Precise and complete description of Neuro endocrine tumours Review of literature and classification Ihc differential diagnosis

1. Pathology of NET

2. Neuroendocrine System
• Dispersed system of cells present in the CNS,
PNS and in many organs including classic
endocrine organs, the gut, pancreas, lung, etc.

3. What is a Neuroendocrine Cell?
• “Neuroendocrine” defines the peptide hormone –
producing cells
• These cells have in common the ability for Amine
Precursor (viz. DOPA and 5 OH tryptophan)
Uptake and Decarboxylation - APUD cells

4. Definition of NET
• Neuroendocrine tumors (NET) are neoplasms which
produce and secrete glycopeptide hormones and biogenic
amines and share neural – endocrine markers.
• GEP – NET most common of all NET’s
• Homogenous in terms of morphology but are heterogeneous
in terms of biological and clinical features
Bosman FT, et al. WHO Classification of Tumors of the Digestive System.Lyon, France: IARC Press;2010.

5. Gastroenteropancreatic
Neuroendocrine Tumor
• Standardized histopathological diagnosis and
classification on biopsy or surgical specimen -
basis for prognostic stratification, for optimal
selection of the respective tumor specific
imaging procedure and therapeutic option.

6. Nomenculature issues
1. Endocrine Vs Neuroendocrine
 Neoplastic cells have features of neural and
epithelial cells.
 WHO recommended term – Neuroendocrine.
2. Tumor vs neoplasm
Tumor = mass
Neoplasm = acurate
Widespread acceptance in many systems –
Neuroendocrine tumor (NET).

7. 3. Carcinoid tumor
 Term does not adequately convey the potential for
malignant behavior that accompanies many of these
neoplasms.
 However this term retains widespread colloquial
usage.
Nomenculature issues

8. How to diagnose NET

9. Neuroendocrine Cell
Small Synaptic vesicle
Synaptophysin expression
Neurosecretory granule
with peptide secretion
Chromogranin A at NSG
membrane
N
Blood (Tumor
diameter is 3mm)
Biomarkers

10. Blood biomarkers
Chromogranin A (CgA)
• Sensitivity: CgA
78 – 84%
• Specificity : CgA
71 – 85%
• False positive
- Renal insufficiency
- Hypertension
- PPI
Zatelli MC, et al., Endocr Relat Cancer.2007;14(2):473-482

11. Tissue Diagnosis: FNAC vs Core
Biopsy
Core Biopsy
• More tissue
• Higher comfort level to diagnose
malignancy
• IHC for diagnosis and grading

12. Diagnosis of NET
• Monotonous small round cells with uniform nuclei,
stippled chromatin (salt and pepper)

13. In 1971 Soga and Tazawa described 4 microscopic patterns:
1. Insular (nodular solid nests with peripheral invading cords)
NET - Microscopic Patterns

14. 2. Trabecular (anastomosing trabeculae or ribbons)
NET - Microscopic Patterns

15. 3. Glandular (tubules, acini or rosettes)
NET - Microscopic Patterns

16. 4.Poorly differentiated with no well - organized growth pattern
NET - Microscopic Patterns

17. Markers of neuroendocrine
differentiation – IHC
Non Hormonal Markers
• Chromogranin- acidic proteins in
secretory granules. Type A, B, C
• Synaptophysin
• NSE
• PGP9.5, CD57, CD56, VMAT2
Hormonal markers –
Gastrin (G cells),
Somatostatin (D Cells),
Serotonin (E cells),
Glucagon (L cells)
Calcitonin
CgA
Synap

18. Role of CgA in Dx of NET
Benefits
• Integral part of the membrane of neurosecretory hormone
granules
• Can be detected in the secretory granules of most NET, both
symptomatic and asymptomatic
Taupenot L, Harper KL, O’Connor DT.N Engl J Med.2003;348:1134-1149

19. Role of CgA in Dx of NET
Limitations:
• Many NET of the large bowel and some of the appendix
primarily secrete CgB
• Dependent on no.of neurosecretory vesicles / cell
• CgA may be negative in poorly differentiated NET

20. Role of Synaptophysin in Dx of NET
Benefits:
• Expressed independently of
secretory granules
• Useful in identifying poorly
granulated and poorly
differentiated NET that may not
exhibit CgA
Chetty R et al. Arch.Pathol Lab Med 2008;132:1285-1289
Limitations:
• Expression is not limited to
neuroendocrine cells

21. Unknown primary
• For metastatic GEP-NET with unknown primary
evidence of specific transcription factors in addition to
hormones is important.

22. Liver metastasis
CgA

23. Islet 1 (IsI1) expression is a reliable marker for
pancreatic neuroendocrine tumors and their
metastases1
Liver mts
IsI1
1.Schmitt AM et al.Am J Surg Pathol.2008 Mar;32(3):420-5.
PNET – has liver / LN mets by the time of diagnosis

24. CDX2 as a marker of intestinal EC-cells and related
well-differentiated neuroendocrine tumors1
1. La Rosa S et al Virchows Arch.2004 Sep;445(3):248-54
CDX2
1. CDX2 - Positive in 90% of NET of ileum and appendix but
not in pulmonary NET
2. TTF -1 is expressed in 50% of bronchopulmonary NET but
only <2% of GEP - NET

25. Stomatostatin Receptors
• Somotostatin receptor (SSTR) are expressed on the
surface of Neoplastic Neuroendocrine cells
• 5 types of SST receptors
• SSTR 2A has greatest binding affinity to somatostatin
analogues

26. sstr2 in NETs
• Almost 40% of the patients with NET have very
strong staining for sstr2
Missiaglia E, et al. J Clinic Oncol.2010, 28(2):245-255

27. SSTR IHC: 77% correlates with Octreotide
Scintigraphy
107 Cases (41 pre-operative samples)
Volante M.et al Mod Pathol.2007 Nov;20(11):1172-1182

28. Functionality issue of NET
• Functional NETs - defined based on the presence of
clinical symptoms due to excess hormone secretion by
the tumor
• Functional status of the tumor is defined by clinical
findings and not by pathologic appearance or IHC
profile (eg: carcinoid syndrome)
• Non functional NET’s – associated with symptoms
related to mass

29. • Pathologic diagnosis of functioning NETs should be
the same as for analogous nonfunctioning NETs of the
same anatomic site, with the descriptive functional
designation appended to the diagnosis when there is
knowledge of a clinical syndrome.
Functional status need not be included in the
pathology report
Functionality issue of NET

30. 0 24 48 72 96 120
0 24 48 72 96 120
Cumulative
Survival
Probability
Cumulative
Survival
Probability
Time of survival (months)
Time of survival (months)
Impact of histology, proliferation, &
stage on prognosis. P-NEN
St.l (108 pts)
St.ll (16 pts)
St.lll (54 pts)
St.lV (96 pts)
0 – 5% (152 pts)
>5 – 20% (63 pts)
>20% (22 pts)
Ki 67 levels
0 24 48 72 96 120
Cumulative
Survival
Probability
Time of survival (months)
WDET-B (51 pts)
WDET-U (56 pts)
WDEC (139 pts)
PDEC (28 pts)
WHO 2000 classification
TNM coding
Scarpa et al Mod Pathol 2010

31. NENs, NETs, NECs & MANECs of the GEP
Comparison of Classifications
Bosman FT, et al. WHO Classification of Tumours of the Digestive System. Lyon, France: IARC Press; 2010.
WHO 1980 WHO 2000 WHO 2010
Carcinoid WDET- Benign
Uncertain
WDEC
PDEC/ SCC
NET G1
NET G2
NET G3
NEC G3
Mucocarcinoid
Mixed carcinoid and
adenoca
Mixed exocrine
endocrine carcinoma
(MEEC)
Mixed adeno-
neuroendocrine
carcinoma (MANEC)
Pseudotumour
lesions
Tumour-like lesions Hyperplastic and
preneoplastic lesions

32. WHO 2010 Update
Classification, Staging, Prognosis
Working principles
– New classification – retains basic criteria of WHO 2000 classification
– All GI NET’s have a malignant potential
– Separation of histological grading & staging parameters
– “Neuroendocrine neoplasm/tumor” includes well and poorly
differentiated tumors
– Benign & low malignant highly diff NET – jointly referred as
Neuroendocrine tumors (G1(synonym for carcinoid) & G2)
– Well differentiated NET – G1,G2,G3
– Neuroendocrine Carcinoma – All poorly differentiated NET – G3(small
cell & large cell NEC)

33. NET – Tumor differentiation by histology

34. Well differentiated NET - Histology
• Well - differentiated tumors have characteristic organoid
arrangement of the tumor cells, with nesting, trabecular or
gyriform patterns.
• Cells are uniform and produce abundant neurosecretory
granules, reflected in the strong and diffuse immunoexpression
of neuroendocrine markers Cg A and synaptophysin.

35. Poorly differentiated NET - Histology
• Poorly differentiated NETs less closely resemble non-
neoplastic neuroendocrine cells and have a more sheetlike
or diffuse architecture, irregular nuclei, and less cytoplasmic
granularity.
• Immunoexpression of neuro-endocrine markers is usually
more limited.

36. Can pathologists provide predictive
markers?
In a well or moderately differentiated NET, even in the
absence of a positive octreoscanTM , somatostatin
analogue therapy can have benefit
1. Zatelli MC et al. Horm Metab Res.2003.35(6):349-354; 2. Vezzosi D et al. Clin
Endocrinol (Oxf).2008,68(6): 904-911; 3. Vezzisi D et al.Eur J Endoscrinol.2005,
152(5):757-467.
Differentiation of well differentiated from poorly differentiated NET is the
most important pathological assessment as therapy defers

37. Grade versus differentiation of NET
Differentiation Grade
Well differentiated Low grade G1 – relatively indolent
Intermediate grade G2 - moderately
aggressive
High grade G3 – ext aggressive
Poorly differentiated High grade G3 – ext aggressive
•Grade refers to the inherent biologic aggressiveness of the tumor.
The proliferative index is inherently linked to the grade of NET

38. Mitotic Count
• The simplest method to determine the
proliferative index is to count mitotic figures, and
is necessary for complete pathology reports.
• The mitotic rate should be expressed based on
the number in 10 high power fields (2 mm2)
• A total of 50 fields (10 mm2) should be counted

39. Grading by Mitotic Counts
Rindi G et al. Circhows Arch (2007) 451:757 – 762
American Joint Committee On cancer.AJCC Cancer Staging System.Seventh Edition

40. Ki 67 widely used Europe than in US

41. Ki67 Counting
• Options to quantify Ki67
 Systematically counting manually a defined number of
tumors cells (500 – 2000) and calculating the positive
percentage
 Using a computerized digital image analysis system to
measure the positive percentage
 A general “eyeballed” estimate of the percentage of
positive cells
• Proliferative rate - Provides significant prognostic
information for NET.

42. Example
Cell block
CgA
Core biopsy

43. Ki 67
Cell block / Biopsy - Impossible to count mitotic figures in 40 – 50 / hpf.
Limited tumor tissue
Ki67 staining - more accurate

44. Grading of NET According to Ki67 index
The result should be reported as a single percentage, reflecting the
average of the regions counted, rather than a range of values.

45. 2010 WHO GI NET
Grading by Mitotic Counts vs Ki-67
G1 G2 G3
Morphology low grade low grade high grade
H & E
Mitotic count <2 2 - 20 >20
(10 HPF)
IHC
Ki67 index <2 3 – 20 >20
(% of positive cells per 100 counted cells)

46. Mib 1 Ki67
WD G3 G3 – high grade malignant behavior >20%

47. MANEC
• Carcinoma phenotype that is recognizable as both
adenocarcinoma and neuroendocrine carcinoma
• Each component exceeds at least 30% of all
neoplastic cells
• Both components should be graded
• The identification in adenocarcinomas of scattered
neuroendocrine cells (<30%) does not qualify for
MANEC

48. Staging issues
• American Joint Committee on Cancer (AJCC) –
Anatomic site specific TNM staging for NETs
• European Neuroendocrine tumor society
(ENETS) (2006, 2007)
• Considerable over lap with some differences
between these two
• For Appendix & Pancreas – use both ENETS &
AJCC TNM staging as they differ in definitions of
T stages of tumor

49. Pancreatic-NETs- TNM staging

50. NET - Minimum Pathology Data Set
• Diagnostic term
• Anatomic site of tumor
• Size (3 dimensions)
• Tumor histopathology
• Morphology, extent of invasion (T) IHC staining, multicentric
disease, non-ischemic tumor necrosis, vascular invasion,
perineural invasion, lymph node metastases (total no/ number
positive - N)
• Proliferative activity grade (mitotic rate, Ki67 index)
• TNM staging (specify staging used)
• Resection margins (positive/negative/close)
Am J Surg Pathol; 2010:34;300-313

51. SUMMARY
• All GEP NET’s are of low grade malignant potential
• Use WHO 2010 classification
• Evidence of neuroendocrine nature of the tumor (morphology
& IHC for neuroendocrine markers)
• Histological distinction between well and poorly differentiated
tumors
• Proliferation based grading (Ki67 mandatory for grading
(G1,G2,G3)
• PTNM staging with reference of specific system used