SummaryCXCR2 has been suggested to have both tumor-promoting and tumor-suppressive properties. Here we show that CXCR2 signaling is upregulated in human pancreatic cancer, predominantly in neutrophil/myeloid-derived suppressor cells, but rarely in tumor cells. Genetic ablation or inhibition of CXCR2 abrogated metastasis, but only inhibition slowed tumorigenesis. Depletion of neutrophils/myeloid-derived suppressor cells also suppressed metastasis suggesting a key role for CXCR2 in establishing and maintaining the metastatic niche. Importantly, loss or inhibition of CXCR2 improved T cell entry, and combined inhibition of CXCR2 and PD1 in mice with established disease significantly extended survival. We show that CXCR2 signaling in the myeloid compartment can promote pancreatic tumorigenesis and is required for pancreatic cancer metastasis, making it an excellent therapeutic target.

MYC is implicated in the development and progression of Pancreatic cancer, yet the precise level of MYC deregulation required to contribute to tumour development has been difficult to define.We used modestly elevated expression of human MYC, driven from the Rosa26 locus, to investigate the pancreatic phenotypes arising in mice from an approximation of MYC trisomy. We show that this level of MYC alone suffices to drive pancreatic neuroendocrine tumours, and to accelerate progression of KRAS-initiated precursor lesions to metastatic pancreatic ductal adenocarcinoma. Our phenotype exposed suppression of the Type I Interferon pathway by the combined actions of MYC and KRAS and we present evidence of repressive MYC/MIZ1 complexes binding directly to the promoters of type I Interferon regulators IRF5, IRF7, STAT1 and STAT2. Derepression of Interferon regulators allows pancreatic tumour infiltration of B and NK cells, resulting in increased survival.

Highlights d HNF4A loss upregulates GSK3b and drives a squamous-like metabolic profile d GSK3b targeting inhibits glycolysis in squamous patientderived cell lines (PDCLs) d A subset of squamous PDCLs acquires GSK3b drug tolerance d ATAC-seq analysis reveals an accessible WNT gene program in drug-tolerant PDCLs

No abstract

BackgroundPancreatic ductal adenocarcinoma (PDAC) remains a dismal disease, with very little improvement in survival over the past 50 years. Recent large‐scale genomic studies have improved understanding of the genomic and transcriptomic landscape of the disease, yet very little is known about molecular heterogeneity according to tumour location in the pancreas; body and tail PDACs especially tend to have a significantly worse prognosis. The aim was to investigate the molecular differences between PDAC of the head and those of the body and tail of the pancreas.MethodsDetailed correlative analysis of clinicopathological variables, including tumour location, genomic and transcriptomic data, was performed using the Australian Pancreatic Cancer Genome Initiative (APGI) cohort, part of the International Cancer Genome Consortium study.ResultsClinicopathological data were available for 518 patients recruited to the APGI, of whom 421 underwent genomic analyses; 179 of these patients underwent whole‐genome and 96 RNA sequencing. Patients with tumours of the body and tail had significantly worse survival than those with pancreatic head tumours (12·1 versus 22·0 months; P = 0·001). Location in the body and tail was associated with the squamous subtype of PDAC. Body and tail PDACs enriched for gene programmes involved in tumour invasion and epithelial‐to‐mesenchymal transition, as well as features of poor antitumour immune response. Whether this is due to a molecular predisposition from the outset, or reflects a later time point on the tumour molecular clock, requires further investigation using well designed prospective studies in pancreatic cancer.ConclusionPDACs of the body and tail demonstrate aggressive tumour biology that may explain worse clinical outcomes.

BackgroundMultiple genes have been implicated by association studies in altering inflammatory bowel disease (IBD) predisposition. Paediatric patients often manifest more extensive disease and a particularly severe disease course. It is likely that genetic predisposition plays a more substantial role in this group.ObjectiveTo identify the spectrum of rare and novel variation in known IBD susceptibility genes using exome sequencing analysis in eight individual cases of childhood onset severe disease.DesignDNA samples from the eight patients underwent targeted exome capture and sequencing. Data were processed through an analytical pipeline to align sequence reads, conduct quality checks, and identify and annotate variants where patient sequence differed from the reference sequence. For each patient, the entire complement of rare variation within strongly associated candidate genes was catalogued.ResultsAcross the panel of 169 known IBD susceptibility genes, approximately 300 variants in 104 genes were found. Excluding splicing and HLA-class variants, 58 variants across 39 of these genes were classified as rare, with an alternative allele frequency of <5%, of which 17 were novel. Only two patients with early onset Crohn's disease exhibited rare deleterious variations within NOD2: the previously described R702W variant was the sole NOD2 variant in one patient, while the second patient also carried the L1007 frameshift insertion. Both patients harboured other potentially damaging mutations in the GSDMB, ERAP2 and SEC16A genes. The two patients severely affected with ulcerative colitis exhibited a distinct profile: both carried potentially detrimental variation in the BACH2 and IL10 genes not seen in other patients.ConclusionFor each of the eight individuals studied, all non-synonymous, truncating and frameshift mutations across all known IBD genes were identified. A unique profile of rare and potentially damaging variants was evident for each patient with this complex disease.

Because of the complexity of gene-phenotype relationships machine learning approaches have considerable appeal as a strategy for modelling interactions. A number of such methods have been developed and applied in recent years with some modest success. Progress is hampered by the challenges presented by the complexity of the disease genetic data, including phenotypic and genetic heterogeneity, polygenic forms of inheritance and variable penetrance, combined with the analytical and computational issues arising from the enormous number of potential interactions. We review here recent and current approaches focusing, wherever possible, on applications to real data (particularly in the context of genome-wide association studies) and looking ahead to the further challenges posed by next generation sequencing data.

No abstract