Meet the Expert: what’s the forecast for the of neuroendocrine

tumours in your crystal ball

Disclosures

Honoraria: Novartis, Ipsen, Pfizer, Keocyt, SIRTex, Celgene

Grant Funding: Novartis, AstraZeneca

No experience with crystal balls!

Overview

•  Classification – are we there yet?

•  Improving study methodology – and future challenges

•  Selection of therapy – how and when?

•  More tools?...or learn to use them better?

•  The era of “personalised medicine”

Nomenclature – no wonder progress was slow!

APUDoma

Endocrine tumour

Neuroendocrine tumour

Neuroendocrine carcinoma

Endocrine carcinoma

Carcinoid tumour

Carcinoid syndrome

Gastroenteropancreatic (GEP) tumour

Islet cell tumour

Insulinoma

Gastrinoma

Glucagonoma

VIPoma

Siegfried Oberndorfer First described “karzinoide”

tumours in 1907 From Modlin et al

Lancet Oncol 2008;9:61–72

Current Classification

1.  Kulke  MH,  et  al.  J  Clin  Oncol  2011;29:934–943    2.  WHO  Classifica<on  of  Tumours  of  the  Diges<ve  System,  4th  ed.,  2010    

3.  Moran  CA,  et  al.  Am  J  Clin  Pathol  2009;131:206–221  

Differentiation and grade

Mitotic count*

Ki-67 index† (%) Traditional classification

ENETS/WHO classification2 Moran et al3

Well differentiated Low grade

(grade 1) <2 ≤2 Carcinoid, islet cell, pancreatic

(neuro) endocrine tumor NET, grade 1 NEC, grade 1

Intermediate grade (grade 2)

2–20 3–20 Carcinoid, atypical carcinoid,‡ islet cell, pancreatic (neuro) endocrine tumor

NET, grade 2 NEC, grade 2

Poorly differentiated High grade

(grade 3) >20 >20 Small-cell carcinoma NEC, grade 3,

small cell NEC, grade 3, small cell

Large-cell NEC NEC, grade 3, large cell

NEC, grade 3, large cell

NET = Neuroendocrine tumours NEC = neuroendocrine carcinoma *Per 10 high-power fields †Cellular proliferation marker ‡Applies only to intermediate-grade NET of the lung

Current Classification…has clinical implications

1.  Kulke  MH,  et  al.  J  Clin  Oncol  2011;29:934–943    2.  WHO  Classifica<on  of  Tumours  of  the  Diges<ve  System,  4th  ed.,  2010    

3.  Moran  CA,  et  al.  Am  J  Clin  Pathol  2009;131:206–221  

Differentiation and grade

Mitotic count*

Ki-67 index† (%) Traditional classification

ENETS/WHO classification2 Moran et al3

Well differentiated Low grade

(grade 1) <2 ≤2 Carcinoid, islet cell, pancreatic

(neuro) endocrine tumor NET, grade 1 NEC, grade 1

Intermediate grade (grade 2)

2–20 3–20 Carcinoid, atypical carcinoid,‡ islet cell, pancreatic (neuro) endocrine tumor

NET, grade 2 NEC, grade 2

Poorly differentiated High grade

(grade 3) >20 >20 Small-cell carcinoma NEC, grade 3,

small cell NEC, grade 3, small cell

Large-cell NEC NEC, grade 3, large cell

NEC, grade 3, large cell

NET = Neuroendocrine tumours NEC = neuroendocrine carcinoma *Per 10 high-power fields †Cellular proliferation marker ‡Applies only to intermediate-grade NET of the lung

Treatment options: Somatostatin analogues Targeted therapies (sunitinib / everolimus) Interferon Chemotherapy Radionuclide therapy Liver-directed therapy

Treatment option:

Chemotherapy

1 Scarpa A et al. Mod Pathol 23:824-833, 2010 2 Sorbye H et al. Ann Oncol 2013 Jan;24(1):152-60 3 Rindi G et al J Natl Cancer Inst 104:764-777, 2012

Have we got it right yet? Limitations •  Are 2% and 20% the most appropriate cut-off values?

•  N=274 pNET patients 1

•  Ki67-based grading was an independent predictor of survival with cut-offs at 5% and 20%

•  N=305 HG-NET patients 2

•  Ki67 prognostic cut-off: 55%

1 Scarpa A et al. Mod Pathol 23:824-833, 2010 2 Sorbye H et al. Ann Oncol 2013 Jan;24(1):152-60 3 Rindi G et al J Natl Cancer Inst 104:764-777, 2012

Have we got it right yet? Limitations •  Are 2% and 20% the most appropriate cut-off values?

•  n=1072 patients •  Previous surgery for NET •  At least 2 years follow-up

Have we got it right yet?

Limitations •  Is a “historical” biopsy representative of the current disease?

•  Do we know how much heterogeneity exists within a tumour?

Sunnybrook (Toronto) • 43/327 patients with multiple biopsies

–  39 primary + metastasis –  4 multiple metastases

 16/43 (37%) difference in grade  12/43 (28%) increased grade by at least 1 level  7/43 (16%) changed grade to G3

Implications: • Multiple biopsies • Repeat biopsies

May be required

Craig et al ESMO 2012 Ann Oncol 23 (suppl 9), abstr 1158P

Study methodology: historical methods

Streptozocin Alone Compared with Streptozocin plus Fluorouracil in the Treatment of Advanced Islet-Cell Carcinoma

Randomised study Islet-cell carcinoma (n=84) Streptozocin alone vs. streptozocin and 5-FU

Radiological

Hepatomegaly

Biochemical markers

•  Results: –  “The combination had advantages over

streptozocin alone in overall rate of response (63 vs. 36 per cent)”

–  “There was also a difference in median survival of 26 months compared to 16.5 months, although this did not reach statistical significance”

Moertel CG et al. N Eng J Med 1980;303:1189–1194

Better…but not good enough…

Faivre et al Target Oncol 2012 Jun;7(2):127-33

Clinical  Non-­‐standard  radiological  

WHO  criteria  

RECIST  VERSION  XXX  

Better…but not good enough…

Faivre et al Target Oncol 2012 Jun;7(2):127-33 Dreyer et al ESMO 2012; Ann Oncol, 23 (suppl9) abstr 1163P

•  N=25 patients •  Blinded assessment •  RECIST & Choi •  Everolimus or sunitinib

RECIST   Choi  

PR   2   11  

SD   18   8  

PD   2   3  

9  of  18  with  SD  by  RECIST  

converted  to  PR  

Median TTP: PR: 26.1 mo SD: 8.7 mo PD: 3.6 mo; p=0.038

Evolution of NET clinical trial methodology

Patient eligibility: Separate evaluation of carcinoid and pancreatic NETs Well- and poorly-differentiated NETs should be evaluated separately Evidence of disease progression at study entry

Endpoints: PFS recommended where response is not expected OS is not a practical primary endpoint Mindful of potential antitumour effect of SSAs Cross-sectional imaging: CT/MRI (not somatostatin scintigraphy) Biomarkers should be included

Kulke MH et al. J Clin Oncol 2011;29:934–43 SSA = somatostatin analogue

Improving study methodology

QoL assessment – does it matter?

Study   QoL  Assessment  

PROMID   EORTC  QLQ  C30  

RADIANT-­‐3   No  

Suni<nib  A6181111   EORTC  QLQ  C30  

CLARINET   EORTC  QLQ-­‐C30  and  QLQ-­‐GI.NET21  

Many treatment options…

Ramage J K et al. Gut 2012;61:6-32

…and many more to come…

Pavel  Neuroendocrinology  2013;97:99–112  

Chemotherapy: who benefits most?

5-FU, cisplatin and streptozocin regimen

N=79 evaluable patients

 Histological grade predicts response

Response rate: low grade 14% intermediate grade 34% high grade 60% (p=0.025)

 So does mitotic index score (p=0.008) and Ki67

Turner NC et al. Br J Cancer. 2010 Mar 30;102(7):1106-12.

Can we predict patient responses to chemotherapy? We can not predict which patients will respond to most chemotherapy

5-FU, streptozocin, doxorubicin, oxaliplatin etc …

Might we be able to predict response to temozolomide (MGMT*)? RR (0/16) 0% (MGMT+) vs. (4/5) 80% (MGMT-) p<0.001 PFS 9.3 months (MGMT+) vs. 19 months (MGMT-)

Kulke MH et al. Clin Cancer Res 2009;15:338–45 *methyl guanine methyl transferase

Pro

porti

on a

live

1.00

0.75

0.50

0.25

0 0 10 20 30 40 50 60 70

Months

MGMT-intact MGMT-deficient Censored patients MGMT-intact carcinoid tumour

MGMT-deficient pancreatic neuroendocrine tumour

Sequencing therapies

Motzer et al J Clin Oncol 2014; e-pub ahead of print

Sequence  of  everolimus  and  suni<nib  associated  with  similar  outcomes  in  RCC…does  the  same  apply  in  NETs?  

Sponsor: GETNE

RA

ND

OM

ISAT

ION

N=112

Everolimus 10 mg qd

STZ–5-FU STZ–5-FU

Everolimus 10 mg qd

Cross-over upon

progression

Primary endpoint: PFS

Treatment and Assessments: 84 weeks

Phase 3

Patients with advanced progressive pNET

Design: Randomised, open study comparing efficacy of everolimus followed by chemotherapy with STZ-5FU or the reverse sequence, chemotherapy with STZ-5FU followed by everolimus, in advanced progressive pNET

SEQTOR (GETNE1206): Everolimus and STZ–5-FU cross over study in advanced pNET

Sequencing therapies

+ combination therapies + therapies in different settings

Circulating Tumour Cells •  176 patients (90 training set; 85 in validation

set) with measurable metastatic NETs

•  CTCs measured by EPCAM method

•  Number of CTCs in 7.5 mls blood: 1 (49%); 2 (42%), 5 (30%)

•  Presence of CTCs was associated with: –  increased burden –  increased tumor grade –  elevated serum chromogranin A (CgA)

•  The presence of one CTC was associated with

–  worse PFS [HR 6.6, p=0.001] and –  worse OS [HR 8.0, p=0.001]

•  CTCs remained significant in multivariate analysis (inc. grade, tumor burden, and CgA)

Khan et al J Clin Oncol 31:365-372.

May  help  with  risk-­‐stra<fica<on  

Molecular insights

Mutational Analysis •  Microdisect (>80% tumour cells) •  Extract tumour and non-tumour DNA •  Sequence all exomes (Illumina GA IIx) •  Validate mutations (Sanger sequencing)

Jiao et al, Science 2011

  157 somatic mutations in 149 genes

  8-23 mutations per tumour (mean 16)

Somatic mutations in pNET

Discovery  set  

•   n=  10  sporadic  pNETs  •   Non-­‐familial  •   G1/G2  

Valida<on  set  

•   n=58  sporadic  pNETs  •   Non-­‐familial  •   G1/G2  

Somatic mutations in pNET

Gene Discovery set

n=10

Overall (Discovery + Validation)

n=68

MEN1 5 30 (44%) DAXX 3 17 (25%) ATRX 1 12 (18%) PTEN 2 5 (7%) TSC2 2 6 (9%) PIK3CA - 1 (1%)

MEN1 / DAXX / ATRX mutations appear to correlate with prolonged survival

Jiao et al, Science 2011 DAXX = death domain associated protein ATRX = alpha-thalassaemia / mental retardation syndrome X-linked

Gene pNET1

(n=68)

PDAC2

(ductal adenocarcinoma) (n=114)

MEN1 44% 0% DAXX, ATRX 43% 0% mTOR pathway 15% 1% TP53 3% 85% KRAS 0% 100% CDKN2A 0% 25% TGFBR1, SMAD3/4 0% 38%

1 Jiao et al, Science 2011 2 Jones et al Science 2008

Somatic mutations in pNET

•  YY1 regulates mitochondrial function and insulin / IGF signalling

•  T372R mutation enhances transcriptional activity of YY1

•  Mutation associated with older onset of insulinomas

•  YY1 is a target of mTOR inhibition

Somatic mutations in pNET

Cao et al Nat. Commun 2013;4:2810

Somatic mutations in small intestinal NET

•  Whole-­‐exome  and  whole-­‐genome  sequencing  

•  N=55  tumours  from  50  paDents  •  Validated  in  2  addiDonal  cohorts  •  StaDsDcally  significant  mutaDons  in  

only  one  gene:  the  cyclin  dependent  kinase  inhibitor,  CDKN1B,  which  encodes  p27*  

•  Whole-­‐exome  sequencing  •  N=48  small  intesDnal  NETs  •  “Stable  cancers”  (low  frequency  of  

somaDc  single  nucleoDde  variants)  •  Implicated  cancer  pathways:  

— PI3K/Akt/mTOR  — TGF-­‐b  — SRC  oncogene  

Banck et al J Clin Invest 2013; 123(6):2502-2508 Francis et al Nat Genetics 2013;45(12):1483-1487

* controls cell cycle progression at G1

The paradox

  Large studies, previously thought impossible

  Record numbers of patients entering clinical trials

  Moving towards small studies in selected patient sub-groups

Systemic therapy of advanced GEP NETs

Adapted from Lamarca A et al. TJOP. 2014;2:15-25

low

low high

high

fast

+  molecular  profiling?  

+  circulaDng  Tumour  Cells?  

+  circulaDng  biomarkers?  

Summary – a look to the future

•  Histopathology will continue to be refined

•  Clinical trials: more patients; reduced heterogeneity; improved risk-stratification

•  Better understanding of underpinning molecular biology

•  Multiple studies applying our available (and emerging tools) – rational design

•  NETs may be good candidates for the era of “personalised medicine”

Thank you