Molecular Classification of Neuroendocrine Tumors of the Thymus

Helen Dinter, Hanibal Bohnenberger, Julia Beck, Kirsten Bornemann-Kolatzki, Ekkehard Schütz, Stefan Küffer, Lukas Klein, Teri J. Franks, Anja Roden, Alexander Emmert, Marc Hinterthaner, Mirella Marino, Luka Brcic, Helmut Popper, Cleo Aron Weis, Giuseppe Pelosi, Alexander Marx, Philipp Ströbel

Research output: Contribution to journalArticle

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Abstract

Introduction: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. Methods: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. Results: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). Conclusions: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication.

Original languageEnglish (US)
JournalJournal of Thoracic Oncology
DOIs
StatePublished - Jan 1 2019

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Neuroendocrine Carcinoma
Large Cell Carcinoma
Neuroendocrine Tumors
Thymus Gland
Carcinoid Tumor
Small Cell Carcinoma
Polycomb Repressive Complex 2
Genome
Chromogranins
Neoplasms
Lung
Histology
Neoplasm Metastasis

Keywords

  • Carcinoid
  • Classification
  • Genetic
  • Molecular
  • Neuroendocrine
  • Thymus

ASJC Scopus subject areas

  • Oncology
  • Pulmonary and Respiratory Medicine

Cite this

Dinter, H., Bohnenberger, H., Beck, J., Bornemann-Kolatzki, K., Schütz, E., Küffer, S., ... Ströbel, P. (2019). Molecular Classification of Neuroendocrine Tumors of the Thymus. Journal of Thoracic Oncology. https://doi.org/10.1016/j.jtho.2019.04.015

Molecular Classification of Neuroendocrine Tumors of the Thymus. / Dinter, Helen; Bohnenberger, Hanibal; Beck, Julia; Bornemann-Kolatzki, Kirsten; Schütz, Ekkehard; Küffer, Stefan; Klein, Lukas; Franks, Teri J.; Roden, Anja; Emmert, Alexander; Hinterthaner, Marc; Marino, Mirella; Brcic, Luka; Popper, Helmut; Weis, Cleo Aron; Pelosi, Giuseppe; Marx, Alexander; Ströbel, Philipp.

In: Journal of Thoracic Oncology, 01.01.2019.

Research output: Contribution to journalArticle

Dinter, H, Bohnenberger, H, Beck, J, Bornemann-Kolatzki, K, Schütz, E, Küffer, S, Klein, L, Franks, TJ, Roden, A, Emmert, A, Hinterthaner, M, Marino, M, Brcic, L, Popper, H, Weis, CA, Pelosi, G, Marx, A & Ströbel, P 2019, 'Molecular Classification of Neuroendocrine Tumors of the Thymus', Journal of Thoracic Oncology. https://doi.org/10.1016/j.jtho.2019.04.015
Dinter H, Bohnenberger H, Beck J, Bornemann-Kolatzki K, Schütz E, Küffer S et al. Molecular Classification of Neuroendocrine Tumors of the Thymus. Journal of Thoracic Oncology. 2019 Jan 1. https://doi.org/10.1016/j.jtho.2019.04.015
Dinter, Helen ; Bohnenberger, Hanibal ; Beck, Julia ; Bornemann-Kolatzki, Kirsten ; Schütz, Ekkehard ; Küffer, Stefan ; Klein, Lukas ; Franks, Teri J. ; Roden, Anja ; Emmert, Alexander ; Hinterthaner, Marc ; Marino, Mirella ; Brcic, Luka ; Popper, Helmut ; Weis, Cleo Aron ; Pelosi, Giuseppe ; Marx, Alexander ; Ströbel, Philipp. / Molecular Classification of Neuroendocrine Tumors of the Thymus. In: Journal of Thoracic Oncology. 2019.
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abstract = "Introduction: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. Methods: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. Results: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). Conclusions: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication.",
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AU - Dinter, Helen

AU - Bohnenberger, Hanibal

AU - Beck, Julia

AU - Bornemann-Kolatzki, Kirsten

AU - Schütz, Ekkehard

AU - Küffer, Stefan

AU - Klein, Lukas

AU - Franks, Teri J.

AU - Roden, Anja

AU - Emmert, Alexander

AU - Hinterthaner, Marc

AU - Marino, Mirella

AU - Brcic, Luka

AU - Popper, Helmut

AU - Weis, Cleo Aron

AU - Pelosi, Giuseppe

AU - Marx, Alexander

AU - Ströbel, Philipp

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N2 - Introduction: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. Methods: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. Results: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). Conclusions: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication.

AB - Introduction: The WHO classification of pulmonary neuroendocrine tumors (PNETs) is also used to classify thymic NETs (TNETs) into typical and atypical carcinoid (TC and AC), large cell neuroendocrine carcinoma (LCNEC), and small cell carcinoma (SCC), but little is known about the usability of alternative classification systems. Methods: One hundred seven TNET (22 TC, 51 AC, 28 LCNEC, and 6 SCC) from 103 patients were classified according to the WHO, the European Neuroendocrine Tumor Society, and a grading-related PNET classification. Low coverage whole-genome sequencing and immunohistochemical studies were performed in 63 cases. A copy number instability (CNI) score was applied to compare tumors. Eleven LCNEC were further analyzed using targeted next-generation sequencing. Morphologic classifications were tested against molecular features. Results: Whole-genome sequencing data fell into three clusters: CNIlow, CNIint, and CNIhigh. CNIlow and CNIint comprised not only TC and AC, but also six LCNECs. CNIhigh contained all SCC and nine LCNEC, but also three AC. No morphologic classification was able to predict the CNI cluster. Cases where primary tumors and metastases were available showed progression from low-grade to higher-grade histologies. Analysis of LCNEC revealed a subgroup of intermediate NET G3 tumors that differed from LCNEC by carcinoid morphology, expression of chromogranin, and negativity for enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). Conclusions: TNETs fall into three molecular subgroups that are not reflected by the current WHO classification. Given the large overlap between TC and AC on the one hand, and AC and LCNEC on the other, we propose a morphomolecular grading system, Thy-NET G1-G3, instead of histologic classification for patient stratification and prognostication.

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KW - Genetic

KW - Molecular

KW - Neuroendocrine

KW - Thymus

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