The impact of SBF2 on taxane-induced peripheral neuropathy.

Taxane-induced peripheral neuropathy (TIPN) is a devastating survivorship issue for many cancer patients. In addition to its impact on quality of life, this toxicity may lead to dose reductions or treatment discontinuation, adversely impacting survival outcomes and leading to health disparities in African Americans (AA). Our lab has previously identified deleterious mutations in SET-Binding Factor 2 (SBF2) that significantly associated with severe TIPN in AA patients. Here, we demonstrate the impact of SBF2 on taxane-induced neuronal damage using an ex vivo model of SBF2 knockdown of induced pluripotent stem cell-derived sensory neurons. Knockdown of SBF2 exacerbated paclitaxel changes to cell viability and neurite outgrowth while attenuating paclitaxel-induced sodium current inhibition. Our studies identified paclitaxel-induced expression changes specific to mature sensory neurons and revealed candidate genes involved in the exacerbation of paclitaxel-induced phenotypes accompanying SBF2 knockdown. Overall, these findings provide ex vivo support for the impact of SBF2 on the development of TIPN and shed light on the potential pathways involved.

Germline predictors for bevacizumab induced hypertensive crisis in ECOG-ACRIN 5103 and BEATRICE.

BACKGROUND: Bevacizumab is a beneficial therapy in several advanced cancer types. Predictive biomarkers to better understand which patients are destined to benefit or experience toxicity are needed. Associations between bevacizumab induced hypertension and survival have been reported but with conflicting conclusions. METHODS: We performed post-hoc analyses to evaluate the association in 3124 patients from two phase III adjuvant breast cancer trials, E5103 and BEATRICE. Differences in invasive disease-free survival (IDFS) and overall survival (OS) between patients with hypertension and those without were compared. Hypertension was defined as systolic blood pressure (SBP) ≥ 160 mmHg (n = 346) and SBP ≥ 180 mmHg (hypertensive crisis) (n = 69). Genomic analyses were performed to evaluate germline genetic predictors for the hypertensive crisis. RESULTS: Hypertensive crisis was significantly associated with superior IDFS (p = 0.015) and OS (p = 0.042), but only IDFS (p = 0.029; HR = 0.28) remained significant after correction for prognostic factors. SBP ≥ 160 mmHg was not associated with either IDFS or OS. A common single-nucleotide polymorphism, rs6486785, was significantly associated with hypertensive crisis (p = 8.4 × 10-9; OR = 5.2). CONCLUSION: Bevacizumab-induced hypertensive crisis is associated with superior outcomes and rs6486785 predicted an increased risk of this key toxicity.

Identification of a SNP cluster associated with taxane-induced peripheral neuropathy risk in patients being treated for breast cancer using GWAS data derived from a large cooperative group trial.

BACKGROUND: Chemotherapy-induced peripheral neuropathy (CIPN) is a common toxicity of taxanes for which there is no effective intervention. Genomic CIPN risk determination has yielded promising, but inconsistent results. The present study assessed the utility of a collective SNP cluster identified using novel analytics to describe taxane-associated CIPN risk. METHODS: We analyzed GWAS data derived from ECOG-5103, first identifying SNPs that were most strongly associated with CIPN using Fisher's ratio (FR). We then ranked ordered those SNPs which discriminated CIPN-positive (CIPN +) from CIPN-negative phenotypes based on their discriminatory power and developed the cluster of SNPs which provided the highest predictive accuracy using leave-one-out cross-validation (LOOCV). RESULTS: Using aggregated genotype data obtained from the previously reported ECOG-5103 clinical trial (in which two different arrays were used, HumanOmniExpress (727,227 SNPs) and HumanOmni1-Quad1 (1,131,857 SNPs)), we identified a 267 SNP cluster which was associated with a CIPN + phenotype with an accuracy of 96.1%. CONCLUSIONS: A cluster of SNPs was identified which prospectively discriminated patients most likely to develop symptomatic CIPN following taxane exposure as part of a breast cancer chemotherapy regimen. Validation using an independent patient cohort should be performed.

Leveraging GWAS data derived from a large cooperative group trial to assess the risk of taxane-induced peripheral neuropathy (TIPN) in patients being treated for breast cancer: Part 2-functional implications of a SNP cluster associated with TIPN risk in patients being treated for breast cancer.

INTRODUCTION: Using GWAS data derived from a large collaborative trial (ECOG-5103), we identified a cluster of 267 SNPs which predicted CIPN in treatment-naive patients as reported in Part 1 of this study. To assess the functional and pathological implications of this set, we identified collective gene signatures were and evaluated the informational value of those signatures in defining CIPN's pathogenesis. METHODS: In Part 1, we analyzed GWAS data derived from ECOG-5103, first identifying those SNPs that were most strongly associated with CIPN using Fisher's ratio. After identifying those SNPs which differentiated CIPN-positive from CIPN-negative phenotypes, we ranked them in order of their discriminatory power to produce a cluster of SNPs which provided the highest predictive accuracy using leave-one-out cross validation (LOOCV). An uncertainty analysis was included. Using the best predictive SNP cluster, we performed gene attribution for each SNP using NCBI Phenotype Genotype Integrator and then assessed functionality by applying GeneAnalytics, Gene Set Enrichment Analysis, and PCViz. RESULTS: Using aggregate data derived from the GWAS, we identified a 267 SNP cluster which was associated with a CIPN+ phenotype with an accuracy of 96.1%. We could attribute 173 genes to the 267 SNP cluster. Six long intergenic non-protein coding genes were excluded. Ultimately, the functional analysis was based on 138 genes. Of the 17 pathways identified by Gene Analytics (GA) software, the irinotecan pharmacokinetic pathway had the highest score. Highly matching gene ontology attributions included flavone metabolic process, flavonoid glucuronidation, xenobiotic glucuronidation, nervous system development, UDP glycosyltransferase activity, retinoic acid binding, protein kinase C binding, and glucoronosyl transferase activity. Gene Set Enrichment Analysis (GSEA) GO terms identified neuron-associated genes as most significant (p = 5.45e-10). Consistent with the GA's output, flavone, and flavonoid associated terms, glucuronidation were noted as were GO terms associated with neurogenesis. CONCLUSION: The application of functional analyses to phenotype-associated SNP clusters provides an independent validation step in assessing the clinical meaningfulness of GWAS-derived data. Functional analyses following gene attribution of a CIPN-predictive SNP cluster identified pathways, gene ontology terms, and a network which were consistent with a neuropathic phenotype.

Using machine learning algorithms to identify genes essential for cell survival.

BACKGROUND: With the explosion of data comes a proportional opportunity to identify novel knowledge with the potential for application in targeted therapies. In spite of this huge amounts of data, the solutions to treating complex disease is elusive. One reason being that these diseases are driven by a network of genes that need to be targeted in order to understand and treat them effectively. Part of the solution lies in mining and integrating information from various disciplines. Here we propose a machine learning method to mining through publicly available literature on RNA interference with the goal of identifying genes essential for cell survival. RESULTS: A total of 32,164 RNA interference abstracts were identified from 10.5 million pubmed abstracts (2001 - 2015). These abstracts spanned over 1467 cancer cell lines and 4373 genes representing a total of 25,891 cell gene associations. Among the 1467 cell lines 88% of them had at least 1 or up to 25 genes studied in a given cell line. Among the 4373 genes 96% of them were studied in at least 1 or up to 25 different cell lines. CONCLUSIONS: Identifying genes that are crucial for cell survival can be a critical piece of information especially in treating complex diseases, such as cancer. The efficacy of a therapeutic intervention is multifactorial in nature and in many cases the source of therapeutic disruption could be from an unsuspected source. Machine learning algorithms helps to narrow down the search and provides information about essential genes in different cancer types. It also provides the building blocks to generate a network of interconnected genes and processes. The information thus gained can be used to generate hypothesis which can be experimentally validated to improve our understanding of what triggers and maintains the growth of cancerous cells.

A translational bioinformatic approach in identifying and validating an interaction between Vitamin A and CYP19A1.

INTRODUCTION: One major challenge in personalized medicine research is to identify the environmental factors that can alter drug response, and to investigate their molecular mechanisms. These environmental factors include co-medications, food, and nutrition or dietary supplements. The increasing use of dietary supplements and their potential interactions with cytochrome P450 (CYP450) enzymes is a highly significant personalized medicine research domain, because most of the drugs on the market are metabolized through CYP450 enzymes. METHODS: Initial bioinformatics analysis revealed a number of regulators of CYP450 enzymes from a human liver bank gene expression quantitative loci data set. Then, a compound-gene network was constructed from the curated literature data. This network consisted of compounds that interact with either CYPs and/or their regulators that influence either their gene expression or activity. We further evaluated this finding in three different cell lines: JEG3, HeLa, and LNCaP cells. RESULTS: From a total of 868 interactions we were able to identify an interesting interaction between retinoic acid (i.e. Vitamin A) and the aromatase gene (i.e. CYP19A1). Our experimental results showed that retinoic acid at physiological concentration significantly influenced CYP19A1 gene expressions. CONCLUSIONS: These results suggest that the presence of retinoic acid may alter the efficacy of agents used to suppress aromatase expression.

Associations between genetic variants and the effect of letrozole and exemestane on bone mass and bone turnover.

Adjuvant therapy for hormone receptor (HR) positive postmenopausal breast cancer patients includes aromatase inhibitors (AI). While both the non-steroidal AI letrozole and the steroidal AI exemestane decrease serum estrogen concentrations, there is evidence that exemestane may be less detrimental to bone. We hypothesized that single nucleotide polymorphisms (SNP) predict effects of AIs on bone turnover. Early stage HR-positive breast cancer patients were enrolled in a randomized trial of exemestane versus letrozole. Effects of AI on bone mineral density (BMD) and bone turnover markers (BTM), and associations between SNPs in 24 candidate genes and changes in BMD or BTM were determined. Of the 503 enrolled patients, paired BMD data were available for 123 and 101 patients treated with letrozole and exemestane, respectively, and paired BTM data were available for 175 and 173 patients, respectively. The mean change in lumbar spine BMD was significantly greater for letrozole-treated (-3.2 %) compared to exemestane-treated patients (-1.0 %) (p = 0.0016). Urine N-telopeptide was significantly increased in patients treated with exemestane (p = 0.001) but not letrozole. Two SNPs (rs4870061 and rs9322335) in ESR1 and one SNP (rs10140457) in ESR2 were associated with decreased BMD in letrozole-treated patients. In the exemestane-treated patients, SNPs in ESR1 (Rs2813543) and CYP19A1 (Rs6493497) were associated with decreased bone density. Exemestane had a less negative impact on bone density compared to letrozole, and the effects of AI therapy on bone may be impacted by genetic variants in the ER pathway.

Optimization of a human induced pluripotent stem cell-derived sensory neuron model for the in vitro evaluation of taxane-induced neurotoxicity.

Human induced pluripotent stem cell-derived sensory neuron (iPSC-dSN) models are a valuable resource for the study of neurotoxicity but are affected by poor replicability and reproducibility, often due to a lack of optimization. Here, we identify experimental factors related to culture conditions that substantially impact cellular drug response in vitro and determine optimal conditions for improved replicability and reproducibility. Treatment duration and cell seeding density were both found to be significant factors, while cell line differences also contributed to variation. A replicable dose-response in viability was demonstrated after 48-h exposure to docetaxel or paclitaxel. Additionally, a replicable dose-dependent reduction in neurite outgrowth was demonstrated, demonstrating the applicability of the model for the examination of additional phenotypes. Overall, we have established an optimized iPSC-dSN model for the study of taxane-induced neurotoxicity.

An integrated pharmacokinetics ontology and corpus for text mining.

BACKGROUND: Drug pharmacokinetics parameters, drug interaction parameters, and pharmacogenetics data have been unevenly collected in different databases and published extensively in the literature. Without appropriate pharmacokinetics ontology and a well annotated pharmacokinetics corpus, it will be difficult to develop text mining tools for pharmacokinetics data collection from the literature and pharmacokinetics data integration from multiple databases. DESCRIPTION: A comprehensive pharmacokinetics ontology was constructed. It can annotate all aspects of in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. It covers all drug metabolism and transportation enzymes. Using our pharmacokinetics ontology, a PK-corpus was constructed to present four classes of pharmacokinetics abstracts: in vivo pharmacokinetics studies, in vivo pharmacogenetic studies, in vivo drug interaction studies, and in vitro drug interaction studies. A novel hierarchical three level annotation scheme was proposed and implemented to tag key terms, drug interaction sentences, and drug interaction pairs. The utility of the pharmacokinetics ontology was demonstrated by annotating three pharmacokinetics studies; and the utility of the PK-corpus was demonstrated by a drug interaction extraction text mining analysis. CONCLUSIONS: The pharmacokinetics ontology annotates both in vitro pharmacokinetics experiments and in vivo pharmacokinetics studies. The PK-corpus is a highly valuable resource for the text mining of pharmacokinetics parameters and drug interactions.

Genetic associations with toxicity-related discontinuation of aromatase inhibitor therapy for breast cancer.

Up to 25 % of patients discontinue adjuvant aromatase inhibitor (AI) therapy due to intolerable symptoms. Predictors of which patients will be unable to tolerate these medications have not been defined. We hypothesized that inherited variants in candidate genes are associated with treatment discontinuation because of AI-associated toxicity. We prospectively evaluated reasons for treatment discontinuation in women with hormone receptor-positive breast cancer initiating adjuvant AI through a multicenter, prospective, randomized clinical trial of exemestane versus letrozole. Using multiple genetic models, we evaluated potential associations between discontinuation of AI therapy because of toxicity and 138 variants in 24 candidate genes, selected a priori, primarily with roles in estrogen metabolism and signaling. To account for multiple comparisons, statistical significance was defined as p < 0.00036. Of the 467 enrolled patients with available germline DNA, 152 (33 %) discontinued AI therapy because of toxicity. Using a recessive statistical model, an intronic variant in ESR1 (rs9322336) was associated with increased risk of musculoskeletal toxicity-related exemestane discontinuation [HR 5.0 (95 % CI 2.1-11.8), p < 0.0002]. An inherited variant potentially affecting estrogen signaling may be associated with exemestane-associated toxicity, which could partially account for intra-patient differences in AI tolerability. Validation of this finding is required.

Regulation of microRNA expression by rifampin in human hepatocytes.

Rifampin causes drug interactions by altering hepatic drug metabolism. Because microRNAs (miRNAs) have been shown to regulate genes involved in drug metabolism, we determined the effect of rifampin on the expression of hepatic miRNAs. Primary human hepatocytes from seven subjects were treated with rifampin, and the expression of miRNA and cytochrome P450 (P450) mRNAs was measured by TaqMan assays and RNA-seq, respectively. Rifampin induced the expression of 10 clinically important and 13 additional P450 genes and repressed the expression of 9 other P450 genes (P < 0.05). Rifampin induced the expression of 33 miRNAs and repressed the expression of 35 miRNAs (P < 0.05). Several of these changes were highly negatively correlated with the rifampin-induced changes in the expression of their predicted target P450 mRNAs, supporting the possibility of miRNA-induced regulation of P450 mRNA expression. In addition, several other miRNA changes were positively correlated with the changes in P450 mRNA expression, suggesting similar regulatory mechanisms. Despite the interindividual variability in the rifampin effects on miRNA expression, principal components analysis clearly separated the rifampin-treated samples from the controls. In conclusion, rifampin treatment alters miRNA expression patterns in human hepatocytes, and some of the changes were correlated with the rifampin-induced changes in expression of the P450 mRNAs they are predicted to target.

The impact of glucocorticoid polymorphisms on markers of neonatal respiratory disease after antenatal betamethasone administration.

OBJECTIVE: We previously demonstrated that maternal and fetal genotypes are associated independently with neonatal respiratory distress syndrome. The objective of the current study was to determine the impact of maternal and fetal single-nucleotide polymorphisms (SNPs) in key betamethasone pathways on respiratory outcomes that serve as markers for severity of disease. STUDY DESIGN: DNA was obtained from women who were given betamethasone and from their infants. Samples were genotyped for 73 exploratory drug metabolism and glucocorticoid pathway SNPs. Clinical variables and neonatal outcomes were obtained. Logistic regression analysis that controlled for relevant clinical variables to determine SNP impact on bronchopulmonary dysplasia (BPD), the need for respiratory support, and surfactant therapy use was performed. RESULTS: Data from 109 women who delivered 117 infants were analyzed: 14.5% of the infants experienced BPD; 70.8% of the infants needed some respiratory support after birth, and 27.5% of the infants needed surfactant therapy. In a multivariable regression analysis, gestational age at delivery was associated with most neonatal respiratory outcomes (P ≤ .01), and chorioamnionitis was associated with BPD (P < .03). The following genotypes were associated with respiratory severity outcomes: BPD-fetal Importin 13 gene (IPO13; rs4448553; odds ratio [OR], 0.01; 95% confidence interval [CI], 0.00-0.92); surfactant use-maternal IPO13 (rs2428953 and 2486014; OR, 13.8; 95% CI, 1.80-105.5; and OR, 35.5; 95% CI, 1.71-736.6, respectively). CONCLUSION: Several discrete maternal and fetal SNPs in the IPO13 family may be associated with neonatal respiratory outcomes after maternal antenatal corticosteroid treatment for anticipated preterm birth.

Cytochrome P450 Oxidoreductase (POR) Associated with Severe Paclitaxel-Induced Peripheral Neuropathy in Patients of European Ancestry from ECOG-ACRIN E5103.

PURPOSE: Paclitaxel is a widely used anticancer therapeutic. Peripheral neuropathy is the dose-limiting toxicity and negatively impacts quality of life. Rare germline gene markers were evaluated for predicting severe taxane-induced peripheral neuropathy (TIPN) in the patients of European ancestry. In addition, the impact of Cytochrome P450 (CYP) 2C8, CYP3A4, and CYP3A5 metabolizer status on likelihood of severe TIPN was also assessed. EXPERIMENTAL DESIGN: Whole-exome sequencing analyses were performed in 340 patients of European ancestry who received a standard dose and schedule of paclitaxel in the adjuvant, randomized phase III breast cancer trial, E5103. Patients who experienced grade 3-4 (n = 168) TIPN were compared to controls (n = 172) who did not experience TIPN. For the analyses, rare variants with a minor allele frequency ≤ 3% and predicted to be deleterious by protein prediction programs were retained. A gene-based, case-control analysis using SKAT was performed to identify genes that harbored an imbalance of deleterious variants associated with increased risk of severe TIPN. CYP star alleles for CYP2C8, CYP3A4, and CYP3A5 were called. An additive logistic regression model was performed to test the association of CYP2C8, CYP3A4, and CYP3A5 metabolizer status with severe TIPN. RESULTS: Cytochrome P450 oxidoreductase (POR) was significantly associated with severe TIPN (P value = 1.8 ×10-6). Six variants were predicted to be deleterious in POR. There were no associations between CYP2C8, CYP3A4, or CYP3A5 metabolizer status with severe TIPN. CONCLUSIONS: Rare variants in POR predict an increased risk of severe TIPN in patients of European ancestry who receive paclitaxel.

The impact of drug metabolizing enzyme polymorphisms on outcomes after antenatal corticosteroid use.

OBJECTIVE: To determine the impact of maternal and fetal single nucleotide polymorphisms in key betamethasone pathways on neonatal outcomes. STUDY DESIGN: DNA was obtained from women given betamethasone and their infants. Samples were genotyped for 73 exploratory drug metabolism and glucocorticoid pathway single nucleotide polymorphisms. Clinical variables and neonatal outcomes were obtained. Logistic regression analysis using relevant clinical variables and genotypes to model for associations with neonatal respiratory distress syndrome was performed. RESULTS: One hundred nine women delivering 117 infants were analyzed. Sixty-four infants (49%) developed respiratory distress syndrome. Multivariable analysis revealed that respiratory distress syndrome was associated with maternal single nucleotide polymorphisms in CYP3A5 (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.16-2.30) and the glucocorticoid resistance (OR, 0.28; 95% CI, 0.08-0.95) and fetal single nucleotide polymorphisms in ADCY9 (OR, 0.17; 95% CI, 0.03-0.80) and CYP3A7*1E (rs28451617; OR, 23.68; 95% CI, 1.33-420.6). CONCLUSION: Maternal and fetal genotypes are independently associated with neonatal respiratory distress syndrome after treatment with betamethasone for preterm labor.

Passage number affects differentiation of sensory neurons from human induced pluripotent stem cells.

Induced pluripotent stem cells (iPSCs) are a valuable resource for neurological disease-modeling and drug discovery due to their ability to differentiate into neurons reflecting the genetics of the patient from which they are derived. iPSC-derived cultures, however, are highly variable due to heterogeneity in culture conditions. We investigated the effect of passage number on iPSC differentiation to optimize the generation of sensory neurons (iPSC-dSNs). Three iPSC lines reprogrammed from the peripheral blood of three donors were differentiated into iPSC-dSNs at passage numbers within each of the following ranges: low (5-10), intermediate (20-26), and high (30-38). Morphology and pluripotency of the parent iPSCs were assessed prior to differentiation. iPSC-dSNs were evaluated based on electrophysiological properties and expression of key neuronal markers. All iPSC lines displayed similar morphology and were similarly pluripotent across passage numbers. However, the expression levels of neuronal markers and sodium channel function analyses indicated that iPSC-dSNs differentiated from low passage numbers better recapitulated the sensory neuron phenotype than those differentiated from intermediate or high passage numbers. Our results demonstrate that lower passage numbers may be better suited for differentiation into peripheral sensory neurons.

A non-coding GWAS variant impacts anthracycline-induced cardiotoxic phenotypes in human iPSC-derived cardiomyocytes.

Anthracyclines, widely used to treat breast cancer, have the potential for cardiotoxicity. We have previously identified and validated a germline single nucleotide polymorphism, rs28714259, associated with an increased risk of anthracycline-induced heart failure. We now provide insights into the mechanism by which rs28714259 might confer increased risk of cardiac damage. Using hiPSC-derived cardiomyocyte cell lines with either intrinsic polymorphism or CRISPR-Cas9-mediated deletion of rs28714259 locus, we demonstrate that glucocorticoid receptor signaling activated by dexamethasone pretreatment prior to doxorubicin exposure preserves cardiomyocyte viability and contractility in cardiomyocytes containing the major allele. Homozygous loss of the rs28714259 major allele diminishes dexamethasone's protective effect. We further demonstrate that the risk allele of rs28714259 disrupts glucocorticoid receptor and rs28714259 binding affinity. Finally, we highlight the activation of genes and pathways involved in cardiac hypertrophy signaling that are blocked by the risk allele, suggesting a decreased adaptive survival response to doxorubicin-related stress.

Association of QT interval-prolonging drugs with clinical trial eligibility in patients with advanced cancer.

Introduction: Drug-induced prolongation of the heart rate-corrected QT interval (QTc) is associated with increased risk for the potentially fatal arrhythmia torsades de pointes. Due to arrhythmia risk, clinical trials with cancer therapeutics often exclude patients based on thresholds for QTc prolongation. Our objective was to assess associations between prescriptions for QT-prolonging drugs and the odds of meeting cancer trial exclusionary QTc thresholds in a cohort of adults with advanced cancer. Methods: Electronic health records were retrospectively reviewed for 271 patients seen at our institutional molecular solid tumor clinic. Collected data included demographics, QTc measurements, ventricular arrhythmia-related diagnoses, and all inpatient and outpatient prescriptions. Potential associations were assessed between demographic and clinical variables, including prescriptions for QT-prolonging drugs, and QTc measurements. Results: Women had longer median QTc measurements than men (p = 0.030) and were prescribed more QT-prolonging drugs during the study (p = 0.010). In all patients, prescriptions for QT-prolonging drugs were associated with longer median and maximum QTc measurements at multiple assessed time points (i.e., for QT-prolonging drugs prescribed within 10, 30, 60, and 90 days of QTc measurements). Similarly, the number of QT-prolonging drugs prescribed was correlated with longer median and maximum QTc measurements at multiple time points. Common QTc-related exclusionary criteria were collected from a review of ClinicalTrials.gov for recent cancer clinical trials. Based on common exclusion criteria, prescriptions for QT-prolonging drugs increased the odds of trial exclusion. Conclusion: This study demonstrates that prescriptions for QT-prolonging drugs were associated with longer QTc measurements and increased odds of being excluded from cancer clinical trials.

Clinical Opportunities for Germline Pharmacogenetics and Management of Drug-Drug Interactions in Patients With Advanced Solid Cancers.

PURPOSE: Precision medicine approaches, including germline pharmacogenetics (PGx) and management of drug-drug interactions (DDIs), are likely to benefit patients with advanced cancer who are frequently prescribed multiple concomitant medications to treat cancer and associated conditions. Our objective was to assess the potential opportunities for PGx and DDI management within a cohort of adults with advanced cancer. METHODS: Medication data were collected from the electronic health records for 481 subjects since their first cancer diagnosis. All subjects were genotyped for variants with clinically actionable recommendations in Clinical Pharmacogenetics Implementation Consortium guidelines for 13 pharmacogenes. DDIs were defined as concomitant prescription of strong inhibitors or inducers with sensitive substrates of the same drug-metabolizing enzyme and were assessed for six major cytochrome P450 (CYP) enzymes. RESULTS: Approximately 60% of subjects were prescribed at least one medication with Clinical Pharmacogenetics Implementation Consortium recommendations, and approximately 14% of subjects had an instance for actionable PGx, defined as a prescription for a drug in a subject with an actionable genotype. The overall subject-level prevalence of DDIs and serious DDIs were 50.3% and 34.8%, respectively. Serious DDIs were most common for CYP3A, CYP2D6, and CYP2C19, occurring in 24.9%, 16.8%, and 11.7% of subjects, respectively. When assessing PGx and DDIs together, approximately 40% of subjects had at least one opportunity for a precision medicine-based intervention and approximately 98% of subjects had an actionable phenotype for at least one CYP enzyme. CONCLUSION: Our findings demonstrate numerous clinical opportunities for germline PGx and DDI management in adults with advanced cancer.

Genetic variation in DNA-repair pathways and response to radiochemotherapy in esophageal adenocarcinoma: a retrospective cohort study of the Eastern Cooperative Oncology Group.

BACKGROUND: Recent data in esophageal cancer suggests the variant allele of a single-nucleotide polymorphism (SNP) in XRCC1 may be associated with resistance to radiochemotherapy. However, this SNP has not been assessed in a histologically homogeneous clinical trial cohort that has been treated with a uniform approach. In addition, whether germline DNA may serve as a surrogate for tumor genotype at this locus is unknown in this disease. Our objective was to assess this SNP in relation to the pathologic complete response (pCR) rate in subjects with esophageal adenocarcinoma who received cisplatin-based preoperative radiochemotherapy in a multicenter clinical trial (Eastern Cooperative Oncology Group 1201). As a secondary aim, we investigated the rate of allelic imbalance between germline and tumor DNA. METHODS: Eighty-one eligible treatment-naïve subjects with newly diagnosed resectable esophageal adenocarcinoma received radiotherapy (45 Gy) concurrent with cisplatin-based chemotherapy, with planned subsequent surgical resection. The primary endpoint was pCR, defined as complete absence of tumor in the surgical specimen after radiochemotherapy. Using germline DNA from 60 subjects, we examined the base-excision repair SNP, XRCC1 Arg399Gln, and 4 other SNPs in nucleotide excision (XPD Lys751Gln and Asp312Asn, ERCC1 3' flank) and double-stranded break (XRCC2 5' flank) repair pathways, and correlated genotype with pCR rate. Paired tumor tissue was used to estimate the frequency of allelic imbalance at the XRCC1 SNP. RESULTS: The variant allele of the XRCC1 SNP (399Gln) was detected in 52% of subjects. Only 6% of subjects with the variant allele experienced a pCR, compared to 28% of subjects without the variant allele (odds ratio 5.37 for failing to achieve pCR, p = 0.062). Allelic imbalance at this locus was found in only 10% of informative subjects, suggesting that germline genotype may reflect tumor genotype at this locus. No significant association with pCR was noted for other SNPs. CONCLUSIONS: Assessed for the first time in a prospective, interventional trial cohort of esophageal adenocarcinoma, XRCC1 399Gln was associated with resistance to radiochemotherapy. Further investigation of this genetic variation is warranted in larger cohorts. In addition, these data indicate that germline genotype may serve as a surrogate for tumor genotype at this locus.

Identification of germline cancer predisposition variants during clinical ctDNA testing.

Next-generation sequencing of circulating tumor DNA (ctDNA) is a non-invasive method to guide therapy selection for cancer patients. ctDNA variant allele frequency (VAF) is commonly reported and may aid in discerning whether a variant is germline or somatic. We report on the fidelity of VAF in ctDNA as a predictor for germline variant carriage. Two patient cohorts were studied. Cohort 1 included patients with known germline variants. Cohort 2 included patients with any variant detected by the ctDNA assay with VAF of 40-60%. In cohort 1, 36 of 91 (40%) known germline variants were identified through ctDNA analysis with a VAF of 39-87.6%. In cohort 2, 111 of 160 (69%) variants identified by ctDNA analysis with a VAF between 40 and 60% were found to be germline. Therefore, variants with a VAF between 40 and 60% should induce suspicion for germline status but should not be used as a replacement for germline testing.