecularly targeted drugs. The median cpDNA concentration was 17 ng/ml (range: 0.5–1600); this was 3-fold
`higher than in healthy volunteers. Moreover, higher cpDNA concentrations associated with worse overall survival; there was
`an overall survival (OS) hazard ratio of 2.4 (95% CI 1.4, 4.2) for each 10-fold increase in cpDNA concentration and in
`multivariate analyses, cpDNA concentration, albumin, and performance status remained independent predictors of OS.
`These data suggest that plasma DNA in these cancer patients is largely derived from tumor. We also observed high
`detection concordance for critical ‘hot-spot’ mutations (KRAS, BRAF, PIK3CA) in matched cpDNA and archival tumor tissue,
`and important differences between archival tumor and cpDNA. This multiplex sequencing assay can be utilized to detect
`somatic mutations from plasma in advanced cancer patients, when safe repeat tumor biopsy is not feasible and genomic
`analysis of archival tumor is deemed insufficient. Overall, circulating nucleic acid biomarker studies have clinically important
`multi-purpose utility in advanced cancer patients and further studies to pursue their incorporation into the standard of care
`are warranted.
`
`Citation: Perkins G, Yap TA, Pope L, Cassidy AM, Dukes JP, et al. (2012) Multi-Purpose Utility of Circulating Plasma DNA Testing in Patients with Advanced
`Cancers. PLoS ONE 7(11): e47020. doi:10.1371/journal.pone.0047020
`
`Editor: Jose Luis Perez-Gracia, University Clinic of Navarra, Spain
`
`Received May 15, 2012; Accepted September 7, 2012; Published November 7, 2012
`Copyright: ß 2012 Perkins et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
`unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
`
`Funding: The Drug Development Unit of the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research is supported in part by a program grant
`from Cancer Research UK. Support was also provided by the Experimental Cancer Medicine Centre (to The Institute of Cancer Research) and the National Institute
`for Health Research Biomedical Research Centre (jointly to the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research). GP was supported by a
`grant from the French National Institute of Cancer (Institut National du Cancer, InCA, France). TY is recipient of the 2011 Scott Minerd Prostate Cancer Foundation
`Young Investigator Award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
`
`Competing Interests: The authors have declared that no competing interests exist.
`
`* E-mail: johann.de-bono@icr.ac.uk
`
`Introduction
`
`is primarily due to genetic
`The development of cancer
`aberrations that drive oncogenesis and determine the clinical
`manifestations of
`tumors;
`these may also impact response to
`treatment [1]. Our improved knowledge of the underlying biology
`of cancer and the availability of modern biotechnological tools is
`beginning to lead to the successful development of novel antitumor
`molecular
`therapeutics, as well as a better
`recognition of
`mechanisms of resistance [2,3]. Notable examples include KRAS
`mutations in colorectal
`tumors predicting resistance to anti-
`epidermal growth factor receptor (EGFR) targeting monoclonal
`antibodies (cetuximab [ImClone and Bristol-Myers Squibb]; and
`panitumumab [Amgen]) [4,5], and KIT mutations predicting
`antitumor responses to imatinib (Novartis)
`in gastrointestinal
`
`stromal tumors [6]. Molecular analysis of these genomic aberra-
`tions is usually conducted on archival tumor tissue due to ethical
`and safety challenges associated with repeated biopsies. However,
`in view of the potential for genomic instability, concerns remain,
`about the validity of this approach of analyzing archival tumor
`tissue, rather than rebiopsying tumor for molecular analyses at
`each therapeutic decision point. For example, it is unclear if the
`analysis of archival
`tumor biopsies
`taken many years and
`frequently multiple therapies previously, sufficiently reflects disease
`biology at time of treatment. Rebiopsy of a selected tumor lesion
`may not, however, provide sufficient information on intra-patient
`disease molecular heterogeneity and rebiopsying multiple lesions
`remains clinically impractical. Improved strategies
`to pursue
`patient molecular stratification are urgently needed.
`
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`We set out to optimize benefit for patients with advanced solid
`tumors referred for Phase I clinical trials by allocating specific
`targeted therapies
`to patients who harbor tumor molecular
`aberrations
`targeted by the agent
`in question [2,3,7]. We
`evaluated tumors obtained from these patients with the high
`throughput Sequenom MassArray platform utilizing the Onco-
`Carta mutation panel (version 1.0; Sequenom, San Diego, CA).
`This panel utilizes pre-designed and pre-validated mass spectro-
`metric SNP genotyping technology for the parallel multiplex
`analyses of 238 simple and complex mutations across 19 common
`oncogenes, minimizing the amount of specimen required and
`maximizing sensitivity [8]. It has previously been used successfully
`for the screening of mutations in formalin-fixed paraffin-embed-
`ded (FFPE) tumor tissue [9] [10].
`An alternative source of tumor DNA is circulating plasma DNA
`(cpDNA) [11], which may be easily and repeatedly extracted from
`plasma and may be tumor-derived [11,12], with cpDNA
`concentrations associating with disease burden and progression
`[13]. Studies have also demonstrated the feasibility of mutation
`detection from cpDNA in patients with advanced cancer
`[14,15,16,17,18]. We set out to explore the potential utility of
`multiplex mutation detection from cpDNA with the high
`throughput Sequenom MassArray platform utilizing the Onco-
`Carta mutation panel (v1.0) to determine if this may be used as an
`adjunct to tissue biopsies to enrich and support tumor data for
`patient selection. Secondary objectives were to investigate if the
`measurement of cpDNA concentrations has prognostic value.
`
`Materials and Methods
`
`Clinical specimens
`Patients with late stage advanced solid tumors who were
`referred to the Drug Development Unit in the Royal Marsden
`NHS Foundation Trust between September 2009 and August
`2010, and who were eligible for a Phase I trial were included in
`this study. All patients provided written informed consent for
`genetic analysis of their tumors and plasma samples prior to
`participation in this study. Eight mls of peripheral blood were
`sampled in a BD Vacutainer Cell Preparation Tube (CPT)
`containing sodium heparin, which permits plasma and mononu-
`clear cell separation during a single centrifugation step. The tube
`was inverted a minimum of 8 times to ensure thorough mixing of
`the sample, and then centrifuged at 1800 g for 15 min. The
`resultant plasma supernatant was transferred to a clean tube and
`stored at 280uC until analysis. In addition, 20 healthy volunteers
`provided 8 ml of blood for analysis using this method. Corre-
`sponding FFPE samples (primary and/or metastatic sites) for each
`patient were also requested. The relevant
`regulatory and
`independent ethics committee (National Research Ethics Service
`(NRES) Committee London-Chelsea, United Kingdom) approved
`this study prior to trial commencement.
`
`DNA isolation and quantification
`For the analyses of tumor samples, hemotoxylin- and eosin-
`stained slides were reviewed by a board-certified pathologist (K.T.)
`to ensure adequate viable tumor and to determine the tumoral
`zone to core. DNA from FFPE specimens was extracted from
`1 mm cores when possible or from 10 mm unstained sections with
`smaller biopsies using the QIAamp DNA FFPE Tissue Kit
`(Qiagen, Valencia, CA, USA), according to the manufacturer’s
`recommendations. The extracted DNA was subsequently eluted in
`30 ml of ATE buffer and stored at 220uC until further analysis.
`DNA was quantified using the Nanodrop 1000 Spectrophotometer
`(Thermo Scientific).
`
`Oncogenic Mutations in Tumor and Plasma Specimens
`
`thawed at ambient
`For cpDNA extraction, plasma was
`temperature and cpDNA extracted from 2 ml of plasma using a
`QIAamp DNA Blood Midi Kit (Qiagen, Valencia, CA, USA),
`according to the manufacturer’s instructions, with the following
`modifications:
`for each 2 ml sample of plasma, an additional
`centrifugation step (16000 g, 5 min, RT) was added before the
`extraction procedure in order to eliminate cellular debris from the
`plasma. At the end of the procedure, the DNA was eluted in
`100 ml of AE elution buffer. DNA concentration was measured
`with fluorescent staining, using the Quant-iTTM Pico-GreenH
`double stranded DNA (dsDNA) Assay Kit (Invitrogen, Carlsbad,
`CA) and the SynergyHT microplate reader (Biotek). DNA from
`the cancer cell lines analyzed was extracted from pellets using the
`QIAamp DNA Mini Kit (Qiagen, Valencia, CA, USA), according
`to the manufacturer’s recommendations. For purposes of com-
`parison, all cpDNA concentrations presented in this manuscript
`are expressed as ng/ml of plasma.
`
`Mass Spectrometry TypePLEX technology and OncoCarta
`panel (v1.0)
`The OncoCarta panel (v1.0) consists of 24 pools of primer pairs and
`extension primers, and has the capacity to detect 238 mutations in 19
`genes. The protocol provided by Sequenom (San Diego, CA) was
`followed with minor modifications. The amount of DNA added to the
`polymerase chain reaction (PCR) was 20 ng per reaction for FFPE
`DNA samples. For plasma DNA samples, 30 ml of DNA were added to
`30 ml of pure water, and used for the OncoCarta panel
`(v1.0)
`processing. DNA was amplified using the OncoCarta PCR primer
`pools, unincorporated nucleotides were inactivated by shrimp alkaline
`phosphatase (SAP), and a single base extension reaction was performed
`using extension primers that hybridize immediately adjacent to the
`mutations and a custom mixture of nucleotides. Salts were removed by
`the addition of a cation exchange resin. Multiplexed reactions were
`spotted onto SpectroCHIP II arrays, and DNA fragments were
`resolved by MALDI-TOF on the Compact Mass Spectrometer
`(Sequenom, San Diego, CA).
`
`Data analysis
`Data analysis was performed using MassArray Typer Analyzer
`software 4.0.4.20 (Sequenom), which facilitates visualization of data
`patterns and the raw spectra. Typer automates the identification of
`mutants by comparing ratios of the wild type peak to that of all
`suspected mutants and generates an OncoMutation report detailing
`specific mutations and the ratios of wildtype and mutation peaks. All
`mutations from the Oncomutation report were reviewed manually by 2
`blinded operators, with selected reviewed mutations
`from the
`OncoMutation report compared and confirmed to be concordant.
`Manual review of mutations on all OncoCarta spectra was performed
`to identify ‘‘real’’ mutant peaks from salt peaks or other background
`peaks. Statistical analyses are detailed in the Supplemental Methods S1.
`
`FFPE mutation confirmation
`KRAS mutations were also detected using the Therascreen
`KRAS mutation kit (Qiagen, Germany) based on Amplification
`Refractory Mutation System (ARMS)-Scorpion PCR [19]. BRAF
`V600E mutations were also detected using the Capillary
`electrophoresis-single strand conformation analysis (CE-SSCA).
`Further details are provided in the Supplemental Methods S1.
`
`Results
`
`Patient characteristics
`A total of 105 patients referred for phase I trial participation
`were enrolled between September 2009 and August 2010
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`(Table 1; Table S1). One patient was subsequently found to be
`ineligible for Phase I trials and therefore this study as he had not
`exhausted all lines of available antitumor treatments. The different
`tumor types represented in the remaining 104 patients were
`colorectal cancer (CRC) (n = 25), breast cancer (n = 19), melano-
`ma (n = 15), ovarian cancer (n = 15), castration resistant prostate
`cancer (CRPC) (n = 11) and other tumor types (n = 19), including
`non-small cell
`lung cancer (NSCLC), mesothelioma, sarcoma,
`glioblastoma, adenocarcinoma of unknown primary (ACUP),
`cholangiocarcinoma, and cervical, endometrial, duodenal, esoph-
`ageal, pancreatic and renal cancers (Table 1).
`Of the 104 patients analyzed in the study, FFPE primary tumor
`samples were obtained for 69 (66%) subjects, with FFPE nodal
`and/or metastatic tumor samples being available for a further 31
`(30%) patients. cpDNA was collected from 101 (97%) patients; it
`was not possible to draw blood from 1 patient for technical reasons
`and blood was not collected from 2 patients due to logistical errors.
`A total of 60 patients died during follow up, while data for 44
`patients were censored for purposes of
`this publication. The
`median follow up time was 5.8 months (range 0.3–17.5) (Table 1).
`
`DNA serial dilution experiments for assay development
`Dilutions of DNA extracted from the KRAS mutant HCT116
`the KRAS G13D
`human colon cancer cell
`line showed that
`mutation was reproducibly detectable by the OncoCarta v1.0
`panel at DNA concentrations as low as 40 ng/ml (Figure S1).
`
`Table 1. Patient characteristics (n = 104).*
`
`Oncogenic Mutations in Tumor and Plasma Specimens
`
`cpDNA was also collected from healthy volunteers (Table 2); in
`these samples, the cpDNA concentration was found to be low:
`median 6.5 ng/ml of plasma (range 4.5–13.3 ng/ml of plasma),
`and no mutations were detected in any sample. A patient with
`advanced breast cancer who had very high cpDNA levels
`(1600 ng/ml of plasma) was found to have a PIK3CA mutation
`in both FFPE and cpDNA samples; serial dilutions of this cpDNA
`the PIK3CA mutation was detectable up to a
`showed that
`concentration of 2.5 ng/ml of plasma utilizing this assay.
`
`Plasma cpDNA concentration levels and mutation
`detection
`The overall median cpDNA concentration was 17 ng/ml in
`these patients with advanced tumors (range: 0.5–1600) (Figure 1;
`Table S1). The median cpDNA concentration was 18 ng/ml
`(range: 5–230) for patients with CRC; 7 ng/ml (range: 2–50) for
`patients with melanoma, 17 ng/ml (range: 0.5–1600) for patients
`with breast cancer, 15 ng/ml
`(range: 4–49)
`for patients with
`ovarian cancer and 53 ng/ml of plasma (range: 7–1177)
`for
`patients with CRPC who had the highest plasma DNA
`concentrations.
`Matched plasma and FFPE were available for analysis from 84
`patients. A total of 42 mutations were detected in either or both
`FFPE tumor and cpDNA specimens obtained from these patients
`(Table 3; Table S1; Figures S2A–S2D). The overall concor-
`dance in detected mutations between FFPE and cpDNA
`
`Parameter
`
`Gender
`
`Male
`
`Female
`
`Median age, years
`
`Tumor types
`
`Colorectal cancer
`
`Breast cancer
`
`Melanoma
`
`Castration resistant prostate cancer
`
`Ovarian cancer
`
`Other**
`
`ECOG PS at screening
`
`0
`
`1
`
`2
`
`Follow-up time (months)
`
`No. of metastatic sites
`
`No. of patients
`
`Albumin
`
`LDH
`
`cpDNA (ng/mL)***
`
`No. of patients* (%)
`
`45 (43.3%)
`
`59 (56.7%)
`
`56 (range 22–75)
`
`25 (24.0%)
`
`19 (18.3%)
`
`15 (14.4%)
`
`11 (10.6%)
`
`15 (14.4%)
`
`19 (18.3%)
`
`36 (34.6%)
`
`62 (59.6%)
`
`6 (5.8%)
`
`Min
`
`0.3
`
`0
`
`4
`
`23
`
`100
`
`0.5
`
`Median
`
`5.8
`
`1
`
`30
`
`34
`
`202.5
`
`17.3
`
`Max
`
`17.5
`
`2
`
`41
`
`43
`
`3531
`
`1600
`
`Mean
`
`6.1
`
`3
`
`19
`
`34.4
`
`300.3
`
`55.4
`
`sd
`
`3.7
`4+
`
`10
`
`4.2
`
`370.2
`
`196.1
`
`*One patient was subsequently found to be ineligible for this study as he had not exhausted all lines of available antitumor treatments.
`**Includes non-small cell lung cancer (NSCLC), mesothelioma, sarcoma, glioblastoma, adenocarcinoma of unknown primary (ACUP), cholangiocarcinoma, and cervical,
`endometrial, duodenal, esophageal, pancreatic and renal cancers.
`***cpDNA was collected from 101 (97%) patients; it was not possible to draw blood from 1 patient for technical reasons and blood was not collected from 2 patients
`due to logistical errors.
`doi:10.1371/journal.pone.0047020.t001
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`Oncogenic Mutations in Tumor and Plasma Specimens
`
`Table 2. Characteristics of healthy volunteers (n = 20).
`
`Parameters
`
`Gender
`
`Male
`
`Female
`
`n (%)
`
`7 (35%)
`
`13 (65%)
`
`Median age, years
`
`34 (range 25–52)
`
`cpDNA (ng/ml)
`
`doi:10.1371/journal.pone.0047020.t002
`
`n
`
`20
`
`min
`
`4.5
`
`median
`
`6.4
`
`max
`
`13.3
`
`mean
`
`7.4
`
`sd
`
`2.9
`
`(Table 3).
`specimens was 60% (25 of 42 detected mutations)
`Nonparametric ROC analyses were used to assess the limit of the
`Sequenom platform to detect OncoCarta panel mutations in
`cpDNA (Figure 2A). The concentration of cpDNA with the
`optimal ability to detect a mutation was 29.95 ng/ml (Likelihood
`ratio = 7.3043). The AUC calculated was 0.8075 (95% CI 0.6552–
`0.9598). Figure 2B shows the different types of mutations in a
`range of tumor types at the respective cpDNA concentrations they
`were detected at.
`Correlation with patient outcome. The median overall
`survival (OS) for all patients was 7.9 months (95% CI 5.8, 9.2). Patients
`were categorised into low and high cpDNA concentration groups
`based on the maximum healthy volunteer cohort DNA concentration
`of 13.3 ng/ml; 61 patients were classified as having high cpDNA
`concentrations with 40 having low levels. The median OS in patients
`categorised as having low cpDNA concentrations was 10.5 months
`(95% CI 6.0, NC), while those in the high cpDNA concentration group
`had a median OS of 6.5 months (95% CI 4.5, 8.4) (logrank p = 0.0383)
`(Figure 3A). As a continuous variable, there was an OS hazard ratio of
`2.4 (95% CI 1.4, 4.2)
`for each 10-fold increase in cpDNA
`concentration (Figure 3B).
`
`Correlation with RMH prognostic score. We have
`recently prospectively validated a prognostic score (RMH score)
`for patients participating in Phase I clinical trials based on the
`combination of three prognostic factors: serum albumin less than
`35 g/L; lactate dehydrogenase (LDH) greater than the upper limit
`of normal
`(ULN); and two or more sites of metastases. The
`presence of each of these variables associated with worsening
`outcome [20]. The mean cpDNA concentration was higher in
`patients with a worse RMH prognostic score (F[3,98] = 9.97,
`p,0.0001); Post-tests revealed a significant positive linear trend
`between log10(cpDNA) and RMH score (beta = 0.247, p,0.0001)
`(Figure 4).
`and multivariate
`univariate
`with
`Correlation
`analysis. Univariate testing was used to determine significant
`predictors of overall survival, which included cpDNA concentra-
`tion as a continuous variable (HR 2.4 per 10-fold increase, 95% CI
`1.4–4.2), albumin ,35 g/L (logrank p = 0.0003), and ECOG
`performance status equal to 2 (logrank p = 0.0007). When cpDNA,
`albumin and performance status were incorporated into a
`multivariate model, all
`three parameters were found to be
`(Table 4). The number of
`independent predictors of survival
`
`Figure 1. DNA concentrations (ng/mL) classified by tumor types. Box and whisker plots showing 25th, 50th and 75th percentiles, upper and
`
`lower adjacent values (whiskers) and Tukey outliers (N). P value is for a two-sided unpaired t-test on log10 DNA concentrations using Welch’s
`
`correction for unequal variances.
`doi:10.1371/journal.pone.0047020.g001
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`Table 3. Concordance in detected mutations between paired FFPE tumors and cpDNA.
`
`BRAF
`
`KRAS
`
`NRAS
`
`HRAS
`
`MET
`
`AKT
`
`PIK3CA
`
`KIT
`
`Oncogenic Mutations in Tumor and Plasma Specimens
`
`Colorectal
`
`Melanoma
`
`Breast
`
`Prostate
`
`Ovarian
`
`ACUP
`
`Cholangiocarcinoma
`
`Duodenal carcinoma
`
`3/3 (100%)
`
`7/10 (70%)
`
`-
`
`2/3 (66.7%)
`
`-
`
`-
`
`-
`
`-
`
`0/1 (0%)
`
`0/1 (0%)
`
`-
`
`-
`
`-
`
`3/5 (60%)
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`0/2 (0%)
`
`-
`
`-
`
`-
`
`1/1 (100%)
`
`0/1 (0%)
`
`0/1 (0%)
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`1/1 (100%)
`
`1/3 (33.3%)
`
`1/1 (100%)
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`1/1 (100%)
`
`3/4 (75%)
`
`1/1 (100%)
`
`1/1 (100%)
`
`-
`
`-
`
`-
`
`-
`
`0/1 (0%)
`
`0/1 (0%)
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`-
`
`Total = 25/42 (60%)
`
`6/8 (75%)
`
`7/13 (54%)
`
`3/6 (50%)
`
`0/1 (0%)
`
`1/1 (100%)
`
`3/3 (100%)
`
`5/9 (55.6%)
`
`0/1 (0%)
`
`doi:10.1371/journal.pone.0047020.t003
`
`metastatic sites was not found to be a significant predictor of
`survival in the univariate analysis and was therefore excluded from
`the multivariate model.
`
`Mutational detection and concordance between FFPE
`and cpDNA
`Colorectal cancer. Of 25 patients with CRC, cpDNA
`samples were obtained from all patients, while FFPE tumor
`samples were available for analysis for 22 patients. Overall,
`mutations were detected in 15 of 22 (68.2%) available FFPE
`tumors and 14 of 25 (56%) cpDNA specimens (Table S1).
`Specifically, KRAS, BRAF and PIK3CA mutations were detected in
`10 (45%), 3 (14%) and 2 (9%) tumor specimens, respectively.
`Comparatively, 9 (36%) KRAS, 3 (12%) BRAF and 3 (12%) PIK3CA
`mutations were detected in cpDNA samples.
`Concordance in the detection of mutations between matched FFPE
`archival tumors and cpDNA specimens by Sequenom OncoCarta
`analyses was 70% (7 of 10 patients) for KRAS and 100% (3 of 3 patients)
`for BRAF mutational status (Table 3). No patients with wildtype KRAS
`or BRAF tumor tissue genotypes had mutations in their respective
`cpDNA. Five patients had detectable PIK3CA mutations in either or
`both FFPE tumor and/or cpDNA: 1 patient had a Q546K mutation
`detected in both FFPE tissue and cpDNA; 1 patient had an E545K
`mutation detected only in FFPE, but not cpDNA; 1 patient had an
`E542K mutation detected in a liver metastasis (FFPE), but not in the
`primary tumor (FFPE) or cpDNA; 1 patient had E545K detected only
`in plasma but not FFPE; and 1 patient had a Q546K mutation found
`in cpDNA but no FFPE specimen was available. The recently reported
`oncogenic AKT1 E17K mutation [21] was detected in 1 patient in both
`tissue and plasma. No mutations in other tested oncogenes were
`detected.
`There was 90% (9 of 10 KRAS mutated samples) concordance
`for FFPE tumoral KRAS mutational status between the OncoCarta
`panel and the ARMS-Scorpion PCR platforms. The BRAF
`concordance between the OncoCarta panel and CE-SSCA
`method was 100% (3 of 3 BRAF mutated samples).
`Melanoma. Of the 15 patients with melanoma, FFPE tumor
`samples were available for analysis for 10 patients, while cpDNA
`samples were obtained from all 15 patients. Overall, mutations
`were detected in 8 of 10 (80.0%) available FFPE tumors and 6 of
`15 (40%) cpDNA specimens (Table S1).
`BRAF, NRAS and MET mutations were detected in 5 (50%), 3
`(30%) and 1 (10%) of 10 FFPE tumor specimens, respectively, and
`3 (20%), 2 (13.3%) and 2 (13.3%) of 15 cpDNA samples,
`respectively. Concordance in the detection of mutations between
`matched FFPE and cpDNA was 60% (3 of 5 patients) for BRAF,
`
`66.7% for NRAS (2 of 3 patients) and 100% for MET mutational
`status (1 of 1 patient) (Table 3). Another MET mutation, T992I,
`was found in one cpDNA sample, but no FFPE tumor specimen
`was available. No patients with wildtype tumor tissue genotypes
`had mutations in their respective cpDNA.
`There was 100% concordance (5 of 5 samples) for the BRAF
`mutational status between the OncoCarta panel and CE-SSCA
`method.
`Breast cancer. FFPE tumor samples and cpDNA samples
`were available for analysis for all 19 patients with breast cancer.
`Overall, mutations were detected in 5 of 19 (26.3%) FFPE tumors
`and 4 of 19 (21.1%) cpDNA specimens (Table S1).
`The PIK3CA H1047R mutation was detected in 4 of 19 (21.5%)
`tumor specimens and 3 of 19 (15.8%) cpDNA samples, with
`concordance between 3 of 4 (75%) matched FFPE and cpDNA
`specimens (Table 3). The AKT1 E17K mutation was detected in 1
`patient in both FFPE tissue and cpDNA. No mutations in any of
`the other oncogenes studied were detected with the OncoCarta
`panel. No patients with wildtype tumor tissue genotypes had
`mutations in their respective cpDNA.
`Castration resistant prostate cancer. Of the 11 patients
`with CRPC, cpDNA samples were obtained from all patients,
`while FFPE tumors were available for 8 patients. Overall,
`mutations were detected in 3 of 8 (37.5%) FFPE tumors, and 3
`of 11 (27.3%) cpDNA specimens (Table S1).
`PIK3CA, HRAS and AKT1 (all n = 1) mutations were detected in
`FFPE tumor specimens, while NRAS, PIK3CA and AKT1 (all n = 1)
`mutations were found in cpDNA samples. The corresponding
`FFPE tumor PIK3CA and AKT1 mutations were found in the
`cpDNA samples, but the FFPE tumor HRAS mutation was not
`found in the matched cpDNA sample (Table 3). The Q61K
`NRAS mutation was found in 1 cpDNA specimen, but not in the
`corresponding FFPE tumor sample.
`Ovarian cancer. Of the 15 patients with advanced ovarian
`cancer, cpDNA samples were obtained from all patients, while
`FFPE tumor samples were available for 14 patients. Overall,
`mutations were detected in 5 of 14 (35.7%) FFPE tumors, and 0 of
`14 (0%) cpDNA specimens (Table S1).
`(n = 3) and the PIK3CA
`KRAS mutations (G12V and G13D)
`H1047R mutation (n = 1) were detected in FFPE tumor samples,
`but no mutations were found in any cpDNA samples (Table 3).
`One patient with ovarian carcinosarcoma had a KIT P585P
`mutation detected in FFPE, but not in cpDNA.
`Other tumor types. Of the remaining 19 patients with a
`range of tumor types, cpDNA samples were obtained from 17
`patients, while FFPE tumors were available for 12 patients.
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`Oncogenic Mutations in Tumor and Plasma Specimens
`
`Figure 2. cpDNA concentrations for mutational detection by
`(v1.0). 2A: Nonparametric ROC
`Sequenom OncoCarta panel
`analyses were used to assess the limit of the Sequenom platform to
`detect OncoCarta panel mutations in cpDNA. Each dot on the graph
`corresponds to the sensitivity and specificity at one of the observed
`concentrations. Mutations were considered ‘available for detection’ if
`they were detected in the patient’s FFPE tissue. Mutations were
`detected in FFPE samples from 37 patients. The concentration of
`cpDNA with the optimal ability to detect a mutation is 29.95 ng/ml
`(Likelihood ratio = 7.3043). The AUC calculated is 0.8075 (95% CI 0.6552–
`0.9598). Patients whose FFPE was unavailable or tested negative for
`mutations were excluded from the analysis. The specificity reference
`lines for quartiles of DNA concentrations are indicated in red dashed
`lines. 2B: Graph showing the types of mutations and cpDNA
`concentrations at which they were detected in different tumors.
`Mutations were detected in six oncogenes. Symbols represent different
`tumor types.
`doi:10.1371/journal.pone.0047020.g002
`
`The NRAS G12D mutation was found in both FFPE tumor and
`plasma from a patient with ACUP (Table 3). The NRAS G13R
`mutation was detected in the plasma, but not in FFPE tumor from
`a patient with cholangiocarcinoma. The KRAS G12D mutation
`was found in FFPE tumor, but not in plasma from a patient with
`duodenal cancer. No mutations were detected in the other
`patients, including no epidermal growth factor receptor (EGFR)
`mutations in the 5 patients with NSCLC.
`
`Concordance in mutation detection between FPFE and
`cpDNA for primary tumor or metastatic specimens
`When considering all patients with matched samples, including
`those with no mutations detected (n = 83), the concordance in
`detecting mutations between FFPE and cpDNA was higher in
`
`Figure 3. Relationship between cpDNA concentration and
`survival. (3A) Kaplan-Meier graph showing survival curves by cpDNA
`concentration in 101 patients with advanced solid tumors. Patients in
`the unfavorable category had concentrations greater than a healthy
`volunteer cohort maximum of 13.3 ng/ml (logrank p = 0.0383). (3B)
`Survivor function estimated from univariate Cox regression showing
`predicted survival curves for a range of cpDNA concentrations. A hazard
`ratio of 2.4 (p = 0.002) is depicted between adjacent curves.
`doi:10.1371/journal.pone.0047020.g003
`
`metastases (83.3% of 18 specimens) compared with primary tumor
`(78.5% of 65 specimens). When considering only patients with
`mutations detected in at
`least blood and/or primary tumor
`(n = 40), the concordance in detecting mutations between FFPE
`and cpDNA was again higher in metastases
`(70.0% of 10
`specimens) compared with primary tumor (53.3% of 30 speci-
`mens). However, because of the difference in the number of
`primary tumor
`(n = 65) and metastatic
`(n = 18)
`specimens
`obtained, we are unable to draw any statistical conclusions from
`these data.
`
`Discussion
`
`This study has demonstrated, for the first time, the feasibility of
`multiplex detection of
`tumor DNA mutations utilizing the
`multiplex OncoCarta panel from both DNA extracted from FFPE
`archival tumor tissue and cpDNA. We have shown that total
`cpDNA levels in patients with advanced cancers are, in general,
`significantly higher than those in healthy volunteers, with the
`highest concentrations found in patients with advanced prostate
`and breast cancers, although this difference was not significant in
`melanoma and ovarian cancer (Figure 1). The maximum
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`Oncogenic Mutations in Tumor and Plasma Specimens
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`Figure 4. Relationship between cpDNA concentration and RMH prognostic score. Scatterplot showing the relationship between cpDNA
`concentration and RMH prognostic score. There was a significant positive linear trend between log10(cpDNA) and RMH score (beta = 0.252,
`p,0.0001).
`doi:10.1371/journal.pone.0047020.g004
`
`concentration detected in healthy volunteers was found to split
`patients into two groups that were associated with significantly
`different prognoses; patients in the low cpDNA group had a
`significantly higher OS relative to those in the high cpDNA group
`[11,13,22]. Furthermore,
`the cpDNA concentration remained
`highly prognostic for OS in a multivariate analyses utilizing the
`prognostic biomarkers for the Phase I trial patient population that
`we have previously described [20]. We have also shown a
`correlation between cpDNA concentrations and the prognostic
`score that we have previously described to predict the outcome of
`patients referred for Phase I trial participation; cpDNA concen-
`tration, albumin ,35 g/L and performance status had prognostic
`value in our series of patients as independent predictors of survival.
`These data overall indicate that cpDNA in this patient population
`is largely tumor derived, although this may be generated by both
`malignant and stromal cells.
`The Sequenom OncoCarta panel has also enabled us to analyze
`more than 230 known mutation ‘hot-spots’ mutations in over a
`hundred patients in a high throughput fashion. The OncoCarta
`panel covers a large and increasing number of oncogenes and can
`be adapted to include additional genes of interest. It allows tumor
`mutation detection even with minimal amounts of tumor DNA,
`poor tissue preservation and the presence of significant amounts of
`
`normal DNA. Next generation sequencing technology will allow
`more DNA coverage and data acquisition, allowing the sequenc-
`ing of hundreds of full length genes, which will be critical to the
`study of genes where mutations can be found in multiple disparate
`locations, as is the case for many tumor suppressor genes such as
`BRCA1, BRCA2, p53 and PTEN.
`As we move towards the development of molecularly targeted
`agents for selected populations of patients, it is crucial that the
`molecular