Relevancia práctica de la clasificación de subtipos intrínsecos en cáncer de mama

Miguel Martín

Instituto de Investigación Sanitaria

Gregorio Marañón

Universidad Complutense

Madrid

The new technologies have changed our

understanding of breast cancer

XIX century 1980s 1990s

morphology/ histology single genes

multiple genes

XXI century

DNA/RNA arrays

SNP analysis

Multiplex PCR

NGS TECHNOLOGY

IHC FISH HE

Molecular portraits of human breast tumors

Perou CM et al, Nature 406:747,2000

The intrinsic subtype classification

doi:10.1038/nature11412

Comprehensive molecular portraits of human breast tumors

The Cancer Genome Atlas Network

Gen Mutado

TP53 187 (37%)

PIK3CA 180 (36%)

GATA3 54 (11%)

MAP3K1 39 (8%)

MLL3 37 (7%)

CDH1 33 (6.5%)

MAP2K4 21 (4%)

RUNX1 18 (3.5%)

PTEN 17 (3.4%)

TBX3 13 (2.5%) Integration of information across 5 platforms confirmed

the existence of 4 main breast cancer classes

The Oncologist 2015;20:474–482

Conclusion

Significant discordance remains between clinical assay-defined subsets and intrinsic subtype.

The Oncologist 2015;20:474–482

Distribution of PAM50 intrinsic subtype across IHC-based biomarkers (N=1396, Both Centrally Determined)

PR

ER

Data from: TAMseries (CCR 2010), GEICAM 9906 (JCO 2013) and GEICAM 2012-09 (CMRO 2015)

N % N % N %

LumA 93 48% 378 53% 267 58%

LumB 100 52% 333 47% 196 42%

0-10% 11-90% 91-100%

N % N % N %

LumA 243 42.1% 347 58% 160 73%

LumB 334 57.9% 249 42% 59 27%

0-10% 11-90% 91-100%

30-40%??

N % N % N % N %

LumA 620 70.1% 112 34% 28 20% 4 10%

LumB 265 29.9% 219 66% 112 80% 36 90%

>30%0-10% 11-20% 21-30%Ki-67

Cortesy: A. Prat

The Oncologist 2013;18:123–133

Conclusions

The standard immunohistochemical panel for breast cancer (ER, PR, and HER2)

does not adequately identify the PAM50 gene expression subtypes.

Bastien et al. BMC Medical Genomics 2012, 5:44

Plataformas Genómicas en Cáncer

de Mama

Oncotype Dx (Genomic Health, 21 genes)

Mammaprint (Agendia, 70 genes)

ProsignaTM (Nanostring, 50 genes-PAM50)

EndoPredict (Sividon, 12 genes)

Map-Quant Dx (Ipsogen, 97 genes)

Breast Cancer Index/Theros (Biotheranostics,

2 genes)

Genomic platforms:potenial clinical

applications in breast cancer

prognostication

prediction of

response to

hormones

prediction of

response to

chemotherapy

Prediction of

response to

specific CT drugs

Prediction of

response to

targeted therapies

Genomic platforms:potenial clinical

applications in breast cancer

prognostication

Oncotype DX® : B-14 Results – Distant

Recurrence

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 2 4 6 8 10 12 14 16

Years

P <0.001

RS <18 n = 338

RS 18-30 n = 149

RS 31 n = 181

Paik et al. N Engl J Med. 2004;351:2817-2826.

Pro

po

rtio

n w

ith

ou

t D

ista

nt

Rec

urr

ence

Riesgo de recurrencia a los 10 años •Bajo riesgo (6.8%) •Riesgo intermedio (14.3%) •Alto riesgo (30.5%)

78 breast tumors

Age < 55 years, Tumor size < 5 cm

Lymph node negative & No adjuvant therapy

No distant metastases

for at least 5 years

Distant metastases

within 5 years

van‘t Veer L et al., Nature, 2002; Van de Vijver M et al; N Engl J Med 347:1999,2002

CLASSIFICATION THRESHOLD

Low Risk Signature

High Risk Signature

Mammaprint

43%

Mammaprint: TRANSBIG Validation

Results

Buyse et al (2006) J Natl Cancer Inst 17;1183-1192

15%

Martin et al., Breast Cancer Res Treat (2016) 156:81–89

EP Score 92% MFS

EPclin Score 100% MFS

ABCSG-8 trial

Genomic platforms:potenial clinical

applications in breast cancer

prognostication

prediction of

response to

hormones

Tamoxifen Benefit and Oncotype DX™

Design

Objective: Determine whether the 21-gene RS assay provides predictive information for patients who were treated with tamoxifen (likelihood of recurrence)

NSABP B-14 Tam Benefit Study in N–, ER+ Patients

Randomized

Placebo-Eligible

Tam-Eligible

Paik et al. ASCO 2004. Abstract #510.

B-14 Benefit of Tamoxifen

By Recurrence Score Risk Category

B-14 Benefit of Tamoxifen

By Recurrence Score Risk Category

Prognostic value of PAM50 and risk of recurrence score in patients

with earlystage breast cancer with long-termfollow-up

Ohnstad et al. Breast Cancer Research (2017) 19:120

Observational Oslo1 study (1995–1998)

Prognostic value of PAM50 and risk of recurrence score in patients

with earlystage breast cancer with long-term follow-up

Ohnstad et al. Breast Cancer Research (2017) 19:120

Genomic platforms:potenial clinical

applications in breast cancer

prognostication

prediction of

response to

hormones

prediction of

response to

chemotherapy

Prognostication and prediction are linked

in ER+/HER2- breast cancer

Chemotherapy Benefit and Oncotype DX®

Randomized

Tam + MF

Tam + CMF

Tam

NSABP B-20

Paik et al. J Clin Oncol. 2006;24:3726-3734.

High Recurrence Score® result correlates with

greater benefit from chemotherapy (NSABP B-20)

Overall, 4.4% absolute benefit from tamoxifen + chemotherapy

Paik S, et al. J Clin Oncol. 2006;24:3726-3734.

Paik S, et al. J Clin Oncol. 2006;24:3726-3734.

HIGH RS (>30) INTERMEDIATE RS GROUP

Recurrence Score 18-30

High Recurrence Score® result correlates with

greater benefit from chemotherapy (NSABP B-20)

LOW RS GROUP

Recurrence Score <18

Overall, 4.4% absolute benefit from tamoxifen + chemotherapy

28% absolute benefit

Number of Patients Needed to Treat (NNT) to Avoid a Distant

Recurrence with tamoxifen + CT vs tamoxifen alone (NSABP B-20)

Population

Distant Recurrence Rate with

tamoxifen

Distant Recurrence Rate with

tamoxifen + chemotherapy

All patients 12% 8%

High RS 40% 12%

NNT

22.7

3.6

Pathologic complete response to neoadjuvant

chemotherapy differs by subtype

T-FAC1

(N=82)

AC-T2

(n=107)

Luminal A/B 2/30 (7%) 4/62 (7%)

Normal-like 0/10 (0) NA

HER2+/ER- 9/20 (45%) 4/11 (36%)

Basal-like 10/22 (45%) 9/34 (26%)

P<0.001

1Rouzier R, Clin Cancer Res 2005; 2Carey LA, Clin Cancer Res, 2007

P=0.003

Genomic platforms: potential clinical

applications in breast cancer

prognostication

prediction of

response to

hormones

prediction of

response to

chemotherapy

Prediction of

response to

specific CT drugs

Prediction of

response to

targeted therapies

Responsiveness of Intrinsic Subtypes to Adjuvant Anthracycline

Substitution in the NCIC.CTG MA.5 Randomized Trial

Premenopausal N+

(n=710)

CMFx6

CEFx6

Levine MN, et al. J Clin Oncol. 2005;23:5166;.

Responsiveness of Intrinsic Subtypes to Adjuvant Anthracycline

Substitution in the NCIC.CTG MA.5 Randomized Trial

Premenopausal N+

(n=710)

CMFx6

CEFx6

Levine MN, et al. J Clin Oncol. 2005;23:5166; Cheang M et al, Clin Cancer Res 18:2402.

44,7%

11,7%

30,9%

12,8%

pCR

RCB-I

RCB-II

RCB-III

Respuesta global (Symmans)

Isabel Echavarría, Tesis Doctoral, UCM 2017

83%

13%

1% 3%

Distribución subtipo intrínseco

Basal

HER2E

LumB

Normal

Respuesta a quimioterapia neoadyuvante con docetaxel+carboplatino

en cáncer de mama triple negativo (n=96)

44,7%

11,7%

30,9%

12,8%

pCR

RCB-I

RCB-II

RCB-III

Respuesta global (Symmans)

Isabel Echavarría, Tesis Doctoral, UCM 2017

83%

13%

1% 3%

Distribución subtipo intrínseco

Basal

HER2E

LumB

Normal

Respuesta a quimioterapia neoadyuvante con docetaxel+carboplatino

en cáncer de mama triple negativo

51,30%

12,50%

10,30%

18,80%

29,50%

37,50%

9,00%

31,30%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Basal No-basal

pCR RCB-I RCB-II RCB-III

p=0,007

Genomic platforms:potenial clinical

applications in breast cancer

prognostication

prediction of

response to

hormones

prediction of

response to

chemotherapy

Prediction of

response to

specific CT drugs

Prediction of

response to

targeted therapies