Asa, SL

Beck, S

Caplin, M

Dibra, H

Feber, A

Francis, JM

Karpathakis, A

Kulke, MH

Luong, TV

Mandair, D

Meyer, T

Mohmaduvesh, M

Morris, T

Novelli, M

Ogunbiyi, O

Oukrif, D

Pericleous, M

Pipinikas, C

Serra, S

Thirlwell, C

Toumpanakis, C

UCL Discovery

1  Progressive epigenetic dysregulation in neuroendocrine tumour liver metastasis. 1 Anna Karpathakis1,3, Harpreet Dibra1, Christodoulos Pipinikas1, Andrew Feber1, Tiffany 2 Morris1, Joshua Francis2, Dahmane Oukrif1, Dalvinder Mandair1,3, Marinos Pericleous3, 3 Mullan Mohmaduvesh3, Stefano Serra4, Olagunju Ogunbiyi3, Marco Novelli1, TuVinh 4 Luong3, Sylvia L Asa4, Matthew Kulke5, Christos Toumpanakis3, Tim Meyer1,3, Martyn 5 Caplin3, Stephan Beck1, Christina Thirlwell1,3. 6 Affiliations: 1University College London, London, UK; 2The Broad Institute, Boston, USA; 7 3The Royal Free Hospital, London, UK; 4UHN Princess Margaret Cancer Centre, Toronto, 8 Canada; 5DanaFaber Cancer Institute, Boston, USA 9 Corresponding author: Dr Christina Thirlwell, UCL Cancer Institute, 72 Huntley St, London, 10 WC1E6BT.  Tel: 020 76796882, Fax: 020 76796817, christina.thirlwell@ucl.ac.uk 11 Keywords:  Neuroendocrine tumour, epigenetics, methylation, metastasis 12 Short Title: Epigenetics of SINET liver metastases 13  14 Word count:  1494 15  16  17  18  19  20  21 Page 1 of 14 Accepted Preprint first posted on 3 January 2017 as Manuscript ERC-16-0419 Copyright © 2017 by the Society for Endocrinology.2  Dear Editor 22 The incidence of small intestinal neuroendocrine tumours (SINETs) is increasing and distant 23 metastases are present at diagnosis in 70% of cases, the liver being the commonest site of 24 metastasis (Yao et al. 2008). Despite this, our understanding of the mechanisms underlying 25 metastatic progression of SINETs is currently limited and prior studies of the molecular 26 biology of SINET liver metastases (LM) have been performed predominantly in small 27 cohorts utilising candidate based techniques.   28 SINETs have a low rate of mutations compared to most cancers.  Tthe most frequently 29 mutated gene is CDKN1B (encoding p27, a cell cycle regulator); however mutations in this 30 gene occur in only 8% of tumours and there is no characteristic mutational hotspot (Francis 31 et al. 2013).  Furthermore, mutation of CDKN1B does not correlate with expression of p27 32 (Crona et al. 2015).   We previously identified that SINETs are epigenetically dysregulated, 33 and a panel of candidate driver epimutation genes has been identified (Karpathakis et al. 34 2016). Therefore we postulated that metastatic progression in SINETs may also be 35 epigenetically regulated.  Here we present findings from the largest molecular profiling study 36 of SINET LM performed to date, integrating copy number variance (CNV), DNA 37 methylation and RNA expression profiling to characterise the mechanisms underlying 38 metastatic progression. 39 Experimental details of DNA methylation, CNV and RNA expression profiling are as 40 previously published (Karpathakis et al. 2016).  Patients provided informed consent for their 41 tissue to be analysed in this study which was Research Ethics Committee approved (Ref: 42 09/H0722/27). All cases were reviewed by two expert NET histopathologists (TVL/MN).   43 Nucleic acids were extracted using standard methods (Qiagen:QIAamp DNA Mini kit, 44 Roche:High Pure RNA Paraffin kit).  H&E stained sections were evaluated to ensure >80% 45 Page 2 of 143  purity of tumour specimens. Methylation profiling was performed on the 46 HumanMethylation450 BeadChip (HM450)(Illumina). Methylation data analysis was 47 performed using ChAMP pipeline 48 (https://www.bioconductor.org/packages/release/bioc/html/ChAMP.html).  Whole genome 49 methylation profiling using Methylated DNA Immunoprecipitaion sequencing (MeDIP) was 50 performed as previously described. MeDIP data was analysed using the custom pipeline 51 MeDUSAv2.0 (https://www.ucl.ac.uk/cancer/research/department-cancer-biology/medical-52 genomics-group/past-projects/medusa-project).   Gene expression analysis was performed on 53 the Whole genome cDNA-mediated annealing, selection and ligation (DASL)(Illumina) 54 assay.  Expression data was analysed using the ‘limma’ package in R 55 (https://bioconductor.org/packages/release/bioc/html/limma.html).  Raw data from this study 56 will be deposited in GEO (Accession number: XXXXXX) 57 In summary, n=90 samples underwent array based DNA methylation analysis, n=26 samples 58 underwent methylation specific immunoprecipitation followed by DNA sequencing, and 59 n=49 underwent array based RNA expression analysis.  Of cases with relevant clinical data, 60 93% had received no systemic treatment prior to specimen collection (27/29 cases). 61 The CNV profile of SINET LM (n=20) mirrors that of primary tumours with the most 62 frequent alteration of chr18 LOH seen in 79% of cases. A greater proportion of LM 63 demonstrate amplification of chr20 (42%), deletion of chr19 (35%), whilst gain of 17q is 64 found only in LM (21%). A trend of increased incidence of CNVs was seen in LM compared 65 to SINET primary tumours (SINET primary: median 78megabasepair; LM: median 114mbp, 66 p=0.08). 67 Comparison of methylation profiles of SINET LM to that of primary SINETs identified 68 29,263 methylation variable positions (MVPs) (adj p <0.05). Using a cut off of >30% 69 Page 3 of 144  difference in methylation between SINET primaries and LM, MVPs involving eight genes 70 were identified (CLEC16A, HOXC4, HOXD4, IGF2AS, INS-IGF2, LDHA, RTN4RL1, 71 SASH1). This suggests that the methylation profile of SINET primaries and metastases are 72 broadly similar and that these epigenetic differences occurring in metastatic progression may 73 be more subtle than those involved in primary tumorigenesis.  Global hypomethylation is 74 noted in SINET primary tumours and occurs to an even greater extent in SINET LM (normal 75 tissue methylation 0.628, primary 0.572, LM 0.515, p<0.001).   76 Almost three thousand (n=2857) genes were significantly differentially expressed between 77 LM and primary tumours. Using a > 3-fold alteration in gene expression, more genes were 78 found to be upregulated (n=321) than downregulated (n=171) in LM.  KEGG pathway 79 analysis (http://bioinfo.vanderbilt.edu/webgestalt/) of differentially expressed genes between 80 LM and SINET primary identified significant enrichment of multiple cancer related pathways 81 overexpressed in LM including PI3K signalling events, ErbB1 downstream signalling, 82 PDGFRβ signalling pathway, and mTOR signalling pathway (adjusted p<0.001).  83 Analysis of SINET LM identified progressive changes between SINET primaries and LM in 84 DNA methylation and RNA expression in genes which had previously been identified in 85 primary tumours when compared to normal tissue. This phenomenon was observed in a panel 86 of 21 epigenetically dysregulated candidate driver genes which was previously identified 87 (Karpathakis et al. 2016)(Table 1). 88 LM demonstrated hyper/hypomethylation of all 21 genes in concordance with the pattern 89 seen in SINET primaries when compared to normal tissue.  In 19 genes (90.5% of the panel) 90 a trend for progressive hyper/hypomethylation was demonstrated in LM, of which 14 (66.6%) 91 of the panel were significantly differentially methylated compared to the primary SINET. 92 Page 4 of 145  All of the 21 genes included in the panel demonstrated over/under expression in LM in 93 concordance with SINET primary tumours. In 15 genes (71.4% of panel) there was a 94 progression of aberrant expression to a greater extent in LM than was demonstrated in SINET 95 primaries (Figure 1, Table 1). 96 Validation of SINET LM methylation status was performed in an independent cohort of 97 seven LM profiled by methylated DNA immunoprecipitation sequencing (MeDIP-seq).  It 98 was demonstrated that 20/21 (95.2%) genes exhibited concordant trends in methylation 99 during progression from NSI to SI primary tumour to liver metastasis as was identified using 100 HM450 profiling.  Statistically significant progressive aberrant methylation was 101 demonstrated in 10/21 genes (47.6%). 102 Validation of SINET LM expression status was performed utilising a publicly available 103 dataset including three SINET primaries and three LM (GSE9576, Leja et al. 2009).  In total, 104 10/21 (47.6%) of the candidate panel demonstrated a trend for progressive dysregulation in 105 LM compared to primary tumours in keeping with the findings from the discovery dataset.  106 The small number of cases included in this validation set limit the ability to confirm 107 statistical significance. 108 Page 5 of 146  Through integrated DNA methylation, CNV and RNA expression analysis we have identified 109 progressive genomic derangements in SINET LM when compared to primary tumours.  110 CNVs were seen more frequently in LM, in particular arm level amplifications, as previously 111 reported (Hashemi et al. 2013).  Amplification of chromosome 17q was observed more 112 frequently in LM than primaries in this cohort. This alteration has previously been described 113 in both SINET and pancreatic NET primary tumours but this is the first time that increased 114 frequency in LM has been identified.  Chromosome 17 harbours the proto-oncogene 115 HER2/neu (17q11-21), amplification of which may be related to a more aggressive 116 phenotype. 117 The finding of progressive global hypomethylation in metastases compared to primary 118 tumours is in keeping with previously published data (Verdugo et al. 2014).  A pattern of 119 progressive aberrant methylation observed in our previously identified panel of 21 120 epimutated genes in liver metastases, suggests that increasing epigenetic dysregulation may 121 drive progression to metastasis. 122 Transcriptome profiling demonstrated differential expression of 492 genes between LM and 123 SINET primary tumours which may represent drivers of metastasis, including components of 124 the PI3K/mTOR pathways.  Progressively dysregulated expression of the panel of candidate 125 genes was demonstrated in liver metastases compared to primary tumours. This indicates 126 escalating deregulation of aberrant expression of the genes and pathways associated 127 development of SINET primary tumours occurs in association with metastatic progression.   128 In total, 71.4% (15/21, expression) to 90.5% (19/21, methylation) of cases are affected by 129 progressive dysregulation in association with metastasis. The gene encoding the gastric 130 inhibitory polypeptide receptor (GIPR) is one of a panel of epigenetically dysregulated genes 131 in SINETs which is significantly progressively hypermethylated in LM compared to primary 132 Page 6 of 147  tumours.  This may represent a target for novel therapeutic agents in the management of 133 SINETs, and has already been investigated as a target for novel imaging modalities (Sherman 134 et al. 2013). 135 In summary, integrated genomic analysis of a large cohort of SINET LM has identified novel 136 molecular mechanisms associated with metastatic progression.  Epigenetic dysregulation of a 137 panel of 21 candidate genes was identified in LM concordant with those found in primary 138 SINET. Components of cancer related pathways including PI3K, mTOR and ErbB1 are 139 overexpressed in liver metastases compared to normal tissue, which may be utilised as 140 therapeutic targets.  Current clinical practice includes the use of agents targeting the mTOR 141 pathway is based on evidence from the RADIANT trials of everolimus in pancreatic and 142 SINETs (Yao et al. 2016).  The use of second line dual mTORC/PI3K inhibition for 143 pancreatic NETs was not supported in a recently clinical trial (Fazio et al. 2016). Our data 144 suggest the development of novel agents targeting epigenetic modifications in these pathways 145 may hinder metastatic progression. 146 Large scale alterations in the transcriptome of SINET LM compared to primary tumours have 147 been identified, with more subtle alterations in the methylome.  This may indicate that small 148 alterations in the epigenetic status of key genes are sufficient to drive metastatic progression, 149 or that alternative mechanisms are also contributing to progression including for example 150 histone modifications.  To date there have been no identified driver genetic mutations 151 responsible for SINET development or progression.  The data presented in this manuscript 152 suggest that epigenetic alterations are significant in this tumour type.  We believe that future 153 research should be focused on further elucidating epigenetic mechanisms in the evolution of 154 neuroendocrine tumours. 155  156 Page 7 of 148  Acknowledgments 157 This work was supported by the UCL Experimental Cancer Medicine Centre and the NIHR 158 UCLH Biomedical Research Centre   159 Disclosure 160 I declare that there is no conflict of interest that could be perceived as prejudicing the 161 impartiality of the research reported. 162  163 Reference List 164  165 Crona J, Gustavsson T, Norlen O, Edfeldt K, Akerstrom T, Westin G, Hellman P, Bjorklund P, Stalberg 166 P. Somatic Mutations and Genetic Heterogeneity at the CDKN1B Locus in Small Intestinal 167 Neuroendocrine Tumors. Annals of surgical oncology 2015. 168  169 Fazio N, Buzzoni R, Baudin E, Antonuzzo L, Hubner R, Lahner H, De Herder W, Raderer M, Teule A, 170 Capdevila J et al A phase II study of BEZ235 in patients with everolimus resistant advanced 171 pancreatic neuroendcrine tumours.  Anticancer Research 2016;36(2):713-719 172  173 Francis JM, Kiezun A, Ramos AH, Serra S, Pedamallu CS, Qian ZR, Banck MS, Kanwar R, Kulkarni AA, 174 Karpathakis A et al. Somatic mutation of CDKN1B in small intestine neuroendocrine tumors. Nature 175 genetics 2013;45(12):1483-6. 176  177 Hashemi J, Fotouhi O, Sulaiman L,Kjellman M, Hoog A, Zedenius J, Larsson C. Copy number 178 alterations in small intestinal neuroendocrine tumors determined by array comparative genomic 179 hybridization. BMC cancer 2013;13:505. 180 Page 8 of 149   181 Karpathakis A, Dibra H, Pipinikas C, Feber A, Morris T, Francis J, Oukrif D, Mandair D, Pericleous M, 182 Mohmaduvesh M et al. Prognostic Impact of Novel Molecular Subtypes of Small Intestinal 183 Neuroendocrine Tumours.  Clinical cancer research 2016;22(1):250-8 184  185 Leja J, Essaghir A, Essand M,Wester K, Oberg K, Totterman TH, Lloyd R, Vasmatzis G, Demoulin JB, 186 Giandomenico V. Novel markers for enterochromaffin cells and gastrointestinal neuroendocrine 187 carcinomas. Modern pathology : an official journal of the United States and Canadian Academy of 188 Pathology, Inc 2009;22(2):261-72. 189  190 Sherman SK, Carr JC, Wang D,O'Dorisio MS, O'Dorisio TM, Howe JR. Gastric inhibitory polypeptide 191 receptor (GIPR) is a promising target for imaging and therapy in neuroendocrine tumors. Surgery 192 2013;154(6):1206-13; discussion 1214. 193  194 Verdugo AD, Crona J, Starker L,Stalberg P, Akerstrom G, Westin G, Hellman P, Bjorklund P. Global 195 DNA methylation patterns through an array-based approach in small intestinal neuroendocrine 196 tumors. Endocrine-related cancer 2014;21(1):L5- 197  198 Yao JC, Fazio N, Singh S, Buzzoni R, Carnaghi C, Wolin E, Tomasek J, Raderer M, Lahner H, Voi M et al. 199 Everolimus for the treatment of advanced non-functional neuroendcrine tumours of the lung or 200 gastrointestinal tract (RADIANT-4): a randomised placebo controlled phase 3 study.  Lancet 201 2016;387(10022):968-77  202  203 Yao JC, Hassan M, Phan A, Dagohoy C, Leary C, Mares JE, Abdalla EK, Fleming JB, Vauthey JN, Rashid 204 A et al. One hundred years after "carcinoid": epidemiology of and prognostic factors for 205 Page 9 of 1410  neuroendocrine tumors in 35,825 cases in the United States. Journal of clinical oncology : official 206 journal of the American Society of Clinical Oncology 2008;26(18):3063-72. 207  208  209  210 Page 10 of 14Figure and Table Legends Figure 1 Methylation and expression profile of SINET LM demonstrates progressive dysregulation compared to SINET primary tumours in a panel of genes Table 1 Methylation and expression profile of SINET LM demonstrates progressive dysregulation compared to SINET primary tumours in a panel of genes.  Normal small intestine (NSI), Small intestinal primary neuroendocrine tumour (SINET), Liver metastasis (LM).  Page 11 of 14  Median methylation Median Expression   NSI SINET LM Lm progressing trend? p (LM vs SINET) NSI SINET LM Lm progressing trend? p (LM vs SINET) Downregulated :               CDX1 0.55 0.90 0.91 yes 0.48 5,481.4 1,503.0 570.8 yes 0.03 FBP1 0.43 0.82 0.83 yes 0.58 10,896.0 2,193.1 2,937.5 no 0.54 TMEM171 0.18 0.61 0.73 yes 0.11 3,632.7 519.6 201.9 yes 0.08 C20orf54 0.34 0.64 0.60 no 0.64 2,320.5 577.0 176.7 yes 0.056 GATA5 0.89 0.69 0.57 yes 0.006 658.2 64.0 65.8 no 0.96 NGEF 0.89 0.72 0.60 yes 0.018 3,819.7 512.2 309.9 yes 0.23 PNLIPRP2 0.77 0.47 0.33 yes 0.007 1,419.4 235.0 95.5 yes 0.34 TRIM15 0.53 0.87 0.87 no 0.65 615.8 93.1 27.2 yes 0.009 Upregulated :                     PTPRN 0.38 0.11 0.07 yes 0.001 349.8 4,319.1 5,456.3 yes 0.1 C3orf14 0.32 0.12 0.07 yes <0.001 212.4 1,016.7 1,803.9 yes 0.002 CNTNAP5 0.26 0.09 0.08 yes 0.009 280.3 4,343.1 3,518.3 no 0.22 DSCAM 0.50 0.15 0.08 yes <0.001 59.9 1,142.3 1,028.6 no 0.61 GDAP1L1 0.38 0.08 0.05 yes 0.002 74.3 659.7 1,051.8 yes 0.07 PCSK1 0.38 0.08 0.05 yes 0.001 217.9 2,420.4 2,911.0 yes 0.39 PRLHR 0.44 0.13 0.06 yes <0.001 193.6 3,909.3 2,676.2 no 0.08 SNTG1 0.28 0.07 0.04 yes <0.001 78.6 2,126.9 3,396.3 yes 0.003 CELSR3 0.10 0.57 0.67 yes 0.11 2,029.6 7,869.0 9,442.6 yes 0.17 GIPR 0.30 0.66 0.74 yes 0.034 248.1 1,900.0 2,283.6 yes 0.27 KCNH6 0.07 0.36 0.48 yes 0.01 998.3 5,146.7 5,935.3 yes 0.35 LMX1B 0.30 0.59 0.60 yes 0.99 286.8 3,503.9 1,979.4 no 0.034 RUNDC3A 0.08 0.42 0.66 yes 0.02 454.2 3,966.4 5,677.8 yes 0.081 Table 1Page 12 of 14 Page 13 of 14Expression Methylation Downregulated Upregulated Upregulated Downregulated Page 14 of 14

Progressive epigenetic dysregulation in neuroendocrine tumour liver metastasis

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Progressive epigenetic dysregulation in neuroendocrine tumour liver metastasis

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