Correlación entre la anatomía patológica y las plataformas ... · Correlación entre la...
Transcript of Correlación entre la anatomía patológica y las plataformas ... · Correlación entre la...
Correlación entre la anatomía
patológica y las plataformas
genómicas
Federico RojoFundación Jiménez Díaz
Estimation of the risk of recurrence (prognosis) and of the benefit from systemic treatments (prediction) based on combinations of clinico-pathologic risk factors :
✓ Histologic grade (and tumor type)
✓ Measures of proliferation: mitotic index (and Ki67)
✓ Tumor size
✓ Lymph node staging
✓ Breast cancer biomarkers: ER, PR, HER2
And…
✓ Multigene signatures
How get clinical decisions for breast cancer patients?
Qué información adicionalproporcionan las plataformas
genómicas sobre los parámetrosclínico-patológicos?
Paik S, et al. J Clin Oncol 2006Badve, SS et al. J Clin Oncol 2008Stemmer S et al. Presented at SABCS 2015 (Poster P5-08-02)
Significant proportion of high-grade tumors (13-25%)
have low RS
ECOG2197 trial, n=776
prospective, randomized, clinical trial that included 2,872 assessable patients with HRbreast cancer and 0 to 3 positive lymph nodes.protocol specified treatment with four 3doxorubicin (60 mg/mcyclophosphamidemg/mmg/mtherapy if HR positive
NSABP B-20
1. Histological grade: Correlation between Grade and RS
194 (67%
)
90 (31%)
6 (2%)
524 (51%)
404 (39%)
98 (10%
)
85 (25%)
159 (47%)
94 (28%
)
Clalit, n=2028
Clark, BZ et al. Appl Imm Mol Morphol 2013Khoury, T et al. Appl Imm Mol Morph 2016
1. Histological grade: Correlation between Grade and RS
N=1074
Reproducibility performance of pre- and
post-educational evaluations
Paradiso, A et al. J Clin Pathol 2009
term
-
reproducibility versus the
shows the 25th and 75th
limits of the two whiskers
1. Histological grade: Correlation between Grade and RS
Educational evaluations improve Grade reproducibility
Gluz, O. J Clin Oncol 2016
PlanB: Grade assesment by local and
central pathology lab
Overall agreement in HR+ disease 66%
Re
pro
du
cib
ility
pe
rfo
rman
ce
Bomeisl, PE et al. Arch Pathol Lab Med 2015
n=184
2. Tumor type: Correlation between histology and RS
Conlon, N et al. Breast J 2015Tsai, ML et al. Clin Breast Can 2016
Lobular carcinoma
2. Tumor type: Correlation between histology and RS
NSABP B-20
A significant proportion of small tumors have high RS (6-16%)
3. Tumor size: Correlation between size and RS
Paik S, et al. J Clin Oncol 2006Stemmer S et al. Presented at SABCS 2015 (Poster P5-08-02)
Clalit, n=2028
Badve, SS et al. J Clin Oncol 2008
ECOG2197 trial
4. Hormonal receptors: Correlation between ER/PgR and RS
Good correlation between ER/PgR IHC and OncotypeDX
93% concordance 88% concordance
Cheang, MCU et al. Oncologist 2015
N=1557 (GEICAM9906, NCIC CTG MA.5, NCIC CTG MA.12)
ER and PgR staining (%) distributed by intrisic subtypes
4. Hormonal receptors: Correlation between ER/PgR and PAM50 subtype
ER: Pearson’s correlation: 0.68; 95%CI: 0.66–0.71; p=.0001PgR: Pearson’s correlation: 0.59;95%CI: 0.56–0.62; p=.0001
Prat, A et al. J Clin Oncol 2013Clark, BZ et al. Appl Imm Mol Morphol 2013
4. Hormonal receptors: Correlation between PgR and PAM50 subtype
20% of PgR IHC staining correlates with Luminal B phenotype
Perez, EA et al. Breast Can Res 2015
Alliance N9831 trial (Phase III adjuvant trastuzumab trial)
5. HER2 status: Correlation between HER2 amplification and OncotypeDX
Prat, A et al. JNCI 2013
5. HER2 status: Correlation between HER2 and PAM50
Distribution of intrinsic subtypes in HER2 clinical status
Reis-Filho, JS & Pusztai, L. Lancet 2011 Liebermann, N. et al. ESMO 2011
N=2477
6. Proliferation: Correlation between Ki67 and OncotypeDX and Mammaprint
Clalit (n=2477)
6. Proliferation: Poor reproducibility in Ki67 betweenobservers
Dowsett, M et al. JNCI 2011Polley, M et al. JNCI 2013De Nielsen, TO et al. SABCS 2013
PlanB: RS by (central) Ki-67
6. Proliferation: Correlation between Ki67 and OncotypeDX
Gluz, O. J Clin Oncol 2016
n=2568
Stalhammar, G et al. Mod Pathol 2016
N=436
6. Proliferation: Correlation between Ki67 and PAM50
Concordance index (c index) for risk of recurrence for ROR, RS, IHC4 and clinical treatment score (CTS)
Cuzick, J et al. J Clin Oncol 2011Dowsett, M et al. J Clin Oncol 2013
Predicted time to distant recurrence for a node-negative patient age ≥ 65 years with a poorly differentiated 1- to 2-cm tumor treated with anastrozole
IHC4 = 94.7*(-0.100*ER10 – 0.079*PgR10 + 0.586*HER2 + 0.240*ln(1 +10*ki67)
7. Combined parameters: Correlation between IHC4 and PAM50 or RS
Magee equations:
✓ Recurrence score = 15.31385 + Nottingham score*1.4055 + ERIHC*(-0.01924) + PRIHC*(-0.02925) + (0 for HER2 negative, 0.77681 for equivocal, 11.58134 for HER2 positive) + tumorsize*0.78677 + Ki-67 index*0.13269
✓ Recurrence score = 18.8042 + Nottingham score*2.34123 + ERIHC*(-0.03749) + PRIHC*(-0.03065) + (0 for HER2 negative, 1.82921 for equivocal, 11.51378 for HER2 positive) + tumorsize*0.04267
✓ Recurrence score = 24.30812 + ERIHC*(-0.02177) + PRIHC*(-0.02884) + (0 forHER2 negative, 1.46495 for equivocal, 12.75525 for HER2 positive) + Ki-67*0.18649
Flanagan, MB et al. Mod Pathol 2008Klein, ME et al. Mod Pathol 2013Turner, BM et al. Mod Pathol 2015 http://path.upmc.edu/onlineTools/MageeEquations.html
7. Combined parameters: Correlation between Magee equationand RS
Flanagan, MB et al. Mod Pathol 2008Klein, ME et al. Mod Pathol 2013Turner, BM et al. Mod Pathol 2015
7. Combined parameters: Correlation between Magee equationand RS
✓ Pearson correlation coefficient (r) for the OncotypeDX and Magee recurrence scores = 0.6644 (n=283; P=0.0001)
✓ The PPV was 0.86 for low risk RS and 1.0 for high risk, and the NPV, 0.45 and 0.97, respectively
✓ Eliminating high and low risk cases, between 5% and 23% of cases would potentially not have been sent for OncotypeDXtesting, creating a potential cost savings between $56,550 and $282,750.
Elloumi, F. et al. BMC Med Genomics 2011
8. Potential limitations of multigene plataforms: Role of cancer stroma
Turner, BM et al. Mod Pathol 2015Acs, G et al. Mod Pathol 2012
8. Potential limitations of multigene plataforms: Role of cancer stroma
✓ Increased stromal cellularity and presence of inflammatory cells are associated with RS≥18
✓ Elevated Ki67 in stroma predicts RS≥18
Gyanchandani, R et al. Clin Can Res 2016
8. Potential limitations of multigene plataforms: Tumor heterogeneity
1-Intragroup correlation coefficient distribution by gene signature
✓ Non-significant correlation between whole section and representative cores
✓ OncotypeDX, Mammaprint and PAM50 show higher heterogeneity (25% missclasification) between whole section and core sample, associated with high Ki67 and low PgR
1. Qué correlación podemos esperar de los parámetros clínico-patológicos y el riesgo determinado por palaformas genómicas en cáncer de mama?
✓ Grado (y tipo tumoral): moderada (80-85%; tipo histológico, 65%), limitada por la alta proporción de G2 y la concordancia inter-observador
✓ Tamaño tumoral: moderada (67-84%)
✓ Receptores hormonales: moderada-alta (85-95%)
✓ HER2: variable (47-91%)
✓ Proliferación: baja (45-85%), limitada por baja reproducibilidad de Ki67
✓ Fenotipo: moderada (48-87%)
✓ Parámetros combinados (IHC4, Maggie): moderada-alta (70-95%)
2. Existen factores limitantes: Heterogeneidad y estroma tumoral
3. Y… la concordancia de resultados inter-plataforma es moderada*
Conclusiones
*0.33-0.56; Stein, RC et al. ECC 2015