GA

TA

GC

GA

CG

AT

C-

GA

AA

GA

AG

TT

A

++

++

+

+

++

+PGR

GA

TA

GC

GA

CG

AT

C-

GA

AA

GA

AG

TT

A+

+

+

+ERBB2

GA

TA

GC

GA

C

GA

TA

GC

GA

CG

AT

C-

GA

AA

GA

AG

TT

A

+++

+ESR1

++

++

MKI67

molecular diagnostic test for quantitative determination of breast cancer biomarkers ER, PR, HER2, Ki-67 mRNA expression for any laboratory.

Innovation for your breast cancer diagnostics

High-performance

2 3

Breast Cancer Subtypes ER PR HER2 Ki-67

Luminal A-like pos pos neg neg

Luminal B-like (HER2 negative) pos pos/neg+ neg pos/neg+

Luminal B-like (HER2 positive) pos pos/neg pos pos/neg

HER2 positive (non-luminal) neg neg pos pos/neg

Triple negative (ductal) neg neg neg pos/neg

3

Molecular information drives treatment choices in breast cancer

Goldhirsch A et al., Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Annals of Oncology 2013; 24: 2206-2223Kreipe H, Nitz U, Klinische Pathologie des Mammakarzinoms. Der Gynäkologe 2016; 49:737-745 Luporsi E et al., Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review. Breast Cancer Res. Treat 2012; 132(3):895-915 Noske et al., Comparison of different approaches for assessment of HER2 expression on protein and mRNA level: prediction of chemotherapy response in the neoadjuvant GeparTrio trial. Breast Cancer Res. Treat 2011; 109-17 RT-qPCR = Reverse transcription quantitative real-time PCR

Definition of Breast Cancer Surrogate Subtypes (St Gallen 2013)

*with the exception of the combination PR pos and Ki-67 neg = Luminal A-like

MammaTyper® precisely determines mRNAexpression of ER, PR, HER2 and Ki-67

Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and the marker of proliferation Ki-67 are key biomarkers in the evaluation of breast cancer tumors

The combination of the biomarker results allows the assessment of the different St Gallen subtypes, which are a key parameter for treatment decisions

Ki-67 is a prognostic and predictive marker. Analytical challenges like high observer variability hinder its standardized and reproducible determination

Quantitative RT-qPCR assay (CE marked IVD)

› Highly reproducible biomarker assessment

› Reliable results through standardized biomarker detection

› Accurate stratification of breast cancer tumors into St Gallen subtypes

Clinical value validated in numerous performance evaluation studies

› Outperforms IHC by accurate Ki-67 determination

› Provides information on patient‘s prognosis

› Accurate subtyping supports treatment decisions

› Reliable method for any molecular pathology laboratory

› Validated for multiple qPCR instruments*

› From resection or core needle biopsy FFPE sample to result within 6 hours

High-performance test

Promising clinical utility

Easy-to-use

1.

2.

3.

MammaTyper® Key Characteristics:

MammaTyper®‘s RT-qPCR technology has the following accepted advantages:

Standardized performance and fast turn-around time

Minimized inter- and intra-laboratory variability

Quantitative results with wide dynamic range

* Validated RT-qPCR instruments: Roche cobas z® 480 Analyzer, Roche LightCycler® 480 II, Applied Biosystems® 7500 Fast (Dx), Siemens Versant® kPCR Cycler, Bio-Rad CFX96®, Agilent Technologies Mx3000PFFPE = formalin fixed paraffin embeddedLaible M et al., Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer 2016; DOI: 10.1186/s12885-016-2476-xWirtz RM et al., Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry. Breast Cancer Res Treat 2016; 157(3), 437-446Varga Z et al., An international reproducibility study validating the quantitative determination of ERBB2, ESR1, PGR and MKI67 mRNA in breast cancer using MammaTyper®. Breast Cancer Research 2017; 19:55: DOI 10.1186/s13058-017-0848-zSinn HP et al., Comparative analysis of quantitative IHC with automated scoring versus reverse transcription quantitative real-time PCR on FFPE tissue samples for the assessment of ER, PR and Ki-67 labeling index and the prediction of pathological complete response in breast cancer. BMC Cancer 2017; 17:124

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MammaTyper® cut-offs classify biomarker values into positive or negative results. Dichotomized biomarker results enable stratification into subtypes.

MammaTyper® mRNA expression results correlate very well to quantitative IHC values.

Precise and reproducible biomarker assessment with MammaTyper®

MammaTyper® cut-offs are validated based on clinical outcome

MammaTyper® results express a wider dynamic range than IHC

Precise and highly reproducible biomarker results through standardized assessment

MammaTyper® enhances breast cancer biomarker

assessment

Laible M et al., Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantificationof ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer 2016; DOI: 10.1186/s12885-016-2476-xWirtz RM et al., Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry. Breast Cancer Res Treat 2016; 157(3), 437-446Scatter plot based on in-house data

Gene nomenclature ERBB2 = HER2, ESR1 = ER, PGR = PR, MKI67 = Ki-67Values in the ranges colored in light blue/orange have been observed in a cohort of 752 breast cancer samples. Values in the ranges colored in dark blue/orange have not yet been observed but are still validGoldhirsch A et al., Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Annals of Oncology 2013; 24: 2206-2223

MammaTyper® provides guidance for treatment decisions of breast cancer patients

5

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Results enable accurate molecular subtyping of tumor tissue according to St Gallen guidelines

MammaTyper® provides quantitative results reflecting the degree of mRNA expression per biomarker

Validated cut-offs are used to determine the positivity or negativity of the biomarker

Quantitative gene expression reportMammaTyper® results provide a quantitative measure for each biomarker

Example: Scatter plot shows quantitative MammaTyper® PGR values vs. quantitative IHC PR values

Qu

antit

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90

80

70

60

50

40

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20

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MammaTyper® Cut-off

IHC Cut-off

MammaTyper® PGR values (40-∆∆Cq)

27 29 31 33 35 37 39 41 43 4525

6 76 7

Varying tumor cell content has minimal influence on MammaTyper® performance*

Fluctuating tumor cell content (TCC) could possibly affect the validity of quantitative assessment of ER, PR, HER2 and Ki-67. Therefore, the performance of MammaTyper® was investigated under different scenarios of TCC.

Wirtz RM et al., Low influence of tumor cell content on mRNA expression levels of ERBB2, ESR1, PGR and MKI67 when performing the MammaTyper® RT-qPCR kit. Poster SABC 2014 Laible M et al., Technical validation of an RT-qPCR in vitro diagnostic test system for the determination of breast cancer molecular subtypes by quantification of ERBB2, ESR1, PGR and MKI67 mRNA levels from formalin-fixed paraffin-embedded breast tumor specimens. BMC Cancer 2016; DOI: 10.1186/s12885-016-2476-x* shown for HER2 negative tissue samples with TCC > 20 %; DCIS = ductal carcinoma in situ

----- Cut-off Non enriched (low TCC 5 – 50 %) Enriched by macrodissection (high TCC > 80 %)

40-∆∆C

q

ERBB2

1 2 3 4 5 6 7 8 9

40-∆∆C

q

PGR45

40

35

30

25

1 2 3 4 5 6 7 8 91 2 3 4 5 6 7 8 9

ESR145

40

35

30

25

45

40

35

30

25

1 2 3 4 5 6 7 8 9

MKI6745

40

35

30

25

Sample pair number

Sample pair number

Sample pair number

Sample pair number

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MammaTyper® results of paired tumor samples with high TCC (> 80 %) derived by macrodissection and low TCC (5 – 50 %) including varying DCIS* content (10 – 70 %)

Binary biomarker results ERBB2 ESR1 PGR MKI67

Kappa values 1.00 0.91 0.94 0.94

Quantitative biomarker results ERBB2 ESR1 PGR MKI67

ICC 0.987 0.992 0.998 0.98o

Varga Z et al., An international reproducibility study validating the quantitative determination of ERBB2, ESR1, PGR and MKI67 mRNA in breast cancer using MammaTyper®. Breast Cancer Research 2017; 19:55: DOI 10.1186/s13058-017-0848-z ICC = Interclass Correlation Coefficient

Low inter-site variance of quantitative single biomarker results is demonstrated by excellent ICC* values ≥ 0.98:

Excellent inter-site agreement of binary single biomarker classification (positive/negative) is represented by high Kappa values:

Determination of breast cancer subtypes shows a high level of agreement across all sites (Kappa = 0.90)

MammaTyper® Reproducibility Study results

MammaTyper® International Multicenter Reproducibility Study

has evaluated the inter- and intra-site reproducibility of the quantitative detection of ERBB2, ESR1, PGR and MKI67 mRNA expression in clinical samples

10 different sites in Europe, North America and Asia

Standardized application training

Locally and centrally extracted total RNA of 24 clinical FFPE samples

Assessment of the precision of the test under different conditions: Laboratories, operators, instruments, days and lots

Despite varying tumor cell content, MammaTyper® results for HER2, ER, PR and Ki-67 revealed a high level of concordance between low TCC and high TCC samples

Macrodissection of FFPE samples with a tumor cell content > 20 % is not required for gene expression analysis using MammaTyper®

MammaTyper® is highly reproducible – reducing inter- and intra- laboratory variations and allows e.g. standardization of Ki-67 assessment

New study results 2017

MammaTyper® International Multicenter Study demonstrates excellent reproducibility

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MammaTyper® is a reliable and accurate test for any molecular pathology laboratory

MammaTyper® is an easy-to-use test delivering precise results within 6 hours

Sample preparation

10 µm FFPE tissue section (tumor cell content > 20 %)

RNA extraction

Use of RNXtract® is recommended for RNA extraction.

MammaTyper® test set up

Preparation of mastermixes and distribution on 96 well plate.

Analysis of up to 8 patient samples per run.

Data processing and reporting

Export of mRNA expression data

Calculation and assessment of results

Results provided within 6 hours

RT-qPCR analysis

Validated on the following qPCR instruments:

Roche cobas z® 480 Analyzer

Roche LightCycler® 480 II

Applied Biosystems® 7500 Fast (Dx)

Siemens Versant® kPCR Cycler

Bio-Rad CFX96® (IVD, non-deep well)

Agilent Technologies Mx3000P

MammaTyper® Kit Facts

Designed for 10 determinations (max. 8 patient samples)

Easy-to-run assay protocol

Reduced hands-on time for pathologists

MammaTyper® delivers results from FFPE sample to report within 6 hours

RNXtract®

RNA extraction

MammaTyper®

Simultaneous assessment of all 4 biomarkes

Manual steps (hands-on time)

Walk away time

Pathologist time

8:00 9:00 10:00 11:00 12:00 13:00 14:00

RNXtract® is an easy to perform and robust procedure for the extraction of highly purified total RNA for RT-qPCR applications like MammaTyper®MammaTyper® and RNXtract® are registered trademarks of BioNTech Diagnostics GmbH

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MammaTyper® delivers consistent treatment guidance supported by accurate MKI67 determination

Comparison of Ki-67 expression determined by MammaTyper® and IHC

Wirtz RM et al., Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry. Breast Cancer Res Treat 2016; 157(3), 437-446Figure modified acc. to Wirtz et al., Breast Cancer Res Treat. 2016DDFS = Distant disease free survival *see page 12

0 2 4 6

Time to distant recurrence (years)

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MKI67 negative/MammaTyper®

MKI67 positive/MammaTyper®

Ki-67 negative/IHCKi-67 positive/IHC

0,20

0.10

0

MammaTyper®: HR = 0.42 (p = 0.001)IHC: HR = 0.56 (p = 0.005)

5

Precise Ki-67 evaluation provides prognostic value for patient outcomes

Favorable DDFS is independently associated with low MKI67 mRNA expression determined by MammaTyper®

Determination of MKI67 by MammaTyper® delivers extended information on patient‘s risk of developing distant metastases based on validated cut-off

MammaTyper® allows accurate biomarker assessment

Clinical performance evaluation: MammaTyper® FinHer study Concordance of MammaTyper® results with IHC/CISH based standard diagnostic methods was evaluated using 769 tissue samples obtained within the FinHer trial.

Patients: Node positive or high risk node negative invasive breast cancer.

FinHer trial design: The trial evaluated the efficacy of combining FEC with Docetaxel vs. Vinorelbine. Patients with HER2 positive tumors were also assigned to receive or not receive Trastuzumab.

Wirtz RM et al., Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry. Breast Cancer Res Treat 2016; 157(3), 437-446. Joensuu H et al., Fluorouracil, Epirubicin, and Cyclophosphamide With Either Docetaxel or Vinorelbine, With or Without Trastuzumab, As Adjuvant Treatments of Breast Cancer: Final Results of the FinHer Trial. J Clin Oncol 2009; 27:5685-5692. Polley et al., An international study to increase concordance in Ki67 scoring. Modern Pathology 2015; 28, 778-786.

Assessment of ER, PR and HER2 by MammaTyper® correlated well with results obtained by IHC and CISH

As expected, Ki-67 shows moderate concordance between the IHC and MammaTyper® results due to known technical limitation in standardization of Ki-67 IHC assessment

MammaTyper® results show a high degree of concordance with IHC/CISH for ER, PR and HER2

ESR1 (ER) PGR (PR) ERBB2 (HER2) MKI67 (Ki-67)

Concordance 91.8 % 660/719 82.5 % 593/719 91.8 % 660/719 75.0 % 516/688

PPA 95.9 % 490/511 93.2 % 368/395 85.9 % 140/163 89.1 % 369/414

NPA 81.7 % 170/208 69.4 % 225/324 93.5 % 520/556 53.7 % 147/274

Kappa statistic 0.80 0.75 – 0.85 0.64 0.58 – 0.70 0.77 0.72 – 0.83 0.45 0.38 – 0.52

p < 0.0001 p < 0.0001 p < 0.0001 p < 0.0001

PPA Positive percent agreement, NPA Negative percent agreement

Concordance between MammaTyper® and IHC/CISH-based biomarker assessments

Clinical outcome proves that Ki-67 determination by MammaTyper® is superior to IHC*

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Triple negative (ductal)14.0 %n = 91

Luminal B-like (HER2 negative)

36.1 %n = 234

Luminal B-like

(HER2 positive)10.9 %n = 71

HER2 positive

(non- luminal)10,8 %n = 70

Luminal A-like28.2 %n = 183

Subtype defined by MammaTyper®

12 13

MammaTyper® results ensure precise determination of breast cancer subtypes correlated with clinical outcome

Concordance of molecular surrogate subtypes defined by MammaTyper® and IHC (FinHer* study)

Wirtz RM et al., Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry. Breast Cancer Res Treat 2016; 157(3), 437-446* FinHer results reclassified according to St Gallen classification

Accurate MKI67 assessment by MammaTyper® has substantial impact on distinction between Luminal A- and B-like breast cancers.

MammaTyper® luminal subtypes correlated with FinHer* clinical outcome data, thus proving the accuracy of MammaTyper® results

Wirtz RM et al., Biological subtyping of early breast cancer: a study comparing RT-qPCR with immunohistochemistry. Breast Cancer Res Treat 2016; 157(3), 437-446 * shown for Luminal B-like (HER2 negative) patientsFinHer results reclassified according to St Gallen classification, OS = Overall survival

Subtype defined by IHC/CISH

Reclassification by MammaTyper® Reclassification by MammaTyper®

Reclassification of all defined subtypes by MammaTyper®

Luminal A-like

Luminal B-like (HER2 positive)

Luminal B-like (HER2 negative)

HER2 positive (non-luminal)

Triple negative (ductal)

By precise subtyping, MammaTyper® results support selection of appropriate treatment strategy for each patient

Hypothesis: MammaTyper® might open up new opportunities of providing predictive information about the benefit of adjuvant Taxane-based treatment

Triple negative (ductal)12.9 %n = 84

Luminal B-like (HER2 negative)

42.8 %n = 278

Luminal B-like

(HER2 positive)12.5 %n = 81

HER2 positive

(non- luminal)

9.9 %n = 64

Luminal A-like21.9 %n = 142

4.4 %n = 8

2.1 %n = 5

5.6 %n = 13

Comparison of OS and different treatment regimens of Luminal A-like and Luminal B-like (HER2 negative) patients stratified by MammaTyper® or IHC

Lum. B-like (HER2 neg) Docetaxel Lum. B-like (HER2 neg) Vinorelbine Luminal A-like Docetaxel Luminal A-like Vinorelbine

Luminal B-like (HER2 negative) Docetaxel vs. Vinorelbinep = 0.012 HR = 0.31

Luminal B-like (HER2 negative) Docetaxel vs. Vinorelbinep = 0.350 HR = 0.63

Lum. B-like (HER2 neg) Docetaxel Lum. B-like (HER2 neg) Vinorelbine Luminal A-like Docetaxel Luminal A-like Vinorelbine

MammaTyper® IHC

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Time to death (years)

0.3

0.2

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Time to death (years)

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Patient stratification based on MammaTyper® shows improved OS of the Luminal B-like (HER2 negative) patients receiving Docetaxel-based treatment compared to those receiving Vinorelbine

By accurate stratification of patients into Luminal A-like and Luminal B-like (HER2 negative) subtypes using MammaTyper®, patient groups that might benefit from Docetaxel-based treatment can be revealed

Classification of the patients in Luminal B-like (HER2 negative) subtype by IHC did not reveal a clear separation in responders and non-responders to a Docetaxel- based treatment

Hypothesis-generating data: MammaTyper® predicts benefit from Taxane treatment* by accurate distinction of molecular subtypes

Patients classified as Luminal B-like (HER2 negative) by MammaTyper® show benefit from Taxane-based chemotherapy.

Luminal B-like (HER2 negative)

74.4 %n = 174 Luminal A-like

18.0 %n = 42

Luminal B-like (HER2 negative)

41.5 %n = 76

Luminal A-like53.6 %n = 98

0.6 %n = 1

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Sinn HP et al., Comparative analysis of quantitative IHC with automated scoring versus reverse transcription quantitative real-time PCR on FFPE tissue samples for the assessment of ER, PR and Ki-67 labeling index and the prediction of pathological complete response in breast cancer. BMC Cancer 2017; 17:124 Box plots based on in-house data

Comparison of MammaTyper® and IHC measurements: Patients responding or not responding to neoadjuvant chemotherapy

Stratification of patients for their probability of achieving a pCR with 100 % sensitivity resulted in a specificity of 52 % using MammaTyper® MKI67 and a specificity of only 7 % using Ki-67 IHC

MammaTyper® MKI67 assessment enables a significant differentiation into groups of responders (pCR) and non-responders (no-pCR) to Taxane-based neoadjuvant chemotherapy

No significant differentiations of the two groups were possible using IHC for Ki-67 determination

MammaTyper® outperforms IHC in predicting pCR in the neoadjuvant setting

Hypothesis: MammaTyper® identifies those patients who are likely to benefit from Taxane-based neoadjuvant chemotherapy based on accurate determination of MKI67

Hypothesis-generating data: Predictive value of MammaTyper® in neoadjuvant setting – first findings

Clinical performance evaluation: MammaTyper® 1st Neoadjuvant StudyConcordance between MammaTyper® and vIHC*/qIHC* results (FFPE samples from 83 core needle biopsies of patients with primary invasive breast cancer)were evaluated as well as the predictive value of Ki-67 assessment by MammaTyper® in comparison to IHC.

Patients: Patients with operable (T2-T4/N0-2/M0) breast cancer eligible for neoadjuvant chemotherapy.

SO80 trial design: Patients were randomized to receive sequential Anthracycline/Taxane-based regimens containing either Pemetrexed or Cyclophosphamide in combination with Epirubicin.

Sinn HP et al., Comparative analysis of quantitative IHC with automated scoring versus reverse transcription quantitative real-time PCR on FFPE tissue samples for the assessment of ER, PR and Ki-67 labeling index and the prediction of pathological complete response in breast cancer. BMC Cancer 2017; 17:124 Schneeweiss et al., A randomized phase II trial of doxorubicin plus pemetrexed followed by docetaxel versus doxorubicin plus cyclophosphamide followed by docetaxel as neoadjuvant treatment of early breast cancer. Annals of Oncology 2011; 22: 609-617* vIHC = visual immunohistochemistry *qIHC = quantitative immunohistochemistry

The predictive clinical claim is currently under further validation in the MammaTyper® 2nd and 3rd Neoadjuvant Study.

MammaTyper® has the potential to predict the probability of neoadjuvant chemotherapy benefit

Proliferative activity of the tumor guides clinical therapy management in primary breast cancer. In the neoadjuvant setting, higher Ki-67 values are consistently associated with higher rates of histologically proven pathological complete response (pCR) to chemotherapy.

Diagnostic accuracy MammaTyper® IHC

Sensitivity [%] 100 100

Specificity [%] 52 7

Ki-

67

vIH

C [%

po

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80

60

40

20

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no-pCR pCR

IHCn = 53

MK

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0-ΔΔ∆∆C

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40

39

38

37

36

35

no-pCR pCR

MammaTyper®

n = 59

p = 0.002 p = 0.106

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Service for Germany:BioNTech Diagnostics GmbH An der Goldgrube 12 55131 Mainz, Germany

Tel: +49 6131 9084 2001Fax: +49 6131 9084 39 2001E-Mail: service@sales.biontech.de

Visit us online:+ biontech.de + mammatyper.com

Precise quantitative results for mRNA expression of HER2, ER, PR and Ki-67

Outperforms IHC by accurate Ki-67 determination

Accurate and reliable test to stratify breast cancer into surrogate subtypes acc. to St Gallen

Highly reproducible results with extremely low inter-/intra-laboratory variation

Clinical value has been validated in numerous performance evaluation studies

Extended information on patient‘s prognosis

Accurate subtyping supports treatment decisions

Reliable method for any pathology laboratory

Easy-to-use test which allows results within 6 hours

High-performance

Reproducible

Validated

Prognostic

Predictive

Optimized

Easy-to-use

To order MammaTyper® or for further information, please contact your local distributor:

Innovation for your breast cancer diagnostics

150

529

-01-

EN

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v. 2

.0

All scientific and technical information in this brochure is based on the MammaTyper® Instructions for Use Rev. 3.1 and Wirtz et al., Breast Cancer Res Treat. 2016; 157(3) 437-446; Laible et al., BMC Cancer 2016; DOI: 10.1186/s12885-016-2476-x; Varga Z et al., Breast Cancer Research 2017; 19:55: DOI 10.1186/s13058-017-0848-z; Sinn et al., BMC Cancer 2017; 17:124