SUMMARY We describe the landscape of genomic alterations in cutaneous melanomas through DNA, RNA, and protein-based analysis of 333 primary and/or metastatic melanomas from 331 patients. We establish a framework for genomic classification into one of four subtypes based on the pattern of the most prevalent significantly mutated genes: mutant BRAF, mutant RAS, mutant NF1, and Triple-WT (wild-type). Integrative analysis reveals enrichment of KIT mutations and focal amplifications and complex structural rearrangements as a feature of the Triple-WT subtype. We found no significant outcome correlation with genomic classification, but samples assigned a transcriptomic subclass enriched for immune gene expression associated with lymphocyte infiltrate on pathology review and high LCK protein expression, a T cell marker, were associated with improved patient survival. This clinicopathological and multidimensional analysis suggests that the prognosis of melanoma patients with regional metastases is influenced by tumor stroma immunobiology, offering insights to further personalize therapeutic decision-making.

SUMMARY We performed integrated genomic, transcriptomic and proteomic profiling of 150 pancreatic ductal adenocarcinoma (PDAC) specimens, including samples with characteristic low neoplastic cellularity. Deep whole-exome sequencing revealed recurrent somatic mutations in KRAS, TP53, CDKN2A, SMAD4, RNF43, ARID1A, TGFβR2, GNAS, RREB1 and PBRM1. KRAS wild-type tumors harbored alterations in other oncogenic drivers, including GNAS, BRAF, CTNNB1 and additional RAS pathway genes. A subset of tumors harbored multiple KRAS mutations, with some showing evidence of biallelic mutations. Protein profiling identified a favorable prognosis subset with low epithelial-mesenchymal transition and high MTOR pathway scores. Associations of non-coding RNAs with tumor-specific mRNA subtypes were also identified. Our integrated multi-platform analysis reveals a complex molecular landscape of PDAC and provides a roadmap for precision medicine.

AIM To identify the multidetector computed tomography (MDCT) features of pancreatic neuroendocrine tumours (pNETs), which correlate with tumour histology and enable preoperative grading. MATERIALS AND METHODS Thirty-nine patients with histologically confirmed pNET who underwent preoperative contrast-enhanced MDCT were included in this study. Nineteen tumours were classified as Grade 1 (G1) and 20 as Grade 2 (G2). Histopathology slides were reviewed to assess the intratumoural microvascular density (MVD) and the amount of tumour stroma. Computed tomography (CT) image analysis included tumour size, margin delineation, calcifications, homogeneity, contrast enhancement (CE) pattern, tumour absolute and relative enhancement, presence of cystic changes, pancreatic duct dilatation, regional and distant metastases. The diagnostic ability to predict tumour grade was measured for each MDCT finding and their combinations. RESULTS The mean arterial enhancement ratio had a mean±standard deviation of 1.53±0.45 in G1 and 1.01±0.33 in G2 pNETs (p=0.0003) and correlated with intratumoural microvascular density (MVD; r=0.55, p=0.0002). Tissue stroma percentage did not correlate with imaging findings. Late CE of the tumour (the peak attenuation observed in the venous phase) was significantly associated with G2. Tumour size ≥20 mm, arterial enhancement ratio <1.1, and late CE showed 74.4%, 79.5%, and 74.4% accuracy, respectively, in diagnosing G2 tumours, while the accuracy of at least two of these criteria used in combination was 82%. Based on these results, a diagnostic algorithm was proposed, which showed high interobserver agreement (k=0.82) in the prediction of tumour grade. CONCLUSION Contrast-enhanced MDCT features correlate with histological findings and enable the differentiation between G1 and G2 pNETs during preoperative examination.