ARTICLE DOI: 10.1038/s41467-017-00992-9 OPEN Insights into beta cell regeneration for diabetes via integration of molecular landscapes in human insulinomas Huan Wang1,2,14, Aaron Bender2,3, Peng Wang3, Esra Karakose3, William B. Inabnet4, Steven K. Libutti5, Andrew Arnold6, Luca Lambertini7, Micheal Stang8, Herbert Chen9, Yumi Kasai10, Milind Mahajan1, Yayoi Kinoshita11, Gustavo Fernandez-Ranvier4, Thomas C. Becker12, Karen K. Takane 3, Laura A. Walker3, Shira Saul 3, Rong Chen1,14, Donald K. Scott3, Jorge Ferrer 13, Yevgeniy Antipin1,14, Michael Donovan11, Andrew V. Uzilov1,14, Boris Reva1, Eric E. Schadt 1,14, Bojan Losic1, Carmen Argmann1 & Andrew F. Stewart3 Although diabetes results in part from a deficiency of normal pancreatic beta cells, inducing human beta cells to regenerate is difficult. Reasoning that insulinomas hold the “genomic recipe” for beta cell expansion, we surveyed 38 human insulinomas to obtain insights into therapeutic pathways for beta cell regeneration. An integrative analysis of whole-exome and RNA-sequencing data was employed to extensively characterize the genomic and molecular landscape of insulinomas relative to normal beta cells. Here, we show at the pathway level that the majority of the insulinomas display mutations, copy number variants and/or dys- regulation of epigenetic modifying genes, most prominently in the polycomb and trithorax families. Importantly, these processes are coupled to co-expression network modules asso- ciated with cell proliferation, revealing candidates for inducing beta cell regeneration. Vali- dation of key computational predictions supports the concept that understanding the molecular complexity of insulinoma may be a valuable approach to diabetes drug discovery. 1 The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 2 The Graduate School, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 3 The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 4 The Department of Surgery, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 5 The Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ 08901, USA. 6 Center for Molecular Medicine, University of Connecticut School of Medicine, Farmington, CT 06030, USA. 7 The Departments of Environmental Medicine and Public Health and Obstetrics, Gynecology, and Reproductive Sciences, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 8 The Department of Surgery, Duke University School of Medicine, Durham, NC 27710, USA. 9 The Department of Surgery, University of Alabama at Birmingham, Birmingham, AL 35233, USA. 10 The New York Genome Center, New York, NY 10013, USA. 11 The Department of Pathology, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. 12 The Sarah W. Stedman Center for Nutrition and Metabolism, Duke University School of Medicine, Durham, NC 27710, USA. 13 The Department of Genetics in Medicine, Imperial College, London, W12 0NN, UK. 14Present address: Sema4, a Mount Sinai venture, Stamford, CT 06902, USA. Huan Wang, Aaron Bender, Peng Wang, Esra Karakose, William B. Inabnet, and Steven K. Libutti contributed equally to this work. Eric E. Schadt, Bojan Losic, Carmen Argmann, and Andrew F. Stewart jointly supervised this work. Correspondence and requests for materials should be addressed to A.F.S. (email: [email protected]) NATURE COMMUNICATIONS | 8: 767 | DOI: 10.1038/s41467-017-00992-9 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-00992-9 ormal physiologic human beta cell replication occurs only human beta cells. We reasoned that although some molecular transiently in human infancy and early childhood, ceasing events in insulinoma are likely relevant to the mechanisms of N 1 irreversibly thereafter . Therapeutically, there is only one tumor formation, some may serve to uncover the genetic class of drugs, still in early development, that reproducibly mechanisms that enforce beta cell quiescence, and are bypassed in induces human beta cell replication: the harmine analogue class such benign tumors. We further validated combinations of lead – of small molecules that inhibit the kinase, DYRK1A2 4. Even candidate genes derived from this approach as beta cell mitogenic here, however, the replication rates induced are modest and not mediators. Notably, we focused on insulinomas from subjects not beta cell-specific. Accordingly, there is an urgent need to discover known to be members of multiple endocrine neoplasia type 1 additional beta cell mitogenic drugs and regenerative pathways. (MEN1) kindreds, as the MEN1 gene has been previously Insulinomas are very rare, small (~ 1–2 cm), slowly proliferating reported as one of the most frequently mutated genes in her- pancreatic beta cell adenomas5, 6. They come to medical attention editary pancreatic neuroendocrine tumors (PNETs), although – through their overproduction of insulin, causing hypoglycemia, MEN1 mutations are uncommon in sporadic insulinomas5 7. with resultant psychomotor symptoms5, 6. They are almost always Despite attempting to exclude MEN1 subjects, we nevertheless benign, and are readily treated by laparoscopic removal. Since they find widespread abnormalities in genes functionally related to are a rare tumor, they are not captured in large cancer genomic MEN1, revealing a previously unsuspected unifying mechanism surveys such as The Cancer Genome Atlas (TGCA) or the underlying insulinoma. International Cancer Genome Consortium (ICGC). Here we report whole-exome sequencing (WES) and RNA sequencing (RNAseq) of thirty-eight human insulinomas. We pro- Results vide these findings for public access with extensive sets of annota- Insulinomas harbor recurrent mutations in epigenetic genes. tions relating to the DNA variants identified, with the ability to WES was performed on genomic DNA from insulinomas and prioritize selection of high-impact mutations in a user-defined way. patient-matched blood cells (as normal controls) from 22 Our primary intent was to employ an integrative genomics patients, with a mean usable sequencing depth of 79X and 105X approach to identify mitogenic mechanisms with potential for the blood and tumor samples, respectively. We included WES application for human beta cell expansion (Supplementary data from four additional insulinomas from a prior report8, Fig. 1). This approach entails integrating whole-exome and RNA- yielding a total of 26 insulinomas with paired normal and tumor sequencing data into network analysis to computationally model DNA data (Supplementary Tables 1, Supplementary Data 1). insulinoma molecular events relative to normal adult and juvenile Mutation analysis was performed as described9, 10. After manual d Structure-specific CDX2 SMARCC1 KDM6A DNA binding Adj P- value 9398T Tumor: 4418T 5408T 8003T BGI_INS38 5407T BGI_INS20 4950T 5331T 5405T 5967T BGI_INS15 5863T 4974T 5329T 5322T 5320T 5406T 5318T 5326T 5333T 5404T 6066T 4973T BGI_INS40 6107T ARHGAP35 <0.01 25 H3F3A a SNV Indel/MNV STAG2 RNF111 20 <0.005 15 10 PER2 MLH3 PSIP1 <0.0005 of SNVs/ 5 Chromatin MNVs/indels Total numbers YY1 0 binding YY1 # genes 4 MEN1 SMAD 2 H3F3A ERBB4 0–5 2 KDM6A binding 2 MEN1 CREBBP 5–10 2 ATR 2 FLNC SMURF1 10–20 2 ARHGAP35 PAX6 DRD2 Regulatory region NCAM2 KATNAL1 DNA binding LMO2 Transcriptional MYOCD CDX2 repressor activity, R-SMAD SMURF1 NDNL2 RNA Pol II activating binding STAG2 TF binding MLLT4 TMTC1 COL4A5 10–6 10–4 10–2 0.1 FDR del MICAL1 efY 1p36.33 X 1q21.3 SUFU 22 1 1q21.1 1 1 1q21.3 ADAMTS9 21 20 2q21.2 GPS1 2q21.2 3p25.3 19 2 2 SLC27A4 2 2q21.2 3q29 RNF111 18 3 3 4p16.3 IL7R 7q11.21 4 4 PIWIL2 17 5q23.1 7q22.1 5 5 7q22.1 NLRP5 3 7p21.3 6 6 9q13 SNVs and indels: Missense Splice site Nonsense Frameshift 16 7q21.12 11p15.5 7q22.1 7 7 11p11.2 CNVs: Gain Loss cnLOH 8 8 b 12 840 7q34 11p11.12 15 9 9 11q13.1 MEN1 4 10p15.1 CDKN1C 10 10 12q24.31 10p11.23 16p13.3 EZH2 14 11 11 0 12q12 16q22.1 12q12 12 12 16q24.3 5 13 13 17p13.2 1000 13 14q11.2 14 14 17p11.2 14q32.33 15 15 17q21.2 size (Mb) Total CNV 16 16 2000 17p11.2 17q25.1 12 17 17 19p13.2 Insulinomas with genomic 6 17q21.2 c 18 18 19q13.31 aberration in selected 19q13.2 19 19 19q13.33 epigenetic modifers (85%) 11 7 20q11.1 20 20 19q13.42 21 21 19q13.42 10 22 22 9 8 22q13.1 amp FDR 0.1 10–2 10–3 10–4 Fig. 1 Global molecular characterization of the insulinoma genomic landscape from whole-exome sequencing data. a A summary of 26 insulinomas (top box) and a subset of their protein-changing key driver variants, each sample displaying the variant with the highest allelic fraction and, if any, the variant from recurrently mutated genes. All variants are somatic, except for a germline MEN1 variant from sample 5967T (at chr11:64,572,613, G>A, p.R420*, nonsense). b A summary of somatic copy number variants from selected model-predicted epigenetic modifiers and CDKN1C. c A summary showing which 85% of insulinomas harbor mutations or CNVs in selected epigenetic modifiers. d GO pathway analysis (Molecular Function) of insulinoma key driver variants reveals terms associated with chromatin-binding and SMAD signaling as the most prominent pathways. e Circos plot of copy number gain (red), loss (blue), or copy-neutral cnLOH (green). Each line within a track represents 20% of the total number of insulinomas. Note that ~ 20% of insulinomas have CNV loss on chromosome 11 (blue), and ~ 20–40% have CNV gain on chromosome 7 (red). f GISTIC2.0 analysis showing finer mapping of regions of significant chromosomal amplification or deletion throughout the genome.