CD44 SNPrs187115: A Novel Biomarker Signature that Predicts Survival in Resectable Pancreatic Ductal Adenocarcinoma

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

Single-nucleotide Polymorphisms in the p53 Signaling Pathway

The p53 tumor suppressor pathway is central both in reducing cancer frequency in vertebrates and in mediating the response of commonly used cancer therapies. This article aims to summarize and discuss a large body of evidence suggesting that the p53 pathway harbors functional inherited single-nucleotide polymorphisms (SNPs) that affect p53 signaling in cells, resulting in differences in cancer risk and clinical outcome in humans. The insights gained through these studies into how the functional p53 pathway SNPs could help in the tailoring of cancer therapies to the individual are discussed. Moreover, recent work is discussed that suggests that many more functional p53 pathway SNPs are yet to be fully characterized and that a thorough analysis of the functional human genetics of this important tumor suppressor pathway is required

The Inheritance of p53

The p53 pathway constitutes a major cellular gene network that is crucial in directing the suppression of cancer formation, mediating the response to commonly used cancer therapies, as well as the regulation of germline maintenance, fertility, and reproduction. It has been demonstrated that various cancer predisposition syndromes are caused by low-frequency, highly penetrant inherited mutations in the p53 network, the knowledge of which is already positively affecting patient survival. Mounting evidence from studies utilizing human material, patient cohorts, and mouse models suggests that higher frequency, lesser penetrant genetic variants can also affect p53 signaling, resulting in differences in cancer risk, prognosis, response to therapies, and/or natural selection. Indeed, multiple genes in the p53 network have been shown to harbor functional single nucleotide polymorphisms (SNPs). Comprehensive analyses of two SNPs have demonstrated that their effects on cancer can be modified by factors such as gender, estrogen, and other p53 pathway SNPs. Together these insights suggest that genetic variants in the p53 network could present an excellent opportunity to further define individuals in their abilities to react to stress, suppress tumor formation, and respond to therapies

Molecular and Cellular Pathobiology Chemosensitivity Profiles Identify Polymorphisms in the p53 Network Genes 14-3-3τ and CD44 That Affect Sarcoma Incidence and Survival

Abstract The p53 regulatory network responds to cellular stresses by initiating processes such as cell cycle arrest and apoptosis. These responses inhibit cellular transformation and mediate the response to many forms of cancer therapies. Functional variants in the genes comprising this network could help identify individuals at greater risk for cancer and patients with poorer responses to therapies, but few such variants have been identified as yet. We use the NCI60 human tumor cell line anticancer drug screen in a scan of single nucleotide polymorphisms (SNP) in 142 p53 stress response genes and identify 7 SNPs that exhibit allelic differences in cellular responses to a large panel of cytotoxic chemotherapeutic agents. The greatest differences are observed for SNPs in 14-3-3τ (YWHAQ; rs6734469, P = 5.6 × 10 −47 ) and CD44 (rs187115, P =

Liver regeneration after portal and hepatic vein embolization improves overall survival compared with portal vein embolization alone: mid-term survival analysis of the multicentre DRAGON 0 cohort

Background: the purpose of this study was to compare 3-year overall survival after simultaneous portal (PVE) and hepatic vein (HVE) embolization versus PVE alone in patients undergoing liver resection for primary and secondary cancers of the liver.Methods: in this multicentre retrospective study, all DRAGON 0 centres provided 3-year follow-up data for all patients who had PVE/HVE or PVE, and were included in DRAGON 0 between 2016 and 2019. Kaplan-Meier analysis was undertaken to assess 3-year overall and recurrence/progression-free survival. Factors affecting survival were evaluated using univariable and multivariable Cox regression analyses.Results: in total, 199 patients were included from 7 centres, of whom 39 underwent PVE/HVE and 160 PVE alone. Groups differed in median age (P = 0.008). As reported previously, PVE/HVE resulted in a significantly higher resection rate than PVE alone (92 versus 68%; P = 0.007). Three-year overall survival was significantly higher in the PVE/HVE group (median survival not reached after 36 months versus 20 months after PVE; P = 0.004). Univariable and multivariable analyses identified PVE/HVE as an independent predictor of survival (univariable HR 0.46, 95% c.i. 0.27 to 0.76; P = 0.003).Conclusion: overall survival after PVE/HVE is substantially longer than that after PVE alone in patients with primary and secondary liver tumours.</p

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Responsep53 Pathway SNPs and Mutations Interact to Affect Cancer

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets

Germline and Somatic Genetic Variants in the p53 Pathway Interact to Affect Cancer Risk, Progression, and Drug Response.

Insights into oncogenesis derived from cancer susceptibility loci (SNP) hold the potential to facilitate better cancer management and treatment through precision oncology. However, therapeutic insights have thus far been limited by our current lack of understanding regarding both interactions of these loci with somatic cancer driver mutations and their influence on tumorigenesis. For example, although both germline and somatic genetic variation to the p53 tumor suppressor pathway are known to promote tumorigenesis, little is known about the extent to which such variants cooperate to alter pathway activity. Here we hypothesize that cancer risk-associated germline variants interact with somatic TP53 mutational status to modify cancer risk, progression, and response to therapy. Focusing on a cancer risk SNP (rs78378222) with a well-documented ability to directly influence p53 activity as well as integration of germline datasets relating to cancer susceptibility with tumor data capturing somatically-acquired genetic variation provided supportive evidence for this hypothesis. Integration of germline and somatic genetic data enabled identification of a novel entry point for therapeutic manipulation of p53 activities. A cluster of cancer risk SNPs resulted in increased expression of prosurvival p53 target gene KITLG and attenuation of p53-mediated responses to genotoxic therapies, which were reversed by pharmacologic inhibition of the prosurvival c-KIT signal. Together, our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel combinatorial therapies. SIGNIFICANCE: These results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and present novel therapeutic targets.This work was funded in part by the Ludwig Institute for Cancer Research, the Nuffield Department of Medicine, the Development Fund, Oxford Cancer Research Centre, University of Oxford, UK, by the Intramural Research Program of the National Institute of Environmental Health Sciences-National Institutes of Health (Z01-ES100475), and NIH grant (DP5-OD017937), US, and by the S-CORT Consortium from the Medical Research Council and Cancer Research UK