Targeted next-generation sequencing of cancer genes dissects the molecular profiles of intraductal papillary neoplasms of the pancreas

Abstract

Intraductal neoplasms are important precursors to invasive pancreatic cancer and provide 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 four 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 IPMNs and 5/17 IPMN-associated carcinomas. In contrast to IPMNs, only one of four ITPNs had detectable driver gene (GNAS and NRAS) mutations. Deep sequencing DNA from seven 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.

Keywords: IPMN; biomarkers; next-generation sequencing (NGS); pancreatic tumours.

Figure 1

Representative haematoxylin and eosin (H&E) images and differential mucins immunolabelling of pancreatic intraductal neoplasms (original magnification = ×20). PB, pancreaticobiliary; ITPN, intraductal tubulopapillary neoplasm.

Figure 2

Mutational profiles of matched non-invasive and invasive IPMN components identified by ion torrent sequencing. (A) Three cases (128 fp, 129fp and 138fp) presented a non-invasive intermediate-grade (IG) or high-grade (HG) dysplastic component and an invasive adenocarcinoma (K) component, both of which were analysed using the 50-gene Ampliseq Hotspot Cancer Panel; representative H&E images from case 138fp are presented (original magnifications = ×2 and ×20). (B) For each pair of samples, the first column denotes mutations detected in IG or HG dysplastic samples and the second column represents mutations detected in cancer samples. Rows are the genes in which mutations were detected, and the orange bars represent the mutation. Seven mutations observed in the GNAS, KRAS, BRAF, KRAS and STK11 genes were common to both samples; three mutations were observed in only one of the matched lesions.

Figure 3

Concomitant IPMN and ITPN sharing a common GNAS mutation. Patient 130fp presented two different neoplastic lesions, an intestinal-type IPMN and an ITPN coexisting in pancreatic head. The two phenotypically different lesions showed a common GNAS R201H mutation; the ITPN component presented a NRAS Q61L mutation; representative H&E images of the lesions are shown (original magnifications = ×20). On the right of each sample is a representation of the reads aligned to the reference genome, as provided by the Integrative Genomics Viewer software (IGV v 2.1, Broad Institute) for the hotspot mutations in the GNAS and NRAS genes.

Figure 4

IPMN showing a KRAS mutation V14I. The intestinal-type IPMN 128fp presented a V14I KRAS mutation in both the high grade (HG) dysplastic and the invasive carcinomatous (K) component, analysed separately using the 50-gene Ampliseq Hotspot Cancer Panel; a representative H&E image of the lesions is shown (original magnification = ×20). On the right there is a representation of the reads aligned to the reference genome, as provided by the Integrative Genomics Viewer software (IGV v 2.1, Broad Institute).

Figure 5

TP53 mutational status corresponds to p53 protein accumulation. (A) Case 939 showed a heterogeneous pattern of staining, which is consistent with TP53 mutational status (21% of mutated alleles, I195N). (B) Case 108, with no evident p53 labelling, corresponds to a homozygous stop mutation (83% of mutated alleles, R306*). For each sample, a representative p53 immunohistochemical image (original magnification = ×20) and a representation of the reads aligned to the reference genome, as provided by the Integrative Genomics Viewer software (IGV v 2.1, Broad Institute), are presented.

Figure 6

P16 and Smad4 immunoexpression in IPMN. Representative images of p16 (A–D) and Smad4 (E–H) immunoreactions are shown. (A) In normal pancreatic parenchyma, p16 is expressed in Langerhans’ islets and in random acinar and duct cells. (B) A barcode-like p16 positivity in a gastric-type IPMN. (C) Strong nuclear and cytoplasmic p16 expression in an oncocytic-type IPMN. (D) p16 expression heterogeneity in a case of pancreatobiliary-type IPMN (positive and negative p16 components are evident). (E) Normal pancreas shows a strong Smad4 expression in all epithelial and stromal cell types, with stronger positivity in Langerhans’ islets. Strong Smad4 expression in intestinal-type (F) and oncocytic-type (G) IPMNs. (H) A Smad4 negative invasive carcinoma infiltrating the stroma surrounding a pancreatobiliary-type IPMN. Original magnifications = ×10 and ×20.