Presentation on theme: "NanoString’s Prosigna Breast Cancer Assay"— Presentation transcript:
1 NanoString’s Prosigna Breast Cancer Assay Bringing Genomic Testing Into Your Lab
2 Measuring Nucleic Acids in Clinical Samples Current clinical practiceFormalin-fixed, paraffin-embedded (FFPE) samples pose challenges to accurate and reproducible estimation of biomoleculesChallenges of expression-profiling FFPE samplesFFPE processed samples provide low and variable yields of mRNAFormalin fixation modifies and degrades mRNA, making it difficult to measure by traditional techniquesAnalytical needA robust and validated methodology is required to accurately estimate RNA expression levels in tumor FFPE samplesThe traditional clinical method of choice for processing and storing tumor samples is not biomolecule-friendly.While optimal for the original intended purpose (ie, histologic review), formaldehyde preservation hydrolyses phosphodiester linkages of polynucleotide chains, breaking long-chain nucleotide (nt) sequences into shorter strandsMoreover, the protocols for formaldehyde fixation are not uniform across clinical centers, adding further variability to the extent of degradation of biomoleculesAlso, samples may vary in age
3 nCounter: Designed for Translational Research Highly Multiplexed800 targets per reactionNo Amplification (for > 25ng RNA input)Tolerant of FFPE and no biasPrecisionDigital counting means unparalleled reproducibility over nearly 6 logs of dynamic rangeSimple and FastEasier, faster, automated data productionReporter ProbeCapture ProbeTargetTarget-Probe Complex
4 nCounter Advantage for Quantitating Nucleic Acids in FFPE Samples Direct measurement minimizes error/bias from enzyme-based processes (reverse transcriptase and polymerase)Ability to detect short chain RNA templatesLinearity of measurement over a wide dynamic range ensures accurate quantitation of both rare and abundant transcriptsFacilitated by solution phase hybridizationDigital counting designExcess probesAllows for flexible range of sample inputThe nCounter platform has inherent advantages in accurate quantification of mRNA form FFPE derived samples over competing solid-phase GEP platforms.Amplification bias is eliminatedAs mentioned previously, chip-based protocols require c-DNA synthesis and amplification which can skew data particularly for relatively rare transcriptsDynamic rangeAllows for wider range of sample input minimizing potential dilution/concentration stepsSolution phase hybridizationIn addition, the solution-phase hybridization protocol used in nCounter is far more efficient than solid-phase hybridization used in microarrays allowing for efficient capture and quantitation of both abundant and rare transcripts
5 nCounter Workflow: Hands-off Process Enables Decentralized Testing MinimalHANDS-ONMinimalHANDS-ONMinimalHANDS-ONStep 112 HOURS OR OVERNIGHTStep 22.5 – 3.0 HOURS, AUTOMATEDStep 33 – 4.5 HOURS, AUTOMATEDnCounter® Prep StationnCounter® Digital Analyzer1Hybridize2Purify3CountSimple and fast workflow is well suited for qualified clinical laboratories
6 nCounter Dx Analysis System With Flex Configuration A single instrument system can be used toValidate genomic discoveries from NGS or arraysTranslate validated discoveries into clinical useRun clinical diagnostics
7 nCounter Elements: Enabling More Options for Dx Development CodeSetsCustom-built assaysStandardized panels300+ peer-reviewed papersProsigna™Prosigna Breast Cancer AssayCE Marked & launched in EUExpected Q U.S. launchFDA-cleared:September 9, 2013Since 2009Advanced Disease Research Global Diagnostic Kits
8 nCounter Elements: Enabling More Options for Dx Development Advanced Disease Research Enable Clinical Testing Global Diagnostic KitsSince 2009Commercial Release:February 11, 2014FDA-cleared:September 9, 2013CodeSetsCustom-built assaysStandardized panels300+ peer-reviewed papersnCounter Elements™Components to Develop AssaysRegistered with FDAFlexible FormatProsigna™Prosigna Breast Cancer AssayCE Marked & launched in EUExpected Q U.S. launch
9 Development and Output ProsignaDevelopment and Output
10 Origins of Prosigna—PAM50 Gene Signature Deriving the Gene Set and Prognostic Algorithm Determine optimal gene setHierarchical clustering of 1,906 “intrinsic” genes defined by previous studiesOptimized gene set (qRT-PCR data from 122 breast cancers) to 161 genes that passed FFPE performance criteriaCross-validation (random 10% left out in each of 50 cycles) by “N” t-test method selected 50 genesDevelopalgorithmCompared reproducibility of classification across 3 centroid-based prediction methodsSelected Prediction Analysis of Microarray (PAM)Luminal ABasal-likeLuminal BHER2-enrichedUBE2CCCNB1MYBL2PTTG1TYMSHSPC150BIRC5CEP55KNTC2MELKORC6LRRM2CDC6EXO1KIF2CANLNCDC20CDCA1CENPFGRB7CCNE1MKI67TMEM45BGPR160BLVRAERBB2NAT1MMP11FOXA1SLC39A6ESR1CXXC5ACTR3BBAG1PGRMIAKRT5MYCFOXC1KRT14KRT17SFRP1CDH3PHGDHBCL2MDM2FGFR4EFGRMAPTMLPHNormalThe PAM50 gene set is a subset of the expanded gene set that delineated the intrinsic subtypes of breast cancer based on the gene expression profile of breast tumor tissue.First, a broad technical optimization screen was used to identify transcripts in FFPE-preserved tissues that could accurately be measured by qRT-PCRCross-validation with the prototypical intrinsic subtypes resulted in the optimal set of 50 genes which were then trained on the node-negative, untreated subset of the van de Vijver cohort1Reference:1. van de Vijver MJ, et al. N Engl J Med. 2002;347:Trained with a multivariable Cox modelRisk of recurrence (ROR) score developed for test case using correlation to subtype alone:ROR-S = 0.05*basal *HER2 – 0.34*LumA * LumBor using subtype correlation plus tumor size:ROR-C= 0.05*basal *HER2 – 0.23*LumA *LumB * TParker JS, et al. J Clin Oncol. 2009;27(8):
11 Subtype Predictions by PAM50 Shows Distinct Clinical Outcomes Intrinsic subtypes assigned using PAM50 show clear differences in RFS in node- negative patients who did not receive systemic adjuvant therapySimilar differences in RFS by subtype were seen in the subset of patients with ER+ BCPatients who did not receive systemic adjuvant therapySubset of patients with ER+ disease1.01.00.80.80.60.6Relapse-Free Survival (probability)PAM50-assigned intrinsic subtypes are associated with distinct risks of recurrence.An important finding from these analyses was that all intrinsic subtypes are present and clinically significant in terms of outcome predictions in cohorts of patients diagnosed with ER-positive diseaseThus the molecular subtypes are not simply another method of classification that reflects ER statusHowever, as shown in the next slide, the PAM50 gene set and algorithm provides clinically significant information beyond intrinsic subtypeRelapse-Free Survival (probability)0.40.4Basal-likeHER2-enrichedLuminal ALuminal BBasal-likeHER2-enrichedLuminal ALuminal B0.20.2Log-rank P = 2.26e-12Log-rank P = 1.89e-10246810246810Time, yearsTime, yearsRFS, relapse-free survival.Parker JS, et al. J Clin Oncol. 2009;27(8):
12 PAM50 ROR-Score Provides Increased Accuracy in Outcome Predictions Risk prediction based on the PAM50 gene set added significant information to pathologic staging, histologic grade, and standard clinical molecular markersKaplan-Meier estimates of risk groups show clear separation of RFS1.00.8PAM50 risk scores discriminate the risk of recurrence within intrinsic subtypes, demonstrating the additive prognostic value.Relapse-Free Survival (probability)0.60.4HighLowLog-rank P = 9.52e-11Medium246810Time, yearsParker JS, et al. J Clin Oncol. 2009;27(8):
13 PAM50 Gene Signature Is Robust Validated by TCGA (Independent Dataset, Different Platform) Semi-supervised hierarchical cluster analysis showed consensus across breast cancer intrinsic subtypes defined in independent datasets using 5 different genomic/ proteomic platformsaThese data are independent of nCounter technology.The TCGA study in breast cancer shows that intrinsic subtype assignments obtained using the PAM50 gene expression profile were concordant with intrinsic subtype assignments derived from analyses of protein expression, miRNA, copy number variation, and methylation.Notably, these analyses are based on an independent data set and on measurements based on alternate high-throughput platforms, including that used for PAM50 (ie, Agilent 244K WGA rather than nCounter)Figure legend:Consensus clustering analysis of subtypes identified major groups (n = 348). The blue and white heat map displays sample consensus.Heat map display of subtypes defined independently by microRNAs, DNA methylation, copy number, PAM50 mRNA expression, and RPPA expression.Associations with molecular and clinical features. P values were calculated using a Chi-square test.a Heat map display of subtypes defined independently by microRNAs, DNA methylation, copy number, PAM50 mRNA expression, and RPPA expression.The Cancer Genome Atlas Network. Nature. 2012;490(7418):61-70.
14 Transitioning qRT-PCR–Based PAM50 to nCounter Platform (NanoString) ObjectiveReplace qRT-PCR protocol with an automated, multiplexed assay (nCounter) to assign risk scoreEndpointsAssess concordance between outputs:Expression measurements of each geneAssignment of intrinsic subtypeProliferation and risk scoresApproachAssess concordance with above endpointsRetrain algorithm using nCounter-based measurementsnCounter provides simplified up-stream and downstream processing to determine nCounter-PAM50 ROR score.However, to transition to the nCounter platform, it is necessary to establish concordance in expression measurements of each gene and to assess the effects of variation of these estimates on assignment of intrinsic subtype and evaluation of risk score
15 nCounter-Based Measurements Concordant With qRT-PCR ROR scores or proliferation scores obtained using estimates of gene expression of the nCounter-PAM50 gene signature gene panel by qRT-PCR or by the nCounter platform were very similarnCounter results versus qRT-PCRROR ScoreProliferation Score800.560Estimates of PAM50 gene expression on nCounter were concordant with qRT-PCR–based estimates, as were the ROR scores.The concordance between qRT-PCR and nCounter data for the level of gene expression was presented in Liew M, et al.0.0qRT-PCR40qRT-PCR20–05icc = 0.951icc = 0.947–1.020406080–1.0–0.50.00.5NanoStringNanoStringLiew M, et al, AMP National Meeting, 2010.
16 Switching Analytic Platform to nCounter Retraining the Algorithm Data from Parker et al1 were re-analyzed using the prototypical subtype centroids from nCounter trainingSubtypes showed a similar prognostic profile to the originally reported dataAll1.00.80.60.40.20.02468Probability of EventLog-rank P = 1.14e-08LumA 72/297LumB 94/204Her2 48/95Basal 42/111ER+1.00.80.60.40.20.0246810Probability of EventLog-rank P = 4.16e-07LumA 62/243LumB 72/157Her2 42/81Basal 32/82ER–1.00.80.60.40.20.0246810Probability of EventLumA 7/51LumB 19/42Her2 5/11Basal 9/28Log-rank P =Clinical outcomes in the nCounter-based subtypes were similar to those observed for qRT-PCR–based assignments.10Parker JS, et al. J Clin Oncol. 2009;27(8):
17 nCounter (NanoString) Subtype2 New Training as Robust as Published Classifier in the Intended Use PopulationThe recurrence-free curves of the intrinsic subtype cohorts defined by qRT-PCR (left) and nCounter (right) are highly concordantqRT-PCR Subtype1nCounter (NanoString) Subtype21.01.00.80.80.60.6Probability of EventProbability of Event0.40.4The nCounter retrained algorithm was successfully validated in an independent data set.Test set of samples independent of training samplesCommunity cohort of ER+ patients treated with tamoxifen onlyHer2 4/14LumA 10/54LumB 22/58Normal 0/30.20.2Her2-enriched 3/13Luminal A 3/31Luminal B 30/85Log-rank P = .155Log-rank P = .03360.00.051015510151. Nielsen et al. Clin Cancer Res. 2010;16(21):2. NanoString data on file.
18 Prosigna AssayUses the expression profile of 50 classifier genes (and 8 housekeeping genes for normalization) to determine breast cancer subtype and probability of relapseAlgorithm provides a continuous risk of recurrence (ROR) score; henceforth, referred to as the “Prosigna Score”Incorporates intrinsic subtype, proliferation score, and tumor sizeUses different cut-points for probability of relapse in patients with node- negative and node-positive breast cancerValidated on the nCounter platform allowing decentralized and standardized breast cancer testing worldwideThe nCounter-PAM50 gene signature assay integrates standard clinicopathologic characteristics with intrinsic subtype and proliferation score to provide an objective assessment of risk of recurrence.
19 Prosigna Algorithm Prosigna Score for Individual Patients ROR score integrates intrinsic subtype, proliferation index, and tumor size (in the context of nodal status) to provide an integer score proportional to the risk of recurrenceDetermine intrinsic subtype through Pearson’s correlation to centroidsCalculate ROR (Risk of Recurrence Score)Patientexpression profileLumBLumABasal-likeHER2-enrichedPAM50 centroidsaRLumA+bRLumB+cRHer2e+dRBasal+ROR =Pearson’s correlation to centroidsROR score integrates intrinsic subtype, proliferation index, and tumor size (in the context of nodal status) to provide an integer score proportional to the risk of recurrence.Gene expression data are weighted with clinical variables to determine an integer score from 0 through 100 (ROR) indicative of the probability of disease recurrenceROR is based on the similarity of the gene expression profile to intrinsic subtypes, proliferation score, and tumor sizeRisk algorithm requires input of gross tumor size and nodal statuseP+fTProliferation scoreGross tumor sizeGnant M, et al. SABCS. 2012; poster P19
20 Prosigna Score Is a Continuous Risk Function The probability of distant recurrence within 10 years increases as a function of ROR and nodal status based on data in the tested patient populationNode-negativeNode-positive (1-3 nodes)The probability of distant recurrence within 10 years increases as a function of ROR Score and nodal status based on data in the tested patient population.A change of 10 ROR units corresponds to an average change in 10-year distant recurrence free survival of 7% and 6% for node negative and node positive patients respectivelyPackage Insert (US).
21 Prosigna Categorizes Risk Groups by Nodal Status ROR RangeRisk CategorizationNode-negative0 - 40LowIntermediateHighNode-positive(1 - 3 nodes)Risk classification groups are provided based on cutoffs related to clinical outcome in the tested patient populations:Low risk: 10-year probability of distant recurrence of < 10%High risk: 10-year probability of distant recurrence of > 20%ROR score discriminates risk groups within patients with node-negative diseaseDistinct ROR thresholds for node-negative and node-positive tumors define risk groups.This slide is for the US audiencePackage Insert (US).Gnant M, et al. Ann Oncol. 2014;25(2):
22 Prosigna Patient Report The nCounter-PAM50 Gene Signature Assay is intended for use as a prognostic indicator for distant recurrence-free survival at 10 yearsIndicated for postmenopausal women with Stage I/II lymph node- negative or Stage II lymph node-positive (1 to 3 positive nodes) hormone receptor-positive breast cancer who have undergone surgery in conjunction with locoregional treatment consistent with standard of careRisk of Recurrence (ROR Score)Zero to 100Relates to recurrence rate at 10 years on 5 years of endocrine therapy aloneRisk GroupsNode NegativeLow, Intermediate, or High riskBased on ROR Score and nodal statusNode PositiveLow or High riskThe nCounter-PAM50 Gene Signature patient report is readily interpretable.US Prosigna Patient Report; FDA 510K cleared.
24 nCounter-PAM50 ROR Score Analytic Reproducibility of nCounter-PAM50 Gene Signature Assay Evaluated in Two StudiesStudy 1: Reproducibility from tissueStudy 2: Precision from RNAExtract RNA from FFPEtumor sampleRun on the nCounter Dx Analysis SystemThe analytical validation evaluated all procedural variables related to sample extraction, reagents, operator, and instrumentation.nCounter-PAM50 ROR Score
25 Evaluating Variation in nCounter Gene Expression Estimate RNA Precision StudyAssessed reproducibility of device, reagents, and operator-specific components using a common template RNAMeasured variability between and within assay variables includingTesting site (n = 3)Sample type (n = 5)Operator (n = 6)Reagent lot (n = 3)Assay run (n = 18/site)Site 1Site 2Site 3Operator 1Operator 2Reagent Lot 1Reagent Lot 2Reagent Lot 3This study design evaluated the effects of variation in the gene expression estimate and ROR score across sites.Run 1Run 2Run 3Basal-likeHER2-ELum ALum B1Lum B2X 2Nielsen T, et al. BMC Cancer. 2014;14(1):177.
26 Reproducibility of nCounter-PAM50 Gene Signature Assay Concordance in Risk Group Reproducibility StudyFor each tissue sample, macrodissection, RNA extraction, and processing with the assay were performed by a single operator at each site per standard operating procedures43 tissues across all sites represent a wide range (94 units) of ROR scores and all risk categoriesSamplesSite 1Site 2Site 3Pathologist 1Pathologist 2Pathologist 3Operator 1Operator 2Operator 3This study design evaluated the effects of variation in the RNA input on evaluation of the ROR score.RNA Isolation Kit 1RNA Isolation Kit 1RNA Isolation Kit 1Duplicate Run with Reagent Lot 1Duplicate Run with Reagent Lot 1Duplicate Run with Reagent Lot 1The definition of “high reproducibility” was pre-specified to be a total SD<4.3Nielsen T, et al. BMC Cancer. 2014;14(1):177.
27 Prosigna Analytically Validated for Decentralized Testing Reproducibility from 43 FFPE Tissue Samples1Precision from 5 Pooled RNA Samples1Prosigna ScoreProsigna ScoreProsigna ScoreAverage of 90% risk group concordance between sitesSite-to-site or operator-to-operator <1% of varianceProsigna Score Standard Deviation = 2.9100% concordance between risk groupsSite-to-site or operator-to-operator <1% of varianceProsigna Score Standard Deviation = 0.67Analytical Reproducibility of the Breast Cancer Intrinsic Subtyping Test and nCounter® Analysis System Using Formalin-Fixed Paraffin-Embedded (FFPE) Breast Tumor Specimens. T Nielsen, S McDonald, S Kulkarni, J Storhoff, C Schaper, B Wallden, S Ferree, S Liu, V Hucthagowder, K Deschryver, V Holtschlag, G Barry, M Evenson, N Dowidar, M Maysuria, D Gao. CAP 2013Output of the U.S. version of Prosigna submitted for 510(k) does not report intrinsic subtype. Reporting intrinsic subtype in the U.S. will require a future PMA supported by additional clinical studies
28 Heterogeneity of Breast Cancer The Benefit: Risk Equation
29 Heterogeneity of Breast Cancer Clinicopathologic covariates and receptor status inform treatment decisionsHowever, disease course and treatment outcomes in patients with similar baseline disease covariates vary considerablyAdvances in molecular understanding suggest underlying heterogeneityTraditional clinical characteristics of breast tumors do not adequately predict treatment outcomes, reflecting the underlying heterogeneity of the disease.Clinicopathologic covariates such as nodal status and tumor size are the primary considerations in determining treatment modalityNCCN Guidelines1 recommend adjuvant therapy in all patients with node-positive disease regardless of HR and HER2 status of tumor (ie, HR+/HER2– disease or HR–/HER2– disease)However, clinical data show that these factors alone, or in combination, do not adequately reflect the risk of late recurrence, and disease course varies within patient subgroups defined by common clinicopathologic covariatesFor example, patients with positive nodal status may be at low risk for recurrence, and conversely, patients with node-negative disease may be at high risk for late recurrenceAs a result, treatment decisions are suboptimalMolecular approaches can provide objective tools to quantifying the individual patient’s risk of recurrence and help guide the treatment choiceMolecular approaches to treatment selection will not only improve overall treatment outcomes but will likely also enhance patient quality of lifeReference:1. NCCN Clinical Practice Guidelines in Oncology: Breast Cancer. V
31 Time to distant metastasis, months Defining Heterogeneity in Breast Cancer Predictive Value of Intrinsic SubtypesClinical evidence suggests that intrinsic subtype is predictive of clinical outcomes1,21Luminal ALuminal BBasalERBB2+0.80.6P < .01Probability0.4Classification of patients into risk-categories on the basis of the prognosis profile may be a useful means of guiding adjuvant therapy decisions in patients with early stage breast cancer.(Note: the use for guiding treatment approaches the definition of ‘predictive’)The figure in the slide shows a reanalysis of the van’t Veer samples by Sorlie et al,1 and concludes that clinical outcomes were worst for basal (and ERBB2), best for luminal A, and intermediate for luminal B subtypesThe van’t Veer data set2:98 breast tumors were selected for analysis of which34 patients developed distant metastases within 5 years44 patients were disease-free for at least 5 yearsData shown in the figure above was derived from 97 of these casesReference:Sorlie T, et al. Proc Nat Acad Sci (USA). 2003;100(14):van’t Veer LJ, et al. Nature. 2002;415(6871):0.224487296120144168192Time to distant metastasis, months1. Wirapati P, et al. Breast Cancer Res. 2008;10(4):R65.2. Figure from Sorlie T, et al. Proc Nat Acad Sci (USA). 2003;100(14):
32 Tumor Size, Grade, Lymph Node Status, ER, PR, Her2 Tumor Boards-Good actor vs bad actor
33 Breast cancer prognostic classification in the molecular era: the role of histological grade Histologic grade (NGS) is a robust, prognostic, with good to excellent reproducibility.The scrutiny applied to histologic grading has only recently been applied to molecular tests.36% intermediate Histologic Grade; 40% of oncotype dx tests are Intermediate RS.Rare: Grade 1-Grade3.*Rakha EA, Reis-Filho JS, Baehner F, Dabbs DJ, Decker T, Eusebi V, Fox SB, Ichihara S, Jacquemier J, Lakhani SR, Palacios J, Richardson AL, Schnitt SJ, Schmitt FC, Tan PH, Tse GM, Badve S, Ellis IO. Breast Cancer Res ;12(4):207. doi: /bcr2607. Epub 2010 Jul 30. Review. PMID:
34 What your Pathologists Know – histological surrogates for the intrinsic subtypes Luminal A:ER +, very high (HS )PR + Very High (HS )Ki67: Low 3-14%Grade: 1, few percent grade 2.Luminal B:ER + intermediate-low (HS 1-200)PR: negative or low (HS <100)Grade 2 or 3Ki67 >15%, often much higher
35 Significant Clinical Impact of Oncotype-MammaPrint Discordance Molecular Subtype (MP)PatientsOncotype DxLUM A% Major Discordance47 Low, 12 Int, 4 HighLUM B51 35% Major discordance18 Low, 17 Int, 16 HighMolecular Subtypes of Cases Discordant Between Risk Classification Assays in ER+ N0-N1 Patients: Shivers et al Miami Breast Conference March, 2014
36 Dabbs et al. ASCO-June, 2014 Molecular Subtype (MP) Patients Oncotype DxLUM A% Major Discordance188 Low, 95 Int, 4 HighLUM B% Major Discordance16 Low, 47 Int, 27 High
37 Breast Cancer Gene Expression Profiling Risk assessment profiles are not uniform.Platforms are not uniform.Information is often driven by marketing.Patient results show greater discordance for treatment purposes than the variation that is seen with pathologist grading of tumors.The need for FDA to regulate…..July 31, 2014.
38 Take Home Message..Why Magee is Offering Prosigna New generation Nanostring platform.Prosigna (PAM50) has superior prognostic information compared to Oncotype.*Intrinsic subtype adds more information to differentiate risk assessment, decreasing intermediate scores by 25%.Low Risk for node negative and positive.10 year DR prognostic information is unique.A transparent, FDA cleared platform for patient safety.Value-added pathology.*Sestak I et al. Factors Predicting Late Recurrence for ER+ breast Cancer JNCI 2013; 105(19):*Dowsett M et al. Comparison of PAM50 ROR with Oncotype Dx and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol 2013; 31(22):
39 Tumor Biomarker Tests The Burden of Proof1 Analytical validationRobustness of hypothesis and algorithmReproducibility of sampling and assayClinical validationProspective/retrospective study in the target population2,aClinical utilitySignificant association of biomarker-defined patient subset with treatment outcomeValue in guiding treatment decisionEconomic utilityThe economic impact of consequent effects on treatment decisions is within accepted regional normsTumor biomarker-based assays must satisfy key technical and clinical criteria for the intended use (ie, analytical validity, clinical validity, and clinical utility) in addition to being economically viable.a Prospective analysis plan sufficient for Level 1 evidence.Hayes DF, et al. Breast. 2013;22(suppl 2):S22-S26.Simon RM, et al. J Natl Cancer Inst 2009;101(12):
40 Clinical Validation in HR+ Breast Cancer TransATAC, ABCSG-8
41 nCounter-PAM50 Gene Signature Assay Clinically Validated in Two Studies Representative of the ‘Intended Use Population’TransATAC Study (n=1017)N = 1,007 patientsPresented at San Antonio Breast Cancer Symposium in December 2011Published in Journal of Clinical Oncology1ABCSG-8 Study (n=1478)Presented at San Antonio Breast Cancer Symposium in December 2012Published in Annals of Oncology2Prospectively defined analysis of two registration-quality databases with ≥10-yr median follow-up in postmenopausal women with HR+ early stage breast cancer treated with endocrine therapy alonePrimary Objective: Validate published observations that the nCounter-PAM50 gene signature score provides additional prognostic information over and above standard clinical variables for DRFS at 10 yearsPrimary Analysis: All patientsSecondary Analysis: Node-negative, node-positive, and HER2-negative patientsSecondary Objective: Validate observations that Luminal A and Luminal B patients have statistically significantly different DRFS at 10 yearsaThe evidence for the clinical validation of the nCounter-PAM50 gene signature assay is robust and was conducted in a large patient sample from randomized controlled trials with eligibility criteria representative of the ‘intended use population’.The nCounter-PAM50 Gene Signature Assay is indicated in female breast cancer patients who have undergone either mastectomy or breast-conserving therapy in conjunction with locoregional treatment consistent with standard of care, either as:A prognostic indicator for distant recurrence-free survival at 10 years in post-menopausal women with Hormone Receptor- Positive (HR+), lymph node-negative, Stage I or II breast cancer to be treated with adjuvant endocrine therapy alone, when used in conjunction with other clinicopathological factorsA prognostic indicator for distant recurrence-free survival at 10 years in post-menopausal women with Hormone Receptor-Positive (HR+), lymph node-positive (1-3 positive nodes, or 4 or more positive nodes), Stage II or IIIA breast cancer to be treated with adjuvant endocrine therapy alone, when used in conjunction with other clinicopathological factorsROR score was clinically validated in TransATAC and ABCSG-8a Output of the U.S. version of the nCounter-PAM50 gene signature assay FDA cleared for 510(k) does not report intrinsic subtype.1. Dowsett M, et al. J Clin Oncol. 2013;31(22):2. Gnant M, et al. Ann Oncol. 2014;25(2):
42 TransATAC and ABCSG8 Studies: Met Primary and Secondary Objectives Prosigna adds statistically significant prognostic information in addition to standard clinical-pathological variables1,2.AnalysesPopulationTransATACNumber of PatientsP-valueABCSG8PrimaryAll Evaluable1,007<0.00011,478SecondaryNode-negative7391,047Node-positive(1-3 nodes)2680.002382HER2 Negative8881,397Because the statistical analysis plan for ABCSG8 was so similar to that for TransATAC, and the results were so positive, I will move quickly through the same set of analyses that we have previously covered.As you can see from this table, ABCSG8 met its primary and secondary endpoints with similar significant results. The p-values here are all less thanThe relationship between Prosigna’s risk score and outcome is very strong.1. Dowsett et al. JCO 20132. Gnant et al. Annals of Oncology 2014.
43 Node-negative Patients ABCSG-8: Prosigna Score Discriminates Recurrence Risk Within Nodal SubgroupsNode-negative PatientsNode-positive Patients (1-3 nodes)The KM curves here show that we achieve good separation between high, intermediate, and low risk in the node-negative patients, and between high and low risk in the node-positive patients.The risk groups defined by Prosigna are similarly prognostic, and most importantly the patients categorized as low risk have excellent outcomes when treated with endocrine therapy alone.We believe that most physicians would spare these low risk women chemotherapy.Risk GroupN (%)Events% withoutrecurrence at 10 yrLow487 (47%)1597% [94% - 98%]Intermediate335 (32%)2890% [86% - 93%]High225 (21%)3284% [78% - 89%]Total1,047Risk GroupN (%)Events% withoutrecurrence at 10 yrLow158 (41%)794% [88% - 97%]High224 (59%)4676% [69% – 81%]Total382Source: Gnant et al. Annals of Oncology 2014.
44 TransATAC: Prosigna v RS: Fewer Intermediate Risk Node-Negative Patients Risk groups prospectively defined based on predicted probability of 10-year distant recurrence (low < 10%, intermediate 10% to 20%, high > 20%)Clinical and pathologic variables excluded from analysis10090807060Percent Without Distance RecurrenceROR scores categorize fewer patients in the intermediate risk group compared with 21 gene test.Clinical outcome between the intermediate risk groups classified by the nCounter-PAM50 Gene Signature Assay is acceptable. Patients classified as intermediate risk by the nCounter-PAM50 Gene Signature Assay do not require adjuvant therapy (acceptable risk)In contrast, the clinical outcome of the intermediate risk group defined by RS is higher (separates early and reaches ~15% at 10 years). Thus it is likely that most patients with RS-defined intermediate risk may opt for adjuvant treatmentROR, lowRS, lowROR, intermediateRS, intermediateROR, highRS, highFollow-Up Time (Years)* Risk groups prospectively defined based on predicted probability of 10-yr distant recurrence (Low <10%, Intermediate 10-20%, High >20%)Dowsett M, et al. J Clin Oncol. 2013;31(22):
45 Combined Analysis Clinical Validation in More Than 2,400 Patients 9,366 enrolled in ATAC3,901 enrolled in ABCSG-85,880 eligible for TransATAC3,714 eligible for ABCSG-82,006 tissue specimen received1,620 re-consented or deceased1,017 sufficient residual RNA25 insufficient cancer in specimen73 insufficient RNA isolated44 failed QC specs for device10 failed QC specs for deviceA combined analysis of patients included in the TransATAC and ABCSG-8 was conducted according to a prospectively defined analysis plan.Again, these analyses may be considered as Level 1 evidenceThe primary objective was evaluated inAll patients (Primary Analysis)Node-negative/positive, HER2-negative patients (Secondary Analysis)The 2 trials explored different endocrine regimensTransATAC: TAM vs ANA vs TAM + ANAABCSG-8: TAM followed by TAM vs TAM followed by ANA1,007 evaluable RNA specimens1,478 evaluable tissue specimens2,485 evaluable specimensGnant M, et al. ASCO 2013; Poster 506.
46 Update--Late Recurrence Prosigna provides for additional information on the observed risk of distant recurrence in years 5-10 for node negative (1.3% Distant Recurrence) and node positive (3.7% Distant Recurrence).Patients in years 5-10 may avoid further endocrine therapy.FDA-cleared
47 5 years after endocrine therapy Node-negative Prosigna identifies Low Risk node-negative patients that remain Low Risk in all time periods--Low Risk node-negative patients had a total 10-year risk of recurrence of 3.4%
48 5 years after endocrine therapy Node-positive (1-3 nodes) Prosigna identifies Low Risk node-positive (1-3 nodes) patients that remain Low Risk in all time periods--Low Risk node-negative patients had a total 10-year risk of recurrence of 5.8%
49 Conclusions Across Clinical Studies Support the clinical validity of Prosigna Score for the risk of late recurrence in postmenopausal women with HR+ ESBCProsigna Score discriminates risk groups within subsets of patients defined byNodal status (negative versus positive)Prosigna Score score provides clinically actionable informationIdentifies node negative and node-positive patients at sufficiently low risk to be spared chemotherapyIdentifies patients at sufficiently low risk of late-recurrence to be spared extended endocrine therapyThe results of the TransATAC and ABCSG8 studies provide Level 1 evidence for the clinical validity of the PAM50 testThe nCounter-PAM50 Gene Signature Assay based risk groups in node-negative and node-positive patients provide clinically meaningful information to inform treatment decisions.
50 GEICAM Spanish Breast Cancer Group Decision Impact Study Prosigna changed the treatment decision in 20% of cases--94% of physicians were confident with the prognosis--93% of physicians were confident with the intended treatment
51 ConclusionsProsigna has successfully undergone rigorous analytic validationHighly reproducible and suited for decentralized testingProsigna has been clinically validated in 2 large trials of adjuvant endocrine therapy (TransATAC and ABCSG-8)The results of the TransATAC and ABCSG8 studies provide Level 1 evidence for the clinical validity of the PAM50 test.Prosigna Score provides more prognostic information in endocrine treated patients than RS, with better differentiation of intermediate and high risk groups.Prosigna Score has strong prognostic information in years 5-10, which may help select patients who could benefit most from hormonal therapy beyond 5 years of treatment.The nCounter-PAM50 Gene Signature Assay is based on a robust and reproducible analytic platform and process that provides meaningful information for determining treatment selection in patients with early stage, hormone-receptor–positive breast cancer.The modular algorithm (intrinsic subtype, proliferation score, clinical characteristics) may potentially be retrained/adapted to inform other types of treatment decisions in breast cancer.