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Global challenges in access to diagnostics and treatment for neuroendocrine tumor (NET) patients

Dureja S, McDonnell M, Van Genechten D, Bouvier C, Kolarova T, O'Toole D, et al.

J Neuroendocrinol, 2023 Jun;35(6):e13310.
PMID: 37351944 DOI: 10.1111/jne.13310

SCAN, an online survey, measured access to diagnosis, treatments and monitoring of neuroendocrine tumor (NET) patients globally. Between September and November 2019, NET patients and healthcare professionals (HCPs) completed an online, semi-standardized survey with 54 patient questions and 33 HCP questions. A total of 2359 patients with NETs and 436 HCPs responded. Misdiagnosis was common (44% [1043/2359]). Mean time to diagnosis was 4.8 years (standard deviation [SD], 6.2). Compared with global figures (60% [1407/2359]), the availability of 68 Ga-DOTA positron emission tomography (PET)/computed tomography (CT) was significantly lower in Asia (45% [126/280]) and higher in Oceania (86% [171/200]). HCPs reported that 68 Ga-DOTA PET/CT was free/affordable to fewer patients in Emerging and Developing Economies (EDE) than Advanced Economies (AE; 17% [26/150] and 59% [84/142], respectively). Compared with global data (52% [1234/2359]), patient-reported availability of peptide receptor radionuclide therapy (PRRT) was significantly lower in Asia (31% [88/280]) and higher in Oceania (61% [122/200]). Significant differences were observed in average annual NET specialist costs between AE and EDE ($1081 and $2915, respectively). Compared with AE, patients in EDE traveled further for NET specialists (1032 [SD, 1578] and 181 [SD, 496] km, respectively). Patients and HCPs both recommended referral to HCPs that were more knowledgeable in the field of NETs and had better access to NET experts/specialist centers. National care pathways, enhancing HCP NET knowledge and ensuring effective diagnostics and access to appropriate treatments are crucial to improving patient survival and NET care worldwide.
Fulltext Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer

Klein AP, Wolpin BM, Risch HA, Stolzenberg-Solomon RZ, Mocci E, Zhang M, et al.

Nat Commun, 2018 02 08;9(1):556.
PMID: 29422604 DOI: 10.1038/s41467-018-02942-5

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.
Fulltext Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer

Walsh N, Zhang H, Hyland PL, Yang Q, Mocci E, Zhang M, et al.

J Natl Cancer Inst, 2019 Jun 01;111(6):557-567.
PMID: 30541042 DOI: 10.1093/jnci/djy155

BACKGROUND: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes.
METHODS: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.
RESULTS: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.
CONCLUSION: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.

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