ESP / ESMO: Diagnostic and therapeutic
advances in neuroendocrine tumours
Hormonally active and non-active
neuroendocrine tumours of the
gastrointestinal tract
Aurel Perren
Institute of Pathology
University of Bern
ECP, Köln 2016
1
Programm pathology:
1. Classifikation of NEN: WHO 2017
i. Grading
ii. Concept of differentiation
iii. Reasons for changing WHO classification
2. Diagnostic biomarkers
i. When to use hormones
ii. Transcription-factors
3. Predictive biomarkers
MBI (Ki67): Grading
<3
TNM-Grading: Evidence pNET
JNCI 2012, Rindi et al.
TNM-Grading: Evidence NET
270 NET patients after PRRT
EJNMMI; 2016, Brunner et al
New WHO Klassifikation of NEN 2010
old
1. Neuroendocrine Tumor, NET G1
Grading
<2% MIB <2 Mitosis
2. Neuroendocrine Tumor, NET G2
3. Neuroendocrine carcinoma, NEC
(small or large-cell)
+TNM Staging
Bosman FT, Carneiro F, Hruban RH, Theise ND WHO Classification of Tumours of the Digestive System, 2010
Differentiation
WHO Classification 2017 (pNET)
1. Neuroendocrine Tumor, NET G1
Grading
<3% MIB <2 Mitosis
2. Neuroendocrine Tumor, NET G2
3a. Neuroendocrine Tumor, NET G3
3b. Neuroendocrine carcinoma, NEC
(small or large-cell)
Differentiation
+TNM Staging
Programm pathology:
1. Classifikation of NEN: WHO 2017
i. Grading
ii. Concept of differentiation
iii. Reasons for changing WHO classification
2. Diagnostic biomarkers
i. When to use hormones
ii. Transcription-factors
3. Predictive biomarkers
NEC G3
NET G3
NET common features
Neuroendocrine
markers
Syn
Growth patterns
Crg-A
Ki-67 in NET G3 lower
13
AJSP 2015, Basturk et al.
Programm pathology:
1. Classifikation of NEN: WHO 2017
i. Grading
ii. Concept of differentiation
iii. Reasons for changing WHO classification
2. Diagnostic biomarkers
i. When to use hormones
ii. Transcription-factors
3. Predictive biomarkers
G3 NEN, response to therapy
15
Ann Oncol 2013, Sorbye et al.
G3 NEC, genetically = NET
P53 RB mutations
11 small cell NEC
p53 RB Mutation
9 large cell NEC
DAXX/ATRX/Men1/mTOR
11 pNET
16
AJSP 2012, Yachida et al.
Diagnosis NET G3
AJSP 2016, Tang et al.
How to do it? Ki67 >20%:
Small-cell
NEC
Large-cell
not allways
search for wd areas
search for adeno-ca areas
heterogenous Ki-67- low Ki-67
progression from wd NET? -
NET G3
IHC markers
DAXX/ATRX loss, MEN1 loss
P53 / Rb
NET G3
NEC G3
Clin Cancer Research 2015, Tang et al.
Programm pathology:
1. Classifikation of NEN: WHO 2017
i. Grading
ii. Concept of differentiation
iii. Reasons for changing WHO classification
2. Diagnostic biomarkers
i. When to use hormones
ii. Transcription-factors
3. Predictive biomarkers
Immuno for Hormones?
1. When you need them
i. (potentially) multiple tumors
ii. CUP
iii. Confirm clinical syndrome
Gastrin
Glucagon
Insulin
PP
Somatostatin
Unclassified
Lk Metastasen
Endokrine Tumore
> 5 mm
< 5 mm - 1 mm
< 1 mm - 0.5mm
endokrine Hyperplasie
sstr2 +
< 0.5 mm
Anlauf et al. AJSP 2008
Cdx-2 Ileum
Isl1 ileum
Cdx-2 peripancreatic
Isl1 peripancreatic
Liver metastasis, NET G1/G2
Transcription-factors
Ileum, Appendix
Pancreas, duodenum
Lung, (MTC)
Cdx-2
Isl-1
Ttf-1
This does not work for NEC!
Programm pathology:
1. Classifikation of NEN: WHO 2017
i. Grading
ii. Concept of differentiation
iii. Reasons for changing WHO classification
2. Diagnostic biomarkers
i. When to use hormones
ii. Transcription-factors
3. Predictive biomarkers
NEN: Common features
AJSP 2012, Körner et al.
Sstr2 on paraffin
270 patients with DOTATOC treatment
EJNMMI; 2016, Brunner et al
MGMT expression
IHC for MGMT, loss in
subset of pNET
MGMT promotor
methylation correlates
Response to TMZ
better if MGMT loss
Kulke et al, (2006) JCO
Walter et al, (2015) BJC
The future?
pNET,
RNA expression profiles:
4 Subgroups
pNET,
miRNA expression
profiles: 2 Subgroups
pNET,
Methylation data
- Ch. Thirlwell
Needs
• Standardization
• Interdisciplinary collaboration
• Clinical trials
• Follow-up
• Networks
• Tissue banks
Survival
AJSP 2015, Basturk et al.
Unpublished data NEC vs. NET
200 G3 NEN of Nordic NEC study
Review by 4 pathologists
interobserver wd vs pd: 0.7-0.78
High correlation with Ki-67
31
Tang et al.
NET G3 vs NEC G3
Tang et al. In prep
More than Ki-67
Survival
33
Tang et al.
Tissue biomarkers:
1. Diagnostic
- Synaptophysin, Chromogrannin-A,
others if neded
- Ki-67
- DAXX/ATRX, P53, RB
2. Predictive
- Sstr-2?
- MGMT?