scholarly journals Polygenic and multifactorial scores for pancreatic ductal adenocarcinoma risk prediction

2020 ◽  
pp. jmedgenet-2020-106961 ◽  
Author(s):  
Alice Alessandra Galeotti ◽  
Manuel Gentiluomo ◽  
Cosmeri Rizzato ◽  
Ofure Obazee ◽  
John P Neoptolemos ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Prediction ◽  
Association Studies ◽  
Statistical Significance ◽  
Ductal Adenocarcinoma ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Individual Snps ◽  
Risk Snps

BackgroundMost cases of pancreatic ductal adenocarcinoma (PDAC) are asymptomatic in early stages, and the disease is typically diagnosed in advanced phases, resulting in very high mortality. Tools to identify individuals at high risk of developing PDAC would be useful to improve chances of early detection.ObjectiveWe generated a polygenic risk score (PRS) for PDAC risk prediction, combining the effect of known risk SNPs, and carried out an exploratory analysis of a multifactorial score.MethodsWe tested the associations of the individual known risk SNPs on up to 2851 PDAC cases and 4810 controls of European origin from the PANcreatic Disease ReseArch (PANDoRA) consortium. Thirty risk SNPs were included in a PRS, which was computed on the subset of subjects that had 100% call rate, consisting of 839 cases and 2040 controls in PANDoRA and 6420 cases and 4889 controls from the previously published Pancreatic Cancer Cohort Consortium I–III and Pancreatic Cancer Case-Control Consortium genome-wide association studies. Additional exploratory multifactorial scores were constructed by complementing the genetic score with smoking and diabetes.ResultsThe scores were associated with increased PDAC risk and reached high statistical significance (OR=2.70, 95% CI 1.99 to 3.68, p=2.54×10−10 highest vs lowest quintile of the weighted PRS, and OR=14.37, 95% CI 5.57 to 37.09, p=3.64×10−8, highest vs lowest quintile of the weighted multifactorial score).ConclusionWe found a highly significant association between a PRS and PDAC risk, which explains more than individual SNPs and is a step forward in the direction of the construction of a tool for risk stratification in the population.

scholarly journals The synergism of Clinacanthus nutans Lindau extracts with gemcitabine: downregulation of anti-apoptotic markers in squamous pancreatic ductal adenocarcinoma

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Ling-Wei Hii ◽  
Swee-Hua Erin Lim ◽  
Chee-Onn Leong ◽  
Swee-Yee Chin ◽  
Ngai-Paing Tan ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Cells ◽  
Cell Lines ◽  
Statistical Significance ◽  
Ductal Adenocarcinoma ◽  
Enzyme Linked Immunosorbent Assay ◽  
Leaf Extracts ◽  
Pancreatic Cancer Cells ◽  
Clinacanthus Nutans

Abstract Background Clinacanthus nutans extracts have been consumed by the cancer patients with the hope that the extracts can kill cancers more effectively than conventional chemotherapies. Our previous study reported its anti-inflammatory effects were caused by inhibiting Toll-like Receptor-4 (TLR-4) activation. However, we are unsure of its anticancer effect, and its interaction with existing chemotherapy. Methods We investigated the anti-proliferative efficacy of polar leaf extracts (LP), non-polar leaf extracts (LN), polar stem extract (SP) and non-polar stem extracts (SN) in human breast, colorectal, lung, endometrial, nasopharyngeal, and pancreatic cancer cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, MTT assay. The most potent extracts was tested along with gemcitabine using our established drug combination analysis. The effect of the combinatory treatment in apoptosis were quantified using enzyme-linked immunosorbent assay (ELISA), Annexin V assay, antibody array and immunoblotting. Statistical significance was analysed using one-way analysis of variance (ANOVA) and post hoc Dunnett’s test. A p-value of less than 0.05 (p < 0.05) was considered statistical significance. Results All extracts tested were not able to induce potent anti-proliferative effects. However, it was found that pancreatic ductal adenocarcinoma, PDAC (AsPC1, BxPC3 and SW1990) were the cell lines most sensitive cell lines to SN extracts. This is the first report of C. nutans SN extracts acting in synergy with gemcitabine, the first line chemotherapy for pancreatic cancer, as compared to conventional monotherapy. In the presence of SN extracts, we can reduce the dose of gemcitabine 2.38–5.28 folds but still maintain the effects of gemcitabine in PDAC. SN extracts potentiated the killing of gemcitabine in PDAC by apoptosis. Bax was upregulated while bcl-2, cIAP-2, and XIAP levels were downregulated in SW1990 and BxPC3 cells treated with gemcitabine and SN extracts. The synergism was independent of TLR-4 expression in pancreatic cancer cells. Conclusion These results provide strong evidence of C. nutans extracts being inefficacious as monotherapy for cancer. Hence, it should not be used as a total substitution for any chemotherapy agents. However, SN extracts may synergise with gemcitabine in the anti-tumor mechanism.

scholarly journals Genetic Alterations Featuring Biological Models to Tailor Clinical Management of Pancreatic Cancer Patients

Cancers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1233 ◽  
Author(s):  
Shannon R. Nelson ◽  
Naomi Walsh
Keyword(s):  
Pancreatic Cancer ◽  
Association Studies ◽  
Treatment Options ◽  
Genetic Alterations ◽  
Ductal Adenocarcinoma ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Primary Cell Lines ◽  
On Chip ◽  
New Research

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death worldwide. This high mortality rate is due to the disease’s lack of symptoms, resulting in a late diagnosis. Biomarkers and treatment options for pancreatic cancer are also limited. In order to overcome this, new research models and novel approaches to discovering PDAC biomarkers are required. In this review, we outline the hereditary and somatic causes of PDAC and provide an overview of the recent genome wide association studies (GWAS) and pathway analysis studies. We also provide a summary of some of the systems used to study PDAC, including established and primary cell lines, patient-derived xenografts (PDX), and newer models such as organoids and organ-on-chip. These ex vitro laboratory systems allow for critical research into the development and progression of PDAC.

scholarly journals Genetic determinants of polygenic prediction accuracy within a population

2022 ◽  
Author(s):  
Tianyuan Lu ◽  
Vincenzo Forgetta ◽  
J. Brent Richards ◽  
Celia Greenwood
Keyword(s):  
Risk Prediction ◽  
Association Studies ◽  
Genetic Effects ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Test Set ◽  
Polygenic Risk ◽  
Genomic Risk

Abstract Genomic risk prediction is on the emerging path towards personalized medicine. However, the accuracy of polygenic prediction varies strongly in different individuals. In this study, based on up to 352,277 White British participants in the UK Biobank, we constructed polygenic risk scores for 15 physiological and biochemical quantitative traits after performing genome-wide association studies (GWASs). We identified 185 polygenic prediction variability quantitative trait loci (pvQTLs) for 11 traits by Levene’s test among 254,376 unrelated individuals. We validated the effects of pvQTLs using an independent test set of 58,927 individuals. A score aggregating 51 pvQTL SNPs for triglycerides had the strongest Spearman correlation of 0.185 (p-value < 1.0x10−300) with the squared prediction errors. We found a strong enrichment of complex genetic effects conferred by pvQTLs compared to risk loci identified in GWASs, including 89 pvQTLs exhibiting dominance effects. Incorporation of dominance effects into polygenic risk scores significantly improved polygenic prediction for triglycerides, low-density lipoprotein cholesterol, vitamin D, and platelet. After including 87 dominance effects for triglycerides, the adjusted R2 for the polygenic risk score had an 8.1% increase on the test set. In addition, 108 pvQTLs had significant interaction effects with measured environmental or lifestyle exposures. In conclusion, we have discovered and validated genetic determinants of polygenic prediction variability for 11 quantitative biomarkers, and partially profiled the underlying complex genetic effects. These findings may assist interpretation of genomic risk prediction in various contexts, and encourage novel approaches for constructing polygenic risk scores with complex genetic effects.

scholarly journals A Proteomic Study on the Personalized Protein Corona of Liposomes. Relevance for Early Diagnosis of Pancreatic DUCTAL Adenocarcinoma and Biomarker Detection

2021 ◽  
Vol 2 (2) ◽  
pp. 82-93
Author(s):  
Luca Digiacomo ◽  
Francesca Giulimondi ◽  
Daniela Pozzi ◽  
Alessandro Coppola ◽  
Vincenzo La Vaccara ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Early Diagnosis ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Protein Corona ◽  
Detection Sensitivity ◽  
Ductal Adenocarcinoma ◽  
Protein Biomarkers ◽  
Ca 19.9 ◽  
Proteomic Study

Due to late diagnosis, high incidence of metastasis, and poor survival rate, pancreatic cancer is one of the most leading cause of cancer-related death. Although manifold recent efforts have been done to achieve an early diagnosis of pancreatic cancer, CA-19.9 is currently the unique biomarker that is adopted for the detection, despite its limits in terms of sensitivity and specificity. To identify potential protein biomarkers for pancreatic ductal adenocarcinoma (PDAC), we used three model liposomes as nanoplatforms that accumulate proteins from human plasma and studied the composition of this biomolecular layer, which is known as protein corona. Indeed, plasma proteins adsorb on nanoparticle surface according to their abundance and affinity to the employed nanomaterial, thus even small differences between healthy and PDAC protein expression levels can be, in principle, detected. By mass spectrometry experiments, we quantified such differences and identified possible biomarkers for PDAC. Some of them are already known to exhibit different expressions in PDAC proteomes, whereas the role of other relevant proteins is still not clear. Therefore, we predict that the employment of nanomaterials and their protein corona may represent a useful tool to amplify the detection sensitivity of cancer biomarkers, which may be used for the early diagnosis of PDAC, with clinical implication for the subsequent therapy in the context of personalized medicine.

scholarly journals Pharmacogenetic Polygenic Risk Score for Bronchodilator Response in Children and Adolescents with Asthma: Proof-of-Concept

2021 ◽  
Vol 11 (4) ◽  
pp. 319
Author(s):  
Joanne E. Sordillo ◽  
Sharon M. Lutz ◽  
Michael J. McGeachie ◽  
Jessica Lasky-Su ◽  
Scott T. Weiss ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Risk Score ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Linear Regression Models ◽  
Standard Deviation Increase ◽  
Polygenic Risk ◽  
Bronchodilator Response ◽  
Children With Asthma

Genome-wide association studies (GWAS) of response to asthma medications have primarily focused on Caucasian populations, with findings that may not be generalizable to minority populations. We derived a polygenic risk score (PRS) for response to albuterol as measured by bronchodilator response (BDR), and examined the PRS in a cohort of Hispanic school-aged children with asthma. We leveraged a published GWAS of BDR to identify relevant genetic variants, and ranked the top variants according to their Combined Annotation Dependent Depletion (CADD) scores. Variants with CADD scores greater than 10 were used to compute the PRS. Once we derived the PRS, we determined the association of the PRS with BDR in a cohort of Hispanic children with asthma (the Genetics of Asthma in Costa Rica Study (GACRS)) in adjusted linear regression models. Mean BDR in GACRS participants was5.6% with a standard deviation of 10.2%. We observed a 0.63% decrease in BDR in response to albuterol for a standard deviation increase in the PRS (p = 0.05). We also observed decreased odds of a BDR response at or above the 12% threshold for a one standard deviation increase in the PRS (OR = 0.80 (95% CI 0.67 to 0.95)). Our findings show that combining variants from a pharmacogenetic GWAS into a PRS may be useful for predicting medication response in asthma.

scholarly journals Polygenic Risk Score of Longevity Predicts Longer Survival Across an Age Continuum

2020 ◽  
Author(s):  
Niccolo’ Tesi ◽  
Sven J van der Lee ◽  
Marc Hulsman ◽  
Iris E Jansen ◽  
Najada Stringa ◽  
...  
Keyword(s):  
Older Adults ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Risk Scores ◽  
Human Longevity ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Age Related

Abstract Studying the genome of centenarians may give insights into the molecular mechanisms underlying extreme human longevity and the escape of age-related diseases. Here, we set out to construct polygenic risk scores (PRSs) for longevity and to investigate the functions of longevity-associated variants. Using a cohort of centenarians with maintained cognitive health (N = 343), a population-matched cohort of older adults from 5 cohorts (N = 2905), and summary statistics data from genome-wide association studies on parental longevity, we constructed a PRS including 330 variants that significantly discriminated between centenarians and older adults. This PRS was also associated with longer survival in an independent sample of younger individuals (p = .02), leading up to a 4-year difference in survival based on common genetic factors only. We show that this PRS was, in part, able to compensate for the deleterious effect of the APOE-ε4 allele. Using an integrative framework, we annotated the 330 variants included in this PRS by the genes they associate with. We find that they are enriched with genes associated with cellular differentiation, developmental processes, and cellular response to stress. Together, our results indicate that an extended human life span is, in part, the result of a constellation of variants each exerting small advantageous effects on aging-related biological mechanisms that maintain overall health and decrease the risk of age-related diseases.

scholarly journals Roles of autophagy and metabolism in pancreatic cancer cell adaptation to environmental challenges

2017 ◽  
Vol 313 (5) ◽  
pp. G524-G536 ◽  
Author(s):  
Sandrina Maertin ◽  
Jason M. Elperin ◽  
Ethan Lotshaw ◽  
Matthias Sendler ◽  
Steven D. Speakman ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cell Proliferation ◽  
Cell Growth ◽  
Oxidative Phosphorylation ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Environmental Stresses ◽  
Ductal Adenocarcinoma ◽  
Cell Adaptation ◽  
Autophagy Inhibition ◽  
Dependent Mechanism

Pancreatic ductal adenocarcinoma (PDAC) displays extensive and poorly vascularized desmoplastic stromal reaction, and therefore, pancreatic cancer (PaCa) cells are confronted with nutrient deprivation and hypoxia. Here, we investigate the roles of autophagy and metabolism in PaCa cell adaptation to environmental stresses, amino acid (AA) depletion, and hypoxia. It is known that in healthy cells, basal autophagy is at a low level, but it is greatly activated by environmental stresses. By contrast, we find that in PaCa cells, basal autophagic activity is relatively high, but AA depletion and hypoxia activate autophagy only weakly or not at all, due to their failure to inhibit mechanistic target of rapamycin. Basal, but not stress-induced, autophagy is necessary for PaCa cell proliferation, and AA supply is even more critical to maintain PaCa cell growth. To gain insight into the underlying mechanisms, we analyzed the effects of autophagy inhibition and AA depletion on PaCa cell metabolism. PaCa cells display mixed oxidative/glycolytic metabolism, with oxidative phosphorylation (OXPHOS) predominant. Both autophagy inhibition and AA depletion dramatically decreased OXPHOS; furthermore, pharmacologic inhibitors of OXPHOS suppressed PaCa cell proliferation. The data indicate that the maintenance of OXPHOS is a key mechanism through which autophagy and AA supply support PaCa cell growth. We find that the expression of oncogenic activation mutation in GTPase Kras markedly promotes basal autophagy and stimulates OXPHOS through an autophagy-dependent mechanism. The results suggest that approaches aimed to suppress OXPHOS, particularly through limiting AA supply, could be beneficial in treating PDAC. NEW & NOTEWORTHY Cancer cells in the highly desmoplastic pancreatic ductal adenocarcinoma confront nutrient [i.e., amino acids (AA)] deprivation and hypoxia, but how pancreatic cancer (PaCa) cells adapt to these conditions is poorly understood. This study provides evidence that the maintenance of mitochondrial function, in particular, oxidative phosphorylation (OXPHOS), is a key mechanism that supports PaCa cell growth, both in normal conditions and under the environmental stresses. OXPHOS in PaCa cells critically depends on autophagy and AA supply. Furthermore, the oncogenic activation mutation in GTPase Kras upregulates OXPHOS through an autophagy-dependent mechanism.

41 Cathepsin D Expression in Pancreatic Ductal Adenocarcinoma (PDAC) Cells Increases Proliferation and Reduces Survival of Pancreatic Cancer Patients

2015 ◽  
Vol 148 (4) ◽  
pp. S-13
Author(s):  
Ujjwal M. Mahajan ◽  
Enno Langhoff ◽  
Eithne Costello ◽  
William Greenhalf ◽  
Christopher Halloran ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cancer Patients ◽  
Cathepsin D ◽  
Ductal Adenocarcinoma

scholarly journals Challenges of Adjusting Single-Nucleotide Polymorphism Effect Sizes for Linkage Disequilibrium

2021 ◽  
pp. 1-11
Author(s):  
Valentina Escott-Price ◽  
Karl Michael Schmidt
Keyword(s):  
Linkage Disequilibrium ◽  
Association Studies ◽  
Statistical Significance ◽  
Ordinary Least Squares ◽  
Effect Sizes ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Tikhonov Regularisation

<b><i>Background:</i></b> Genome-wide association studies (GWAS) were successful in identifying SNPs showing association with disease, but their individual effect sizes are small and require large sample sizes to achieve statistical significance. Methods of post-GWAS analysis, including gene-based, gene-set and polygenic risk scores, combine the SNP effect sizes in an attempt to boost the power of the analyses. To avoid giving undue weight to SNPs in linkage disequilibrium (LD), the LD needs to be taken into account in these analyses. <b><i>Objectives:</i></b> We review methods that attempt to adjust the effect sizes (β<i>-</i>coefficients) of summary statistics, instead of simple LD pruning. <b><i>Methods:</i></b> We subject LD adjustment approaches to a mathematical analysis, recognising Tikhonov regularisation as a framework for comparison. <b><i>Results:</i></b> Observing the similarity of the processes involved with the more straightforward Tikhonov-regularised ordinary least squares estimate for multivariate regression coefficients, we note that current methods based on a Bayesian model for the effect sizes effectively provide an implicit choice of the regularisation parameter, which is convenient, but at the price of reduced transparency and, especially in smaller LD blocks, a risk of incomplete LD correction. <b><i>Conclusions:</i></b> There is no simple answer to the question which method is best, but where interpretability of the LD adjustment is essential, as in research aiming at identifying the genomic aetiology of disorders, our study suggests that a more direct choice of mild regularisation in the correction of effect sizes may be preferable.

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