Early onset pancreatic cancer (EOPC) is a rare disease with a very high mortality rate. Almost nothing is known on the genetic susceptibility of EOPC, therefore we performed a genome-wide association study (GWAS) to identify novel genetic variants specific for patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) at younger ages. In the first phase, conducted on 821 cases with age of onset ≤60 years, of whom 198 with age of onset ≤50, and 3227 controls from PanScan I-II, we observed four SNPs (rs7155613, rs2328991, rs4891017 and rs12610094) showing an association with EOPC risk (P < 1x10-4 ). We replicated these SNPs in the PANcreatic Disease ReseArch (PANDoRA) consortium and used additional in silico data from PanScan III and PanC4. Among these four variants rs2328991 was significant in an independent set of 855 cases with age of onset ≤60 years, of whom 265 with age of onset≤50, and 4142 controls from the PANDoRA consortium while in the in silico data we observed no statistically significant association. However, the resulting meta-analysis supported the association (P = 1.15x10-4 ). In conclusion we propose a novel variant rs2328991 to be involved in EOPC risk. Even though it was not possible to find a mechanistic link between the variant and the function, the association is supported by a solid statistical significance obtained in the largest study on EOPC genetics present so far in the literature. This article is protected by copyright. All rights reserved.

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Genome-wide association study identifies an early onset pancreatic cancer risk locus.

Translational genomics in pancreatic ductal adenocarcinoma: A review with re-analysis of TCGA dataset.

Notch signaling plays a key role in the development of pancreatic cancer. Among the four identified Notch receptors, Notch1 and Notch2 share the highest homology. Notch1 has been reported to be an oncogene but some reports indicate that Notch2, not Notch1, plays a key role in pancreatic carcinogenesis. As both are transcription factors, examination of their genomic binding sites might reveal interesting functional differences between them. Notch proteins do not have DNA-binding domain. In the canonical Notch signaling pathway, ligand binding induces the release and nuclear translocation of Notch receptor intracellular domains (NICDs), which then interact with the transcription factor CSL, resulting in subsequent activation of the canonical Notch target genes. We investigated the binding site profiles of Notch1and Notch2 in the BxPC3 genome using CHIP-Seq and bioinfomatics. We found that Notch1, Notch2 and CSL generally bound to different target genes. We also found that only a small subset of Notch1 and Notch2 binding sites overlap with that of CSL, but about half of the CSL binding overlap with that of Notch1 or Notch2, indicating most Notch signaling activities are CSL-independent.

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Comparative analysis of Notch1 and Notch2 binding sites in the genome of BxPC3 pancreatic cancer cells.

MiRNA-associated genetic variants occurring in regulatory regions can affect the efficiency of transcription and potentially modify pri-miRNA or pre-miRNA processing. Since miRNA-based mechanisms are shown to be involved in the pathogenesis of prostate cancer (PCa), the aim of the present study was to evaluate the effect of rs4938723, rs1076064 and rs4705343 occurring in regulatory regions of miR-34b/c, miR-143/145 and miR-378, respectively, on PCa risk and progression in Serbian population. We examined a total of 1060 subjects, of which 350 were patients with PCa, 354 were patients with benign prostatic hyperplasia (BPH), while 356 healthy volunteers were included in the control group. Genotyping of rs4938723, rs1076064 and rs4705343 was performed by using Taqman® SNP Genotyping Assays. Allele C of rs4705342 was found to increase the risk of PCa (P=0.031 for codominant model, P=0.0088 for recessive model). Rs1076064 minor allele G was found to associate with serum PSA score, as well as with PCa T category and disease aggressiveness. For rs4938723 minor allele C was shown to be associated with the lower PCa T category (Pdom=0.0046; OR=0.36, 95 % CI 0.17-0.76) in T2 vs. T1 comparison. Rs4705342 was identified as PCa susceptibility variant in Serbian population, while for rs1076064 and rs4938723 association with PCa progression parameters was found.

Analysis of association of potentially functional genetic variants within genes encoding miR-34b/c, miR-378 and miR-143/145 with prostate cancer in Serbian population.

For optimal pancreatic cancer treatment, early and accurate diagnosis is vital. Blood-derived biomarkers and genetic predispositions can contribute to early diagnosis, but they often have limited accuracy or applicability. Here, we seek to exploit the synergy between them by combining the biomarker CA19-9 with RNA-based variants. We use deep sequencing and deep learning to improve differentiating pancreatic cancer and chronic pancreatitis. We obtained samples of nucleated cells found in peripheral blood from 268 patients suffering from resectable, non-resectable pancreatic cancer, and chronic pancreatitis. We sequenced RNA with high coverage and obtained millions of variants. The high-quality variants served as input together with CA19-9 values to deep learning models. Our model achieved an area under the curve (AUC) of 96% in differentiating resectable cancer from pancreatitis using a test cohort. Moreover, we identified variants to estimate survival in resectable cancer. We show that the blood transcriptome harbours variants, which can substantially improve noninvasive clinical diagnosis.

Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants.

// Jinyun Chen 1 , Xifeng Wu 1, 4 , Yujing Huang 1 , Wei Chen 1 , Randall E. Brand 2 , Ann M. Killary 3, 4 , Subrata Sen 3, 4 , Marsha L. Frazier 1, 4 1 Department of Epidemiology The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA 2 Department of Gastroenterology, Hepatology, and Nutrition, The University of Pittsburgh, Pittsburgh, Pennsylvania, USA 3 Department of Translational Molecular Pathology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas, USA 4 Program in Human and Molecular Genetics, The University of Texas Graduate School of Biomedical Sciences, Houston, Texas, USA Correspondence to: Subrata Sen, email: ssen@mdanderson.org Ann M. Killary, email: akillary@mdanderson.org Keywords: SNP, genetic variant, age at diagnosis, pathway, pancreatic cancer Received: September 14, 2015      Accepted: January 01, 2016      Published: July 29, 2016 ABSTRACT Biomarkers are critically needed for the early detection of pancreatic cancer (PC) are urgently needed. Our purpose was to identify a panel of genetic variants that, combined, can predict increased risk for early-onset PC and thereby identify individuals who should begin screening at an early age. Previously, we identified genes using a functional genomic approach that were aberrantly expressed in early pathways to PC tumorigenesis. We now report the discovery of single nucleotide polymorphisms (SNPs) in these genes associated with early age at diagnosis of PC using a two-phase study design. In silico and bioinformatics tools were used to examine functional relevance of the identified SNPs. Eight SNPs were consistently associated with age at diagnosis in the discovery phase, validation phase and pooled analysis. Further analysis of the joint effects of these 8 SNPs showed that, compared to participants carrying none of these unfavorable genotypes (median age at PC diagnosis 70 years), those carrying 1–2, 3–4, or 5 or more unfavorable genotypes had median ages at diagnosis of 64, 63, and 62 years, respectively ( P = 3.0E–04). A gene-dosage effect was observed, with age at diagnosis inversely related to number of unfavorable genotypes ( P trend = 1.0E–04). Using bioinformatics tools, we found that all of the 8 SNPs were predicted to play functional roles in the disruption of transcription factor and/or enhancer binding sites and most of them were expression quantitative trait loci (eQTL) of the target genes. The panel of genetic markers identified may serve as susceptibility markers for earlier PC diagnosis.

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Yu-jing Huang

Papers

Identification of genetic variants predictive of early onset pancreatic cancer through a population science analysis of functional genomic datasets