3/23/2017
Disclosure Statement
• Dr. Klimstra receives royalty payments from Up To
Date and the American Registry of Pathology
“When Immunostains Can Get You Into
Trouble” (and how they can help you out):
Neuroendocrine Neoplasms
PET‐CT
Arthur Purdy Stout Society – March 5, 2017
David S. Klimstra, MD
Chairman, Department of Pathology
James Ewing Alumni Chair of Pathology
Attending Pathologist
Memorial Sloan Kettering Cancer Center
Professor of Pathology and Laboratory Medicine
Weill Cornell Medical College
Differentiation:
Neuroendocrine Neoplasms
• Diverse
“Extent of resemblance of the cells of a
neoplasm to their
normal cellular counterparts”
but related groups of tumors
• Lung, thymus, pancreas, GI tract, other sites
• Characteristic pathologic features
 Usually closely linked to grade (for NETs)
 Immunohistochemical evidence of neuroendocrine differentiation
(chromogranin / synaptophysin / CD56)
• Range of biological aggressiveness
• Can be either well differentiated tumors or poorly differentiated carcinomas
Well Differentiated vs. Poorly
Differentiated Neuroendocrine Neoplasms
Differentiation: Immunohistochemistry

Two different families

Both share neuroendocrine
CarcinoidTumor
differentiation
Chromogranin A
Synaptophysin

Can be difficult to distinguish

Fundamentally different

Cell of origin

Relationship to non-NE neoplasia

Genetic background

Clinical aggressiveness

Treatment
Small Cell Carcinoma
1
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Poorly
Well
Differentiated Differentiated
Classification of Pulmonary
Neuroendocrine Neoplasms
Low Grade
Carcinoid Tumor
Intermediate Grade
Atypical Carcinoid Tumor
High Grade
Small Cell Carcinoma
WHO 2010 Grading of GEP-NETs
Grade
Mitoses
G1
< 2 / 10 H.P.F.
< 3%
G2
2-20 / 10 H.P.F.
3-20%
G3
> 20 / 10 H.P.F.
> 20%
Large Cell Neuroendocrine Carcinoma
Ki-67 Index
Poorly Differentiated (High Grade ) Neuroendocrine Carcinoma
Pancreatic NETs:
Overall Survival by Grade
Terminology for Neuroendocrine Neoplasms:
WHO 2010/2015


Well Differentiated NETs

Well differentiated NET (pancreas, GI tract, etc.)

Carcinoid tumor / atypical carcinoid tumor (lung, thymus)
Poorly Differentiated NECs

Small cell carcinoma

Large cell neuroendocrine carcinoma

Mixed neuroendocrine carcinoma (with component of
adenocarcinoma, squamous cell carcinoma, etc.)
Rindi et al., J Natl Cancer Inst 2012; 104: 764
Use of Immunohistochemistry in
Neuroendocrine Neoplasms
Recognition of Neuroendocrine Differentiation
Diagnosis (recognition of neuroendocrine differentiation)
• Delineation of primary site
PET-CT
Well Differentiated Neuroendocrine (Carcinoid) Tumor
PET-CT
Determination of grade, classification, prognosis
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Recognition of Neuroendocrine Differentiation:
Recognition of Neuroendocrine Differentiation
Immunohistochemical Markers
• Conventional markers
 Chromogranin A
 Synaptophysin
• CD56 (neural cell adhesion molecular / NCAM)
• Neuron specific enolase (NSE)
• CD57 / Leu7
PET-CT
• PGP9.5
PET-CT
• Novel markers
• Synaptic vesicle protein 2 (SV2)
• Achaete-scute complex homolog (MASH1)
Poorly Differentiated Neuroendocrine Carcinoma
• Insulinoma-associated protein 1 (INSM1)
• Neuroendocrine secretory protein 55 (NESP55)
Sensitivity of Chromogranin A
Sensitivity of Synaptophysin
% Negative (n)
Pulmonary carcinoid tumor
3% (368)
Duodenal NET
7% (61)
Ileal NET
4% (51)
Pancreatic NET
17% (108)
Thymic carcinoid tumor
19% (95)
Pheochromocytoma
1% (182)
Pulmonary small cell carcinoma
57% (596)
Pulmonary large cell NE carcinoma
37% (252)
Source: Immunoquery®
Small Bowel Tumor with Mesenteric Deposits
% Negative (n)
Pulmonary carcinoid tumor
2% (333)
Pulmonary atypical carcinoid tumor
10% (115)
Rectal NET
4% (28)
Ileal NET
2% (58)
Pancreatic NET
1% (75)
Thymic carcinoid tumor
21% (101)
Pheochromocytoma
2% (188)
Pulmonary small cell carcinoma
25% (97)
Pulmonary large cell NE carcinoma
17% (268)
Source: Immunoquery®
Tumor positive with somatostatin receptor scintigraphy
Chromogranin
Synaptophysin
CD56
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Specificity of CD56 for Neuroendocrine Neoplasms
Specificity of Chromogranin and Synaptophysin
% Chromogranin
Positive (n)
% Positive (n)
Lung adenocarcinoma
% Synaptophysin
Positive (n)
3% (639)
Lung squamous cell carcinoma
9% (520)
2% (287)
Renal cell carcinoma
17% (455)
Breast colloid carcinoma
18% (112)
41% (105)
Pancreatic solid pseudopapillary neoplasm
98% (152)
Pulmonary adenocarcinoma
2% (689)
11% (689)
Pulmonary squamous cell carcinoma
2% (586)
4% (584)
Breast ductal carcinoma
GIST
1% (88)
Adrenal cortical carcinoma
2% (81)
Adrenal cortical carcinoma
63% (269)
Renal cell carcinoma
2% (379)
Clear cell sarcoma
Melanoma
88% (49)
Melanoma
7% (130)
Adult granulosa cell tumor
100% (40)
Synovial sarcoma
51% (68)
Rhabdomyosarcoma
76% (34)
Granular cell tumor
95% (58)
25% (59)
Glioma
36% (148)
11% (114)
Dendritic cell tumor
94% (164)
Nk T-cell lymphoma
74% (267)
Chloroma
27% (62)
Source: Immunoquery®
Source: Immunoquery®
Immunohistochemical Staining for the Diagnosis of
Well Differentiated Neuroendocrine (Carcinoid) Tumors
• Sensitivity
•
For most primary sites, chromogranin and synaptophysin are highly sensitive
•
When used in combination, ~95% positive
(Am J Surg Pathol 2010;34:300-313)
• Specificity
•
Certain specific non-NE neoplasms stain predictably
•
2 - 5% idiosyncratic staining of other neoplasms
PET-CT
Are immunohistochemical stains for “general neuroendocrine markers”
mandated as necessary in all cases?
• Is it necessary?
•
•
•
Specific differential diagnoses
Metastatic disease
Agree strongly
23.53%
4
Agree with minor reservation
11.76%
2
Agree with major reservation
0%
0
Disagree with minor reservation (disagree mildly)
11.76%
2
Disagree with major reservation (disagree moderately)
23.53%
4
Disagree strongly
29.41%
5
100%
17
What about histologically typical primary tumors?
Immunohistochemical Staining for the Diagnosis of
Poorly Differentiated Neuroendocrine Carcinomas
Totals
NO AGREEMENT
Large Cell Neuroendocrine Carcinoma
• Small cell carcinoma
•
NOT mandated when classic morphologic findings are present
•
Chromogranin or synaptophysin positive in ~75% of cases
•
Consider ruling out alternatives (e.g., basaloid squamous cell carcinoma, spindle cell carcinoid tumor,
primitive neuroectodermal tumor, etc.)
• Large cell neuroendocrine carcinoma
•
NE marker expression required for diagnosis
•
Which makers?
•
•
•
Must be positive in 100% of cases (by definition)
Thoracic vs. gastroenteropancreatic
How strongly / diffusely positive?
Chromogranin
WHO 2015: “The diagnosis of LCNEC requires immunohistochemistry for confirmation of neuroendocrine differentiation. In decreasing
order of frequency, NCAM/CD56 stains 92–100% of LCNEC cases, followed by chromogranin A in 80–85%, and synaptophysin in 50–60%.
NCAM/CD56 needs a note of caution because of its lower specificity for neuroendocrine differentiation in lung cancer, but it is the
most sensitive marker in the appropriate morphological context of a neuroendocrine neoplasm. Chromogranin A and synaptophysin
are the most reliable stains for diagnostic accuracy in distinguishing LCNEC from non-neuroendocrine tumours, and one positive marker
is enough if the staining is clear-cut.”
Chr
Syn
CD56
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Large Cell Neuroendocrine Carcinoma
Chr
Syn
CD56
“Large Cell” Lung Carcinoma
Chromogranin
Large Cell Carcinoma with Neuroendocrine Morphology
• Large Cell Undifferentiated Carcinoma
• Large Cell Neuroendocrine Carcinoma
• Large Cell Carcinoma with Neuroendocrine Morphology
• Large Cell Carcinoma with Neuroendocrine Differentiation
Chr, Synapto, CD56
Large Cell Carcinoma with Neuroendocrine Differentiation
Genomic subgroups in LCNEC
Adeno
35
30
25
20
15
10
5
0
Number of altered genes per case
Gene alterations typical of:
SCLC
TP53
RB1
KRAS
78%
40%
22%
STK11
40%
MYCL
7%
SCLC
MYCN
IRS2
SOX2
2%
4%
11%
SCLC/SqCC
FGFR1
PTEN
4%
4%
MEN1
Chromogranin
total loss
Loss
total amp
Gain
total mut
Mutation
↓
↓
↓
SCLC‐like
↓
NSCLC‐like
(predominantly adeno‐like)
↓
Loss
Gain
Missense mutation
Truncating mutation
↓ Loss by IHC/WT gene
Carcinoid‐
like
Rekhtman et al., Clin Cancer Res2016; 22: 3618
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Mixed Adenocarcinoma Neuroendocrine Carcinoma
“Combined” Neuroendocrine Carcinomas
• At least 30% of both neuroendocrine and non-neuroendocrine
components
•
•
Adenocarcinoma most common (“MANEC”)
Also squamous, pancreatic acinar, other exocrine types
• Neuroendocrine component usually poorly differentiated; small cell
carcinoma or LCNEC
• Lung, colon, pancreas, gallbladder, etc.
• Various combinations
•
•
•
Biphasic
“Waxing and waning”
Amphicrine
• Aggressive biology; evolving genomic data; treatment as small cell
carcinoma (?)
Mixed Adenocarcinoma Neuroendocrine Carcinoma
Synaptophysin
Pancreas Mixed Acinar Neuroendocrine Carcinoma
Chromogranin
Chymotrypsin
Chromogranin
Adenocarcinoma with Neuroendocrine
Differentiation

Morphologically adenocarcinoma


Neuroendocrine component <30%
Neuroendocrine differentiation detected

incidentally
Focal NE differentiation: no prognostic impact

Role of IHC for NE markers ? ? ?
Chromogranin
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3/23/2017
Synaptophysin
Chromogranin
Synaptophysin
Chromogranin
Neuroendocrine Differentiation in Carcinomas:
Treatment Implications

Small cell carcinoma (lung or extrapulmonary)

 Platinum + etoposide
Large cell neuroendocrine carcinoma



Commonly treated like small cell carcinoma
Few compelling studies; no randomized trials
Neuroendocrine Neoplasms:
Determination of Grade,
Classification, and Prognosis
Carcinoma with neuroendocrine morphology / differentiation
/ features / minor elements / etc.

Who knows????
WHO 2010 Grading of GEP-NETs
Grade
Mitoses
G1
< 2 / 10 H.P.F.
Ki-67 Index
< 3%
G2
2-20 / 10 H.P.F.
3-20%
G3
> 20 / 10 H.P.F.
> 20%
ENETS/WHO Grading of GEP-NETs: Provisions

Count mitoses in 50 high power fields

Assess Ki67 based on counting 2000 (500) cells

Assess Ki67 in “hot spots”

If mitotic rate and Ki67 are discordant, assign higher grade
Poorly Differentiated (High Grade ) Neuroendocrine Carcinoma
Ki67
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Ki67 Labeling Index of NETs
Digital Image Analysis for Ki67 Quantification
• Strong predictor of prognosis
• Correlates well with mitotic index
• Sharp separation of well and poorly
differentiated neuroendocrine neoplasms
• Methods of Assessment
• Manual counting (2000 cells per ENETS)
• “Eyeballed” estimate
• Digital image analysis
Ki67% = 1.7
Consistency of Ki67 Determination by
Digital Image Analysis, Manual Cell Counting,
and “Eyeballed” Estimate
Determining the Ki67 Labeling Index of NETs: How We Do It
Intraclass Correlation
(ICC)
95% Confidence Interval
0.98
0.97-0.99
0.88
0.80-0.93
0.13
0.05-0.37
Image Analysis vs. Manual
Counting
Image Analysis vs. Eyeballed
Estimate
(Mean of 20 observers)
Eyeballed Estimate
Interobserver
(n=20)
Tang et al. Am J Surg Pathol 2012; 36: 1761-70
Ki67: variation in labeling intensity
Courtesy of Dr. Laura H. Tang
My count of Ki67
positive cells in this
highlighted area is … ?
A.
B.
C.
D.
<3
4-6
7-10
>10
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Ki67 Heterogeneity in PanNETs
Ki67
Inst. 1
Inst. 2
Inst. 3
Heterogeneity of Ki67 Labeling in NETs:
Impact on Prognostic Significance of Grading
Ki67 on virtual
biopsies and on
whole sections
“Virtual biopsy”
TMA
45 resected hepatic
metastases of WD NETs
Heterogeneity of Ki67 Labeling in NETs:
Impact on Prognostic Significance of Grading
• 47% of cases with G1 vs. G2 heterogeneity
• Define grade based on highest Ki67 on whole
sections:
– G2 identified in 48% of core biopsies (3 cores)
– G2 identified in 35% of core biopsies (1 core)
– Predictive value of G1 on core biopsy:
• 65% (3 cores); 59% (1 core)
Yang et al., Am J Surg Pathol 2011; 35:853-60
Ki67 and Mitotic Rate Discordance in PanNETs
Ki67 and Mitotic Rate Discordance in PanNETs
297 WD PanNETs with Ki‐67 data (1984‐2009)
264 Mitotic G1
Mitotic rate: <1 per 10 hpf (G1)
Ki-67: 15% positive (G2)
165 Ki‐67 G1
99 Ki‐67 G2
36% discordance
33 Mitotic G2
8 Ki‐67 G1
25 Ki‐67 G2
McCall et al., Am J Surg Pathol 2013; 37: 1671-7
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Ki67 and Mitotic Rate Discordance in PanNETs
1.0
36% discordance
0.6
0.2
264 Mitotic G1
p < 0.01
0.4
33 Mitotic G2
Percentage Surviving
0.8
297 WD PanNETs with Ki‐67 data (1984‐2009)
Ki-67 G2/mitotic G1 PanNETs have
decreased overall survival
165 Ki‐67 G1
8 Ki‐67 G1
K1M1
K2M1
25 Ki‐67 G2
0.0
99 Ki‐67 G2
0
5
McCall et al., Am J Surg Pathol 2013; 37: 1671-7
10
15
20
25
Survival in Years
Well Differentiated PanNET
What about G2 / G3
discordance??
(well differentiated tumor vs.
Mitotic rate = 8 / 10 HPF
Mitotic rate = 12 / 10 HPF
poorly differentiated carcinoma)
Ki67 = 45%
Poorly Differentiated Neuroendocrine Carcinoma
Ki67
Chromogranin
Ki67 = 55%
Progression of Low Grade to High Grade Neuroendocrine Tumor
Mitoses <1/10 HPF
Mitoses 13/10 HPF
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Mixed Ductal Neuroendocrine Carcinoma of Pancreas
Ki67 = 2%
G1
Ki67 = 45%
G3
Tang et al., Clin Cancer Res 2016; 22: 1011
Genetics of Neuroendocrine Neoplasms of the Pancreas
Gene
Small Cell
Large Cell NEC
W.D. PanNET
Ductal ACa
Small Cell Lung CA
KRAS
25%
33%
0%
>90%
0‐10%
CDKN2A
11%
50%
0%
80‐95%
0‐10%
100%
90%
4%
75%
80%
SMAD4
0%
10%
0%
55%
0%
RB1
89%
50%
0%
13%
90%
DAXX/ATRX
0%
0%
43%
0%
MEN1
0%
0%
44%
0%
15%
1%
TP53
mTOR genes
0%
Yachida et al., Am J Surg Pathol 2012; 36: 173
Jiao et al., Science 2011; 331: 1199
Conclusion:
Predictive and prognostic factors for treatment and
survival in 305 patients with advanced gastrointestinal
neuroendocrine carcinoma (WHO G3)
• Reviewed clinical data on advanced stage G3 NECs, 20002009
•
Ki67 > 20%
• 252 patients received chemotherapy (platinum-based)
•
•
•
Median survival = 11 mos.
Response rate = 31%
Stable disease rate = 33%
 Ki67 < 55% predicted a lower response rate (15% vs 42%, p < 0.001)
 Ki67 < 55% predicted a better survival (14 vs 10 months, P < 0.001)
Sorbye et al., Ann Oncol 2013; 24: 152-60
Survival of High Grade Neuroendocrine
Neoplasms of the Pancreas
Some G3 NETs with Ki67 20-55%
may be well differentiated
biologically!!
(“Well Differentiated NET with an
Elevated Proliferative Rate” or
“Well Differentiated NET, G3”)
Basturk et al., Am J SurgPathol 2015; 39: 683-690
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PD NE Carcinoma
WD NE Tumor
Grading of Pancreatic Neuroendocrine Neoplasms (WHO 2017)
Well differentiated NE tumor*
Poorly differentiated NE carcinoma*
Grade
Mitoses
Ki-67 Index
Grade
G1
<2 / 10 HPF
</= 2%
Carcinoma
NE Tumor
Lower Grade
Stable Disease
G2
2-20 / 10 HPF
3-20%
G3**
>20 / 10 HPF
>20%
NE Carcinoma
High Grade
*Organoid architecture, “well differentiated”
cytology, absence of non-neuroendocrine carcinoma
components, may have components of G1 or G2,
usually strong immunoexpression of general NE
markers
Grade Progression
High Grade
Rapid Disease
Progression, Death
Disease Progression
G3**
Mitoses
>20 / 10 HPF
Ki-67 Index
>20%
*Small cell carcinoma and large cell NE carcinoma;
less organoid architecture, classic cytology of small
cell and large cell NE CA, absence of G1 or G2 NE
components, may have non-neuroendocrine
carcinoma components, less diffuse immunoexpression
of general NE markers
**mitoses >20/10 HPF; Ki67 >20% and usually >50%
**mitoses usually <20/HPF; Ki 67 >20% but usually
<50%
Two Pathways to the Development of High Grade (G3) NE Neoplasms
G1
G2
G3
How to distinguish G3 NEC (esp. large
cell NE carcinoma) from G3 NET?
G3
WDNET
PDNEC
0
10
20
30
40
50
60
70
80
90
100
Ki67%
Pancreatic G3 NE Neoplasms
Large Cell NEC
G3 NET
How to distinguish G3 NEC (esp. large cell
NE carcinoma) from G3 NET?
• Clinical clues
• History of well differentiated NET?
• Octreotide scan positive?
• FDG-PET positive?
• Morphologic clues
• Lower grade component?
• Non-neuroendocrine component?
• Mitotic rate?
• Molecular clues
• Status of TP53, RB1, DAXX, ATRX, MEN1
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Well Differentiated PanNETs (G1-3)
Exhibit a Different Molecular Phenotype from
Poorly Differentiated NECs (G3)
PD-NEC
PD-NEC
p53
TP53
RB1
DAXX /
ATRX
MEN1
WD‐PanNET
4%
0
43%
44%
PD‐PanNEC
56%
72%
0
0
p53
Jiao et al. Science 2011; 331: 1199
Yachida et al., Am J Surg Pathol 2012; 36: 173
WD-NET
Rb
Rb
DAXX
Tang et al., Am J Surg Pathol 2016; 40: 1192
Classification of 33 High Grade Pancreatic Neuroendocrine Neoplasms by Secondary Evidence
Immunohistochemical
Abnormalities
DAXX
ATRX
DAXX
DAXX
ATRX
DAXX
ATRX
DAXX
DAXX
p53/Rb
p53/SMAD4
p53/Rb
p53/Rb
p53
DAXX
Rb
p53
Rb
p53/Rb
Rb
p53
Other Histologic Components
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
G1/G2 WD-NET
Ductal adenocarcinoma
G1/G2 WD-NET
Ductal adenocarcinoma
Ductal adenocarcinoma
Ductal adenocarcinoma
Confirmed Classification
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
PD-NEC
PD-NEC
PD-NEC
PD-NEC
PD-NEC
Undetermined
WD-NET
PD-NEC
PD-NEC
PD-NEC
PD-NEC
PD-NEC
PD-NEC
PD-NEC
Disease Specific Survival of High Grade (G3) Pancreatic
Neuroendocrine Neoplasms
100
18/19 (95%)
morphologically
ambiguous high grade
pancreatic
NEneoplasms
successfully classified
Tang et al., Am J Surg Pathol 2016; 40: 1192
Percent survival
19/33 (58%) of
high grade (G3)
pancreatic NE
neoplasms were
morphologically
ambiguous
Initial Consensus
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
WD-NET
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
PD-NEC-LCC
PD-NEC-LCC
PD-NEC-LCC
PD-NEC-SCC
PD-NEC-SCC
PD-NEC-SCC
PD-NEC
PD-NEC
WD-NET (N=20)
PD-NEC
(N=12)
75
50
25
p<0.0001
0
0
50
100
150
Months
Tang et al., Am J Surg Pathol 2016; 40: 1192
Sequencing of Pancreatic Neuroendocrine Neoplasms at MSKCC
p53
p53
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Distinction of G3 NEC from G3 NET:
Practical Issues
• Primary site
–
Pancreas
–
Other GI / pulmonary NETs
•
•
•
•
•
•
Most common
DAXX/ATRX, MEN1
WD G3 NETs uncommon
Formal WHO classification pending
p53, Rb, associated exocrine elements for PD
Morphology for WD
• Role of Ki67
–
–
>50% = usually PD NEC
<50% = either WD NET or PD NEC
• Role of mitotic rate
–
–
<20 per 10 HPF = WD NET
>20 per 10 HPF = PD NEC
Use of Immunohistochemistry in
Neuroendocrine Neoplasms: Conclusions
• IHC is needed for neuroendocrine neoplasm diagnosis, classification,
and grading
• Limitations exist in interpretation and significance
• Exercise pragmatism, not nihilism
 IHC is just one tool in the diagnostic arsenal – use morphology, clinical
findings, molecular data, and common sense!
14