Genomic landscape of breast cancer
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1 Genomic landscape of breast cancer Aleix Prat MD PhD Head of the Translational Genomics Group Attending Physician at the Breast Cancer Unit VHIO, Barcelona, Spain
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4 Major research advance for breast cancer by ASCO (
5 Prat et al. Nat Rev Clin Oncol 2012 Weigelt et al. PNAS 2003 Lacroix et al. Endo Relat Cancer 2004 Identification of tumor individuality using global gene-expression analyses Supervised hierarchical clustering of breast cancer data of 367 breast samples using 1,900 intrinsic genes. Paired tumor samples are highlighted by the red lines in the array tree, with 41 out of 43 (95%) possible pairs being paired.
6 Prat & Perou Mol Oncol 2011; Prat et al. BCR 2010 Deconstructing the molecular portraits of breast cancer Basal-like Claudin-low HER2-enriched Normal-like Luminal A and B
7 Prat & Perou Mol Oncol 2011; Prat et al. BCR 2010 Deconstructing the molecular portraits of breast cancer Basal-like Claudin-low HER2-enriched Normal-like Luminal A and B Mean Expression
8 Prat & Perou Mol Oncol 2011; Prat et al. BCR 2010 Deconstructing the molecular portraits of breast cancer Basal-like Claudin-low HER2-enriched Normal-like Luminal A and B Mean Expression
9 Normal Breast Claudin-low HER2-enriched Luminal A Luminal B Basal-like Intrinsic Subtypes Perou et al., Nature 2000 Sorlie et al., PNAS 2001 Sorlie et al., PNAS 2003 Hu et al., BMC Genomics 2006 Herschkowitz et al., GB 2007 Cheang et al. JNCI 2008 Parker et al., JCO, Feb 2009 Prat et al., BCR 2010 Nielsen et al., CCR 2010 Cheang et al., CCR 2012 Prat et al. Ann Oncol 2012 Chia et al., CCR 2012 Prat et al. BCRT 2012 TCGA Nature 2012 Prat et al. JCO 2013 Martín et al. BRCT 2013 Prat et al. Oncologist 2013 Prat et al. CCR 2014
10 Normal Breast Claudin-low HER2-enriched Luminal A Luminal B Basal-like Intrinsic Subtypes Perou et al., Nature 2000 Sorlie et al., PNAS 2001 Sorlie et al., PNAS 2003 Hu et al., BMC Genomics 2006 Herschkowitz et al., GB 2007 Cheang et al. JNCI 2008 Parker et al., JCO, Feb 2009 Prat et al., BCR 2010 Nielsen et al., CCR 2010 Cheang et al., CCR 2012 Prat et al. Ann Oncol 2012 Chia et al., CCR 2012 Prat et al. BCRT 2012 TCGA Nature 2012 Prat et al. JCO 2013 Martín et al. BRCT 2013 Prat et al. Oncologist 2013 Prat et al. CCR 2014
11 TCGA: Analyses Performed 825 patients patients Gene Expression DNA Copy Number mirna Expression DNA Methylation Exome Sequencing 348 patients Reverse Phase Protein Arrays
12 Significantly Mutated Genes SMG All Tumors (n=507) Mutated FDR TP (37%) 0.00E+00 PIK3CA 180 (36%) 0.00E+00 GATA3 54 (11%) 0.00E+00 MAP3K1 39 (8%) 0.00E+00 MLL3 37 (7%) 0.00E+00 CDH1 33 (6.5%) 0.00E+00 MAP2K4 21 (4%) 0.00E+00 RUNX1 18 (3.5%) 0.00E+00 PTEN 17 (3.4%) 0.00E+00 TBX3 13 (2.5%) 6.72E TCGA Nature 2012
13 Significantly Mutated Genes 13
14 TCGA Breast Tumor Significantly Mutated Gene List by Clinical Receptor Status (n=507) Gene All Tumors (n=507) ER+/HER2- (n=330) Clinical HER2+ (n=75) Triple-negative (n=86) #Cases LRT CT #Cases LRT CT #Cases LRT CT #Cases LRT CT PIK3CA E E-10 TP GATA NA NA MAP3K NA NA 0 NA NA CDH NA NA 1 NA NA MLL NA NA 3 NA NA MAP2K NA NA 1 NA NA PTEN NA NA 1 NA NA RUNX NA NA 0 NA NA USH2A E E NA NA 4 NA NA 9 NA NA RYR E E NA NA 5 NA NA 3 NA NA NCOR E E E E-07 1 NA NA 1 NA NA NF E E E E-02 1 NA NA 2 NA NA TBX E E E E-12 0 NA NA 1 NA NA CTCF E E E E-06 1 NA NA 1 NA NA AKT E E E E-12 1 NA NA 0 NA NA PIK3R E E E E-06 4 NA NA 1 NA NA PTPRD E E-02 8 NA NA 2 NA NA 2 NA NA SF3B E E E E-02 1 NA NA 0 NA NA CBFB E E E E-08 0 NA NA 1 NA NA AFF E E-03 6 NA NA 3 NA NA 4 NA NA TBL1XR E E E E-05 1 NA NA 1 NA NA ZFP36L E E E E-04 0 NA NA 1 NA NA RPGR E E-03 5 NA NA 0 NA NA 3 NA NA CDKN1B E E E E-05 0 NA NA 0 NA NA DCAF4L E E-02 4 NA NA 2 NA NA 1 NA NA GPS E E E E-02 1 NA NA 1 NA NA OR6A E E E E-03 0 NA NA 0 NA NA RB E E-03 3 NA NA 1 NA NA E E-02 PTPN E E-03 3 NA NA E E-02 0 NA NA SEPT E E-02 3 NA NA 0 NA NA 1 NA NA HIST1H2BC E E-02 2 NA NA 1 NA NA 1 NA NA CCND E E E E-03 0 NA NA 0 NA NA GPR E E-02 1 NA NA 1 NA NA 1 NA NA CLEC19A E E E E-02 0TCGA NA et al., Nature, NA (PMID NA )
15 Shah et al. Nature TNBC with DNA somatic mutation status Considering background mutation rates, p53 (53%), PIK3CA (10.2%), MYO3A (9.2%), RB1 (7.7%), PTEN (7.7%), and GH1 (4.6%) showed evidence of single gene selection (q < 0.1). Known drivers such as p53, PIK3CA and PTEN have among the highest clonal frequencies.
16 Basal-like 9% HER2-enriched 39% Luminal A 45% Luminal B 29% 180/507 PIK3CA Mutant tumors TCGA et al., Nature, 2012 (PMID )
17 Basal-like 9% HER2-enriched 39% Luminal A 45% Luminal B 29% 180/507 PIK3CA Mutant tumors TCGA et al., Nature, 2012 (PMID )
18 Basal-like 9% HER2-enriched 39% Luminal A 45% Luminal B 29% 180/507 PIK3CA Mutant tumors TCGA et al., Nature, 2012 (PMID )
19 Multi-platform PIK3CA Pathway Analysis (390 tumors) TCGA et al., Nature 2012 (PMID ) Luminal A Luminal B HER2E Basal-like
20 Multi-platform PIK3CA Pathway Analysis (390 tumors) TCGA et al., Nature 2012 (PMID ) Luminal A Luminal B HER2E Basal-like
21 Integration of all data types gene 21 expression-only. Intrinsic Subtypes Integration of information across 5 platforms demonstrated the existence of 4 main breast cancer classes. which are highly concordant with the main intrinsic subtypes defined by
22 Integration of all data types gene 22 expression-only. Intrinsic Subtypes Integration of information across 5 platforms demonstrated the existence of 4 main breast cancer classes. which are highly concordant with the main intrinsic subtypes defined by
23 Genomic Analyses across Six Cancer Types Identify Basal-like Breast Cancer as a Unique Molecular Entity 76%, 72% and 17% of Basal-like breast tumors were found more similar to SQCLC than to Luminal A, Luminal B and HER2- enriched breast tumors, respectively. Prat et al. Sci Rep 2013
24 The genomic and transcriptomic architecture of 2,000 breast tumors reveals novel subgroups. Curtis et al., Nature 2012 (PMID )
25 The genomic and transcriptomic architecture of 2,000 breast tumors reveals novel subgroups. Curtis et al., Nature 2012 (PMID ) LumB HER2E Basal-like LumA LumA (1q/16q)
26 PAM50 and 10 IntClust subtypes Disease specific survival (DSS) KM plots of subtypes defined by the PAM50 or the IntClust predictors on the validation/test set. PAM50 and IntClust subtype calls as provided by Curtis et al. IntClust PAM50 N=295 Curtis et al., Nature 2012 (PMID )
27 PAM50 and 10 IntClust subtypes Disease specific survival (DSS) KM plots of subtypes defined by the PAM50 or the IntClust predictors on the validation/test set. PAM50 and IntClust subtype calls as provided by Curtis et al. IntClust PAM50 N=295 Curtis et al., Nature 2012 (PMID )
28 PAM50 and 10 IntClust subtypes Curtis et al., Nature 2012 (PMID )
29 PAM50 Subtype Testing in Phase III Clinical Trials (n=5,486) NCIC MA.12 (Chia, CCR 2012) Chemo vs Chemo+Tam (n=395) NCIC MA.5 (Cheang, CCR 2012) CMF vs CEF (n=475) GEICAM 9906 (Martin, BCRT 2013) FEC vs FEC-T (n=820) TransATAC (Dowsett, JCO 2013) Tam vs AI (n=1007) CALGB 9741 (Liu, SABCS 2012) q2 AC-T vs q3 AC-T (n=1311) ABCSG8 (Gnant, SABCS 2012) Tam-Tam vs Tam-AI (n=1478) LumA LumB
30 PAM50 Subtype Testing in Phase III Clinical Trials (n=5,486) NCIC MA.12 (Chia, CCR 2012) Chemo vs Chemo+Tam (n=395) NCIC MA.5 (Cheang, CCR 2012) CMF vs CEF (n=475) GEICAM 9906 (Martin, BCRT 2013) FEC vs FEC-T (n=820) CHEMO+/-ENDOCRINE CHEMO+ENDOCRINE CHEMO+ENDOCRINE TransATAC (Dowsett, JCO 2013) Tam vs AI (n=1007) CALGB 9741 (Liu, SABCS 2012) q2 AC-T vs q3 AC-T (n=1311) ABCSG8 (Gnant, SABCS 2012) Tam-Tam vs Tam-AI (n=1478) ENDOCRINE CHEMO+ENDOCRINE ENDOCRINE LumA LumB
31 PAM50 Subtype Testing in Phase III Clinical Trials (n=5,486) NCIC MA.12 (Chia, CCR 2012) Chemo vs Chemo+Tam (n=395) NCIC MA.5 (Cheang, CCR 2012) CMF vs CEF (n=475) GEICAM 9906 (Martin, BCRT 2013) FEC vs FEC-T (n=820) CHEMO+/-ENDOCRINE CHEMO+ENDOCRINE CHEMO+ENDOCRINE TransATAC (Dowsett, JCO 2013) Tam vs AI (n=1007) CALGB 9741 (Liu, SABCS 2012) q2 AC-T vs q3 AC-T (n=1311) ABCSG8 (Gnant, SABCS 2012) Tam-Tam vs Tam-AI (n=1478) ENDOCRINE CHEMO+ENDOCRINE ENDOCRINE LumA LumB
32 Ellis et al. Nature 2012 N=77 pre-treatment ER+/HER2- tumor samples
33 Ellis et al. Nature 2012 N=77 pre-treatment ER+/HER2- tumor samples
34 Ellis et al. Nature 2012 N=77 pre-treatment ER+/HER2- tumor samples
35 2013 St Gallen International Expert Consensus 14-20% Endocrine Therapy (chemo in selected cases) Endocrine + Chemo (most) Endocrine+ Chemo + anti-her2 Chemo + anti-her2 Chemo Quote: The Panel recognized the superior accuracy and reproducibility of multi-gene molecular assays. Goldhirsch et al. Ann Oncol 2013 Cheang et al. JNCI 2009
36 2013 St Gallen International Expert Consensus 14-20% Endocrine Therapy (chemo in selected cases) Endocrine + Chemo (most) Endocrine+ Chemo + anti-her2 Chemo + anti-her2 Chemo Quote: The Panel recognized the superior accuracy and reproducibility of multi-gene molecular assays. Goldhirsch et al. Ann Oncol 2013 Cheang et al. JNCI 2009
37 Pathologic Complete Response Rates based on HR status in HER2+ Breast Cancer Clinical trials evaluating dual HER2 blockade Trial NeoALTTO (Lancet 2012) CALGB40601 (ASCO 2013) NSABP B41 (ASCO 2012) NeoSphere (Lancet Oncol 2012) TBCRC006 (JCO 2013) Treatment Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel AC Lapatinib + Paclitaxel AC Trastuzumab + Paclitaxel AC Lapatinib + Trastuzumab + Paclitaxel Trastuzumab + Docetaxel Trastuzumab + Pertuzumab+Docetaxel Pertuzumab + Docetaxel Trastuzumab + Pertuzumab Lapatinib + Trastuzumab + Letrozole Lapatinib + Trastuzumab pcr in HR+ 16% 23% 42% 31% 39% 42% 48% 47% 56% 20% 26% 17% 6% pcr in HR 34% 36% 61% 37% 55% 77% 61% 66% 73% M.F. Rimawi J Clin Oncol 8 Abril 2013 Gianni, Lancet Oncol % % 63% 30% 27% % DIFF 18% 13% 19% 6% 16% 27% 13% 19% 17% 17% 37% 13% 21% 15%
38 Pathologic Complete Response Rates based on HR status in HER2+ Breast Cancer Clinical trials evaluating dual HER2 blockade Trial NeoALTTO (Lancet 2012) CALGB40601 (ASCO 2013) NSABP B41 (ASCO 2012) NeoSphere (Lancet Oncol 2012) TBCRC006 (JCO 2013) Treatment Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel AC Lapatinib + Paclitaxel AC Trastuzumab + Paclitaxel AC Lapatinib + Trastuzumab + Paclitaxel Trastuzumab + Docetaxel Trastuzumab + Pertuzumab+Docetaxel Pertuzumab + Docetaxel Trastuzumab + Pertuzumab Lapatinib + Trastuzumab + Letrozole Lapatinib + Trastuzumab pcr in HR+ 16% 23% 42% 31% 39% 42% 48% 47% 56% 20% 26% 17% 6% pcr in HR 34% 36% 61% 37% 55% 77% 61% 66% 73% M.F. Rimawi J Clin Oncol 8 Abril 2013 Gianni, Lancet Oncol % % 63% 30% 27% % DIFF 18% 13% 19% 6% 16% 27% 13% 19% 17% 17% 37% 13% 21% 15%
39 The HER2-enriched subtype is associated with higher responses and improved survival outcomes in HER2+ breast cancer in the NOAH study Prat et al. Clin Cancer Res 2014 Chemotherapy: AT x 3 T x 4 CMF x (46.7%) pre-treatment samples were PAM50 profiled.
40 The HER2-enriched subtype is associated with higher responses and improved survival outcomes in HER2+ breast cancer in the NOAH study Chemotherapy: AT x 3 T x 4 CMF x (46.7%) pre-treatment samples were PAM50 profiled. RESPONSE pcr Odds Ratio P-value Subtype HER2+/HER2-E No-trastuzumab (n=29) 27.6% Trastuzumab (n=34) 52.9% HER2+/nonHER2-E No-trastuzumab (n=22) 18.2% Trastuzumab (n=29) 34.5% HER2+/HR-/HER2-E No-trastuzumab (n=28) 25.0% Trastuzumab (n=27) 63.0% HER2+/HR-/nonHER2-E No-trastuzumab (n=9) 11.1% Trastuzumab (n=16) 31.3% Note: interaction test between HER2E subtype and treatment was not statistically significant. 8.7 Prat et al. Clin Cancer Res 2014
41 The HER2-enriched subtype is associated with higher responses and improved survival outcomes in HER2+ breast cancer in the NOAH study Chemotherapy: AT x 3 T x 4 CMF x (46.7%) pre-treatment samples were PAM50 profiled. Subtype HER2+/HER2-E pcr No-trastuzumab (n=29) 27.6% Trastuzumab (n=34) 52.9% HER2+/nonHER2-E No-trastuzumab (n=22) 18.2% Trastuzumab (n=29) 34.5% HER2+/HR-/HER2-E No-trastuzumab (n=28) 25.0% Trastuzumab (n=27) 63.0% HER2+/HR-/nonHER2-E No-trastuzumab (n=9) 11.1% Trastuzumab (n=16) 31.3% RESPONSE Odds Ratio P-value Note: interaction test between HER2E subtype and treatment was not statistically significant. 8.7 HER2+ HER2+/HR- Prat et al. Clin Cancer Res 2014
42 Pathologic Complete Response Rates based on HR status in HER2+ Breast Cancer Clinical trials evaluating dual HER2 blockade Trial NeoALTTO (Lancet 2012) CALGB40601 (ASCO 2013) NSABP B41 (ASCO 2012) NeoSphere (Lancet Oncol 2012) TBCRC006 (JCO 2013) Treatment Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel AC Lapatinib + Paclitaxel AC Trastuzumab + Paclitaxel AC Lapatinib + Trastuzumab + Paclitaxel Trastuzumab + Docetaxel Trastuzumab + Pertuzumab+Docetaxel Pertuzumab + Docetaxel Trastuzumab + Pertuzumab Lapatinib + Trastuzumab + Letrozole Lapatinib + Trastuzumab pcr in HR+ 16% 23% 42% 31% 39% 42% 48% 47% 56% 20% 26% 17% 6% pcr in HR 34% 36% 61% 37% 55% 77% 61% 66% 73% M.F. Rimawi J Clin Oncol 8 Abril 2013 Gianni, Lancet Oncol % % 63% 30% 27% % DIFF 18% 13% 19% 6% 16% 27% 13% 19% 17% 17% 37% 13% 21% 15%
43 Pathologic Complete Response Rates based on HR status in HER2+ Breast Cancer Clinical trials evaluating dual HER2 blockade Trial NeoALTTO (Lancet 2012) CALGB40601 (ASCO 2013) NSABP B41 (ASCO 2012) NeoSphere (Lancet Oncol 2012) TBCRC006 (JCO 2013) Treatment Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel Lapatinib + Paclitaxel Trastuzumab + Paclitaxel Lapatinib + Trastuzumab + Paclitaxel AC Lapatinib + Paclitaxel AC Trastuzumab + Paclitaxel AC Lapatinib + Trastuzumab + Paclitaxel Trastuzumab + Docetaxel Trastuzumab + Pertuzumab+Docetaxel Pertuzumab + Docetaxel Trastuzumab + Pertuzumab Lapatinib + Trastuzumab + Letrozole Lapatinib + Trastuzumab pcr in HR+ 16% 23% 42% 31% 39% 42% 48% 47% 56% 20% 26% 17% 6% pcr in HR 34% 36% 61% 37% 55% 77% 61% 66% 73% M.F. Rimawi J Clin Oncol 8 Abril 2013 Gianni, Lancet Oncol % % 63% 30% 27% % DIFF 18% 13% 19% 6% 16% 27% 13% 19% 17% 17% 37% 13% 21% 15%
44 Conclusions
45 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like).
46 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like). Classification of breast cancer into 10 subtypes based on DNA CNV and GEP does not provide additional prognostic information beyond 4 subtypes.
47 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like). Classification of breast cancer into 10 subtypes based on DNA CNV and GEP does not provide additional prognostic information beyond 4 subtypes. Expression signatures (gene or protein), +/- PI3KCA mutations (E545K? H1047R?), might better recapitulate the status of the PI3K/mTOR pathway.
48 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like). Classification of breast cancer into 10 subtypes based on DNA CNV and GEP does not provide additional prognostic information beyond 4 subtypes. Expression signatures (gene or protein), +/- PI3KCA mutations (E545K? H1047R?), might better recapitulate the status of the PI3K/mTOR pathway. Among the two main Luminal subtypes, the Luminal B subtype requires additional therapies beyond endocrine therapy-only.
49 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like). Classification of breast cancer into 10 subtypes based on DNA CNV and GEP does not provide additional prognostic information beyond 4 subtypes. Expression signatures (gene or protein), +/- PI3KCA mutations (E545K? H1047R?), might better recapitulate the status of the PI3K/mTOR pathway. Among the two main Luminal subtypes, the Luminal B subtype requires additional therapies beyond endocrine therapy-only. HER2+ disease is clinically and biologically heterogeneous and all the intrinsic subtypes (i.e. not just Luminal B and HER2-enriched) can be identified and dominate the molecular and clinical phenotype within HER2+ disease.
50 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like). Classification of breast cancer into 10 subtypes based on DNA CNV and GEP does not provide additional prognostic information beyond 4 subtypes. Expression signatures (gene or protein), +/- PI3KCA mutations (E545K? H1047R?), might better recapitulate the status of the PI3K/mTOR pathway. Among the two main Luminal subtypes, the Luminal B subtype requires additional therapies beyond endocrine therapy-only. HER2+ disease is clinically and biologically heterogeneous and all the intrinsic subtypes (i.e. not just Luminal B and HER2-enriched) can be identified and dominate the molecular and clinical phenotype within HER2+ disease. HER2+/HER2-enriched tumors might benefit the most from anti-her2 treatments in combination with chemotherapy.
51 Conclusions Breast cancer is an heterogeneous disease in terms of many data-types, all of which converge into 4 main intrinsic molecular subtypes (Luminal A and B, HER2- enriched and Basal-like). Classification of breast cancer into 10 subtypes based on DNA CNV and GEP does not provide additional prognostic information beyond 4 subtypes. Expression signatures (gene or protein), +/- PI3KCA mutations (E545K? H1047R?), might better recapitulate the status of the PI3K/mTOR pathway. Among the two main Luminal subtypes, the Luminal B subtype requires additional therapies beyond endocrine therapy-only. HER2+ disease is clinically and biologically heterogeneous and all the intrinsic subtypes (i.e. not just Luminal B and HER2-enriched) can be identified and dominate the molecular and clinical phenotype within HER2+ disease. HER2+/HER2-enriched tumors might benefit the most from anti-her2 treatments in combination with chemotherapy. Molecular classifications for prediction are the future, with DNA mutations, copy number, and gene/protein expression being promising methods alone or in combination.
52 Acknowledgements Patricia Galván Barbara Adamo Maria Vidal Ana Vivancos Javier Cortés Josep Tabernero Vicente Peg Santiago Ramon y Cajal Isabel Rubio UPM University of North Carolina, NC, USA Chuck Perou Lisa Carey Maggie Cheang Joel S. Parker GRANT SEOM PARA FORMACION EN INVESTIGACION TRASLACIONAL GRANT ROCHE FOR TRANSLATIONAL RESEARCH CAREER CATALYST GRANT FROM SUSAN G KOMEN FOUNDATION GEICAM, Spain Miguel Martín Eva Carrasco Rosalía Caballero Maribel Casas SOLTI, Spain Antonio Llombart Eva Ciruelos Lorena de la Peña Josep Vazquez
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