Pancreatic neuroendocrine tumors (pNETs) are uncommon cancers arising from pancreatic islet cells. Here we report the analysis of gene mutation, copy number, and RNA expression of 57 sporadic well-differentiated pNETs. pNET genomes are dominated by aneuploidy, leading to concordant changes in RNA expression at the level of whole chromosomes and chromosome segments. We observed two distinct patterns of somatic pNET aneuploidy that are associated with tumor pathology and patient prognosis. Approximately 26% of the patients in this series had pNETs with genomes characterized by recurrent loss of heterozygosity (LoH) of 10 specific chromosomes, accompanied by bi-allelicMEN1inactivation and generally poor clinical outcome. Another ~40% of patients had pNETs that lacked this recurrent LoH pattern but had chromosome 11 LoH, bi-allelicMEN1inactivation, and universally good clinical outcome. The somatic aneuploidy allowed pathogenic germline variants (e.g.,ATM) to be expressed unopposed, with RNA expression patterns showing inactivation of downstream tumor suppressor pathways. No prognostic associations were found with tumor morphology, single gene mutation, or expression of RNAs reflecting the activity of immune, differentiation, proliferative or tumor suppressor pathways. In pNETs, single gene mutations appear to be less important than aneuploidy, withMEN1the only statistically significant recurrently mutated driver gene. In addition, only one pNET in the series had clearly actionable single nucleotide variants (SNVs) (inPTENandFLCN) confirmed by corroborating RNA expression changes. The two clinically relevant patterns of LoH described here define a novel oncogenic mechanism and a plausible route to genomic precision oncology for this tumor type.

Tumor evolution underlies many challenges facing precision oncology, and improving our understanding has the potential to improve clinical care. This study represents a rare opportunity to study tumor heterogeneity and evolution in a patient with an understudied cancer type.A patient with pulmonary atypical carcinoid, a neuroendocrine tumor, metastatic to 90 sites, requested and consented to donate tissues for research. 42 tumor samples collected at rapid autopsy from 14 anatomically distinct sites were analyzed through DNA whole-exome sequencing and RNA sequencing, and five analyzed through linked-read sequencing. Targeted DNA sequencing was completed on two clinical tissue biopsies and one blood plasma sample.Chromosomal alterations and gene variants accumulated over time, and specific chromosomal alterations preceded the single predicted gene driver variant (ARID1A). At the time of autopsy, all sites shared the gain of one copy of Chr 5, loss of one copy of Chr 6 and 21, chromothripsis of one copy of Chr 11, and 39 small variants. Two tumor clones (carrying additional variants) were detected at metastatic sites, and occasionally in different regions of the same organ (e.g., within the pancreas). Circulating tumor DNA (ctDNA) sequencing detected shared tumor variants in the blood plasma and captured marked genomic heterogeneity, including all metastatic clones but few private tumor variants.This study describes genomic tumor evolution and dissemination of a pulmonary atypical carcinoid donated by a single generous patient. It highlights the critical role of chromosomal alterations in tumor initiation and explores the potential of ctDNA analysis to represent genomically heterogeneous disease.Significance: DNA sequencing data from tumor samples and blood plasma from a single patient highlighted the critical early role of chromosomal alterations in atypical carcinoid tumor development. Common tumor variants were readily detected in the blood plasma, unlike emerging tumor variants, which has implications for using ctDNA to capture cancer evolution.

We introduce a proof-of-concept extended reality (XR) environment for discussing cancer, presenting genomic information from multiple tumour sites in the context of 3D tumour models generated from CT scans. This tool enhances multidisciplinary discussions. Clinicians and cancer researchers explored its use in oncology, sharing perspectives on XR’s potential for use in molecular tumour boards, clinician-patient communication, and education. XR serves as a universal language, fostering collaborative decision-making in oncology.

Quality performance indicators (QPIs) are used to monitor the delivery of cancer care. Neuroendocrine tumours (NETs) are a family of individually uncommon cancers that derive from neuroendocrine cells or their precursors, and can occur in most organs. There are currently no QPIs available for NETs and their heterogeneity makes QPI development difficult. CommNETs is a collaboration between NET clinicians, researchers and advocates in Canada, Australia and New Zealand. We created QPIs for NETs using a three-step consensus process. First, a multidisciplinary team used the nominal group technique to create candidates (n = 133) which were then curated into appropriateness statements (62 statements, 44 sub-statements). A two-stage modified RAND/UCLA Delphi consensus process was conducted: an online survey rated the statement appropriateness then the top-ranked statements (n = 20) were assessed in a face-to-face meeting. Finally, 10 QPIs met consensus criteria; documentation of primary site, proliferative index, differentiation, tumour board review, use of a structured pathology report, presence of distant metastasis, 5- and 10-year disease-free and overall survival. These NET QPIs will be trialed as a method to monitor and improve care for people with NETs and to facilitate international comparison.