genomic landscape of breast cancerarchives.innovationinbreastcancer.com/files... · 76%, 72% and...

Genomic landscape of breast cancer

Aleix Prat MD PhDHead of the Translational Genomics Group

Attending Physician at the Breast Cancer UnitVHIO, Barcelona, Spain

Major research advance for breast cancer by ASCO

(http://www.cancerprogress.net).

http://www.cancerprogress.net/�

Identification of tumor individuality usingglobal 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.

Prat et al. Nat Rev Clin Oncol 2012Weigelt et al. PNAS 2003

Lacroix et al. Endo Relat Cancer 2004

Deconstructing the molecular portraits of breast cancer

Luminal A and BNormal-likeHER2-enrichedBasal-like

Prat & Perou Mol Oncol 2011; Prat et al. BCR 2010

Claudin-low

Deconstructing the molecular portraits of breast cancer

Luminal A and BNormal-likeHER2-enrichedBasal-like

Prat & Perou Mol Oncol 2011; Prat et al. BCR 2010

Claudin-low

Mea

n Ex

pres

sion

Luminal ANormal Breast

Basal-likeLuminal BClaudin-low HER2-enriched Intrinsic Subtypes

Perou et al., Nature 2000Sorlie et al., PNAS 2001Sorlie et al., PNAS 2003Hu et al., BMC Genomics 2006Herschkowitz et al., GB 2007Cheang et al. JNCI 2008Parker et al., JCO, Feb 2009Prat et al., BCR 2010Nielsen et al., CCR 2010Cheang et al., CCR 2012Prat et al. Ann Oncol 2012Chia et al., CCR 2012Prat et al. BCRT 2012TCGA Nature 2012Prat et al. JCO 2013Martín et al. BRCT 2013Prat et al. Oncologist 2013Prat et al. CCR 2014

11

TCGA: Analyses Performed

• Gene Expression • DNA Copy Number• miRNA Expression• DNA Methylation• Exome Sequencing

• Reverse Phase Protein Arrays

825 patients

463 patients

348 patients

http://cancergenome.nih.gov/

12

Significantly Mutated Genes

SMGAll Tumors (n=507)

Mutated FDRTP53 187 (37%) 0.00E+00

PIK3CA 180 (36%) 0.00E+00GATA3 54 (11%) 0.00E+00

MAP3K1 39 (8%) 0.00E+00MLL3 37 (7%) 0.00E+00CDH1 33 (6.5%) 0.00E+00

MAP2K4 21 (4%) 0.00E+00RUNX1 18 (3.5%) 0.00E+00PTEN 17 (3.4%) 0.00E+00TBX3 13 (2.5%) 6.72E-13

TCGA Nature 2012

13

Significantly Mutated Genes

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 180 0 0 145 0 0 23 0 0 9 5.55E-09 3.22E-10TP53 187 0 0 68 0 0 41 0 0 68 0 0

GATA3 54 0 0 45 0 0 8 0 0 0 NA NAMAP3K1 39 0 0 36 0 0 2 NA NA 0 NA NA

CDH1 33 0 0 30 0 0 2 NA NA 1 NA NAMLL3 37 0 0 28 0 0 5 NA NA 3 NA NA

MAP2K4 21 0 0 19 0 0 1 NA NA 1 NA NAPTEN 17 0 0 16 0 0 0 NA NA 1 NA NA

RUNX1 18 0 0 15 0 0 1 NA NA 0 NA NAUSH2A 27 2.08E-02 1.42E-03 13 NA NA 4 NA NA 9 NA NARYR2 22 4.08E-02 1.09E-02 13 NA NA 5 NA NA 3 NA NA

NCOR1 17 1.25E-02 2.99E-05 13 1.10E-05 4.33E-07 1 NA NA 1 NA NANF1 14 1.84E-02 4.20E-03 11 1.09E-02 1.39E-02 1 NA NA 2 NA NA

TBX3 13 2.77E-13 6.72E-13 11 5.74E-12 4.91E-12 0 NA NA 1 NA NACTCF 13 4.68E-03 3.74E-05 11 6.46E-04 2.31E-06 1 NA NA 1 NA NAAKT1 12 1.76E-12 6.83E-11 11 2.75E-13 3.94E-12 1 NA NA 0 NA NA

PIK3R1 14 3.99E-10 6.34E-11 9 8.44E-07 1.82E-06 4 NA NA 1 NA NAPTPRD 12 3.87E-02 1.69E-02 8 NA NA 2 NA NA 2 NA NASF3B1 10 6.26E-04 9.08E-04 7 2.27E-03 1.07E-02 1 NA NA 0 NA NACBFB 8 9.90E-08 7.72E-08 7 1.32E-07 5.10E-08 0 NA NA 1 NA NAAFF2 13 1.98E-02 3.97E-03 6 NA NA 3 NA NA 4 NA NA

TBL1XR1 8 2.38E-04 9.26E-06 6 6.33E-04 1.83E-05 1 NA NA 1 NA NAZFP36L1 7 5.89E-04 2.60E-04 6 7.14E-05 1.27E-04 0 NA NA 1 NA NA

RPGR 10 1.00E-02 1.59E-03 5 NA NA 0 NA NA 3 NA NACDKN1B 5 7.09E-05 1.11E-03 5 4.60E-06 5.94E-05 0 NA NA 0 NA NADCAF4L2 7 2.36E-02 4.99E-02 4 NA NA 2 NA NA 1 NA NA

GPS2 6 1.87E-05 4.75E-04 4 6.98E-03 3.73E-02 1 NA NA 1 NA NAOR6A2 4 1.71E-02 2.54E-02 4 3.67E-03 4.32E-03 0 NA NA 0 NA NA

RB1 9 1.59E-02 1.59E-03 3 NA NA 1 NA NA 4 2.77E-02 4.64E-02PTPN22 7 2.44E-03 8.63E-03 3 NA NA 4 6.57E-03 3.36E-02 0 NA NASEPT13 4 1.32E-03 4.71E-02 3 NA NA 0 NA NA 1 NA NA

HIST1H2BC 4 2.36E-02 2.58E-02 2 NA NA 1 NA NA 1 NA NACCND3 2 5.07E-03 4.11E-02 2 8.48E-04 7.40E-03 0 NA NA 0 NA NAGPR32 5 1.58E-02 3.14E-02 1 NA NA 1 NA NA 1 NA NA

CLEC19A 1 2.36E-02 3.14E-02 1 2.51E-02 3.69E-02 0 NA NA 0 NA NATCGA et al., Nature, 2012 (PMID 23000897)

Shah et al. Nature 2012

• 104 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.

9%

39%

45%

29%

180/507 PIK3CA Mutant tumors TCGA et al., Nature, 2012 (PMID 23000897)

Basal-like

Luminal B

HER2-enriched

Luminal A

Multi-platform PIK3CA Pathway Analysis (390 tumors)TCGA et al., Nature 2012 (PMID 23000897)

Luminal A Luminal B HER2E Basal-like

21

Intrinsic Subtypes

Integration of all data types

• 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 gene expression-only.

22

Intrinsic Subtypes

Integration of all data types

• 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 gene expression-only.

• 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.

Genomic Analyses across Six Cancer Types Identify Basal-like Breast Cancer as a Unique Molecular Entity

Prat et al. Sci Rep 2013

The genomic and transcriptomic

architecture of 2,000 breast tumors reveals novel subgroups.

Curtis et al., Nature 2012

(PMID 22522925)

The genomic and transcriptomic

architecture of 2,000 breast tumors reveals novel subgroups.

Curtis et al., Nature 2012

(PMID 22522925)Basal-like

HER2E

LumA(1q/16q)

LumB

LumA

N=295

• 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.

PAM50 and 10 IntClust subtypes

IntClust PAM50

Curtis et al., Nature 2012 (PMID 22522925)

PAM50 and 10 IntClust subtypes

Curtis et al., Nature 2012 (PMID 22522925)

GEICAM 9906 (Martin, BCRT 2013)

FEC vs FEC-T (n=820)

0

20

40

60

80

100

0 1 2 3 4 5 6 7 8 9 10

ABCSG8 (Gnant, SABCS 2012)

Tam-Tam vs Tam-AI (n=1478)

CALGB 9741 (Liu, SABCS 2012)

q2 AC-T vs q3 AC-T (n=1311)

TransATAC(Dowsett, JCO 2013)Tam vs AI (n=1007)

PAM50 Subtype Testingin Phase III Clinical Trials (n=5,486)

NCIC MA.5 (Cheang, CCR 2012)CMF vs CEF (n=475)

NCIC MA.12 (Chia, CCR 2012)

Chemo vs Chemo+Tam (n=395)

LumALumB

GEICAM 9906 (Martin, BCRT 2013)

FEC vs FEC-T (n=820)

0

20

40

60

80

100

0 1 2 3 4 5 6 7 8 9 10

ABCSG8 (Gnant, SABCS 2012)

Tam-Tam vs Tam-AI (n=1478)

CALGB 9741 (Liu, SABCS 2012)

q2 AC-T vs q3 AC-T (n=1311)

TransATAC(Dowsett, JCO 2013)Tam vs AI (n=1007)

PAM50 Subtype Testingin Phase III Clinical Trials (n=5,486)

NCIC MA.5 (Cheang, CCR 2012)CMF vs CEF (n=475)

NCIC MA.12 (Chia, CCR 2012)

Chemo vs Chemo+Tam (n=395)

LumALumB

CHEMO+/-ENDOCRINECHEMO+ENDOCRINE

CHEMO+ENDOCRINE

ENDOCRINE CHEMO+ENDOCRINE ENDOCRINE

Ellis et al. Nature 2012N=77 pre-treatment ER+/HER2- tumor samples

2013 St Gallen International Expert Consensus

Quote: “The Panel recognized the superior accuracy and reproducibility ofmulti-gene molecular assays”.

Goldhirsch et al. Ann Oncol 2013Cheang et al. JNCI 2009

Endocrine Therapy(chemo in selected cases)

Endocrine + Chemo (most)

Endocrine+ Chemo + anti-HER2

Chemo + anti-HER2

Chemo

14-20%

Pathologic Complete Response Ratesbased on HR status in HER2+ Breast Cancer Clinical trials evaluating dual HER2 blockade

M.F. Rimawi J Clin Oncol 8 Abril 2013Gianni, Lancet Oncol 2011

Trial TreatmentpCR in

HR+pCR in

HR–DIFF

NeoALTTO(Lancet 2012)

Lapatinib + PaclitaxelTrastuzumab + Paclitaxel

Lapatinib + Trastuzumab + Paclitaxel

16%23%42%

34%36%61%

18%13%19%

CALGB40601 (ASCO 2013)



31%39%42%

37%55%77%

6%16%27%

NSABP B41(ASCO 2012)

AC Lapatinib + PaclitaxelAC Trastuzumab + Paclitaxel

AC Lapatinib + Trastuzumab + Paclitaxel

48%47%56%

61%66%73%

13%19%17%

NeoSphere(Lancet Oncol

2012)

Trastuzumab + DocetaxelTrastuzumab + Pertuzumab+Docetaxel

Pertuzumab + DocetaxelTrastuzumab + Pertuzumab

20%26%17%6%

37%63%30%27%

17%37%13%21%

TBCRC006(JCO 2013)

Lapatinib + Trastuzumab + LetrozoleLapatinib + Trastuzumab

21%---

---36%

15%

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 3

• 156 (46.7%) pre-treatmentsamples were PAM50 profiled.

Prat et al. Clin Cancer Res 2014






Note: interaction test between HER2E subtype and treatmentwas not statistically significant.

pCR Odds Ratio P-value

HER2+/HER2-ENo-trastuzumab (n=29) 27.6%

Trastuzumab (n=34) 52.9%HER2+/nonHER2-ENo-trastuzumab (n=22) 18.2%

Trastuzumab (n=29) 34.5%HER2+/HR-/HER2-ENo-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%

0.002

2.4 0.582

Subtype

5.1 0.009

2.1 0.352

8.7

RESPONSE





HER2+ HER2+/HR-


Note: interaction test between HER2E subtype and treatmentwas not statistically significant.

pCR Odds Ratio P-value

HER2+/HER2-ENo-trastuzumab (n=29) 27.6%

Trastuzumab (n=34) 52.9%HER2+/nonHER2-ENo-trastuzumab (n=22) 18.2%

Trastuzumab (n=29) 34.5%HER2+/HR-/HER2-ENo-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%

0.002

2.4 0.582

Subtype

5.1 0.009

2.1 0.352

8.7

RESPONSE

Pathologic Complete Response Ratesbased on HR status in HER2+ Breast Cancer Clinical trials evaluating dual HER2 blockade

M.F. Rimawi J Clin Oncol 8 Abril 2013Gianni, Lancet Oncol 2011

Trial TreatmentpCR in

HR+pCR in

HR–DIFF

NeoALTTO(Lancet 2012)



16%23%42%

34%36%61%

18%13%19%

CALGB40601 (ASCO 2013)



31%39%42%

37%55%77%

6%16%27%

NSABP B41(ASCO 2012)

AC Lapatinib + PaclitaxelAC Trastuzumab + Paclitaxel

AC Lapatinib + Trastuzumab + Paclitaxel

48%47%56%

61%66%73%

13%19%17%

NeoSphere(Lancet Oncol

2012)

Trastuzumab + DocetaxelTrastuzumab + Pertuzumab+Docetaxel

Pertuzumab + DocetaxelTrastuzumab + Pertuzumab

20%26%17%6%

37%63%30%27%

17%37%13%21%

TBCRC006(JCO 2013)

Lapatinib + Trastuzumab + LetrozoleLapatinib + Trastuzumab

21%---

---36%

15%

Conclusions

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.






• 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.

University of North Carolina, NC, USA

Chuck PerouLisa CareyMaggie CheangJoel S. Parker

GRANT SEOM PARA FORMACION EN INVESTIGACION TRASLACIONAL

GEICAM, Spain

Miguel MartínEva CarrascoRosalía CaballeroMaribel Casas

AcknowledgementsPatricia GalvánBarbara AdamoMaria VidalAna VivancosJavier CortésJosep Tabernero

Vicente PegSantiago Ramon y CajalIsabel RubioUPM

GRANT ROCHEFOR TRANSLATIONAL RESEARCH

CAREER CATALYST GRANT FROMSUSAN G KOMEN FOUNDATION

SOLTI, Spain

Antonio LlombartEva CiruelosLorena de la PeñaJosep Vazquez

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