Dataset Information

Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors.

ABSTRACT: Most pancreatic neuroendocrine tumors (PNETs) do not produce excess hormones and are therefore considered 'non-functional'1-3. As clinical behaviors vary widely and distant metastases are eventually lethal2,4, biological classifications might guide treatment. Using enhancer maps to infer gene regulatory programs, we find that non-functional PNETs fall into two major subtypes, with epigenomes and transcriptomes that partially resemble islet ?- and ?-cells. Transcription factors ARX and PDX1 specify these normal cells, respectively5,6, and 84% of 142 non-functional PNETs expressed one or the other factor, occasionally both. Among 103 cases, distant relapses occurred almost exclusively in patients with ARX+PDX1- tumors and, within this subtype, in cases with alternative lengthening of telomeres. These markedly different outcomes belied similar clinical presentations and histology and, in one cohort, occurred irrespective of MEN1 mutation. This robust molecular stratification provides insight into cell lineage correlates of non-functional PNETs, accurately predicts disease course and can inform postoperative clinical decisions.

SUBMITTER: Cejas P

PROVIDER: S-EPMC6919319 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors.

Cejas Paloma P Drier Yotam Y Dreijerink Koen M A KMA Brosens Lodewijk A A LAA Deshpande Vikram V Epstein Charles B CB Conemans Elfi B EB Morsink Folkert H M FHM Graham Mindy K MK Valk Gerlof D GD Vriens Menno R MR Castillo Carlos Fernandez-Del CF Ferrone Cristina R CR Adar Tomer T Bowden Michaela M Whitton Holly J HJ Da Silva Annacarolina A Font-Tello Alba A Long Henry W HW Gaskell Elizabeth E Shoresh Noam N Heaphy Christopher M CM Sicinska Ewa E Kulke Matthew H MH Chung Daniel C DC Bernstein Bradley E BE Shivdasani Ramesh A RA

Nature medicine 20190701 8

Most pancreatic neuroendocrine tumors (PNETs) do not produce excess hormones and are therefore considered 'non-functional'<sup>1-3</sup>. As clinical behaviors vary widely and distant metastases are eventually lethal<sup>2,4</sup>, biological classifications might guide treatment. Using enhancer maps to infer gene regulatory programs, we find that non-functional PNETs fall into two major subtypes, with epigenomes and transcriptomes that partially resemble islet α- and β-cells. Transcription fact ...[more]

PMID: 31263286

Similar Datasets

Project description:BackgroundLymph node status is an important factor for the patients with non-functional pancreatic neuroendocrine tumors (NF-PanNETs) with respect to the surgical methods, prognosis, recurrence. Our aim is to develop and validate a combination model based on contrast-enhanced CT images to predict the lymph node metastasis (LNM) in NF-PanNETs.MethodsRetrospective data were gathered for 320 patients with NF-PanNETs who underwent curative pancreatic resection and CT imaging at two institutions (Center 1, n = 236 and Center 2, n = 84) between January 2010 and March 2022. RDPs (Radiomics deep learning signature) were developed based on ten machine-learning techniques. These signatures were integrated with the clinicopathological factors into a nomogram for clinical applications. The evaluation of the model's performance was conducted through the metrics of the area under the curve (AUC).FindingsThe RDPs showed excellent performance in both centers with a high AUC for predicting LNM and disease-free survival (DFS) in Center 1 (AUC, 0.88; 95% CI: 0.84-0.92; DFS, p < 0.05) and Center 2 (AUC, 0.91; 95% CI: 0.85-0.97; DFS, p < 0.05). The clinical factors of vascular invasion, perineural invasion, and tumor grade were associated with LNM (p < 0.05). The combination nomogram showed better prediction capability for LNM (AUC, 0.93; 95% CI: 0.89-0.96). Notably, our model maintained a satisfactory predictive ability for tumors at the 2-cm threshold, demonstrating its effectiveness across different tumor sizes in Center 1 (≤2 cm: AUC, 0.90 and >2 cm: AUC, 0.86) and Center 2 (≤2 cm: AUC, 0.93 and >2 cm: AUC, 0.91).InterpretationOur RDPs may have the potential to preoperatively predict LNM in NF-PanNETs, address the insufficiency of clinical guidelines concerning the 2-cm threshold for tumor lymph node dissection, and provide precise therapeutic strategies.FundingThis work was supported by JSPS KAKENHI Grant Number JP22K20814; the Rare Tumor Research Special Project of the National Natural Science Foundation of China (82141104) and Clinical Research Special Project of Shanghai Municipal Health Commission (202340123).

Dataset Information

Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors.

Publications

Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets