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.
BackgroundThe upper gastrointestinal tract is home to some of most notorious cancers like esophagogastric and pancreatic cancer. Several factors contribute to the lethality of these tumors, but one that stands out for both tumor types is the strong inter- as well as intratumor heterogeneity. Unfortunately, genetic tumor models do not match this heterogeneity, and for esophageal cancer no adequate genetic models exist. To allow for an improved understanding of these diseases, tissue banks with sufficient amount of samples to cover the extent of diversity of human cancers are required. Additionally, xenograft models that faithfully mimic and span the breadth of human disease are essential to perform meaningful functional experiments.MethodsWe describe here the establishment of a tissue biobank, patient derived xenografts (PDXs) and cell line models of esophagogastric and pancreatic cancer patients. Biopsy material was grafted into immunocompromised mice and PDXs were used to establish primary cell cultures to perform functional studies. Expression of Hedgehog ligands in patient tumor and matching PDX was assessed by immunohistochemical staining, and quantitative real-time PCR as well as flow cytometry was used for cultured cells. Cocultures with Hedgehog reporter cells were performed to study paracrine signaling potency. Furthermore, SHH expression was modulated in primary cultures using lentiviral mediated knockdown.ResultsWe have established a panel of 29 PDXs from esophagogastric and pancreatic cancers, and demonstrate that these PDXs mirror several of the (immuno)histological and biochemical characteristics of the original tumors. Derived cell lines can be genetically manipulated and used to further study tumor biology and signaling capacity. In addition, we demonstrate an active (paracrine) Hedgehog signaling mode by both tumor types, the magnitude of which has not been compared directly in previous studies.ConclusionsOur established PDXs and their matching primary cell lines retain important characteristics seen in the original tumors, and this should enable future studies to address the responses of these tumors to different treatment modalities, but also help in gaining mechanistic insight in how some tumors respond to certain regimens and others do not.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-015-0469-1) contains supplementary material, which is available to authorized users.
Circulating tumor DNA (ctDNA) is assumed to reflect tumor burden and has been suggested as a tool for prognostication and follow‐up in patients with metastatic pancreatic ductal adenocarcinoma (mPDAC). However, the prognostic value of ctDNA and its relation with tumor burden has yet to be substantiated, especially in mPDAC. In this retrospective analysis of prospectively collected samples, cell‐free DNA from plasma samples of 58 treatment‐naive mPDAC patients was isolated and sequenced using a custom‐made pancreatobiliary NGS panel. Pathogenic mutations were detected in 26/58 (44.8%) samples. Cross‐check with droplet digital PCR showed good agreement in Bland–Altman analysis (p = 0.217, nonsignificance indicating good agreement). In patients with liver metastases, ctDNA was more frequently detected (24/37, p < 0.001). Tumor volume (3D reconstructions from imaging) and ctDNA variant allele frequency (VAF) were correlated (Spearman's ρ = 0.544, p < 0.001). Median overall survival (OS) was 3.2 (95% confidence interval [CI] 1.6–4.9) versus 8.4 (95% CI 1.6–15.1) months in patients with detectable versus undetectable ctDNA (p = 0.005). Both ctDNA VAF and tumor volume independently predicted OS after adjustment for carbohydrate antigen 19.9 and treatment regimen (hazard ratio [HR] 1.05, 95% CI 1.01–1.09, p = 0.005; HR 1.00, 95% CI 1.01–1.05, p = 0.003). In conclusion, our study showed that ctDNA detection rates are higher in patients with larger tumor volume and liver metastases. Nevertheless, measurements may diverge and, thus, can provide complementary information. Both ctDNA VAF and tumor volume were strong predictors of OS.
Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of all common cancers. However, divergent outcomes exist between patients, suggesting distinct underlying tumor biology. Here, we delineated this heterogeneity, compared interconnectivity between classification systems, and experimentally addressed the tumor biology that drives poor outcome. RNA-sequencing of 90 resected specimens and unsupervised classification revealed four subgroups associated with distinct outcomes. The worst-prognosis subtype was characterized by mesenchymal gene signatures. Comparative (network) analysis showed high interconnectivity with previously identified classification schemes and high robustness of the mesenchymal subtype. From species-specific transcript analysis of matching patient-derived xenografts we constructed dedicated classifiers for experimental models. Detailed assessments of tumor growth in subtyped experimental models revealed that a highly invasive growth pattern of mesenchymal subtype tumor cells is responsible for its poor outcome. Concluding, by developing a classification system tailored to experimental models, we have uncovered subtypespecific biology that should be further explored to improve treatment of a group of PDAC patients that currently has little therapeutic benefit from surgical treatment.
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