Axilla staging and

Molecular Tumour Biology

Florence Godey f.godey@rennes.unicancer.fr

Hamburg , 26 February 2017

RSU = +0.47 x GRB7group score -0.34 x ERgroup score +1.04 x prolif group score +0.10 x invasion group score +0.05 x CD68 - 0.08 x GSTM1 - 0.07 x BAG1

RS = 20x(RSU-6.7) if 0≤RSU≤100RS=0 if RSU<0 RS=100 if RSU>100.

GRB7 group score = 0.9 x GRB7 +0.1x HER2 (if the result is less than 8, then the GRB7 group score is considered 8)

ER group score = (0.8 x ER +1.2 x PGR + BCL2 + SCUBE2 )÷4

proliferation group score = (Survivin + KI67 + MYBL2 + CCNB1 + STK15 )÷5 (if the result is less than 6.5, then the proliferation group score is considered 6.5)

invasion group score = (CTSL2 + MMP11 )÷2

Molecular tumour analysis, What is it?:(ex : oncotype DX)

RT-PCR 447 patients (3 groups)

1) Test development

Selection of 250 gènes

algorithme conception to determinate a score

correlated with recurrence = reccurent

score RS

2) Test validation/ routine use

Paik et al, 2004, NEJM

Biological step Mathematical step

Many molecular signatures….

Name SocietyBCI (Breast Cancer Index) BioTheranostic

Endopredict MyriadGenomic Grade Index (GGI)

(MapQuant Dx)Ipsogen

Mammaprint AgendiaOncotype DX Genomic Health

Prosigna (PAM50) NanostringRotterdam signature

(ROT76) ------

Mammaprint Oncotype Dx Prosigna (PAM 50)

Endopredict

Année de développement

2002 2004 2009 2011

Mode d’élaboration du test

Population étudiée

25000 probes

70 genes T

78 (N-) (RH+/-) (<55ans)(non traitées)

250 genes

16 genes T (+ 5 de référence)

447 (N+/-) (RE+/-) (H/C)

1906 genes

50 genes (46 pour ROR) (+ 8 de reference)

189 T heterogenous 29 prlvts NT

22283 probes

8 genes T (+3 de reference)

964 (N+/-) (RE+) (HER2-)(H)

Technique Chip (centralized test)

RT-PCR (centralized test)

nCounter Dx analysis nanostring

RT-PCR Dedicated machine Myriad

Résultats MPI (Mammaprint Index) (-1…+1)

2 Categories of risk (+ borderlines) Low : >0,4 High : -1 ► - 0,4

then seuil à 0

Molecular subtypes (Blueprint, 3 classes)

RS :

3 Categories of risk Low : 0-18 Interm. : 18-30 High : 31-100

Or Low : 0-10 Interm. : 11-25 High : 26-100

ROR (46 genes + score proliferation score + tumour size)

3 Categories of risk

Molecular subtypes (4 classes)

EP (0 – 15) Epclin (EP + tumour size and N)

2 Categories of risk

Low: 1-3,2 High: 3,3 – 6

PAM50

Oncotype DX

EndoPredict

Mammaprint

10 1

3

Molecular signature, comparaison of genes included

114

62

35

6

Mammaprint (66 gènes)

PAM50 (50 gènes)

Oncotype (16 gènes)

Endopredict (8 gènes)

AA555029_RCALDH4A1 ACTR3B AURKA AZGP1AP2B1 ANLN BAG1 BIRC5BBC3 BAG1 BCL2 DHCR7

C16orf61 BCL2 BIRC5 IL6STC20orf46 BIRC5 CCNB1 MGPC9orf30 BLVRA CD68 RBBP8CCNE2 CCNB1 CTSL2 STC2

CDC42BPA CCNE1 ERBB2 UBE2CCDCA7 CDC20 ESR1CENPA CDC6 GRB7COL4A2 CDH3 GSTM1

DCK CENPF MKI67DHX58 CEP55 MMP11DIAPH3 CXXC5 MYBL2

DTL EGFR PGREBF4 ERBB2 SCUBE2ECT2 ESR1

EGLN1 EXO1ESM1 FGFR4EXT1 FOXA1FGF18 FOXC1FLT1 GPR160GMPS GRB7GNAZ KIF2C

GPR126 KRT14GPR180 KRT17GSTM3 KRT5HRASLS MAPTIGFBP5 MDM2

JHDM1D MELKLIN9 MIA

LOC100131053 MKI67LOC100288906 MLPH

LOC730018 MMP11LPCAT1 MYBL2MCM6 MYCMELK NAT1MMP9 NDC80MS4A7 NUF2MTDH ORC6LNDC80 PGRNMU PHGDH

NUSAP1 PTTG1ORC6L RRM2OXCT1 SFRP1PALM2 SLC39A6PECI TMEM45B

PITRM1 TYMSPRC1 UBE2C

QSOX2 UBE2TRAB6BRASSF7RECQL5RFC4

RTN4RL1RUNDC1SCUBE2SERF1ASLC2A3STK32BTGFB3TSPYL5UCHL5WISP1

ZNF385B

Molecular signatures, different tests

bloc ou 10 lames de 5 µM (> 30% de CT)

Ou Tissu « frais » dans milieu RNAretain

bloc ou

15 lames de 5 µM 1 lame de 10 µm

(>30% de CT)1– 6 lames de 10 µm

(>10% de CT, ≥ 20 mm2

Recommandé :100 mm2)

Mammaprint Oncotype Dx Prosigna (PAM 50)

Endopredict

Centralized analysis

Prosigna (PAM 50)

Endopredict

Molecular signatures: 2 local tests

2-3 days

4 – 6 H Technical time

Molecular signatures comparison

Mammaprint Oncotype Dx Prosigna (PAM 50) (ROR)

Endopredict (Epclin)

Low risk61% 54%

59% 62%

36% 59%

59%

Intermediate risk

28% 33% 28%

29% 24%

High risk39% 18%

8% 10%

35% 17%

41%

XX% : Bartlett et al, JNCI 2016 (236 patientes de l’essai OPTIMA) XX% : Dowsett et al, JCO 2013 (1007 patientes de l’essai ATAC) XX% : Buss et al, JNCI 2016 (928 patientes de l’essai ATAC)

Bartlett et al, 2016 JNCI

Molecular signatures: comparison ROR/RS

Comparison with 3 classes

Dowsett et al, 2013 JCO

50% de cas concordants

58% de cas concordants

Molecular signatures, comparison between two classes

Tests % concordance RéférenceMammaprint/Prosigna 78% Bartlett et al 2016

Mammaprint/Oncotype 74 % Bartlett et al 2016

Mammaprint/Oncotype 81 % Fan et al 2006

Prosigna/Oncotype 78 % Bartlett et al 2016

Prosigna/Oncotype 86 % Dowsett et al 2013

Tests % concordance RéférenceEndopredict/Oncotype 72% Buus et al 2016

Mammaprint Oncotype

PAM50 Endopredict

Advantages - Easy to use - Standardization/

centralization

- Local development - Reimbursement in France - More exchanges between

clinicians , pathologists and biologists

- Molecular classification PAM50 - Most recent Algorithms: Genes

profiling tumour size and nodes involvement are combined to

calculate the score

disadvantages - Mammaprint : 89% concordance between FFPE

and frozen tumour. - Expedition abroad - No reimbursement in

France

- few comparison between laboratories but it’s possible

Axillary metastasis and tumour size are 2 independant prognostic factors and complete tumour molecular analysis to define clinical scores !ROR (PAM50 nanostring)) !EP (Endopredict test)! EP clin Axillary metastasis and tumour size are not include to define clinical scores with all molecular signatures but remain prognostic factors!Mammaprint MPI!Oncotype

ROR PAM50 Nanostring

EP and EPclin ENDOPREDICT

Lymph nodes analysis combined with tumour molecular analysis

what have been done?

• In the retrospective validation studies Epclin or ROR score have been established with conventionnal histological analysis of SLN and NSLN ! Number of positive lymph node include macrometastasis and micrometastasis (but micrometastasis are not always research)

• Lymph nodes analysis are different for SLN and NSLN (much more exhaustive for SLN with detection of micrometastasis, but only detection of macrometastasis for NSLN)

• There is a challenge to associate OSNA standardized lymph nodes molecular analysis with molecular tumour analysis for better clinical prediction

OSNA One step nucleic Acid Amplication

– CE approved – whole node analysis possible extemporaneously – without prior isolation and purification of mRNA – After a 16 min amplification time, the CK19 mRNA copy number per µl of lysate determine the node status defined as follows:

– copy numbers <250 = no metastasis, – copy numbers 250-5000 = micrometastasis, – copy numbers >5000 = macrometastasis

– This interpretation has been validated to give the same result as histopathological intensive analysis

–> now CK19 mRNA copy numbers has to be considered as a value

OSNA :TTL

Recently, the molecular study of the SLN by OSNA generated the concept of Total Tumor Load (TTL), defined as the sum of the copy number of CK19 mRNA detected in every SLN examined, expressed as a concentration (copies/uL). !Since a TTL cut-off around 15.000 copies/uL has been proven a useful criteria to individualized axillary clearance

• TTL has been identified as the single most powerful predictor of the metastatic involvement of additional axillary lymph nodes (Peg V et al.Intraoperative molecular analysis of total tumor load in sentinel lymph node: a new predictor of axillary status in early breast cancer patients. Breast Cancer Res Treat 2013)

• TTL correlates with prognosis at 5 years of follow-up in PLUTTO Study (Peg V. et al. Analysis of total tumor load of sentinel lymph node as a prognostic factor in patients with early breast cancer. J Clin Oncol 34; 2016).

Nomogram to calculate the risk percentage of NSN positivity with the score of 2 variables OSNA CK19 mRNA copy number and tumour size

(Di Filippo et al. Journal of Experimental & Clinical Cancer Research 2015 Elaboration of a nomogram to predict non sentinel node status in breast cancer patients with positive sentinel node, intra-operatively assessed with one step nucleic acid

Fig. 3 Nomogram to calculate the risk percentage of NSN positivity. The score of each of the 2 variables are summed and reported on the total score raw, immediately below the percentage of NSN positivity is identified

Nomogram validation phase Di Filippo et al. Journal of Experimental & Clinical Cancer Research (2016) 35:193 Elaboration of a nomogram to predict nonsentinel node status in breast cancer patients with positive sentinel node,intraoperatively assessed with one step nucleic amplification: Retrospective and validation phaseThe best compromise between false negative and positive rates 31% :<31% ALND is unnecessary >31% ALND is recommended

What is the challenge with molecular technologies for LN and breast tumour assessment

• We know since a long time that breast tumour caracterize and LN involvement are prognosis factors

• To give more precision using the more pertinent technology

• By combining these new technologies it could be possible to have better prognosis

• To give answer at two major questions: – which systemic treatment for breast tumour ( Hormonotherapy 5 years or 10

years, chemotherapy) – which treatment for LN (SLN dissection only, ALND, Radiotherapy, only breast

cancer systemic treatment)

Molecular tumour analysis and molecular Lymph nodes analysis

together for better prediction

• Use of OSNA nomogram could be helpful to estimate the number of metastatic LN if no axillary clearance. This situation is more frequent since ACOZOG Z0011

• Use of TTL as an improved nodal involvement factor to redefine the ROR or EPclin thresholds and the risk groups.

• Assess the role of the Molecular tumour analysis in the prediction of non-SLN affectation, based on the TTL or nomogram obtained from the assessment of SLN(s) by OSNA.

Problems?• The price of tumour molecular signature: impossible

for all patient (in France luminal B, reimbursement)

• The price of molecular lymph node analysis could be a problem even if it’s few compare to breast molecular signature

• Considering the state of the art each country and inside each institution have to chose a strategy with many different options.

• About 600 new breast cancers each year

• OSNA for all SLN analysis, histopathological analysis (HES) for NSLN since 2007.

• Endopredict signature after multiciplinary concertation considering histopathological tumour profile, and comorbidity since december 2016

Exemples Endopredict molecular analysis for clinical prediction

• Lymph nodes involvement (N0, N1-3, N4-10, >N10) micrometastasis, macrometastasis

• Tumour size (T1ab, T1c, T2, >T3) pTNM • EP Score (12 RT PCR amplifications: AZGP1,BIRC5, DHCR7, IL6ST,

MGP, RBBP8, STC2, UBE2C, OAZ1, CALM2, RPL37A, HBB)

!EPclin Score • Two classes

• low risk <3,3 • High risk > or = 3,3

• EP clin 10 years risk = % to develop metastasis within 10 years with 5 years of endocrine treatment

Case report 1: T2 N2• 64 years • Lobular carcinoma (25mm) ! mamectomy • Estrogen receptor 30% (heterogeneity), Progesteron receptor 2% • Ki67 10% (25% biopsy) • Erb2 – • SBR II • 2 Sentinel lymph nodes analyzed with OSNA

– 13000 cp ARNm CK19/µl = Macrometastase – Negative

• 7 Non Sentinel lymph nodes: 1 with metastasis • Endopredict high risk • Multidiciplinary decision: HT, RT and CT

Case report 1: T2 N2

Simulation T2N0

Case report 1: T2 N2Simulation T1c N2

Case report 2: T1c N0

• 46 years • Bifocal ductal carcinoma (7 and 16mm)!mamectomy • ER 100%,PR 95% • Erb2 – • SBR II • Ki67 20% • 1SLN – • Endopredict low risk

Case report 2: T1cN0

Simulation T1c N1

Case report 2: T1cN0

Simulation T2 N0

Case report 3: T2 N3• 40 years old • Multifocal ductal carcinoma (37, 5 et 2mm)! pamectomy • ER 100%, PR 60% • Erb2 – • Ki67 15% • SBR II • 3 SLN:

– 300 cp ARNm CK19/µl micrometastasis – 520 000 cp ARNm CK19/µl macrometastasis – 6400 cp ARNm CK19/µl macrometastasis

• 4NSLN : – • Endopredict high risk • Multidiciplinary decision: HT, RT and CT

Case report 3 T2 N3

Simulation T2 N0

Case report 3: T2 N3

Simulation T1a N3

Case report 4: T1c N1• 78 years • Ductal carcinoma 20mm • ER 10%, PR<1% • Erb2 – • SBR III • 3 SLN ! 1 micrometastasis (HES , IHC) • Endopredict high risk !

Case report 4:T1cN1

Simulation T1a N0

Be careful !

• Good evaluation of LN, tumour size (T) are necessary to validate a good interpretation of breast molecular signatures because there are independant prognosis factors not included in molecular tumour analysis !Epclin and ROR score integrate T and LN but not RS and MPI

• A prognosis score is not a prediction of response to chemotherapy! understanding why high risk could help for treatment.

• Tumour molecular signatures validations studies don’t have been done with OSNA, if 300 cp /ul =N1 or N0 ? New cut off OSNA?

• Use tumour molecular staging when necessary in medical practice because the price don’t justify to do it in all cases (different in research protocol)

• Neverless Tumour molecular staging is more standardized to assess tumour proliferation with a panel of genes than only IHC Ki67

- Molecular technologies allow great possibilities for diagnosis and research:Tumour biology, LN molecular analysis, liquid biopsy (CTC, circulant DNA), genetic analysis…- It is a great challenging for the future But it will be necessary to develop a multidisciplinary collective strategy to well use this new technologies

—> MOTTO Study *assess the role of Tumor molecular subtypes in the prediction of non SLN affectation based on TTL *evaluate the use of TTL as an improved nodal involvement factor to redefine ROR Thresholds and risk group

• Large cohortes of patients with tumour molecular screening, good axillary staging, new treatment and clinical follow up will define the future precision medecine for breast cancer

• Finally the best will not be necessary the most expensive, if to be informed with more precise technology avoid unnecessary treatment and allow personalized medecine

! Could help

Thank you for your attention