Most pancreatic neuroendocrine tumors (PNETs) do not produce excess hormones and are therefore considered ‘non-functional’1,2,3. 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 α- and β-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.
All relevant data are included in the manuscript and/or in its supplementary information files. ChIP-seq and RNA-seq data have been deposited in the National Center Biotechnology Information’s GEO under GSE116356. Other original data that support the findings of this study have been uploaded as Source Data.
Metz, D. C. & Jensen, R. T. Gastrointestinal neuroendocrine tumors: pancreatic endocrine tumors. Gastroenterology 135, 1469–1492 (2008).
Yao, J. C. et al. One hundred years after ‘carcinoid’: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J. Clin. Oncol. 26, 3063–3072 (2008).
Kulke, M. H. et al. NANETS treatment guidelines: well-differentiated neuroendocrine tumors of the stomach and pancreas. Pancreas 39, 735–752 (2010).
Lawrence, B. et al. The epidemiology of gastroenteropancreatic neuroendocrine tumors. Endocrinol. Metab. Clin. North Am. 40, 1–18 (2011). vii.
Collombat, P. et al. Opposing actions of Arx and Pax4 in endocrine pancreas development. Genes Dev. 17, 2591–2603 (2003).
Gannon, M. et al. Pdx-1 function is specifically required in embryonic beta cells to generate appropriate numbers of endocrine cell types and maintain glucose homeostasis. Dev. Biol. 314, 406–417 (2008).
Rindi, G. et al. Nomenclature and classification of neuroendocrine neoplasms of the digestive system. In WHO Classification of Tumours of the Digestive System 4th edn (eds Bosman, F. T. et al.) (International Agency for Research on Cancer, 2017).
Falconi, M. et al. ENETS consensus guidelines update for the management of patients with functional pancreatic neuroendocrine tumors and non-functional pancreatic neuroendocrine tumors. Neuroendocrinology 103, 153–171 (2016).
Kouvaraki, M. A. et al. Surgical treatment of non-functioning pancreatic islet cell tumors. J. Surg. Oncol. 89, 170–185 (2005).
Jiao, Y. et al. DAXX/ATRX, MEN1, and mTOR pathway genes are frequently altered in pancreatic neuroendocrine tumors. Science 331, 1199–1203 (2011).
Scarpa, A. et al. Whole-genome landscape of pancreatic neuroendocrine tumours. Nature 543, 65–71 (2017).
Heaphy, C. M. et al. Altered telomeres in tumors with ATRX and DAXX mutations. Science 333, 425 (2011).
Marinoni, I. et al. Loss of DAXX and ATRX are associated with chromosome instability and reduced survival of patients with pancreatic neuroendocrine tumors. Gastroenterology 146, 453–460 (2014).
Singhi, A. D. et al. Alternative lengthening of telomeres and loss of DAXX/ATRX expression predicts metastatic disease and poor survival in patients with pancreatic neuroendocrine tumors. Clin. Cancer Res. 23, 600–609 (2017).
Zhou, V. W., Goren, A. & Bernstein, B. E. Charting histone modifications and the functional organization of mammalian genomes. Nat. Rev. Genet. 12, 7–18 (2011).
Rivera, C. M. & Ren, B. Mapping human epigenomes. Cell 155, 39–55 (2013).
Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).
Parker, S. C. et al. Chromatin stretch enhancer states drive cell-specific gene regulation and harbor human disease risk variants. Proc. Natl Acad. Sci. USA 110, 17921–17926 (2013).
Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).
Wang, X. et al. SMARCB1-mediated SWI/SNF complex function is essential for enhancer regulation. Nat. Genet. 49, 289–295 (2017).
Ackermann, A. M., Wang, Z., Schug, J., Naji, A. & Kaestner, K. H. Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes. Mol. Metab. 5, 233–244 (2016).
Wang, H. et al. Insights into beta cell regeneration for diabetes via integration of molecular landscapes in human insulinomas. Nat. Commun. 8, 767 (2017).
Barski, A. et al. High-resolution profiling of histone methylations in the human genome. Cell 129, 823–837 (2007).
Larsen, H. L. & Grapin-Botton, A. The molecular and morphogenetic basis of pancreas organogenesis. Semin. Cell Dev. Biol. 66, 51–68 (2017).
Sosa-Pineda, B., Chowdhury, K., Torres, M., Oliver, G. & Gruss, P. The Pax4 gene is essential for differentiation of insulin-producing beta cells in the mammalian pancreas. Nature 386, 399–402 (1997).
Collombat, P. et al. The simultaneous loss of Arx and Pax4 genes promotes a somatostatin-producing cell fate specification at the expense of the alpha- and beta-cell lineages in the mouse endocrine pancreas. Development 132, 2969–2980 (2005).
Collombat, P. et al. Embryonic endocrine pancreas and mature beta cells acquire alpha and PP cell phenotypes upon Arx misexpression. J. Clin. Invest. 117, 961–970 (2007).
Sussel, L. et al. Mice lacking the homeodomain transcription factor Nkx2.2 have diabetes due to arrested differentiation of pancreatic beta cells. Development 125, 2213–2221 (1998).
Yang, Y. P., Thorel, F., Boyer, D. F., Herrera, P. L. & Wright, C. V. Context-specific alpha-to-beta-cell reprogramming by forced Pdx1 expression. Genes Dev. 25, 1680–1685 (2011).
Gutierrez, G. D. et al. Pancreatic beta cell identity requires continual repression of non-beta cell programs. J. Clin. Invest. 127, 244–259 (2017).
Swisa, A. et al. PAX6 maintains beta cell identity by repressing genes of alternative islet cell types. J. Clin. Invest. 127, 230–243 (2017).
Johansson, K. A. et al. Temporal control of neurogenin3 activity in pancreas progenitors reveals competence windows for the generation of different endocrine cell types. Dev. Cell 12, 457–465 (2007).
Arda, H. E. et al. A chromatin basis for cell lineage and disease risk in the human pancreas. Cell Syst. 7, 310–322 e314 (2018).
Wang, Y. J. et al. Single-cell transcriptomics of the human endocrine pancreas. Diabetes 65, 3028–3038 (2016).
Conemans, E. B. et al. Expression of p27(Kip1) and p18(Ink4c) in human multiple endocrine neoplasia type 1-related pancreatic neuroendocrine tumors. J. Endocrinol. Invest. 41, 655–661 (2018).
Cejas, P. et al. Chromatin immunoprecipitation from fixed clinical tissues reveals tumor-specific enhancer profiles. Nat. Med. 22, 685–691 (2016).
Ramond, C. et al. Understanding human fetal pancreas development using subpopulation sorting, RNA sequencing and single-cell profiling. Development 145, 1–15 (2018).
de Laat, J. M. et al. Long-term natural course of pituitary tumors in patients with MEN1: results from the DutchMEN1 study group (DMSG). J. Clin. Endocrinol. Metab. 100, 3288–3296 (2015).
Sadanandam, A. et al. A cross-species analysis in pancreatic neuroendocrine tumors reveals molecular subtypes with distinctive clinical, metastatic, developmental, and metabolic characteristics. Cancer Discov. 5, 1296–1313 (2015).
Chan, C. S. et al. ATRX, DAXX or MEN1 mutant pancreatic neuroendocrine tumors are a distinct alpha-cell signature subgroup. Nat. Commun. 9, 4158 (2018).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Thorvaldsdottir, H., Robinson, J. T. & Mesirov, J. P. Integrative genomics viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
Liao, Y., Smyth, G. K. & Shi, W. Feature counts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).
McDonald, O. G. et al. Epigenomic reprogramming during pancreatic cancer progression links anabolic glucose metabolism to distant metastasis. Nat. Genet. 49, 367–376 (2017).
Ooi, W. F. et al. Epigenomic profiling of primary gastric adenocarcinoma reveals super-enhancer heterogeneity. Nat. Commun. 7, 12983 (2016).
Cohen, A. J. et al. Hotspots of aberrant enhancer activity punctuate the colorectal cancer epigenome. Nat. Commun. 8, 14400 (2017).
Pasquali, L. et al. Pancreatic islet enhancer clusters enriched in type 2 diabetes risk-associated variants. Nat. Genet. 46, 136–143 (2014).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Cnop, M. et al. RNA sequencing identifies dysregulation of the human pancreatic islet transcriptome by the saturated fatty acid palmitate. Diabetes 63, 1978–1993 (2014).
The present study has been supported by the Neuroendocrine Tumor Research Foundation (R.A.S., B.E.B., M.H.K. and D.C.C.), the SPORE program in gastrointestinal cancers (P50CA127003—National Cancer Institute, R.A.S.), the North American Neuroendocrine Tumor Society (C.M.H.) and a grant (no. PI18-01604 to P.C.) from Instituto de Salud Carlos III of the Spanish Economy and Competitiveness Ministry.
C.R.C. Pieterman, B. Havekes, A.R. Hermus, O.M. Dekkers, W.W. de Herder, M.L. Drent, A.N.A. van der Horst-Schrivers and P.H. Bisschop contributed to the Dutch MEN1 Study Group database and tissue repository. We thank J. Chan for critical reading of the manuscript.
The authors declare no competing interests.
Peer review information: J. Carmona was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 PNET subtypes are associated with distinct enhancers of lineage-restricted TFs.
a, H3K27ac, H3K4me2 and mRNA data tracks at ARX and PDX1 in all eight PNETs from the discovery set and from two samples of normal islets of Langerhans (Isl). ChIP-seq signals are scaled by promoter-based DESeq2 normalization (see Methods) and mRNA read counts are normalized by total read numbers (y axis represents 0–2 fragments per million reads). b, Distributions of ARX and PDX1 mRNA levels in A- and B-type PNETs. c, Pearson’s correlations of H3K27ac signals at PNET type A/α-cell and type B/β-cell enhancers in all 21 tumors from the discovery and validation cohorts (n = 8 and n = 13 biologically independent samples, respectively).
a, Double immunofluorescence for PDX1 (red) and ARX (green) in normal islets (marked by dashed white outlines). Scale bar, 50 μm. The results, representing hundreds of islets, verify antibody specificity, lineage-restricted expression and cell distributions: abundant PDX1+ β-cells scattered across islets and fewer ARX+ α-cells enriched in the islet periphery. b, Top: ARX and PDX1 IHC selectively mark endocrine α- and β-cells, respectively, in normal human islets. Many exocrine and ductal cells also express PDX1, as is well known24. The results represent hundreds of normal islets from multiple individuals, which revealed no ARX+ PDX1+ DP cells. Thus, although described in rodent embryos24, such cells are absent or extremely rare in the adult human pancreas. Bottom: IHC for ARX in a representative PNET and surrounding normal cells on TMAs from the Dutch cohort. The area boxed in the left image is magnified on the right. ARX+ cells dominate in the tumor and mark invasive foci (arrows). c, Range of IHC signal strength in ARX+ PNETs (+weak, ++ moderate, +++ strong), contrasted with uniformly robust PDX1 staining. Images are examples selected from 34 ARX+ and 31 PDX+ cases (Fig. 3b). Scale bars, 50 μm.
a, Double immunofluorescence of representative ARX+ (type A, n = 34 biologically independent samples) and PDX1+ (type B, n = 31 biologically independent samples) tumors (T) adjacent to normal islets (N), showing selective detection of ARX (green) and PDX1 (red), respectively. Lack of antibody cross-reactivity controls for ARX and PDX1 co-staining (Fig. 3c) in DP tumors. b, SST expression in normal islets (δ-cells) and absence in all 77 Dutch PNETs, including the representative DN tumor (n = 6 biologically independent samples) shown here. c, IHC results for ARX and PDX1 shown alongside H3K27ac FiT-seq data from the same samples in three of the four cases (one of each subtype) from the discovery cohort where both FFPE and frozen samples were available.
a, H3K27ac, H3K4me2 and mRNA data tracks from all eight PNETs in the discovery set and from two normal islet samples at loci that control early pancreas ontogeny: NEUROG3 and PAX4. Histone marks and RNA-seq data are scaled as in Extended Data Fig. 1a. b, IHC for NEUROG3 in rare normal islets (dashed outlines), showing scarce NEUROG3+ endocrine cells (arrows). Hundreds of normal islets and all 19 biologically independent PNETs represented on one TMA (one example is shown) lacked expression. c, H3K27ac, H3K4me2 and mRNA data tracks from all eight PNETs in the discovery set and from two normal islet samples at loci that control terminal endocrine cell maturation, MAFA and FFAR1. Histone marks and RNA-seq data are scaled as in Extended Data Fig. 1a. A single outlier showed strong H3K27ac and mRNA at FFAR1.
a, Correlations of mRNA profiles in individual PNETs with those of pancreatic endocrine progenitor and mature cells37. x axis: Spearman’s correlations between log2(TPM + 1) values of each tumor and the average log2(TPM + 1) values of mature and progenitor populations.
a,c, Tumor size in all PNET subtypes in the Dutch (a) (n = 56 independent tumors) and the MGH (c) (n = 61 independent tumors) cohorts. Bars represent mean ± s.d. P values for differences in size of primary ARX+ and PDX1+ tumors determined by the two-sided Mann–Whitney U-test. b,d, Analyses of recurrence-free survival in the Dutch (b) (n = 30 cases) and MGH (d) (n = 35 cases) cohorts when ARX+ and PDX1+ tumors were considered separately, ungrouped from DP and DN tumors. P values and HRs were determined using two-sided log-rank and Mantel–Haenszel tests, respectively. e,f, Representative (e) (1 example each from 25 independent ALT+ and 87 independent ALT− cases) and aggregate (f) (n = 112 biologically independent cases) results of telomere-specific FISH in cases classified as positive or negative for ALT. The statistical test was two-sided. g, Kaplan–Meier analysis of disease-free survival in all 112 cases with ALT data from both cohorts, without consideration of PNET subtype. Source data
Unprocessed tissue microarray (TMA) scans with scoring key
Statistical source data
Statistical source data
About this article
Cite this article
Cejas, P., Drier, Y., Dreijerink, K.M.A. et al. Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors. Nat Med 25, 1260–1265 (2019). https://doi.org/10.1038/s41591-019-0493-4
Annals of Surgical Oncology (2021)
Complications After Major Surgery for Duodenopancreatic Neuroendocrine Tumors in Patients with MEN1: Results from a Nationwide Cohort
Annals of Surgical Oncology (2021)
Molecular profile of pancreatic neuroendocrine neoplasms (PanNENs): Opportunities for personalized therapies
Application of multiomics sequencing and advances in the molecular mechanisms of pancreatic neuroendocrine neoplasms
Cancer Letters (2021)
Frontiers in Endocrinology (2021)