American Association for Cancer Research
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10780432ccr160058-sup-160657_2_supp_3502413_s7fksk.pptx (80.64 kB)

Supplementary Figure S1 from CD44 SNPrs187115: A Novel Biomarker Signature that Predicts Survival in Resectable Pancreatic Ductal Adenocarcinoma

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posted on 2023-03-31, 20:25 authored by Giovanni Stracquadanio, Bart Vrugt, Renata Flury, Peter Schraml, Peter Würl, Thomas H. Müller, Uwe Knippschild, Doris Henne-Bruns, Stefan Breitenstein, Pierre-Alain Clavien, Rolf Graf, Gareth L. Bond, Lukasz F. Grochola

Supplementary Figure S1

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University Hospital of Zurich

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ARTICLE ABSTRACT

Purpose: Although pancreatic ductal adenocarcinoma (PDAC) is an aggressive tumor, like other common cancers, it displays a wide range of biology. However, at present, there are no reliable tests to predict patients' cancer-specific outcomes and guide personalized treatment decisions. In this study, we aim to identify such biomarkers in resectable PDAC by studying SNPs in the CD44 gene, which drives the progression of pancreatic cancer.Experimental Design: A total of 348 PDAC patients from three independent cohorts [Switzerland, Germany, The Cancer Genome Atlas (TCGA)] who underwent pancreatic resection are included in the study. Information on the haplotype structure of the CD44 gene is obtained using 1000 Genomes Project data, and the genotypes of the respective tagging SNPs are determined. Cox proportional hazards models are utilized to analyze the impact of SNP genotype on patients' survival.Results: We identify an SNP in the CD44 gene (SNPrs187115) that independently associates with allelic differences in prognosis in all study cohorts. Specifically, in 121 Swiss patients, we observe an up to 2.38-fold (P = 0.020) difference in tumor-related death between the genotypes of SNPrs187115. We validate those results in both the German (HR = 2.32, P = 0.044, 101 patients) and the TCGA cohort (HR = 2.36, P = 0.044, 126 patients).Conclusions: CD44 SNPrs187115 can serve as a novel biomarker readily available at the time of PDAC diagnosis that identifies patients at risk for faster tumor progression and guide personalized treatment decisions. It has the potential to significantly expand the pool of patients that would benefit from tumor resection. Clin Cancer Res; 22(24); 6069–77. ©2016 AACR.