Detecting Somatic Mutations for Well-Differentiated Pancreatic Neuroendocrine Tumors in Endoscopic Ultrasound-Guided Fine Needle Aspiration with Next-Generation Sequencing.


Journal

Annals of surgical oncology
ISSN: 1534-4681
Titre abrégé: Ann Surg Oncol
Pays: United States
ID NLM: 9420840

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 03 03 2023
accepted: 03 07 2023
pubmed: 25 7 2023
medline: 25 7 2023
entrez: 24 7 2023
Statut: ppublish

Résumé

Pancreatic neuroendocrine tumors (PanNETs) exhibit heterogenous behavior, whereby some small tumors are aggressive with a propensity for metastasis. Detection of somatic mutations associated with aggressive biology may help with patient stratification and surgical decision-making in patients with well-differentiated PanNETs. Using next-generation sequencing (NGS), we investigated the feasibility of detecting somatic mutations in endoscopic ultrasound-guided, fine-needle aspiration (EUS-FNA) specimens and determining the mutational concordance between the EUS-FNA specimens and the primary tumors. Thirty-eight patients with well-differentiated, nonfunctioning PanNETs were obtained from two tertiary referral centers. Patient demographic characteristics and tumor, clinicopathologic features were collected. Tissue from both the EUS-FNA specimen and the primary tumor was extracted from archival tissue blocks. NGS using a panel of ten genes was performed on both samples. In our series, the median age was 61.1 years. Tumors were predominantly left-sided (60.5%) and unifocal (94.7%). The median tumor size was 2.2 cm. NGS detected somatic mutations in 29% of primary tumors and 36.8% of EUS-FNA specimens. In primary tumors, DAXX/ATRX mutations were predominantly detected (63.6%). In EUS-FNA specimens, MEN1 mutations were predominantly detected (64.3%). Among non-wild-type specimens, mutational concordance was achieved in 31.6% of cases. In 11 patients with a detectable mutation in the primary tumor, a mutation was detected in the EUS-FNA specimen in 45.5% of cases, with a mutational concordance of 54.5%. NGS can detect somatic mutations in EUS-FNA specimens of well-differentiated PanNETs. Efforts to improve detection sensitivity and mutational concordance are required to overcome current technical limitations.

Sections du résumé

BACKGROUND BACKGROUND
Pancreatic neuroendocrine tumors (PanNETs) exhibit heterogenous behavior, whereby some small tumors are aggressive with a propensity for metastasis. Detection of somatic mutations associated with aggressive biology may help with patient stratification and surgical decision-making in patients with well-differentiated PanNETs. Using next-generation sequencing (NGS), we investigated the feasibility of detecting somatic mutations in endoscopic ultrasound-guided, fine-needle aspiration (EUS-FNA) specimens and determining the mutational concordance between the EUS-FNA specimens and the primary tumors.
METHODS METHODS
Thirty-eight patients with well-differentiated, nonfunctioning PanNETs were obtained from two tertiary referral centers. Patient demographic characteristics and tumor, clinicopathologic features were collected. Tissue from both the EUS-FNA specimen and the primary tumor was extracted from archival tissue blocks. NGS using a panel of ten genes was performed on both samples.
RESULTS RESULTS
In our series, the median age was 61.1 years. Tumors were predominantly left-sided (60.5%) and unifocal (94.7%). The median tumor size was 2.2 cm. NGS detected somatic mutations in 29% of primary tumors and 36.8% of EUS-FNA specimens. In primary tumors, DAXX/ATRX mutations were predominantly detected (63.6%). In EUS-FNA specimens, MEN1 mutations were predominantly detected (64.3%). Among non-wild-type specimens, mutational concordance was achieved in 31.6% of cases. In 11 patients with a detectable mutation in the primary tumor, a mutation was detected in the EUS-FNA specimen in 45.5% of cases, with a mutational concordance of 54.5%.
CONCLUSIONS CONCLUSIONS
NGS can detect somatic mutations in EUS-FNA specimens of well-differentiated PanNETs. Efforts to improve detection sensitivity and mutational concordance are required to overcome current technical limitations.

Identifiants

pubmed: 37488390
doi: 10.1245/s10434-023-13965-8
pii: 10.1245/s10434-023-13965-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

7720-7730

Informations de copyright

© 2023. Society of Surgical Oncology.

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Auteurs

Elie M Ghabi (EM)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Joseph R Habib (JR)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Sami Shoucair (S)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Ammar A Javed (AA)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Jonathan Sham (J)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

William R Burns (WR)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

John L Cameron (JL)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Syed Z Ali (SZ)

Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Eun Ji Shin (EJ)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Paolo Giorgio Arcidiacono (PG)

Pancreato-Biliary Endoscopy and Endosonography Division, Pancreas Translational and Clinical Research Center, San Raffaele Scientific Institute IRCCS, Vita Salute San Raffaele University, Milan, Italy.

Claudio Doglioni (C)

Pathology Unit, Pancreas Translational and Clinical Research Center, IRCCS Ospedale San Raffaele, ENETS Center of Excellence, Milan, Italy.

Massimo Falconi (M)

Pancreatic and Transplant Surgery Unit, Pancreas Translational and Clinical Research Center, IRCCS Ospedale San Raffaele, ENETS Center of Excellence, Milan, Italy.

Jun Yu (J)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Stefano Partelli (S)

Pancreatic and Transplant Surgery Unit, Pancreas Translational and Clinical Research Center, IRCCS Ospedale San Raffaele, ENETS Center of Excellence, Milan, Italy.

Jin He (J)

Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jhe11@jhmi.edu.

Classifications MeSH