Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

The pan-cancer analysis of whole genomes The expansion of whole-genome sequencing studies from individual ICGC and TCGA working groups presented the opportunity to undertake a meta-analysis of genomic features across tumour types. To achieve this, the PCAWG Consortium was established. A Technical Working Group implemented the informatics analyses by aggregating the raw sequencing data from different working groups that studied individual tumour types, aligning the sequences to the human genome and delivering a set of high-quality somatic mutation calls for downstream analysis (Extended Data Fig. 1). Given the recent meta-analysis

The diagnosis of pancreatic neuroendocrine tumours (PanNETs) is increasing owing to more sensitive detection methods, and this increase is creating challenges for clinical management. We performed whole-genome sequencing of 102 primary PanNETs and defined the genomic events that characterize their pathogenesis. Here we describe the mutational signatures they harbour, including a deficiency in G:C > T:A base excision repair due to inactivation of MUTYH, which encodes a DNA glycosylase. Clinically sporadic PanNETs contain a larger-than-expected proportion of germline mutations, including previously unreported mutations in the DNA repair genes MUTYH, CHEK2 and BRCA2. Together with mutations in MEN1 and VHL, these mutations occur in 17% of patients. Somatic mutations, including point mutations and gene fusions, were commonly found in genes involved in four main pathways: chromatin remodelling, DNA damage repair, activation of mTOR signalling (including previously undescribed EWSR1 gene fusions), and telomere maintenance. In addition, our gene expression analyses identified a subgroup of tumours associated with hypoxia and HIF signalling.

Next‐generation sequencing (NGS) was applied to 148 lung neuroendocrine tumours (LNETs) comprising the four World Health Organization classification categories: 53 typical carcinoid (TCs), 35 atypical carcinoid (ACs), 27 large‐cell neuroendocrine carcinomas, and 33 small‐cell lung carcinomas. A discovery screen was conducted on 46 samples by the use of whole‐exome sequencing and high‐coverage targeted sequencing of 418 genes. Eighty‐eight recurrently mutated genes from both the discovery screen and current literature were verified in the 46 cases of the discovery screen, and validated on additional 102 LNETs by targeted NGS; their prevalence was then evaluated on the whole series. Thirteen of these 88 genes were also evaluated for copy number alterations (CNAs). Carcinoids and carcinomas shared most of the altered genes but with different prevalence rates. When mutations and copy number changes were combined, MEN1 alterations were almost exclusive to carcinoids, whereas alterations of TP53 and RB1 cell cycle regulation genes and PI3K/AKT/mTOR pathway genes were significantly enriched in carcinomas. Conversely, mutations in chromatin‐remodelling genes, including those encoding histone modifiers and members of SWI–SNF complexes, were found at similar rates in carcinoids (45.5%) and carcinomas (55.0%), suggesting a major role in LNET pathogenesis. One AC and one TC showed a hypermutated profile associated with a POLQ damaging mutation. There were fewer CNAs in carcinoids than in carcinomas; however ACs showed a hybrid pattern, whereby gains of TERT, SDHA, RICTOR, PIK3CA, MYCL and SRC were found at rates similar to those in carcinomas, whereas the MEN1 loss rate mirrored that of TCs. Multivariate survival analysis revealed RB1 mutation (p = 0.0005) and TERT copy gain (p = 0.016) as independent predictors of poorer prognosis. MEN1 mutation was associated with poor prognosis in AC (p = 0.0045), whereas KMT2D mutation correlated with longer survival in SCLC (p = 0.0022). In conclusion, molecular profiling may complement histology for better diagnostic definition and prognostic stratification of LNETs. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Intraductal neoplasms are important precursors to invasive pancreatic cancer and an opportunity to detect and treat pancreatic neoplasia before an invasive carcinoma develops. The diagnostic evaluation of these lesions is challenging as diagnostic imaging and cytological sampling do not provide accurate information on lesion classification, the grade of dysplasia or the presence of invasion. Moreover, the molecular driver gene mutations of these precursor lesions have yet to be fully characterized. Fifty-two intraductal papillary neoplasms, including 48 intraductal papillary mucinous neoplasms (IPMNs) and 4 intraductal tubulopapillary neoplasms (ITPNs), were subjected to the mutation assessment in 51 cancer-associated genes, using Ion Torrent semiconductor-based next-generation sequencing. P16 and Smad4 immunohistochemistry was performed on 34 IPMNs, and 17 IPMN-associated carcinomas. At least one somatic mutation was observed in 46/48 (96%) IPMNs; 29 (60%) had multiple gene alterations. GNAS and/or KRAS mutations were found in 44/48 (92%) of IPMNs. GNAS was mutated in 38/48 (79%) IPMNs, KRAS in 24/48 (50%), and these mutations coexisted in 18/48 (37.5%) of IPMNs. RNF43 was the third most commonly mutated gene and was always associated with GNAS and/or KRAS mutations, as were virtually all the low frequency mutations found in other genes. Mutations in TP53 and BRAF genes (10% and 6%) were only observed in high-grade IPMNs. P16 was lost in 7/34 IPMNs and 9/17 IPMN-associated carcinomas; Smad4 was lost in 1/34 IPMN and 5/17 IPMN-associated carcinomas. In contrast to IPMNs, only one of four ITPN had detectable driver gene (GNAS and NRAS) mutations. Deep sequencing DNA from 7 cyst fluid aspirates identified 10 of the 13 mutations detected in their associated IPMN. Using next-generation sequencing to detect cyst fluid mutations has the potential to improve the diagnostic and prognostic stratification of pancreatic cystic neoplasms.