Validation of microRNA pathway polymorphisms in esophageal adenocarcinoma survival.

Polymorphisms in miRNA and miRNA pathway genes have been previously associated with cancer risk and outcome, but have not been studied in esophageal adenocarcinoma outcomes. Here, we evaluate candidate miRNA pathway polymorphisms in esophageal adenocarcinoma prognosis and attempt to validate them in an independent cohort of esophageal adenocarcinoma patients. Among 231 esophageal adenocarcinoma patients of all stages/treatment plans, 38 candidate genetic polymorphisms (17 biogenesis, 9 miRNA targets, 5 pri-miRNA, 7 pre-miRNA) were genotyped and analyzed. Cox proportional hazard models adjusted for sociodemographic and clinicopathological covariates helped assess the association of genetic polymorphisms with overall survival (OS) and progression-free survival (PFS). Significantly associated polymorphisms were then evaluated in an independent cohort of 137 esophageal adenocarcinoma patients. Among the 231 discovery cohort patients, 86% were male, median diagnosis age was 64 years, 34% were metastatic at diagnosis, and median OS and PFS were 20 and 12 months, respectively. GEMIN3 rs197412 (aHR = 1.37, 95%CI: [1.04-1.80]; P = 0.02), hsa-mir-124-1 rs531564 (aHR = 0.60, 95% CI: [0.53-0.90]; P = 0.05), and KIAA0423 rs1053667 (aHR = 0.51, 95% CI: [0.28-0.96]; P = 0.04) were found associated with OS. Furthermore, GEMIN3 rs197412 (aHR = 1.33, 95% CI: [1.03-1.74]; P = 0.03) and KRT81 rs3660 (aHR = 1.29, 95% CI: [1.01-1.64]; P = 0.04) were found associated with PFS. Although none of these polymorphisms were significant in the second cohort, hsa-mir-124-1 rs531564 and KIAA0423 rs1053667 had trends in the same direction; when both cohorts were combined together, GEMIN3 rs197412, hsa-mir-124-1 rs531564, and KIAA0423 rs1053667 remained significantly associated with OS. We demonstrate the association of multiple miRNA pathway polymorphisms with esophageal adenocarcinoma prognosis in a discovery cohort of patients, which did not validate in a separate cohort but had consistent associations in the pooled cohort. Larger studies are required to confirm/validate the prognostic value of these polymorphisms in esophageal adenocarcinoma.

The Pathogenesis of Nonalcoholic Fatty Liver Disease: Interplay between Diet, Gut Microbiota, and Genetic Background.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, and it comprises a spectrum of hepatic abnormalities from simple hepatic steatosis to steatohepatitis, fibrosis, cirrhosis, and liver cancer. While the pathogenesis of NAFLD remains incompletely understood, a multihit model has been proposed that accommodates causal factors from a variety of sources, including intestinal and adipose proinflammatory stimuli acting on the liver simultaneously. Prior cellular and molecular studies of patient and animal models have characterized several common pathogenic mechanisms of NAFLD, including proinflammation cytokines, lipotoxicity, oxidative stress, and endoplasmic reticulum stress. In recent years, gut microbiota has gained much attention, and dysbiosis is recognized as a crucial factor in NAFLD. Moreover, several genetic variants have been identified through genome-wide association studies, particularly rs738409 (Ile748Met) in PNPLA3 and rs58542926 (Glu167Lys) in TM6SF2, which are critical risk alleles of the disease. Although a high-fat diet and inactive lifestyles are typical risk factors for NAFLD, the interplay between diet, gut microbiota, and genetic background is believed to be more important in the development and progression of NAFLD. This review summarizes the common pathogenic mechanisms, the gut microbiota relevant mechanisms, and the major genetic variants leading to NAFLD and its progression.

ABCC2 polymorphisms and survival in the Princess Margaret cohort study and the NCIC clinical trials group BR.24 trial of platinum-treated advanced stage non-small cell lung cancer patients.

BACKGROUND: The drug transporter ABCC2 is upregulated in non-small cell lung cancer (NSCLC) and implicated in platinum resistance. We evaluated the association between germline polymorphisms in the ABCC2 gene and survival outcomes of platinum-treated advanced NSCLC patients. MATERIAL AND METHODS: Ten candidate and tagging germline polymorphisms in the ABCC2 gene were genotyped in a discovery cohort of 170 platinum-treated stage IV NSCLC patients from the Princess Margaret Cancer Centre. Associations with overall survival were assessed using multivariate Cox proportional hazard models adjusted for prognostic variables. To validate our results, we analyzed the association of the two top polymorphisms in the ABCC2 gene on survival outcomes of 219 stage IIIB-IV NSCLC patients enrolled on the NCIC Clinical Trials Group BR.24 clinical trial. RESULTS: Only one polymorphism was validated across both cohorts for an association with overall survival: the A allele of the ABCC2 polymorphism, rs8187710 (4544G>A), was associated with adverse overall survival (adjusted hazard ratio [aHR] 2.22; 95% CI: 1.2-4.0; p=0.009) among our stage IV NSCLC patients. A significant association with overall survival (aHR 1.73; 95% CI: 1.0-2.9; p=0.036) was observed for the same ABCC2 polymorphism in the BR.24 validation cohort. No other ABCC2 polymorphisms were associated with outcome. CONCLUSION: The ABCC2 polymorphism, rs8187710 (4544G>A), is associated with overall survival in platinum-treated advanced NSCLC patients. Additional studies are needed to evaluate the predictive versus prognostic nature of this relationship, and to explore the functional effect of this polymorphism on the pharmacokinetics of platinum drugs.

eHealth: past and future perspectives.

eHealth is an umbrella term incorporating any area that combines healthcare and technology to improve efficiencies and reduce costs. The ultimate goal of eHealth is to rationalize treatment selection to improve patient safety and outcomes. Telemedicine, first used in the 1920s, is the oldest form of eHealth. The introduction of broadband Internet, followed by wireless technologies, has allowed an explosion of mHealth applications within this field. Wearable technologies, such as smartwatches, are now being used for diagnostics and patient monitoring. Challenges remain to develop reusable Clinical Decision Support systems that will streamline the flow of data from clinical laboratories to point of care. This review explores the history of eHealth, and describes some of the remaining integration and implementation challenges.

Discovery and validation of vascular endothelial growth factor (VEGF) pathway polymorphisms in esophageal adenocarcinoma outcome.

Polymorphisms in the vascular endothelial growth factor (VEGF)/angiogenesis pathway have been implicated previously in cancer risk, prognosis and response to therapy including in esophageal adenocarcinoma. Prior esophageal adenocarcinoma studies focused on using candidate polymorphisms, limiting the discovery of novel polymorphisms. Here, we applied the tagSNP (single nucleotide polymorphism) approach to identify new VEGF pathway polymorphisms associated with esophageal adenocarcinoma prognosis and validated them in an independent cohort of esophageal adenocarcinoma patients. In 231 esophageal adenocarcinoma patients of all stages/treatment plans, 58 genetic polymorphisms (18 KDR, 7 VEGFA and 33 FLT1) selected through tagging and assessment of predicted function were genotyped. Cox-proportional hazard models adjusted for important socio-demographic and clinico-pathological factors were applied to assess the association of genetic polymorphisms with overall survival (OS) and progression-free survival (PFS). Significantly associated polymorphisms were then validated in an independent cohort of 137 esophageal adenocarcinoma patients. Among the 231 discovery cohort patients, 86% were male, median diagnosis age was 64 years, 34% were metastatic at diagnosis and median OS and PFS were 20 and 12 months, respectively. KDR rs17709898 was found significantly associated with PFS (adjusted hazard ratio, aHR = 0.69, 95% confidence interval (CI): 0.53-0.90; P = 5.9E-3). FLT1 rs3794405 and rs678714 were significantly associated with OS (aHR = 1.44, 95% CI: 1.04-1.99; P = 0.03 and aHR = 1.50, 95% CI: 1.01-2.24; P = 0.045, respectively). No VEGFA polymorphisms were found significantly associated with either outcome. Upon validation, FLT1 rs3794405 remained strongly associated with OS (aHR = 1.59, 95% CI: 1.04-2.44; P = 0.03). FLT1 rs3794405 is significantly associated with OS in esophageal adenocarcinoma, whereby each variant allele confers a 45-60% increased risk of mortality. Validation and evaluation of this association in other cancer sites are warranted.

Pharmacogenomic assessment of Mexican and Peruvian populations.

BACKGROUND: Clinically relevant polymorphisms often demonstrate population-specific allele frequencies. Central and South America remain largely uncategorized in the context of pharmacogenomics. MATERIALS & METHODS: We assessed 15 polymorphisms from 12 genes (ABCB1 3435C>T, ABCG2 Q141K, CYP1B1*3, CYP2C19*2, CYP3A4*1B, CYP3A5*3C, ERCC1 N118N, ERCC2 K751Q, GSTP1 I105V, TPMT 238G>C, TPMT 460G>A, TPMT 719A>G, TYMS TSER, UGT1A1*28 and UGT1A1 -3156G>A) in 81 Peruvian and 95 Mexican individuals. RESULTS: Six polymorphism frequencies differed significantly between the two populations: ABCB1 3435C>T, CYP1B1*3, GSTP1 I105V, TPMT 460G>A, UGT1A1*28 and UGT1A1 -3156G>A. The pattern of observed allele frequencies for all polymorphisms could not be accurately estimated from any single previously studied population. CONCLUSION: This highlights the need to expand the scope of geographic data for use in pharmacogenomics studies.

Fast and frugal trees: translating population-based pharmacogenomics to medication prioritization.

AIM: Fast and frugal decision trees (FFTs) can simplify clinical decision making by providing a heuristic approach to contextual guidance. We wanted to use FFTs for pharmacogenomic knowledge translation at point-of-care. MATERIALS & METHODS: The Pharmacogenomics for Every Nation Initiative (PGENI), an international nonprofit organization, collects data on regional polymorphisms as a predictor of metabolism for individual drugs and dosages. We advanced FFTs to work with PGENI pharmacogenomic data to produce medication recommendations that are accurate, transparent and straightforward to automate. RESULTS: By streamlining medication selection processes in the PGENI workflow, information technology applications can now be deployed. CONCLUSION: We developed a decision tree approach that can translate pharmacogenomic data to provide up-to-date recommended care for populations based on their medication-specific markers.

A Bridging Opportunities Work-frame to develop mobile applications for clinical decision making.

BACKGROUND: Mobile applications (apps) providing clinical decision support (CDS) may show the greatest promise when created by and for frontline clinicians. Our aim was to create a generic model enabling healthcare providers to direct the development of CDS apps. METHODS: We combined Change Management with a three-tier information technology architecture to stimulate CDS app development. RESULTS: A Bridging Opportunities Work-frame model was developed. A test case was used to successfully develop an app. CONCLUSION: Healthcare providers can re-use this globally applicable model to actively create and manage regional decision support applications to translate evidence-based medicine in the use of emerging medication or novel treatment regimens.

Pyrosequencing of clinically relevant polymorphisms.

Despite the influx of high throughput sequencing techniques, there is still a niche for low-medium throughput genotyping technologies for small-scale screening and validation purposes. Pyrosequencing is a genotyping assay based on sequencing-by-synthesis. Short runs of sequence around each polymorphism are generated, allowing for internal controls for each sample. Pyrosequencing can also be utilized to identify tri-allelic, indel, and short repeat polymorphisms, as well as determining allele percentages for methylation or pooled sample assessment. This range of applications makes it well-suited to the research laboratory as a one-stop system.

Personalized medicine policy challenges: measuring clinical utility at point of care.

Pharmacogenomics, driven by advances in genomics, helps to explain patients' individual variability in response to therapies. Personalized medicine, the application of the increasing understanding of pharmacogenomics, and information technology are intertwined from discovery to delivery at point of care, through to tracking clinical outcomes. Although exemplary cases of personalized medicine adoption demonstrate patient benefit and cost-effectiveness, a remaining barrier to large-scale real-world uptake of this novel approach in medicine is policy change. At point-of-care implementation, case studies will need to measure personalized medicine application outcomes of relevance to policy-makers and as evidence of clinical utility. Assessments need to be consistent across case studies. Standardizing specifications for case studies will better inform policy-makers performing economic evaluations on the use of personalized medicine.

Pharmacogenomics of third-generation aromatase inhibitors.

INTRODUCTION: Breast cancer is a common, life-threatening disease among women. Contemporary hormonal therapy with third-generation aromatase inhibitors for estrogen-receptor-positive breast cancers in postmenopausal women is still facing the challenge of interpatient variability in therapeutic response and intensity of adverse effects. AREAS COVERED: This review highlights up-to-date literature regarding genomic findings in the literature pertaining to anastrozole, exemestane and letrozole metabolism, as well as the drug target aromatase. Genetic polymorphisms in phase I and II aromatase inhibitor metabolizing enzymes that contribute to altered responses among different patient genotypes are discussed. Similarly, aromatase CYP19A1 functional genetic polymorphisms are presented in correlation to altered aromatase activity, disease prognosis and severity of aromatase inhibitor adverse effects. EXPERT OPINION: The field of pharmacogenomics has shown remarkable progress over the last few years, notably in cancer. However, large comprehensive genotyping studies, evaluated under clinical settings, are still needed to unravel the potential impact of aromatase inhibitor pharmacogenomics on breast cancer treatment, monitoring and predicting adverse effects.

Genetic polymorphisms as predictive and prognostic biomarkers in gynecological cancers: a systematic review.

PURPOSE: Numerous studies have explored the potential role of genetic polymorphisms as predictive or prognostic biomarkers in gynecologic malignancies. A systematic review for all eligible polymorphisms has not yet been reported. The aim of this study was to summarize the current status of the field and provide direction for future research. DESIGN: We searched literature databases (MEDLINE, EMBASE, Cochrane) from 2006 to April 2011 to identify studies evaluating the association between gene polymorphisms and clinical outcome in ovarian, endometrial, cervical, or vulvar cancer. The main outcome measures were overall survival (OS) and progression-free survival (PFS). Studies reporting relationships between polymorphisms and toxicity were also included. RESULTS: Sixty two studies met the inclusion criteria. The median sample size was 140. Most of the included studies (n=50, 81%) were conducted in ovarian cancer patients. Almost a third assessed potential predictive associations between gene polymorphism and outcome in ovarian cancer. The most commonly evaluated genes were ERCC1, VEGF, ABCB1 (MDR), and GSTP1. Most studies (n=44, 71%) were observational case-series. Only four studies (6%) included a validation arm and patient population ethnicity was explicitly stated only in 27% of included studies. CONCLUSION: No consistent association between any gene polymorphism and clinical outcome in gynecological cancers has been found across studies. There is incomplete adherence to the REMARK guidelines and inadequate methodology reporting in most studies. Moving forward, analysis of large trial-based clinical samples; adherence to the highest methodological standards, and focus on validation analyses are necessary to identify clinically useful pharmacogenomic biomarkers of outcome.

Improving oncology outcomes through targeted therapeutics will require electronic delivery systems.

Typically, chemotherapy selection takes into account patient demographic data, including disease symptoms, family history, environmental factors and concurrent medications. Although validated and approved genomics tests are available for targeted therapeutics, a major challenge facing healthcare is the ability to process the genomic data in the patient's context and to return clinically interpretable dosing guidance to the physician in a realistic time frame. Delivery of these targeted therapeutics, made possible by clinical decision support systems connected to an electronic health record may help drive both the acceptance and adaptation of an electronic health record system, as well as provide personalized information at point-of-care, as part of the routine workflow. The realization of targeted therapeutics will depend on the concerted efforts of stakeholder groups as they address political, ethical, socioeconomical and technical challenges to achieve personalized medicine adoption through real-world implementation.

The NQO1*2/*2 polymorphism is associated with poor overall survival in patients following resection of stages II and IIIa non-small cell lung cancer.

NAD(P)H:quinone oxidoreductase 1 (NQO1), is a cytosolic flavoenzyme that catalyzes the two-electron reduction of quinones into hydroquinones. A polymorphism (NQO1*2) alters enzymatic activity of NQO1 resulting in diminished NQO1 activity. Malignancies with NQO1*2 may be resistant to radiation and chemotherapy with resulting poorer survival. NQO1 allele was evaluated in subjects enrolled in ECOG 3590, a randomized comparison of radiation (RT) vs radiation and chemotherapy with cisplatin/etoposide (RCT) in patients with completely resected stages II and IIIa NSCLC. Overall survival was estimated using the Kaplan-Meier method and compared via the log-rank test. Cox models were used to assess the impact of covariates on outcomes. Among 152 patients with assessable samples, 24 (16%) had NQO1*2. Median follow-up was 139 months. The presence of NQO1*2/*2 was associated with decreased overall survival (OS) (median in the heterozygote/wild-type group 42.3 vs. 33.5 months in the variant group, p=0.04). In a multivariable Cox model, variant NQO1 (HR = 1.58, p = 0.05), age <60 (HR = 0.67, p = 0.04), PS 1 (HR = 1.47, p = 0.05), cardiovascular disease (HR = 1.93, p = 0.003) and alkaline phosphatase <100 mg/ml (HR = 0.59, p = 0.005) were all significant predictors of OS. NQO1*2/*2 may be an independent predictor of poor overall survival in individuals with resected stages II and IIIa NSCLC. Although the basis for the NQO1 association with decreased survival requires additional evaluation, NQO1 may represent a biomarker for guiding individualized therapy.