Predictive Biomarkers of EGFR Targeted Therapy: Beyond KRAS

Josep Tabernero, MD PhD

Vall d’Hebron University Hospital and

Vall d’Hebron Institute of Oncology (VHIO)

Barcelona, Spain

NCIC CTG CO.17: mCRC Cetuximab vs BSC

HR OS: ITT 0.7 KRAS wt 0.55

1Jonker, DJ et al. NEJM; 357:2040-8,2007 2Karapetis, CS. et al. NEJM;359:1757-65,2008

EGFR inhibitors: beyond KRAS

Baseline Predictive Biomarkers

MUTATIONS•KRAS mut•NRAS mut, BRAF mut•PIK3CA mut•TP53 mut, PTEN mut

RECEPTOR EXPRESSION• EGFR (HER1),

HER-2/neu, HER-3, HER-4, IGF1R

LIGAND EXPRESSION• EGF, TGF-α, HB-EGF,

amphiregulin (AREG), betacellulin, epiregulin (EREG) and epigen

DOWNSTREAM EFECTORS EXPRESSION• MPK-1 (DUSP-1), DUSP-4,

DUSP-6

Mutant BRAF11/79 (14%)

Wild-type BRAF68/79 (86%)

Responders 0/11 (0%)‡ 22/68 (32%)‡

Non-responders 11/11 (100%)‡ 46/68 (68%)‡

Mutant KRAS34/113 (30%)

Wild-type KRAS79/113 (70%)

Responders 2/34 (6%)* 22/79 (28%)*

Non-responders 32/34 (94%)* 57/79 (72%)*

BRAF mutational status on wild-type KRAS tumours (n=79)

KRAS mutational status (evaluable patients n=113)

mCRC patients treated with panitumumab or cetuximab, n=114

*p<0.05 (p=0.011)

‡p<0.05 (p=0.029) Di Nicolantonio, et al. J Clin Oncol 2008;26:5705-12

BRAF mutations

aCochran–Mantel–Haenszel test Van Cutsem E, et al. J Clin Oncol 2011; 29:2011-9

BRAF mutations

• European Consortium:– Refractory CRC

patients treated with irinotecan + cetuximab

– 1022 tumour samples– 773 samples of quality

De Roock, W et al. Lancet Oncol 2010;11:753-62

BRAF, NRAS, PIK3CA mutations

Response Rate

Overall Survival

De Roock, W et al. Lancet Oncol 2010;11:753-62

BRAF, NRAS, PIK3CA mutations

Ir vs IrCsnon-inferior efficacy

primary endpoint PFS at 12 wks

IrPanirinotecan + pan’mab

IrCsirinotecan + c’sporin

Iririnotecan alone

Ir vs IrPansuperior efficacy

primary endpoint OS

Iririnotecan alone

KRAS mutated or unknown KRAS-wt (c.12/13 & 61)

PICCOLO studytarget total n = 1200

(including 494 accrued under previous design)eligibility as before

Seymour et al. Proc ASCO 2011:A3523

BRAF, NRAS mutations

IrPan better Ir better

*Adjusted HRs, 95% CIs

KRAS wt: 460 pts, 312 eventsHR=0.91 (0.73, 1.14), p=0.44

Double wt : 348 pts, 230 events; HR=0.87 (0.67, 1.13), p=0.30

BRAF mut: 63 pts, 53 events; HR=2.03 (1.13, 3.64)

NRAS mut: 21 pts, 15 eventsHR=4.59 (1.19, 17.67)

KRAS146 mut: 17 pts, 14 eventsHR=1.32 (0.30, 5.81)

Any mut: 99 pts, 80 eventsHR=2.03 (1.26, 3.28)

All wt: 264 pts, 171 events; HR=0.86 (0.63, 1.16), p=0.32

Seymour et al. Proc ASCO 2011:A3523

BRAF, NRAS mutations

OS

Presented by:

BRAF, NRAS mutations

Oliner et al. Proc ASCO 2013:A3511

PRIME study: FOLFOX +/- PanitumumabOverall Survival

Bertotti A et al. Cancer Discov 2011;1:508-23

Yonesaka K et al. Sci Transl Med 2011;3:99ra86

Quadruple* wtnon-responders

(n=11 xenopatients)

36.4%

(P<0.001)

Normal HER2 amplification

HER2

FISH - HER2

*KRAS/NRAS/

BRAF/PIK3CA

HER-2 amplification

HER-2 ampl HER-2 non-ampl

N 13 220

mPFS (d) 89 149 p=NS

mOS (d) 307 515 p=0.0013

mCRC treated with cetuximab (DFCI)

Scartozzi M et al. Oncologist 2011;16:53-60

Scartozzi M et al. Ann Oncol 2012;23:1706-1712

HER-3 overexpression

HER-3 + HER-3 -

N 44 40

mPFS (m) 2.8 6.3 p<0.0001

mOS (m) 10.5 13.6 p=0.01

mCRC treated with irinotecan + cetuximab

PFS OS

1Singh, AB et al. Cell Signal; 17:1183-1193,20052Shelly, M et al. J Biol Chem; 273:10496-10505,1998

3Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 20074Tabernero J et al, J Clin Oncol 2010;28:1181-1189

5Jacobs B et al, J Clin Oncol 2009;27:5068-5074

• EGFR ligands:– 1 in C. Elegans– 4 in Drosophila– 7 in mammals: EGF, TGF-α,

HB-EGF, amphiregulin (AREG), betacellulin, epiregulin (EREG) and epigen1

– EREG and AREG bind more weakly to EGFR than EGF but much more potently and more prolonged

– EREG preferentially activates heterodimers2

• High gene expression levels of EREG and AREG predict response to cetuximab3-5

EGFR Ligands

Ligands: AREG, EREG, TGFalpha

Presented by:

Tabernero J et al, J Clin Oncol 2010;28:1181-1189

mCRC 1st-line treatment Cetuximab (window) + FOLFIRI

• Combimarker: K-Ras wt and high EREG– Pre-especified threshold1

– Minimum threshold: 169/384 (44%)– All comers 394 (100%) HR: 0.7– K-Ras wt 230 (58%) HR: 0.55– Combimarker 169 (44%) HR: 0.46

1Khambata-Ford, S. et al. J Clin Oncol; 25:3230-3237, 20072Jonker, D et al. Proc ASCO 2009

Ligands: AREG, EREG, TGFalpha

Low EREG by minimum-p threshold

Cetuximab + BSC

BSC alone

HR 0.93 [0.51-1.71], p=0.81

Pro

por

tion

aliv

e

0

20

40

60

80

100

Time from randomization (months)

03026

22518

41615

61310

885

1053

High EREG by minimum-p threshold

Pro

por

tion

aliv

e

0

20

40

60

80

100

Time from randomization (months)

08485

28073

47654

66626

84319

102814

121810

1485

Cetuximab + BSC

HR 0.46 [0.32-0.65], p<0.0001

BSC alone

On-treatment Predictive Biomarkers(“under pressure”)

MUTATIONS•KRAS mut•EGFR mut

RECEPTOR EXPRESSION• HER-2/neu, HER-3,

IGF1R

RECEPTOR AMPLIFICATION• C-Met

Misale S, et al. Nature 2012Diaz E, et al. Nature 2012

KRAS mut/ampl under pressure

Initial response to cetuximab followed by PD

Quantitative analysis of KRAS(Q61H) mutant DNA in plasma, as assessedby BEAMing

Misale S, et al. Nature 2012Diaz E, et al. Nature 2012

KRAS mut/ampl under pressure

Bardelli A, et al. Cancer Discov 2013;e

C-Met amplification

Montagut C, et al. Nature Med 2012;18:221-223Morelli MP et al. Proc ASCO 2013:A3512

EGFR mutations

EGFR ectodomain mutation (S492R) that prevents Cetuximab binding, but retain binding to panitumumab

S492R EGFR mutation was detected in 4 (7%) out of55 pts (MDACC) KRAS wt after treatment with cetuximab

CD73 – 5’nucleotidase (5’-NT)

Mizumoto N et al, Nat Med 2002;8:358-365Stagg J et al, PNAS 2010;107:1547-1552

• The release of extracellular ATP in response to cell death or stress activates immune responses

• The hydrolysis of extracellular ATP into adenosine acts as a negative feedback mechanism to prevent excessive inflammation and tissue damage

• CD73 converts AMP to adenosine and is considered as a an immunosuppressor inducer

• Anti-CD73 mAb therapy delays tumor growth in immune-competent mice and inhibits the development of metastasis, through the induction of adaptive immune response

CALGB80203Study Design – Biomarker program

A: FOLFIRI

B: FOLFIRI + Cetuximab

C: FOLFOX

D: FOLFOX + Cetuximab

1st line Metastatic Colorectal Cancer

n = 238

Key inclusion criteria:EGFR positiveRas status not requiredAccrual: 01/21/2004-12/03/2004

Total patients for biomarker analysis

(n=103)

Hurwitz H, et al. Proc ASCO 2013

Prognostic Analyses: Chemotherapy only population

52 patients

Hurwitz H, et al. Proc ASCO 2013

Prognostic Analyses: Chemotherapy only, WT KRAS population

29 patients

Hurwitz H, et al. Proc ASCO 2013

Predictive Analyses: CD73 and Her3Overall Population

Population: 52 w/o + 51 w CetuximabHurwitz H, et al. Proc ASCO 2013

Predictive Analyses: CD73 and Her3Wild type KRAS Population

Population: 29 w/o + 26 w CetuximabHurwitz H, et al. Proc ASCO 2013

Author’s Conclusions & Personal Comments

• Multiple Her axis members and CD73 were identified as candidate prognostic markers for patients treated with FOLFOX/FOLFIRI chemotherapy

• CD73 and Her3 were identified as candidate predictive markers for benefit/lack of benefit from cetuximab

➔ Candidate markers were selected from the literature and confirmed –only as candidates- in the study

+ Predictive

Genes & outcomeKRAS wt population

• 144 KRAS wt mCRC treated with cetuximab

• 4-gene predictive classifier (AREG, EREG, DUSP6, SLC26A3) constructed using multivariate analysis with two-layer five-fold cross-validation

• Patients below the classifier cutpoint had PFS and disease control rates similar to those of patients with KRAS mutant mCRC.

Khambata-Ford, S. et al. J Clin Oncol 2007;25:3230-3237.Baker JB, et al. Br J Cancer 2011;104:488-495

• These results – Merit confirmation in other randomized studies– Suggest potentially intersecting roles for tumor inflammation,

Her family cross talk, and Ras signaling– Suggest potential novel patient selection and combination

treatment approaches

➔ Important correlative translational study:➔ Negative, prematurely closed study, poor recruitment➔ In this circumstances, high tumor acquisition rate (43%)➔ Hypothesis generating study➔ No power to confirm any previous finding…➔ …but raises new potential prognostic/predictive biomarkers to

be explored in the future

Author’s Conclusions & Personal Comments

What’s next?

• Reproduce these results in large cohorts datasets, especially for the new candidates, i.e. CD73

• Evaluate these proposed candidates in trials with Panitumumab, in order to address the class-effect or the Ig subtype-effect (IgG1 vs IgG2)

• Integrate different correlative studies into large datasets

• Make the results open access

Acknowledgements

• ASCO Scientific & Educational Committee• The authors, especially Herb Hurwitz, for the very

constructive interaction

• Special claim for implementing more correlative studies and for data sharing for the best interest of our patients