When Immunostains Can Get You Into Trouble (and how they can help you out): Neuroendocrine Neoplasms

When Immunostains Can Get You Into Trouble (and how they can help you out): Neuroendocrine Neoplasms 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

Disclosure Statement Dr. Klimstra receives royalty payments from Up To Date and the American Registry of Pathology PET-CT

Neuroendocrine Neoplasms Diverse but related groups of tumors Lung, thymus, pancreas, GI tract, other sites Characteristic pathologic features Immunohistochemical evidence of neuroendocrine differentiation (chromogranin / synaptophysin / CD56) Range of biological aggressiveness Can be either well differentiated tumors or poorly differentiated carcinomas

Differentiation: Extent of resemblance of the cells of a neoplasm to their normal cellular counterparts Usually closely linked to grade (for NETs)

Differentiation: Immunohistochemistry Chromogranin A Synaptophysin

Well Differentiated vs. Poorly Differentiated Neuroendocrine Neoplasms Two different families Both share neuroendocrine differentiation Can be difficult to distinguish Fundamentally different Cell of origin Relationship to non-ne neoplasia Genetic background Clinical aggressiveness Treatment

Grading of Pulmonary Neuroendocrine Neoplasms Low Grade Carcinoid Tumor Intermediate Grade Atypical Carcinoid Tumor High Grade Small Cell Carcinoma Large Cell Neuroendocrine Carcinoma

WHO 2010 Grading of GEP-NETs Grade Mitoses Ki-67 Index G1 < 2 / 10 H.P.F. < 3% G2 2-20 / 10 H.P.F. 3-20% G3 > 20 / 10 H.P.F. > 20% Poorly Differentiated (High Grade ) Neuroendocrine Carcinoma

Pancreatic NETs: Overall Survival by Grade Rindi et al., J Natl Cancer Inst 2012; 104: 764

Terminology for Neuroendocrine Neoplasms: WHO 2010 Well Differentiated NETs Well differentiated NET (pancreas, GI tract, etc.) 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.)

Use of Immunohistochemistry in Neuroendocrine Neoplasms Diagnosis (recognition of neuroendocrine differentiation) Delineation of primary site PET-CT Determination of grade, classification, prognosis

Recognition of Neuroendocrine Differentiation PET-CT

Recognition of Neuroendocrine Differentiation: Immunohistochemical Markers Conventional markers Chromogranin A PET-CT Synaptophysin CD56 (neural cell adhesion molecular / NCAM) Neuron specific enolase (NSE) CD57 / Leu7 PGP9.5 Novel markers Synaptic vesicle protein 2 (SV2) Achaete-scute complex homolog (MASH1) Insulinoma-associated protein 1 (INSM1) Neuroendocrine secretory protein 55 (NESP55)

Large Cell Neuroendocrine Carcinoma Chromogranin

Sensitivity of Chromogranin A % 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

Sensitivity of Synaptophysin % 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

Small Bowel Tumor with Mesenteric Deposits

Tumor positive with somatostatin receptor scintigraphy Chromogranin Synaptophysin CD56

Specificity of Chromogranin and Synaptophysin % Chromogranin Positive (n) Breast ductal carcinoma 2% (287) % Synaptophysin Positive (n) Breast colloid carcinoma 18% (112) 41% (105) Pulmonary adenocarcinoma 2% (689) 11% (689) Pulmonary squamous cell carcinoma 2% (586) 4% (584) GIST 1% (88) Adrenal cortical carcinoma 2% (81) 63% (269) Renal cell carcinoma 2% (379) Clear cell sarcoma 25% (59) Melanoma 11% (114) Source: Immunoquery

Specificity of CD56 for Neuroendocrine Neoplasms Source: Immunoquery % Positive (n) Lung adenocarcinoma 3% (639) Lung squamous cell carcinoma 9% (520) Renal cell carcinoma 17% (455) Pancreatic solid pseudopapillary neoplasm 98% (152) Adrenal cortical carcinoma 88% (49) Melanoma 7% (130) Adult granulosa cell tumor 100% (40) Synovial sarcoma 51% (68) Rhabdomyosarcoma 76% (34) Granular cell tumor 95% (58) Glioma 36% (148) Dendritic cell tumor 94% (164) Nk T-cell lymphoma 74% (267) Chloroma 27% (62)

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 Specificity PET-CT Certain specific non-ne neoplasms stain predictably 2-5% idiosyncratic staining of other neoplasms Is it necessary? Specific differential diagnoses Metastatic disease What about histologically typical primary tumors?

(Am J Surg Pathol 2010;34:300-313) Are immunohistochemical stains for general neuroendocrine markers mandated as necessary in all cases? 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 Totals 100% 17 NO AGREEMENT

Immunohistochemical Staining for the Diagnosis of Poorly Differentiated Neuroendocrine Carcinomas Small cell carcinoma NOT mandated when classic morphologic findings are present Consider ruling out alternatives (e.g., basaloid squamous cell carcinoma, spindle cell carcinoid tumor, etc.) Chromogranin or synaptophysin positive in ~75% of cases Large cell neuroendocrine carcinoma NE marker expression required for diagnosis Must be positive in 100% of cases (by definition) Which makers? Thoracic vs. gastroenteropancreatic How strongly / diffusely positive? 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.

Large Cell Neuroendocrine Carcinoma Chr Syn CD56

Chromogranin

Large Cell Lung Carcinoma Large Cell Undifferentiated Carcinoma Large Cell Neuroendocrine Carcinoma Large Cell Carcinoma with Neuroendocrine Differentiation Large Cell Carcinoma with Neuroendocrine Morphology

Large Cell Carcinoma with Neuroendocrine Morphology Chr, Synapto, CD56

Large Cell Carcinoma with Neuroendocrine Differentiation Chromogranin

Morphology vs. Immunohistochemistry in Large Cell Carcinoma

Neuroendocrine Differentiation in NSCLCs: Clinical Implications Found by IHC in 10-35% of NSCLCs Reports of both better and worse prognosis for NSCLC-ND vs. other NSCLCs Proposal that NSCLC-ND may respond better to chemotherapy Treatment of LCNEC with platinumbased chemotherapy

Genomic subgroups in LCNEC Gene alterations typical of: SCLC Adeno SCLC SCLC/SqCC Number of altered genes per case 35 30 25 20 15 10 5 0 TP53 78% RB1 40% KRAS 22% STK11 40% MYCL 7% MYCN 2% IRS2 4% SOX2 11% FGFR1 4% PTEN 4% MEN1 SCLC-like NSCLC-like (predominantly adeno-like) Carcinoidlike total Loss loss total Gain amp Mutation total mut Loss Gain Missense mutation Truncating mutation Loss by IHC/WT gene

Morphology of LCNEC subsets TP53 78% RB1 40% KRAS 22% STK11 40% SCLC-like NSCLC-like Morphology: N S S N S S i i S S S N i S S i N N N N S S N N N S i N N N N N N N N i N N N N N N S SC-like 9 (50%) 4 (16%) NSC-like 5 (28%) 19 (76%) Intermed/mixed 4 (22%) 2 (8%) Morphology strongly NSCLC-like SCLC-like molecular profile Rb IHC While morphology corresponds to molecular type in most cases in 35% of cases morphology is discordant or indeterminate?? Is clinical behavior predicted by genotype, phenotype or a combination?? (clinical outcomes with molecular correlates currently under investigation)

Combined Neuroendocrine Carcinomas At least 30% of both neuroendocrine and exocrine 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

Mixed Adenocarcinoma Neuroendocrine Carcinoma Chromogranin

Pancreas Mixed Acinar Neuroendocrine Carcinoma Chromogranin Chymotrypsin

Synaptophysin Chromogranin

Retinoblastoma Protein

Poorly Differentiated Neuroendocrine Carcinoma Retinoblastoma Protein

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

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 Carcinoma with neuroendocrine morphology / differentiation / features / minor elements / etc. Who know????

Neuroendocrine Neoplasms: Determination of Grade, Classification, and Prognosis

WHO 2010 Grading of GEP-NETs Grade Mitoses Ki-67 Index G1 < 2 / 10 H.P.F. < 3% G2 2-20 / 10 H.P.F. 3-20% G3 > 20 / 10 H.P.F. > 20% Poorly Differentiated (High Grade ) Neuroendocrine Carcinoma

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

Ki67

Issues with Grading GEP-NETs Ki67 assessment Intratumoral and intertumoral heterogeneity Discordance between Ki67 and mitotic rate Distinction of well differentiated vs. poorly differentiated neoplasms

Ki67 Labeling Index of NETs Strong predictor of prognosis Basis for grading systems 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

Digital Image Analysis for Ki67 Quantification Ki67% = 1.7

Correlation between Digital Image Analysis and Manual Cell Count (2000 cells) ICC, 0.981; CI, 0.966-0.991 Tang et al. Am J Surg Pathol 2012; 36: 1761-70

Consistency of Ki67 Determination by Digital Image Analysis, Manual Cell Counting, and Eyeballed Estimate Image Analysis vs. Manual Counting Image Analysis vs. Eyeballed Estimate (Mean of 20 observers) Eyeballed Estimate Interobserver (n=20) Intraclass Correlation (ICC) 95% Confidence Interval 0.98 0.97-0.99 0.88 0.80-0.93 0.13 0.05-0.37 Tang et al. Am J Surg Pathol 2012; 36: 1761-70

Courtesy of Dr. Laura H. Tang Determining the Ki67 Labeling Index of NETs: How We Do It

Phosphohistone H3 (PHH3): an Immunohistochemical Marker of Mitoses Close correlation between phosphorylation on histone h3 and mitotic chromosome condensation Highlights mitotic figures Distinguishes from pyknotic nuclei More sensitive and specific than h&e counting Allows hot spot detection Potential for automated counting Percent of cells in mitoses, versus number per unit area Tsuta et al. am j clin pathol 2011; 136: 252-259 Fung et al. acta cytol 2013; 57: 501-508 Yang et al. am j surg pathol 2015; 39: 13-24

Ki67 Ki67 Heterogeneity in PanNETs

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 Yang et al., Am J Surg Pathol 2011; 35:853-60

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)

Survival based on Ki67 Labeling Core Biopsies OS DFS PFS Three core Cum. Survival 1.8.6.4.2 0 G2 1 1 p<0.0001 p=0.002 p<0.0001.8.8 G1 0 20 40 60 80 100 120 140 160 Time Cum. Survival.6.4.2 0 G2 G1 0 20 40 60 80 100 120 Time Cum. Survival.6.4.2 0 G2 G1 0 20 40 60 80 100 120 140 160 Time Single core Cum. Survival 1.8.6.4.2 0 G2 0 20 40 60 80 100 120 140 160 Time Cum. Survival 1 p=0.0038 p<0.0001 p<0.0001 G1.8.6.4.2 0 G2 G1 0 20 40 60 80 100 120 Time Cum. Survival 1.8.6.4.2 0 G2 G1 0 20 40 60 80 100 120 140 160 Time

Ki67 and Mitotic Rate Discordance in PanNETs Mitotic rate: <1 per 10 hpf (G1) Ki-67: 15% positive (G2)

Ki67 and Mitotic Rate Discordance in PanNETs 297 WD PanNETs with Ki-67 data (1984-2009) 36% discordance 264 Mitotic G1 33 Mitotic G2 165 Ki-67 G1 99 Ki-67 G2 8 Ki-67 G1 25 Ki-67 G2 McCall et al., Am J Surg Pathol 2013; 37: 1671-7

Ki-67 G2/mitotic G1 PanNETs have decreased overall survival Percentage Surviving 0.0 0.2 0.4 0.6 0.8 1.0 K1M1 K2M1 p < 0.01 0 5 10 15 20 25 Survival in Years

Ki-67 G2/mitotic G1 PanNETs are not significantly different from concordant G2 Percentage Surviving 0.0 0.2 0.4 0.6 0.8 1.0 K2M1 K2M2 p = 0.13 0 5 10 15 20 Survival in Years

What about G2 / G3 discordance?? (well differentiated vs. poorly differentiated)

Well Differentiated PanNET Mitotic rate = 8 / 10 HPF Mitotic rate = 12 / 10 HPF Ki67 = 45% Ki67 = 55%

Poorly Differentiated Neuroendocrine Carcinoma Chromogranin

Are all G3 Neuroendocrine Neoplasms the Same? NO! Small cell carcinoma vs. Large cell NE carcinoma Large cell NE carcinoma vs. G3 well differentiated NET NEC G3 vs. NET G3

WD NE Tumor PD NE Carcinoma Carcinoma Stable Disease NE Tumor Lower Grade NE Carcinoma High Grade Grade Progression High Grade Disease Progression Rapid Disease Progression, Death Two Pathways to the Development of High Grade (G3) NE Neoplasms

Whole Exome Sequencing of PanNETs: Three Mountains 1. MEN1 inactivation 44% Previously known 2. DAXX/ATRX mutations 43% DAXX = death-domain-associated protein, Chr 6p ATRX = α thalassemia/mental retardation syndrome X-linked Together form a complex Both required for H3.3 incorporation in telomeres Mutually exclusive 3. mtor pathway 15% PTEN 7.3% TSC2 8.8% PIK3CA 1.4% ATRX Jiao et al. Science 2011; 331: 1199-1203

PanNET vs. Ductal Adenocarcinoma Genes PanNET Adenocarcinoma KRAS 0% 100% TP53 4% 75% CDKN2A 0% 95% SMAD4 0% 55% MEN1 44% 0% DAXX, ATRX 43% 0% Genes in mtor pathway 15% 1% Jones et al., Science 2008; 321: 1801. Jiao et al., Science 2011; 331: 1199.

Genetics of Poorly Differentiated Neuroendocrine Carcinoma of Pancreas Gene Small Cell Large Cell NEC W.D. PanNET Ductal ACa Small Cell Lung CA KRAS 25% 33% 0% >90% 0-10% p16 11% 50% 0% 80-95% 0-10% p53 100% 90% 4% 75% 80% Smad4 0% 10% 0% 55% 0% Rb 89% 50% 0% 13% 90% DAXX/ATRX 0% 0% 45% 0% Rb Yachida et al., Am J Surg Pathol 2012; 36: 173 Large Cell Neuroendocrine Carcinoma

Basturk et al., Am J SurgPathol 2015; 39: 683-690

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, 2000-2009 Ki67 > 20% 252 patients received chemotherapy (platinumbased) 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

Conclusion: 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 )

Grading of Pancreatic Neuroendocrine Neoplasms (WHO 2017) Well differentiated NE tumor* Grade Mitoses Ki-67 Index G1 <2 / 10 HPF </= 2% G2 2-20 / 10 HPF 3-20% G3** >20 / 10 HPF >20% *Organoid architecture, well differentiated cytology, absence of nonneuroendocrine carcinoma components, may have components of G1 or G2, usually strong immunoexpression of general NE markers **mitoses usually <20/HPF; Ki 67 >20% but usually <50% Poorly differentiated NE carcinoma* Grade Mitoses Ki-67 Index G3** >20 / 10 HPF >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 nonneuroendocrine carcinoma components, less diffuse immunoexpression of general NE markers **mitoses >20/10 HPF; Ki67 >20% and usually >50%

G1 G2 G3 G3 WDNET PDNEC 0 10 20 30 40 50 60 70 80 90 100 Ki67%

How to distinguish G3 NEC (esp. large cell NE carcinoma) from G3 NET?

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

Ki67 Ki67 Heterogeneity in PanNETs

Mitosis <1/10 HPF Mitosis 13/10 HPF

Ki67 = 2% G1 Ki67 = 45% G3

Progression of Low Grade to High Grade Neuroendocrine Tumors Fits idea of general concept of neoplastic progression Sites Pancreas 21, small bowel 6, bile duct 2, rectum 2 Progression is NOT to poorly differentiated NEC Rarely (?ever) gives rise to small cell carcinoma Present in primary tumor OR upon disease progression Biological behavior: Tang et al., Clin Cancer Res 2016; 22: 1011

n=35 n=21 n=329 Tang et al., Clin Cancer Res 2016; 22: 1011

Mixed Ductal Neuroendocrine Carcinoma of Pancreas

Tubular GI Tract: Poorly Differentiated NEC

Ampulla of Vater: Small Cell Carcinoma

Well Differentiated PanNETs (G1-3) Exhibit a Different Molecular Phenotype from Poorly Differentiated NECs (G3) WD- PanNET TP53 RB1 SMAD4 DAXX / ATRX MEN1 4% 0 0 43% 44% PD-PanNEC 56% 72%?? (adeno, 55%) 0 0 Jiao et al. Science 2011; 331: 1199 Yachida et al., Am J Surg Pathol 2012; 36: 173

PD-NEC PD-NEC p53 Rb PD-NEC WD-NET SMAD4 DAXX Tang et al., Am J Surg Pathol 2016; 40: 1192

Morphologic Assessment of High Grade Pancreatic Neuroendocrine Neoplasms Tang et al., Am J Surg Pathol 2016; 40: 1192 Consensus Reviewer 1 Reviewer 2 Reviewer 3 Specimen Type WD-NET WD-NET WD-NET WD-NET Resection WD-NET WD-NET WD-NET WD-NET Resection WD-NET WD-NET WD-NET WD-NET Resection WD-NET WD-NET WD-NET WD-NET Resection WD-NET WD-NET WD-NET WD-NET Resection WD-NET WD-NET WD-NET WD-NET Resection Ambiguous WD-NET Uncertain WD-NET Biopsy Ambiguous WD-NET WD-NET Uncertain Resection Ambiguous Uncertain WD-NET WD-NET Biopsy Ambiguous WD-NET WD-NET Uncertain Resection Ambiguous WD-NET WD-NET Uncertain Resection Ambiguous WD-NET WD-NET Uncertain Resection Ambiguous WD-NET WD-NET Uncertain Biopsy Ambiguous WD-NET WD-NET PD-NET-LCC Resection Ambiguous WD-NET WD-NET PD-NET-LCC Biopsy Ambiguous Uncertain Uncertain Uncertain Biopsy Ambiguous Uncertain Uncertain PD-NEC-SCC Resection Ambiguous PD-NEC-SCC Uncertain PD-NEC-SCC Resection PD-NEC-LCC PD-NEC-LCC PD-NEC-LCC PD-NEC-LCC Resection Ambiguous Uncertain Uncertain Uncertain Biopsy PD-NEC-LCC PD-NEC-LCC PD-NEC-LCC PD-NEC-LCC Resection PD-NEC-LCC PD-NEC-LCC PD-NEC-LCC PD-NEC-LCC Resection PD-NEC-SCC PD-NEC-SCC PD-NEC-SCC PD-NEC-SCC Resection PD-NEC-SCC PD-NEC-SCC PD-NEC-SCC PD-NEC-SCC Resection PD-NEC-SCC PD-NEC-SCC PD-NEC-SCC PD-NEC-SCC Resection PD-NEC PD-NEC-LCC PD-NEC-SCC PD-NEC-LCC Resection PD-NEC PD-NEC-SCC PD-NEC-SCC PD-NEC-LCC Resection Ambiguous WD-NET PD-NEC-LCC PD-NEC-LCC Resection Ambiguous PD-NEC-LCC PD-NEC-LCC Uncertain Resection Ambiguous Uncertain Uncertain PD-NEC-SCC Resection Ambiguous Uncertain PD-NEC-SCC Uncertain Biopsy Ambiguous Uncertain PD-NEC-LCC Uncertain Biopsy Ambiguous Uncertain PD-NEC-LCC PD-NEC-LCC Resection

Classification of High Grade Pancreatic Neuroendocrine Neoplasms by Secondary Evidence Initial Consensus Tang et al., Am J Surg Pathol 2016; 40: 1192 Immunohistochemical Abnormalities Other Histologic Components Confirmed Classification WD-NET G1/G2 WD-NET WD-NET WD-NET DAXX G1/G2 WD-NET WD-NET WD-NET ATRX G1/G2 WD-NET WD-NET WD-NET G1/G2 WD-NET WD-NET WD-NET DAXX G1/G2 WD-NET WD-NET WD-NET G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous DAXX G1/G2 WD-NET WD-NET Ambiguous ATRX G1/G2 WD-NET WD-NET Ambiguous DAXX G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous ATRX WD-NET Ambiguous DAXX G1/G2 WD-NET WD-NET Ambiguous DAXX G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous G1/G2 WD-NET WD-NET Ambiguous p53/rb PD-NEC Ambiguous p53/smad4 Ductal adenocarcinoma PD-NEC Ambiguous p53/rb PD-NEC Ambiguous p53/rb PD-NEC Ambiguous p53 PD-NEC Ambiguous Undetermined PD-NEC-LCC DAXX G1/G2 WD-NET WD-NET PD-NEC-LCC Rb PD-NEC PD-NEC-LCC Ductal adenocarcinoma PD-NEC PD-NEC-SCC p53 Ductal adenocarcinoma PD-NEC PD-NEC-SCC Rb PD-NEC PD-NEC-SCC p53/rb Ductal adenocarcinoma PD-NEC PD-NEC Rb PD-NEC PD-NEC p53 PD-NEC

Disease Specific Survival of High Grade (G3) Pancreatic Neuroendocrine Neoplasms 100 Percent survival 75 50 25 WD-NET PD-NEC p<0.0001 (N=20) (N=12) 0 0 50 100 150 Months Tang et al., Am J Surg Pathol 2016; 40: 1192

Sequencing of Pancreatic Neuroendocrine Neoplasms at MSKCC

Chromogranin A Ki67 (45%) p53

Ki67 p53 Ki67 p53

p53

Distinction of G3 NEC from G3 NET: Practical Issues Primary site Pancreas Most common DAXX/ATRX, MEN1 Other GI / pulmonary NETs 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 PET-CT Exercise pragmatism, not nihilism IHC is just one tool in the diagnostic arsenal use morphology, clinical findings, molecular data, and common sense!