société de pneumologie de langue...

I provided consultations for Astra-Zeneca, Bristol-Myers

Squibb, Boehringer–Ingelheim, Clovis Oncology, Eli Lilly

Oncology, F. Hoffmann–La Roche Ltd, Novartis, Merck,

MSD, Pierre Fabre and Pfizer.

Disclosure slide

2016-2020

2016-2020

•  Nouveauté(s) ? – Connaissances scientifiques – Progrès technologiques – Classes thérapeutiques (Ph II ou III)

•  Aspects économiques – Business – Contraintes économiques

Le cancer du poumon

•  45,222 nouveaux cas (3ème) – 90% C. NAPC – 2/3 stades IV

•  30,555 décès (1er)

•  2 x C. colon (17,833)

•  3 x C. sein (11,913)

Les cancers en France en 2015, INCa 2016

Agenda

•  Le whole genome pour tous ?

•  L’immunothérapie, le graal ?

•  Faire du neuf avec du vieux ?

LC genotyping program: France

Available at www.ecancer.fr

•  28 platforms (2006) •  10 routine biomarkers (+ 6 emerging bm)

* i.e. Regional molecular genetics centers

Back to the basics first?

Example from a large phase III trial in NSCLC

Impact of routine molecular profiling

Barlesi et al, Biomarkers France, Lancet 2016

High througpout molecular genotyping

Images: NGS analyses from the SAFIR lung Unicancer IFCT trial

Larger genomic profiling (NGS)

Available www.ecancer.fr

High througpout molecular genotyping

Images: NGS analyses from the NIH website

Enjeux et perspectives

•  Evolutions

des plateformes

France (Biomarkers France)

Barlesi et al, Biomarkers France, Lancet 2016 (in press)

?

How large should be the analysis?

Ferte C et al, AACR 2014

TP53_

mut

MYC_

amp

TP53_

delFG

FR1_d

elAP

C_mu

tME

T_mut

ATM_m

utFG

F6_am

pCC

ND2_a

mpFG

FR2_d

elKR

AS_am

pFH

IT_del

BRAF

_amp

E2F1_

amp

PDGF

RA_am

pKD

R_mu

tDC

C_del

HRAS

_del

JAK2_d

elNO

TCH1

_del

NRAS

_del

PIK3R

5_del

JAK3_m

utPT

K2_am

pRO

S1_de

lSM

AD4_m

utAK

T3_am

pBR

CA2_a

mpCC

ND2_d

elFG

F6_del

NOTC

H2_de

lRE

T_amp

SRC_

amp

VEGF

C_del

KIT_m

utMA

P3K1

_mut

AKT1_

delATM

_del

CDKN

1B_de

lFG

F10_am

pFG

F20_de

lFG

FR3_d

elKR

AS_de

lMT

OR_de

lPIK

3CG_

amp

SUFU

_del

TUSC

3_del

CTNN

B1_m

utST

K11_m

utAP

C_del

Freque

ncy (%

)

0 %2 %

5 %

10 %

15 %

20 %

25 %

30 %

35 %

Mutations (17%)

Copy numberalterations (83%)

CDKN

2B_d

el

CDKN

2A_d

el

PTEN

_del

PIK3C

A_mu

t

FGF4

_amp

CCND

1_am

p

FGF3

_amp

PIK3C

A_am

p

KRAS

_mut

FGFR

1_am

p

EGFR

_amp

MDM2

_amp

CDK4

_amp

ERBB

2_am

p

PIK3C

B_am

p

FGF1

9_am

p

MET_

amp

RB1_

del

CCNE

1_am

p

NOTC

H2_a

mp

CCNE

2_am

p

CDKN

2A_m

ut

CDK6

_amp

CDK2

_amp

EGFR

_mut

NOTC

H1_a

mp

AR_a

mp

PTEN

_mut

AKT2

_amp

IDH2_

amp

KIT_a

mp

FBXW

7_mu

t

CHEK

1_de

l

IGF1R

_amp

BRAF

_mut

ALK_

amp

FGFR

3_mu

t

NOTC

H2_re

ar

CDK8

_amp

AKT1

_mut

PIK3R

5_am

p

NRAS

_mut

EIF4E

BP1_

amp

RICTO

R_am

p

ROS1

_rear

ALK_

rear

HRAS

_mut

ERBB

2_mu

t

Frequ

ency

(%)

0 %

2 %

5 %

10 %

15 %

20 %

Mutations (24%)

Copy numberalterations (76%)

?

Precision medicine for increased survival?

Ferte et al, AACR 2014

Trial status (April 2nd, 2016)

393 patients enrolled

244 w analyses done

152 w an actionable target

Absence of target, n=76 Drug outside SAFIR, n=16

cfDNA for molecular genotyping

Wakelee H et al, ASCO 2016 (abst 9001)

T790M Tissue

Total Positive Negative Inadequate

Plasma (BEAMing)

Positive 313 23 38 374

Negative 74 17 17 108

Total 387 40 55 482

cfDNA as solution to monitor biomarkers?

Tsuy DW et al, Clin Cancer Res (in press)

ddPCR development

Downloaded from biodiscover.com

PFS by tumour and plasma T790M status

Data cutoff: 1 May 2015. Multiple doses included Oxnard G, et al. ELCC 2016; Abstract 1350_PR

Median PFS (95% CIs)

Plasma T790M positive 9.7 (8.3, 11.1)

Plasma T790M negative 8.2 (5.3, 10.9)

Log-rank test p=0.188

0 3 6 9 12 15 18 21 24

100

80

60

40

20

0

All patients with plasma T790M results

Time from first dose (months)

Prob

abilit

y of p

rogr

essio

n-fre

e sur

vival

Plasma T790M negative (n=104) Plasma T790M positive (n=167)

Median PFS (95% CIs)

Tumour T790M positive 16.5 (10.9, NC)

Tumour T790M negative 2.8 (1.4, 4.2)

Log-rank test p<0.0001

•  In plasma T790M negative patients, tumour genotyping can distinguish those patients with better and worse outcomes

•  Interestingly, a difference based on tumour genotype is also seen in plasma T790M positive cases

100

0 3 6 9 12 15 18 21 24

80

60

40

20

0

Plasma T790M negative by tumour T790M status


Prob

abilit

y of p

rogr

essio

n-fre

e sur

vival

Tumour T790M negative (n=40) Tumour T790M positive (n=47)

Tumour T790M unknown (n=17)

0 3 6 9 12 15 18 21 24 Time from first dose (months)

0 3 6 9 12 15 18 21 24

80

60

40

20

0

Plasma T790M positive by tumour T790M status


Prob

abilit

y of p

rogr

essio

n-fre

e sur

vival

Tumour T790M negative (n=18) Tumour T790M positive (n=111)

Tumour T790M unknown (n=38)

100 Median PFS (95% CIs)

Tumour T790M positive 9.3 (8.3, 10.9)

Tumour T790M negative 4.2 (1.3, 5.6)

Log-rank test p=0.0002

T790M heterogeneity in plasma “false positives”

•  We hypothesised that cases T790M negative in tumour and T790M positive in plasma might have heterogeneous presence of T790M

•  Relative T790M AF was calculated as a proportion of EGFR sensitising AF:

– T790M AF / sensitising AF •  Relative T790M AF was lower in

cases with T790M negative in tumour, suggesting T790M may be present as a minor clone

•  There was a trend toward lower response magnitude in the group with relative T790M AF <10% (p=0.08)

Data cutoff: 1 May 2015 Oxnard G, et al. ELCC 2016; Abstract 1350_PR

Relative T790M AF 0.5

Tumour T790M positive

Tumour T790M negative

0.0 1.0 1.5

–100

30

0

–50

Relative T790M AF

0.01 0. 1 1

Best

% ch

ange

in tu

mour

size

Tumour T790M positive

Tumour T790M negative

Tumour T790M unknown

Median T790M AF

Tumour T790M positive 34%

Tumour T790M negative 17%

Lung cancer EGFRm on 1G targeted therapy

Rosell R et al, Lancet Oncol 2012

Where comes the resistance from?

Hata A et al, Nature Med 2016

Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibitionAaron N Hata1,2,14, Matthew J Niederst1,2,14, Hannah L Archibald1, Maria Gomez-Caraballo1, Faria M Siddiqui1, Hillary E Mulvey1, Yosef E Maruvka1,3, Fei Ji4, Hyo-eun C Bhang5, Viveksagar Krishnamurthy Radhakrishna5, Giulia Siravegna6,7, Haichuan Hu1, Sana Raoof1,2, Elizabeth Lockerman1, Anuj Kalsy1, Dana Lee1, Celina L Keating5, David A Ruddy8, Leah J Damon1, Adam S Crystal1,13, Carlotta Costa1,2, Zofia Piotrowska1,2, Alberto Bardelli6,7, Anthony J Iafrate9, Ruslan I Sadreyev4,9, Frank Stegmeier5, Gad Getz1,3,9,10, Lecia V Sequist1,2, Anthony C Faber11,12 & Jeffrey A Engelman1,2

Although mechanisms of acquired resistance of epidermal growth factor receptor (EGFR)-mutant non-small-cell lung cancers to EGFR inhibitors have been identified, little is known about how resistant clones evolve during drug therapy. Here we observe that acquired resistance caused by the EGFRT790M gatekeeper mutation can occur either by selection of pre-existing EGFRT790M-positive clones or via genetic evolution of initially EGFRT790M-negative drug-tolerant cells. The path to resistance impacts the biology of the resistant clone, as those that evolved from drug-tolerant cells had a diminished apoptotic response to third-generation EGFR inhibitors that target EGFRT790M; treatment with navitoclax, an inhibitor of the anti-apoptotic factors BCL-xL and BCL-2 restored sensitivity. We corroborated these findings using cultures derived directly from EGFR inhibitor–resistant patient tumors. These findings provide evidence that clinically relevant drug-resistant cancer cells can both pre-exist and evolve from drug-tolerant cells, and they point to therapeutic opportunities to prevent or overcome resistance in the clinic.

Résistance acquise aux EGFR TKI (1G)

Cortot A & Janne PA, Eur Respir Rev 2014

Résistance acquise au crizotinib

Doebele RC, et al. Clin Cancer Res 2012 Takeda M, et al. J Thorac Oncol 2013

ALK mutations: frequencies

Bayliss R et al, Cell Mol Life Sci 2016

Lung cancer ROS1 on targeted therapy

Shaw A et al, NEJM 2014; Mazieres et al, J Clin Oncol 2015

US

Coh

ort

EU

Coh

ort

Lung cancer BRAFm on targeted therapy

Planchard et al, ASCO 2013; Planchard et al, ASCO 2016 & Lancet Oncol 2016 (in press)

SD PD NE

PR Best Confirmed Response

380 360 340 100

80 60 40 20

0 -20 -40 -60 -80

-100

Max

imum

Per

cent

Red

uctio

n fr

om

Bas

elin

e M

easu

rem

ent

Max

imum

Per

cent

Red

uctio

n at

Tim

e

of B

est D

isea

se A

sses

smen

t

20 10 0

-10 -20 -30 -40 -50 -60 -70 -80 -90

-100

Best Confirmed Response PR SD PD

Dab

rafe

nib

alon

e D

abra

feni

b Tr

amet

inib

Lung cancer EGFRm on targeted therapy

Janne P, NEJM 2015

AZD

9291

O

sim

ertin

ib

Lung cancer ALKrearr on targeted therapy

Seto et al, Lancet Oncol 2013; Shaw A et al, NEJM 2014

3G EGFR-TKI in 1st line (AURA program)

Ramalingam S, et al. ELCC 2016; Abstract LBA1_PR

Proba

bility

of PF

S surv

ival

Number of patients at risk:1st line 80 mg

1st line 160 mg3030

2629

1.00.90.80.70.60.50.40.30.20.10.0

0 3 6 9 12 15 18 21 24 27

2327

2223

2020

1619

147

70

00

00

Month

80 mg n=30

160 mg n=30

Total N=60

Median PFS,* months (95% CI)

NC (12.3, NC)

19.3 (11.1, 19.3)

19.3 (13.7, NC)

Remaining alive and progression-free,† % (95% CI) 12 months 18 months

75 (55, 88) 57 (36, 73)

69 (49, 83) 53 (32, 70)

72 (59, 82) 55 (41, 67)

3G ALKi Alectinib in 1st line

Nokihara H et al, Abst #9008 ASCO 2016

Crizotinib

Alectinib

En résumé 2020

•  Poussée technologique

•  Réorganisation (régionale)

•  Peu de nouvelles cibles actionnables

– KRAS: untargetable target?

– Process décision (plus) complexe

•  Passage en 1ère ligne TKI 3G

Les attentes ne sont pas là

US Cancer Moonshot

Obama, January 2016

Agenda




Consequences

PD1 inhibitor 2L: Nivolumab (PhIII)

Brahmer J et al, NEJM 2015; Borghaei H et al, NEJM 2015

Nsq-NSCLC Sq-NSCLC

PD1 inhibitor 2L: Pembrolizumab (PhIII)

Herbst R et al., Lancet 2016

All NSCLC NSCLC w PD-L1+ >50%

HR for OS (doc vs 2): 0,54 (0,38-0,77) HR for OS (doc vs 10): 0,50 (0,36-0,70)

HR for OS (doc vs 2): 0,71 (0,58-0,88) HR for OS (doc vs 10): 0,61 (0,49-0,75)

PD-L1 inhibitor 2L: Atezolizumab (PhIII)

To be presented at ESMO (Presidential session, Sunday 9th)

Intégration immunothérapie

En 1ère ligne dès 2017 ?

To be presented at ESMO (Presidential session)

En 1ère ligne dès 2017 !

To be presented at ESMO (Presidential session)

En 1ère ligne dès 2017 !

To be possibly presented at ESMO (Presidential session)

Essai combinaison

Cx +/- ICI

PD-L1 expression as a predictive factor?

Kerr K et al, J Thorac Oncol (in press)

PD-L1 IHC %

Highly + #20

Weakly + #40

Negative #40

Personnalized IO? > 2020

Modified from Kim and Chen, Ann Oncol 2016

IMMUNE DESERT

*EVALUATE TUMOUR IMMUNOLOGY

INFLAMED EXCLUDED

No Effectors

Anti-PDL1/PD1 + TCBs

(or IFN, CART, MEKi)

Anti-PDL1/PD1 + aOX40

(or aCD40, aCTLA4, IL2v, vaccine)

MHC Loss Strong PD-L1 & high mutational

load No identified

target Weak PD-L1 expression

Anti-PDL1/PD1 Anti-PDL1/PD1

+ Chemo /targeted therapy/XRT

Anti-PDL1/PD1 + Other CIT (IDOi, aTIGIT,

aCSF1R, TCBs, IL2v)

Anti-PDL1/PD1

+antiangiogenic + anti-stromal

agents

No Identified target

Anti-PDL1/PD1 + Chemo /targeted

therapy/XRT

T-Cells at Periphery

Enjeux et Perspectives

PD-1 inhibitor 1L: Nivolumab

Hellman et al., ASCO 2016 (abst 3001)

PD-1 inhibitor 1L: Nivolumab/Ipilimumab

Hellman et al., ASCO 2016 (abst 3001)

Nivo 3 q2w + Ipi 1 q12w (n=38)

Nivo 3 q2w + Ipi 1 q6w

(n=39)

Nivo 3 q2w (n=52)

Confirmed ORR, % 47 39 23

Median DOR, months (95%CI)

NR (11.3, NR) NR (8.4, NR) NR (5.7, NR)

Median follow-up, months (95%CI)

12.9 (0.9, 18.0) 11.8 (1.1, 18.2) 14.3 (0.2, 30.1)

mPFS, months (95%CI) 8.1 (5.6, 13.6) 3.9 (2.6, 13.2) 3.6 (2.3, 6.6)

1-year OS rate, % (95%CI) NC 69 (52, 81) 73 (59, 83)

Efficacy is enhanced with increasing PD-L1 expression:

≥1% tumour PD-L1 expression: 57% ORR; 83–90% 1-year OS rate

≥50% tumour PD-L1 expression: 92% (12/13) ORR

En résumé 2020

•  ICI 1ère ligne 2017-2018 (20% ?)

•  ICI 2ème ligne 2016 (sans sélection)

•  Combinaisons –  ICIs (2018-2020) –  ICI + CT (2018-2020)

Agenda




Barlesi F et al, Abst #9077 ASCO 2016

Angiogenics (BUCIL)

Cortot A et al, Abst #9077 ASCO 2016

Angiogenics (ULTIMATE)


Primary endpoint(s) •  PFS

Secondary endpoints •  OS, safety

Key patient inclusion criteria • Histologically confirmed NSCLC • Stage IV disease • ≤3 metastases • No RECIST progression after FLST* (n=49)

R

PD

PD

Stratification •  Nodal status, EGFR/EML4-ALK status,

response to FLST, CNS metastases, number of metastases

ST alone (n=24)

LCT† +/- ST (n=25)

Crossover to LCT allowed at progression

Gomez et al, ASCO 2016 (abst 9004)


Gomez et al, ASCO 2016 (abst 9004)

IFCT-UNICANCER SAFIR 02 lung trial

Progression

Stage IV NSCLC No EGFRm No ALK

Fresh biopsy @ 2 cycles max •  CGH •  NGS cDNA FFPE

@ 4 cycles

Bioguided Rx (AZ pipeline: AZD2014, AZD4547, AZD5363, AZD8931, selumetinib, vandetanib)

Standard Cx PMX (nSQ) ERL (SQ)

R2:1 Until PRG

MEDI4736 (durvalumab)

Until PRG R2:1

Absence d’alt. mol. activable

N=230

N=180

Co-PIs JC Soria / F Barlesi

Conclusions

•  2017-2018: – « NGS » accessible facilement

– TKI 3G 1L

– ROS1, BRAF, MET activables

– Complexification décision (RCP bio mol)

– Peu d’autres cibles (essais précoces)

–  ICI (mono PD-L1 high+ et combo?) 1L

Conclusions

•  2019-2020: – Profils prédictifs (Cx, ICI, etc) ?

– Nouveaux réarrangements

– Nouveaux TKI 3G ou 4G (paninhib)

– Nouveaux inhibiteurs (CDK, JAK) ?

–  IO: ICI mono vs combo (ICI, Cx, AA)

–  Impact contraintes économiques ??

Conclusions

•  Laurent Greillier •  Pascale Tomasini •  Celine Mascaux •  Marjorie Baciuchka •  Marie Eve Garcia •  Clothilde Fournier

•  Email: [email protected]

•  Website: www.aphm.fr

•  Twitter:

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