Case 1:20-cv-01580-LPS Document 1-13 Filed 11/23/20 Page 1 of 19 PageID #: 471
`Case 1:20-cv-01580-LPS Document 1-13 Filed 11/23/20 Page 1 of 19 PageID #: 471
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`EXHIBIT 13
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`EXHIBIT 13
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`Case 1:20-cv-01580-LPS Document 1-13 Filed 11/23/20 Page 2 of 19 PageID #: 472
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`RESEARCH ARTICLE
`Clinical and analytical validation of
`FoundationOne Liquid CDx, a novel 324-Gene
`cfDNA-based comprehensive genomic
`profiling assay for cancers of solid tumor
`origin
`
`Ryan WoodhouseID1*, Meijuan Li2, Jason Hughes3, David Delfosse4, Joel Skoletsky4,
`Pei Ma2, Wei Meng2, Ninad Dewal2, Coren Milbury4, Travis Clark5, Amy Donahue6,
`Dan Stover7, Mark Kennedy3, Jennifer Dacpano-Komansky8, Christine Burns4,
`Christine Vietz9, Brian Alexander10, Priti Hegde6, Lucas Dennis11
`
`1 Regulatory Affairs, Foundation Medicine, Inc, Cambridge, Massachusetts, United States of America,
`2 Biometrics and Biomarkers, Foundation Medicine, Inc, Cambridge, Massachusetts, United States of
`America, 3 Computational Biology, Foundation Medicine, Inc, Cambridge, Massachusetts, United States of
`America, 4 Development Operations, Foundation Medicine, Inc, Cambridge, Massachusetts, United States
`of America, 5 Formerly Assay Development, Foundation Medicine, Inc, Cambridge, Massachusetts, United
`States of America, 6 Assay Development, Foundation Medicine, Inc, Cambridge, Massachusetts, United
`States of America, 7 Laboratory Operations, Foundation Medicine, Inc, Cambridge, Massachusetts, United
`States of America, 8 Medical Device Global Regulatory Affairs, Novartis Corporation, Cambridge,
`Massachusetts, United States of America, 9 Product Development, Foundation Medicine, Inc, Cambridge,
`Massachusetts, United States of America, 10 Clinical Development, Foundation Medicine, Inc, Cambridge,
`Massachusetts, United States of America, 11 Franchise Development, Foundation Medicine, Inc,
`Cambridge, Massachusetts, United States of America
`
`* rwoodhouse@foundationmedicine.com
`
`a1111111111
`a1111111111
`a1111111111
`a1111111111
`a1111111111
`
`OPEN ACCESS
`
`Citation: Woodhouse R, Li M, Hughes J, Delfosse
`
`D, Skoletsky J, Ma P, et al. (2020) Clinical and
`
`analytical validation of FoundationOne Liquid CDx,
`
`a novel 324-Gene cfDNA-based comprehensive
`
`genomic profiling assay for cancers of solid tumor
`
`origin. PLoS ONE 15(9): e0237802. https://doi.org/
`
`10.1371/journal.pone.0237802
`
`Editor: Patrick Ha, University of California, San
`
`Francisco, UNITED STATES
`
`Abstract
`
`Received: May 7, 2020
`
`Accepted: July 30, 2020
`
`Published: September 25, 2020
`
`Copyright: © 2020 Woodhouse 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.
`
`Data Availability Statement: All relevant data were
`
`provided as supplementary information with this
`
`revised manuscript. In addition, details may be
`
`obtained by contacting the corresponding authors
`
`at Foundation Medicine, inc.
`
`Funding: This research was funded by Foundation
`
`Medicine, Inc. Portions of this research were also
`
`funded by Novartis Corporation. The funder,
`
`Foundation Medicine, Inc. provided support in the
`
`form of salaries for authors RW, ML, JH, DD, JS,
`
`As availability of precision therapies expands, a well-validated circulating cell-free DNA
`(cfDNA)-based comprehensive genomic profiling assay has the potential to provide consid-
`erable value as a complement to tissue-based testing to ensure potentially life-extending
`therapies are administered to patients most likely to benefit. Additional data supporting the
`clinical validity of cfDNA-based testing is necessary to inform optimal use of these assays in
`the clinic. The FoundationOne®Liquid CDx assay is a pan-cancer cfDNA-based comprehen-
`sive genomic profiling assay that was recently approved by FDA. Validation studies included
`>7,500 tests and >30,000 unique variants across >300 genes and >30 cancer types. Clinical
`validity results across multiple tumor types are presented. Additionally, results demon-
`strated a 95% limit of detection of 0.40% variant allele fraction for select substitutions and
`insertions/deletions, 0.37% variant allele fraction for select rearrangements, 21.7% tumor
`fraction for copy number amplifications, and 30.4% TF for copy number losses. The limit of
`detection for microsatellite instability and blood tumor mutational burden were also deter-
`mined. The false positive variant rate was 0.013% (approximately 1 in 8,000). Reproducibil-
`ity of variant calling was 99.59%. In comparison with an orthogonal method, an overall
`positive percent agreement of 96.3% and negative percent agreement of >99.9% was
`observed. These study results demonstrate that FoundationOne Liquid CDx accurately and
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`Case 1:20-cv-01580-LPS Document 1-13 Filed 11/23/20 Page 3 of 19 PageID #: 473
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
`
`PM, WM, ND, CM, TC, AD, DS, MK, CB, CV, BA,
`
`PH, and LD, but did not have any additional role in
`
`the study design, data collection and analysis,
`
`decision to publish, or preparation of the
`
`manuscript. The funder Novartis Corporation
`
`provided support in the form of salary for author
`
`JD-K, but did not have any additional role in the
`
`study design, data collection and analysis, decision
`
`to publish, or preparation of the manuscript The
`
`specific roles of these authors are articulated in the
`
`‘author contributions’ section.
`
`Competing interests: The authors have the
`
`following interests. At the time of this research RW,
`
`ML, JH, DD, JS, PM, WM, ND, CM, TC, AD, DS,
`
`MK, CB, CV, BA, PH, and LD were employed by
`
`Foundation Medicine, Inc., the funder of this study.
`
`This does not alter the authors’ adherence to all the
`
`PLOS ONE policies on sharing data and materials,
`
`as detailed online in the guide for authors.
`
`reproducibly detects the major types of genomic alterations in addition to complex biomark-
`ers such as microsatellite instability, blood tumor mutational burden, and tumor fraction. Crit-
`ically, clinical validity data is presented across multiple cancer types.
`
`Introduction
`
`As availability of precision therapies expands [1], there is an increasing reliance on genomic
`profiling assays to help identify the most relevant treatment options for advanced cancer
`patients [2–4]. Comprehensive genomic profiling (CGP) utilizes next generation sequencing
`(NGS) technology to examine entire exonic regions of cancer-relevant genes (in contrast to
`limited “hot spot” tests) for all tumor types, identifying the 4 main classes of genomic alter-
`ations: base substitutions (subs), insertions or deletions (indels), copy number alterations
`(CNAs), and gene rearrangements. Further, CGP assays can assess genomic alteration patterns
`across related genes in established cancer pathways to report complex biomarkers such as
`blood tumor mutational burden (bTMB) and microsatellite instability (MSI) to inform cancer
`treatment decisions using a single assay. Historically, CGP has utilized tumor tissue, although
`evaluable tumor tissue is not available for many patients [5–9]. with 38% of stage IV non-small
`cell lung cancer (NSCLC) patients in one single-center cohort study having insufficient quan-
`tity or quality of DNA for NGS. [7].
`Often referred to as liquid biopsy assays, circulating cell-free DNA (cfDNA)-based assays,
`are a growing method for providing genomic profiling results to patients. There are a number
`of reasons that a liquid biopsy may be chosen in the clinical setting. For example, cfDNA-
`based testing is established for patients who are unable to provide evaluable tissue or when tis-
`sue quality or quantity is insufficient in a number of cancers [10–13]. Liquid biopsy assays
`may also offer a reduced time from sample to result as compared to tumor tissue assays due to
`the time required to provide a tumor sample for testing [14,15]. Additionally, due to intratu-
`mor heterogeneity, a tumor biopsy may represent a small sample of the overall tumor cell pop-
`ulation, a limitation that can potentially be overcome with liquid biopsy [10, 16–18]. Tissue-
`based CGP has been shown to have improved clinical value compared to non-CGP testing,
`and liquid testing will likely add value based on its ability to find complementary information
`and provide biomarker results for patients unable to receive tissue testing [19].
`Analytical validity of an NGS assay refers to how well the test identifies a particular genetic
`characteristic, such as a genomic alteration or genomic signature [20]. Analytical validation is
`important to demonstrate that a test accurately and reliably detects genomic alterations pres-
`ent in a sample. Clinical validity refers to the relationship between a genomic variant and the
`presence or absence of a specific disease, while clinical utility refers to the correlation of test
`results with improved health outcomes [20]. Clinical validation is critical to evaluate the corre-
`lation of test results with health outcomes. The US FDA requires robust analytical and clinical
`validation, above and beyond the validation standards set by Clinical Laboratory Improvement
`Amendments (CLIA), prior to approval or clearance of a diagnostic device [21]. Liquid biopsy
`assays may be clinically valuable [10–13] but can be technically challenging. Although there is
`an increasing use of liquid biopsies in clinical practice, additional clinical validity and utility
`data is still needed [22]. Many studies assessing the analytical validity of liquid biopsy assays
`examine concordance between tumor tissue and plasma samples, which introduces confound-
`ing variables such as tumor heterogeneity and has the potential to conflate clinical validity
`with analytical validity [22]. These challenges can be overcome by evaluating analytical validity
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`Case 1:20-cv-01580-LPS Document 1-13 Filed 11/23/20 Page 4 of 19 PageID #: 474
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
`
`using samples with known variants at specified variant allele fractions such as cell line DNA
`diluted in an appropriate matrix [22]. Additionally, an evaluation of the potential impact of
`preanalytical and analytical variables is crucial [22].
`The analyses presented here describe the broad analytical and clinical validation of Founda-
`tionOne1Liquid CDx (Foundation Medicine, Inc; Cambridge, MA), a novel liquid biopsy
`CGP platform. The validation of tumor fraction (TF), variant allele fraction (VAF), and other
`clinical validation studies will be described in detail elsewhere.
`
`Materials and methods
`Assay methods
`
`FoundationOne Liquid CDx is an FDA-approved next generation sequencing-based in vitro
`diagnostic device that targets 324 genes utilizing circulating cell-free DNA (cfDNA) isolated
`from plasma derived from the anti-coagulated peripheral whole blood of cancer patients, per-
`formed at Foundation Medicine, Inc (Cambridge, MA) (link to the FDA label [23]). Addi-
`tional clinical decision insights and genomic analysis are also provided as a professional
`service under CLIA and College of American Pathologists (CAP) regulations. This assay is the
`result of the evolution of Foundation Medicine’s FoundationACT and FoundationOne Liquid
`assays.
`All coding exons of 309 genes are targeted; select intronic or non-coding regions are tar-
`geted in 21 of these genes. Additionally, select intronic or non-coding regions are targeted in
`15 genes, resulting in 324 total targeted genes. Sequence data are processed using a custom
`analysis pipeline that filters sequencing artifacts and variants known to be benign. Known and
`likely pathogenic variants implicated in cancer are reported, which may be somatic and/or
`germline variants. The assay detects substitutions, indels, genomic rearrangements, CNAs
`(amplifications and losses), and genomic signatures including bTMB, MSI, and TF. Through a
`novel hybrid capture approach, a subset of targeted regions in 75 genes is baited for greater
`sensitivity through ultra-deep sequencing coverage (referred to as the enhanced sensitivity
`region). The enhanced sensitivity region was selected based on genomic regions with increased
`actionability with current or future targeted therapies (Fig 1). Other targeted genomic regions
`are baited for high sensitivity through deep sequencing coverage (referred to as the standard
`sensitivity region). Refer to S1 Table for the complete list of targeted genes.
`The FoundationOne Liquid CDx gene content is based on that of the US FDA approved
`FoundationOne1CDx assay. Baited genes and gene regions were chosen based on the current
`and potential future clinical impact, with the size of the baited region and the ability of the cur-
`rent technology to make confident calls from the baited regions being additional key consider-
`ations. Genes with therapeutic, diagnostic, and prognostic relevance, as well as biomarkers
`that may serve to guide cancer treatment in the future, were included in the assay. In addition,
`baited regions are included for confident determination of the bTMB and MSI status, complex
`biomarkers associated with prediction of response to immunotherapy. The FoundationOne
`Liquid CDx assay is intended to provide genomic information for use by qualified health care
`professionals in accordance with professional guidelines and is not conclusive or prescriptive
`for labeled use of any specific therapeutic product unless otherwise noted in the FDA-
`approved assay labeling.
`
`Bioinformatics methods
`
`Sequence data is analyzed using mainly proprietary software developed by Foundation Medi-
`cine. Reads are demultiplexed (sorted into sets of reads deriving from distinct samples), and
`their fragment barcodes (FBCs) are extracted and encoded into the read names. For each
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`Case 1:20-cv-01580-LPS Document 1-13 Filed 11/23/20 Page 5 of 19 PageID #: 475
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
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`Fig 1. FoundationOne Liquid CDx assay utilization overview. FoundationOne Liquid CDx was designed to allow comprehensive genomic profiling,
`understanding that shed of tumor DNA can be variable depending on a patient’s clinical characteristics.
`
`https://doi.org/10.1371/journal.pone.0237802.g001
`
`sample, read pairs with matching FBCs are processed together to: 1) identify clusters of reads
`originating from the same original fragment, 2) merge overlapping read pairs into single
`reads, where possible, and 3) generate consensus reads representing all information in the set
`of reads for each cluster. The consensus reads are then aligned to the reference genome.
`For the detection of short variants and rearrangements, a de novo assembly is performed.
`This is done using proprietary software to generate a de Bruijn graph including all k-mers in
`reads mapping to a particular locus. For each variant, there is a set of k-mers supporting the
`variant and a set of k-mers that would support the reference or another variant at the location.
`Each candidate variant is then scanned against reads in the locus to identify which reads sup-
`port either the candidate variant or a different variant or reference at the location. The final
`variant calls are made based on a model that takes into account the coverage at the location,
`the number of supporting read clusters and their redundancy level, and the number of error-
`containing clusters.
`CNAs are detected using a comparative genomic hybridization-like method. First, a log-
`ratio profile of the sample is obtained by normalizing the sequence coverage obtained at all
`exons and genome-wide single-nucleotide polymorphisms (SNPs) against a process-matched
`normal control. This profile is segmented and interpreted using allele frequencies of sequenced
`SNPs to estimate tumor purity and copy number at each segment.
`To determine MSI status, approximately 2000 repetitive loci (minimum of 5 repeat units of
`mono-, di-, and trinucleotides) are assessed to determine what repeat lengths are present in the
`sample. A locus containing a repeat length present in an internal database generated using
`>3000 clinical samples is considered to be ’unstable’. An MSI indicator is generated by calculat-
`ing the fraction of unstable loci, considering only those loci that achieve adequate coverage for
`consideration for the sample. Samples with >0.5% unstable loci are considered to be MSI-High.
`Blood tumor mutational burden (bTMB) is measured by counting all synonymous and
`non-synonymous variants present at 0.5% allele frequency or greater and filtering out potential
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
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`germline variants according to published databases of known germline polymorphisms
`including dbSNP and ExAC. Additional germline alterations are assessed for potential germ-
`line status and filtered out using a somatic-germline/zygosity algorithm. Furthermore, known
`and likely driver mutations are filtered out to exclude bias of the data set. The resulting muta-
`tion number is then divided by the coding region corresponding to the number of total vari-
`ants counted, or approximately 750 kilobases (kb). The resulting number is reported in units
`of mutations per megabase (mut/Mb).
`
`Sample selection and specimen characteristics
`
`Samples used for assay performance studies consisted of whole blood specimens of cancer
`patients and cfDNA samples selected from an inventory of residual banked cfDNA isolated
`from whole blood specimens of cancer patients, representing >30 cancer types (S2 Table).
`Institutional Review Board approval was obtained from New England IRB prior to use of sam-
`ples in the described validation studies and all data was anonymized prior to performing the
`described analyses. Targeted VAFs were achieved by diluting the samples in fragmented buffy
`coat genomic DNA (gDNA), when required. Assay validation studies were executed between
`April and December of 2019. cfDNA samples were originally extracted from plasma and fro-
`zen as early as May of 2016.
`Due to the scarcity of biomarker-positive cfDNA samples, contrived samples were also
`used. Contrived samples consisted of fragmented cell line DNA diluted in human plasma and
`titrated to target levels with biomarker-negative cfDNA to mimic a clinical plasma sample. For
`substitutions, indels, and rearrangements, cell line pools harboring multiple variants were
`used. Additionally, a plasmid construct was diluted and titrated as described above to repre-
`sent NTRK3 rearrangements. In total, >7,500 samples were processed as part of assay valida-
`tion studies.
`
`Clinical validation
`
`In addition to analytical validation of the platform, a number of relevant biomarkers were eval-
`uated for clinical validity via clinical bridging, either to a predicate companion diagnostic
`using clinical samples or to a clinical trial assay using clinical trial samples. A subset of these
`analyses is presented here. Other clinical validation studies for the assay are in review.
`Clinical validation for detection of PIK3CA alterations. Clinical validity of the assay as
`an aid in identifying breast cancer patients harboring PIK3CA alterations was evaluated
`through retrospective testing of plasma samples from advanced or metastatic HR-positive,
`HER2-negative breast cancer patients enrolled in the Novartis clinical trial CBYL719C2301
`(SOLAR-1) [24]. The primary endpoint for SOLAR-1 was progression-free survival (PFS)
`using Response Evaluation Criteria in Solid Tumors (RECIST v1.1), based on investigator
`assessment. Plasma samples were collected prior to study treatment and analyzed retrospec-
`tively for clinical validation. All available samples were considered; sample exclusion criteria
`included lack of clear identification on stored sample, obvious physical damage of stored sam-
`ple, and insufficient sample volume. The primary analysis was conducted with eligible samples
`with the assay’s recommended DNA input and with valid results from both FoundationOne
`Liquid CDx and the tumor tissue polymerase chain reaction (PCR)-based clinical trial assay
`(CTA). Of the 572 patients enrolled into the clinical study, 359 were included in the primary
`analysis. Concordance with the CTA was assessed and PFS based on assay test results was
`evaluated.
`Concordance study for EGFR exon 19 deletion and EGFR exon 21 L858R. Clinical
`validity of the assay as an aid in identifying patients with advanced NSCLC who may be eligible
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
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`for treatment with an EGFR tyrosine kinase inhibitor (erlotinib, gefitinib, or osimertinib) was
`established through a non-inferiority study with the FDA-approved cobas EGFR Mutation
`Test v2 (referred to as the reference assay) following the methods defined in Li et al. (2016)
`[25]. Samples were prospectively collected from an unrelated clinical trial and were eligible for
`this analysis if the patients did not enter the clinical study. Samples included in this concor-
`dance analysis were selected sequentially starting from a specific testing date until the prede-
`fined number of 150 EGFR-positive and 100 EGFR-negative samples were accrued. One
`replicate of each sample was tested using FoundationOne Liquid CDx (denoted as CGP) and
`two replicates were testing using the reference assay (denoted as Ref1 and Ref2). Samples with
`any missing results were excluded from the analysis. A total of 177 samples were included in
`this analysis to evaluate the non-inferiority as compared to the reference assay. To show that
`the agreement (positive percent agreement [PPA] and negative percent agreement [NPA])
`between CGP and Ref1/Ref2 is non-inferior to the agreement between Ref1 and Ref2, the esti-
`mates of zPPA1, zPPA2, zNPA1 and zNPA2 and the corresponding one-sided 95% upper
`bounds confidence limit were computed using the bootstrap method. In which, zPPA1 is the
`difference between the PPA of Ref1 and CGP and the PPA of Ref1 and Ref2; zPPA2 is the dif-
`ference between the PPA of Ref2 and CGP and the PPA of Ref2 and Ref1; zNPA1 is the differ-
`ence between the NPA of Ref1 and CGP and the NPA of Ref1 and Ref2; zNPA2 is the
`difference between the NPA of Ref2 and CGP and the NPA of Ref2 and Ref1. The one-sided
`95% upper bounds confidence limit of zPPA1, zPPA2, zNPA1 and zNPA2 were then com-
`pared to the pre-defined non-inferiority margin to evaluate non-inferiority as compared to the
`reference assay for the detection of EGFR exon 19 deletions and exon 20 L858R alterations.
`
`Analytical performance validation
`
`Contrived sample functional characterization. To support the use of contrived samples
`in performance evaluation studies, a contrived sample functional characterization (CSFC)
`study was performed to demonstrate commutability of test performance when using contrived
`or clinical specimens. The commutability between clinical and contrived samples was estab-
`lished by testing a dilution series to compare variant detection rates across different alteration
`types (subs, indels, rearrangements, copy number amplifications, copy number losses, MSI,
`and bTMB) totaling 924 cfDNA sample replicates and 1069 enzymatically fragmented cell-line
`gDNA sample replicates (contrived samples).
`Limit of blank. The limit of blank (LoB) describes the highest measurement result that is
`likely to be observed for a blank sample with a stated probability α [27]. According to industry
`standard, an α (type I error rate, false positive rate) of 0.05 was selected. The LoB was estab-
`lished by profiling 30 cfDNA samples from asymptomatic individuals without cancer with 4
`replicates per sample (>130,000 variants evaluated). Donors were all over the age of 60 and
`included smokers and non-smokers with the intent of representing an increased occurrence of
`clonal hematopoiesis. The LoB was estimated via the non-parametric method.
`Limit of detection. The limit of detection (LoD) describes the lowest level at which an
`analyte (genomic variant) can be consistently detected [26]. According to industry standard,
`consistently detected was defined the level at which a 95% detection rate is observed. The LoD
`for each variant type was established by processing a total of 1069 tests across 10 contrived
`samples representing short variants, rearrangements, CNAs, bTMB component variants, and
`MSI. The LoD was defined as the lowest dilution level tested with �95% detection across repli-
`cates. For variants with observed hit rates between 10% and 90% for 3 levels, the probit model
`was used to determine LoD. The LoD estimates were determined as either VAF for subs,
`indels, rearrangements, and bTMB component variants; TF for CNAs; or percent unstable loci
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
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`for MSI. Short variants with hit rates of �95% at all dilution levels or hit rates <95% for all
`dilution levels were excluded from analysis as LoD could not be reliably estimated. As bTMB
`score is an index variable in which qualifying substitutions and indels are counted and the
`resulting score normalized across the genomic region over which the score is calculated, the
`LoD of the component variants were determined in the evaluation of bTMB LoD. A subset of
`clinically actionable alterations were selected for analysis based on currently available targeted
`therapies and therapies currently under evaluation.
`Precision: Reproducibility and repeatability. We evaluated the reproducibility and
`repeatability (precision) of the assay for tumor profiling variants (platform-wide analysis), a
`subset of select clinically actionable alterations, MSI, and bTMB. Repeatability (intra-run: rep-
`licates processed on the same plate under the same conditions) and reproducibility (inter-run:
`replicates processed on different plates under different conditions) were assessed across 3
`reagent lots, 2 sequencers, and 2 processing runs, with 2 replicates per run (24 replicates per
`sample). Confidence was calculated using two-sided exact 95% confidence intervals (CI). For
`the tumor profiling variants and the subset of select clinically actionable alterations, all 47 sam-
`ples were used to evaluate assay precision, including 16 contrived samples and 31 clinical
`cfDNA samples. Precision of reporting of MSI status was evaluated across all 47 samples
`included in this study. Precision of bTMB scores was evaluated across samples with bTMB
`scores �5 muts/Mb.
`Analytical accuracy. Short variant and rearrangement detection rates were compared to
`that of an externally validated cfDNA-based NGS assay. A total of 282 samples (272 cfDNA
`and 10 contrived) representing 37 tumor types were tested and variant detection was com-
`pared in the 74 genes common to both assays. Clinical samples were selected from archival
`cfDNA samples from clinical testing originally processed as early as May 2016 while contrived
`samples using the methods described above were used to represent rare alterations. Concor-
`dance was assessed for short variants and rearrangements across the 74 genes common to both
`platforms. Concordance was also assessed more specifically for a subset of clinically actionable
`alterations. In a separate analysis, the detection of PIK3CA alterations were compared to
`another orthogonal cfDNA-based NGS method using residual plasma samples from the
`Novartis clinical trial CBYL719C2301 (SOLAR-1) [24].
`
`Results
`Clinical validation
`Clinical validation for detection of PIK3CA alterations. Of 572 patients enrolled in
`SOLAR-1, 432 had available baseline plasma samples. The characteristics of the patients at
`baseline have been described previously [24]. Results were available for 375 patients for inclu-
`sion in the primary analysis and considered for the concordance analysis summarized in
`Table 1. A PPA of 71.7% and an NPA of 100% for the detection of eligible PIK3CA alterations
`were observed as compared to the tumor tissue PCR CTA. The PPA observed for detection of
`PIK3A alterations was likely impacted by the use of banked clinical trial samples, as many sam-
`ples were tested with plasma volumes that were significantly lower than those that would be
`expected from the recommended assay input of 17 mL of whole blood. Additionally, variability
`in the shed rate of tumor DNA into the bloodstream [13] could also contribute to reduced
`detection rate in cfDNA.
`A total of 16 samples from the primary analysis set had invalid results from one or both
`assays. The evaluable population encompassed 230 PIK3CA alteration-positive patients and
`129 PIK3CA-negative patients. Comparable demographics and baseline clinical characteristics
`were demonstrated for evaluable and unevaluable patient populations in the primary analysis
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`Validation of a 324-gene comprehensive genomic profiling liquid biopsy assay
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`Table 1. Concordance between FoundationOne Liquid CDx and alpelisib CTAa for eligible PIK3CA alterationsb.
`
`CTA Positive
`
`CTA Negative
`
`Invalid
`
`Total
`
`cfDNA CGP Positive
`
`cfDNA CGP Negative
`
`Invalid
`
`Total
`
`165
`
`65
`
`7
`
`237
`
`0
`
`129
`
`5
`
`134
`
`1
`
`3
`
`0
`
`4
`
`166
`
`197
`
`12
`
`375
`
`PPA (95% CI): 71.7% (65.4%, 77.5%)
`
`NPA (95% CI): 100% (97.2%, 100%)
`
`aTumor tissue PCR assay
`bDefined as alterations with the amino acid effect: C420R, E542K, E545A, E545D (1635G>T only), E545G, E545K, Q546E, Q546R, H1047L, H1047R, H1047Y.
`
`cfDNA = cell-free DNA; CI = confidence interval; CTA = clinical trial assay; NPA = negative percent agreement; PPA = positive percent agreement.
`
`https://doi.org/10.1371/journal.pone.0237802.t001
`
`set for both PIK3CA-positive and PIK3CA-negative patients. The primary analysis set was also
`shown to be representative of the overall SOLAR-1 patient population (not shown).
`Alpelisib in combination with fulvestrant was evaluated in the plasma-positive population
`(n = 165) with an estimated 54% risk reduction in disease progression or death in the alpelisib
`plus fulvestrant arm compared to the placebo plus fulvestrant arm (hazard ratio[HR]: 0.46,
`95% CI: 0.30, 0.70). Median PFS was 11.0 months for the alpelisib plus fulvestrant arm versus
`3.6 months for the placebo plus fulvestrant arm (Table 2).
`Concordance study for EGFR exon 19 deletions and EGFR exon 21 L858R alterations.
`A total of 177 samples from NSCLC patients with two valid replicate results by the reference
`assay (denoted as Ref1 and Ref2) and one replicate by FoundationOne Liquid CDx (denoted
`as CGP) were included in this analysis. The concordance data are summarized in Tables 3 and
`4 and the non-inferiority comparison is provided in Table 5.
`This study establishes the clinical validity of the assay and the non-inferiority to plasma test-
`ing with cobas EGFR Mutation Test v2 for the identification of patients eligible for treatment
`with erlotinib, gefitinib, and osimertinib.
`
`Analytical performance validation
`
`Contrived sample functional characterization. The hit rates for contrived samples and
`cfDNA samples were evaluated and compared across targeted variant concentrations. The hit
`rate was consistent across contrived and clinical cfDNA samples (S3 Table). The cfDNA sam-
`ple and contrived sample targeted levels at which �95% hit rate was observed, respectively
`were: 0.30% and 0.35% VAF for short variants; 0.20% and 0.30% VAF for rearrangements; 5%
`
`Table 2. Progression-free survival among 165 CTA-positive/ FoundationOne Liquid CDx-positive patients.
`
`PFS
`
`No of events (%)
`
`PD (%)
`
`Death (%)
`
`No of censored (%)
`Months, median (95% CI)a
`HRb (95% CI) Alpelisib + Fulvestrant /Placebo + Fulvestrant1
`
`Alpelisib + Fulvestrant n = 84
`
`Placebo + Fulvestrant n = 81
`
`54 (64.3)
`
`52 (61.9)
`
`2 (2.4)
`
`30 (35.7)
`
`11.0 (7.3, 15.9)
`
`0.46 (0.30, 0.70)
`
`67 (82.7)
`
`61 (75.3)
`
`6 (7.4)
`
`14 (17.3)
`
`3.6 (2.4, 5.8)
`
`aThe 95% CI calculated from PRO