Citations

Abstract INTRODUCTION Patient derived xenografts (PDX) may better reflect individual patient (pt) tumor biology; however, the feasibility of collecting PDX from percutaneous tumor biopsies (PTB) in the neoadjuvant setting is unknown. Furthermore, drug response phenotypes observed in PDX have not been prospectively compared to the corresponding pt clinical outcomes. METHODS The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective Mayo study of pts with high-risk breast cancer treated with neoadjuvant weekly paclitaxel (T) +/- trastuzumab followed by anthracycline based chemotherapy. PTB (at baseline) and residual surgical tissue (after all chemotherapy) are obtained for next generation sequencing (NGS) and PDX. Tumor biopsies (1-2 cores from 14 gauge needle) were implanted with Matrigel <1 hour of collection in the flanks of NOD-SCID or NSG mice. Low dose estradiol was supplemented in the drinking water. Primary outgrowth rate was defined as PDX tumor volume >50 mm3. Take rate was defined as development of at least 1 stably transplantable xenograft line/pt. To determine whether clinical T response assessed by MRI corresponded with in vivo T response, pretreatment PDX from 5 pts were injected into NOD-SCID mice (20 mice per pt PDX) and when tumors reached 100-200mm3, mice were randomized to no treatment vs T (20 mg/kg, ip. every 3-4 days). Two of these 5 patients had a MRI response defined as >30% decrease in longest lesion. RESULTS Pretreatment PTB from 81 unique pts were implanted in 251 mice (2-4 mice/pt). PDX outgrowth rates were 33.3% (27/81 pts) and 22 stable PDX were established (overall take rate 27.2%). Take rates were as follows: triple negative breast cancer (46%; 13/28); HER2 (27%; 6/22), Luminal B (13%; 3/22), and luminal A (0%; 0/9). Residual surgical tumor (after all treatment) from 17 pts was injected into 85 mice (average 5 mice/pt) and the initial outgrowth rate was 23% (4/17) with 3 stably transplantable lines established. PDX, derived from pretreatment PTB of 5 pts (2 responders and 3 non-responders), were assessed for in vivo T response. The size of the T treated group was significantly smaller than the no treatment group for the PDX derived from the 2 clinical responders, with complete disappearance of tumor by 18 days. In contrast, the PDX derived from the 3 clinical non-responders had no evidence for T response. CONCLUSIONS We have demonstrated the feasibility of using PTB to establish PDX in a prospective neoadjuvant clinical study and have demonstrated similar T drug response phenotypes in in the PDX as seen in the corresponding pt. These data suggest that PDX generated prospectively may be useful for biomarker validation and the development and individualization of new drug therapy. Funded by the Mayo Clinic Center for Individualized Medicine and the Mayo Clinic Cancer Center Citation Format: Jia Yu, Ping Yin, Bowen Gao, Jason P. Sinnwell, Ann M. Moyer, Daniel W. Visscher, Amy L. Conners, Travis J. Dockter, Krishna R. Kalari, Xiaojia Tang, Kevin J. Thompson, Hugues Sicotte, Douglas W. Mahoney, Steven N. Hart, Peter T. Vedell, Poulami Barman, Katie N. Jones, Sarah A. McLaughlin, John A. Copland, Alvaro Moreno Aspitia, Donald W. Northfelt, Richard J. Gray, Vera J. Suman, Jeanette E. Eckel Passow, Eric D. Wieben, James N. Ingle, Zhenkun Lou, Gianrico Farrugia, Richard Weinshilboum, Matthew P. Goetz, Judy C. Boughey, Liewei Wang. Feasibility of using percutaneous tumor biopsies from a prospective neoadjuvant breast cancer study to develop patient derived xenografts and assess in vivo chemotherapy sensitivity. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1195. doi:10.1158/1538-7445.AM2014-1195

The scaling up of data in clinical pharmacology and the merger of systems biology and pharmacology has led to the emergence of a new discipline of Quantitative and Systems Pharmacology (QSP). This new research direction might significantly advance the discovery, development, and clinical use of therapeutic drugs. Research communities from computational biology, systems biology, and biological engineering—working collaboratively with pharmacologists, geneticists, biochemists, and analytical chemists—are creating and modeling large data on drug effects that is transforming our understanding of how these drugs work at a network level. In this review, we highlight developments in a new and rapidly growing field—pharmacometabolomics—in which large biochemical data‐capturing effects of genome, gut microbiome, and environment exposures is revealing information about metabotypes and treatment outcomes, and creating metabolic signatures as new potential biomarkers. Pharmacometabolomics informs and complements pharmacogenomics and together they provide building blocks for QSP.

Background— The goal of this study was to identify genetic determinants of plasma N-terminal proatrial natriuretic peptide (NT-proANP) in the general community by performing a large-scale genetic association study and to assess its functional significance in in vitro cell studies and on disease susceptibility. Methods and Results— Genotyping was performed across 16 000 genes in 893 randomly selected individuals, with replication in 891 subjects from the community. Plasma NT-proANP 1–98 concentrations were determined using a radioimmunoassay. Thirty-three genome-wide significant single-nucleotide polymorphisms were identified in the MTHFR-CLCN6-NPPA-NPPB locus and were all replicated. To assess the significance, in vitro functional genomic studies and clinical outcomes for carriers of a single-nucleotide polymorphism rs5063 (V32M) located in NPPA that represented the most significant variation in this genetic locus were assessed. The rs5063 variant allozyme in transfected HEK293 cells was decreased to 55±8% of wild-type protein ( P =0.01) as assessed by quantitative western blots. Carriers of rs5063 had lower NT-proANP levels (1427 versus 2291 pmol/L; P <0.001) and higher diastolic blood pressures (75 versus 73 mm Hg; P =0.009) and were at an increased risk of stroke when compared with wild-type subjects independent of age, sex, diabetes mellitus, hypertension, atrial fibrillation, and cholesterol levels (hazard ratio, 1.6; P =0.004). Conclusions— This is the first large-scale genetic association study of circulating NT-proANP levels performed with replication and functional assessment that identified genetic variants in the MTHFR-CLCN6-NPPA-NPPB cluster to be significantly associated with NT-proANP levels. The clinical significance of this variation is related to lower NT-proANP levels, higher blood pressures, and an increased risk of stroke in the general community.

Abstract Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6–96.8% precision and 91.6–95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/.

Abstract Definitive radiotherapy combined with chemotherapy is associated with enhanced locoregional control and clinical outcomes in non-small cell lung cancer (NSCLC) patients who are not candidates for surgery. However, radiation-induced pneumonitis and esophagitis are common dose-limiting inflammatory conditions that occur in these patients. These events can compromise the effect of the overall treatment and reduce quality of life in these patients. It is not clear what factors contribute to differences in the development of toxicities among patients with same clinical or dosimetric parameters. In this study, we conducted a large scale pathway-based analysis to identify inflammation-related genetic variants associated with radiation-induced pneumonitis or esophagitis. In the initial discovery phase, 11,930 inflammation-related genetic variants were genotyped in 243 stage I-III NSCLC patients who were treated with definitive radiotherapy at MD Anderson Cancer Center. A fast-track validation was performed for the top candidate SNPs in an additional 212 NSCLC cases following the same criteria. A total of 14 SNPs and 12 SNPs were validated for pneumonitis and esophagitis, respectively. Meta-analysis was used to summarize the results from two phases. The most significant SNPs for esophagitis and pneumonitis mapped to chromosome 18p (OR=9.05, 95%CI=2.68-30.59, P-meta=3.90×10−4) and 14q (OR=4.75, 95%CI=2.17-10.41, P-meta =9.61×10−5), respectively. To explore the potential underlying mechanisms, we analyzed radiation sensitivity and eQTL relationships of the identified SNPs and their host genes in 277 ethnically defined human lymphoblastoid cell lines. Among the 24 host genes for the 26 identified SNPs, three genes (DDX58, GZMB, CDC2) showed significant association with radiation responses in these cell lines (P&lt;0.05). Moreover, a significant eQTL relationship was identified between CDC2 expression and the genotype of the identified CDC2 SNP (P=0.022). Interestingly, this CDC2 SNP is predicted to create a new miRNA binding site. Luciferase reporter assays to test the influence of this SNP on miRNA regulation is currently ongoing. Our results provide evidence that inflammation-related genetic variants contribute to the development of radiation-induced pneumonitis and esophagitis. The results also suggest that gene expression changes through altered miRNA binding may be an underlying mechanism for these events. Citation Format: Xia Pu, Liewei Wang, Michelle AT Hildebrandt, Yuanqing Ye, Joe Y. Chang, Charles Lu, Heath D. Skinner, Nifang Niu, Gregory D. Jenkins, Ritsuko Komaki, John D. Minna, Jack A. Roth, Richard M. Weinshilboum, Xifeng Wu. Inflammation-related genetic variants predict radiation-induced toxicity following definitive radiotherapy for non-small cell lung cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3626. doi:10.1158/1538-7445.AM2013-3626

Aims Citalopram ( CT ) and escitalopram ( S ‐ CT ) are among the most widely prescribed selective serotonin reuptake inhibitors used to treat major depressive disorder ( MDD ). We applied a genome‐wide association study to identify genetic factors that contribute to variation in plasma concentrations of CT or S ‐ CT and their metabolites in MDD patients treated with CT or S ‐ CT . Methods Our genome‐wide association study was performed using samples from 435 MDD patients. Linear mixed models were used to account for within‐subject correlations of longitudinal measures of plasma drug/metabolite concentrations (4 and 8 weeks after the initiation of drug therapy), and single‐nucleotide polymorphisms ( SNPs ) were modelled as additive allelic effects. Results Genome‐wide significant associations were observed for S ‐ CT concentration with SNPs in or near the CYP2C19 gene on chromosome 10 (rs1074145, P = 4.1 × 10 −9 ) and with S ‐didesmethylcitalopram concentration for SNPs near the CYP2D6 locus on chromosome 22 (rs1065852, P = 2.0 × 10 −16 ), supporting the important role of these cytochrome P450 ( CYP ) enzymes in biotransformation of citalopram. After adjustment for the effect of CYP2C19 functional alleles, the analyses also identified novel loci that will require future replication and functional validation. Conclusions In vitro and in vivo studies have suggested that the biotransformation of CT to monodesmethylcitalopram and didesmethylcitalopram is mediated by CYP isozymes. The results of our genome‐wide association study performed in MDD patients treated with CT or S ‐ CT have confirmed those observations but also identified novel genomic loci that might play a role in variation in plasma levels of CT or its metabolites during the treatment of MDD patients with these selective serotonin reuptake inhibitors.