Bonnie LaCroix

Genetic Variation That Predicts Platinum Sensitivity Reveals the Role of miR-193b* in Chemotherapeutic Susceptibility

Platinum agents are the backbone of cancer chemotherapy. Recently, we identified and replicated the role of a single nucleotide polymorphism (SNP, rs1649942) in predicting platinum sensitivity both in vitro and in vivo. Using the CEU samples from the International HapMap Project, we found the same SNP to be a master regulator of multiple gene expression phenotypes, prompting us to investigate whether rs1649942-mediated regulation of miRNAs may in part contribute to variation in platinum sensitivity. To these ends, 60 unrelated HapMap CEU I/II samples were used for our discovery-phase study using high-throughput genome-wide miRNA and gene expression profiling. Examining the relationships among rs1649942, its gene expression targets, genome-wide miRNA expression, and cellular sensitivity to carboplatin and cisplatin, we identified 2 platinum-associated miRNAs (miR-193b* and miR-320) that inhibit the expression of 5 platinum-associated genes (CRIM1, IFIT2, OAS1, KCNMA1, and GRAMD1B). We further replicated the relationship between the expression of miR-193b*, CRIM1, IFIT2, KCNMA1, and GRAMD1B, and platinum sensitivity in a separate HapMap CEU III dataset. We then showed that overexpression of miR-193b* in a randomly selected HapMap cell line results in resistance to both carboplatin and cisplatin. This relationship was also found in 7 ovarian cancer cell lines from NCI60 dataset and confirmed in an OVCAR-3 that overexpression of miR-193b* leads to increased resistance to carboplatin. Our findings highlight a potential mechanism of action for a previously observed genotype-survival outcome association. Further examination of miR-193b* in platinum sensitivity in ovarian cancer is warranted. Mol Cancer Ther; 11(9); 2054–61. ©2012 AACR.

Integrative analyses of genetic variation, epigenetic regulation, and the transcriptome to elucidate the biology of platinum sensitivity

BackgroundUsing genome-wide genetic, gene expression, and microRNA expression (miRNA) data, we developed an integrative approach to investigate the genetic and epigenetic basis of chemotherapeutic sensitivity.ResultsThrough a sequential multi-stage framework, we identified genes and miRNAs whose expression correlated with platinum sensitivity, mapped these to genomic loci as quantitative trait loci (QTLs), and evaluated the associations between these QTLs and platinum sensitivity. A permutation analysis showed that top findings from our approach have a much lower false discovery rate compared to those from a traditional GWAS of drug sensitivity. Our approach identified five SNPs associated with 10 miRNAs and the expression level of 15 genes, all of which were associated with carboplatin sensitivity. Of particular interest was one SNP (rs11138019), which was associated with the expression of both miR-30d and the gene ABCD2, which were themselves correlated with both carboplatin and cisplatin drug-specific phenotype in the HapMap samples. Functional study found that knocking down ABCD2 in vitro led to increased apoptosis in ovarian cancer cell line SKOV3 after cisplatin treatment. Over-expression of miR-30d in vitro caused a decrease in ABCD2 expression, suggesting a functional relationship between the two.ConclusionsWe developed an integrative approach to the investigation of the genetic and epigenetic basis of human complex traits. Our approach outperformed standard GWAS and provided hints at potential biological function. The relationships between ABCD2 and miR-30d, and ABCD2 and platin sensitivity were experimentally validated, suggesting a functional role of ABCD2 and miR-30d in sensitivity to platinating agents.

MicroRNA biogenesis and cellular proliferation

Given the fundamental roles of microRNAs (miRNAs) in physiological, developmental, and pathologic processes, we hypothesized that genes involved in miRNA biogenesis contribute to human complex traits. For 13 such genes, we evaluated the relationship between transcription and 2 classes of complex traits, namely cellular growth and sensitivity to various chemotherapeutic agents in a set of lymphoblastoid cell lines. We found a highly significant correlation between argonaute RNA-induced silencing complex catalytic component 2 (AGO2) expression and cellular growth rate (Bonferroni-adjusted P < 0.05), and report additional miRNA biogenesis genes with suggestive associations with either cellular growth rate or chemotherapeutic sensitivity. AGO2 expression was found to be correlated with multiple drug sensitivity phenotypes. Furthermore, small interfering RNA knockdown of AGO2 resulted in cellular growth inhibition in an ovarian cancer cell line (OVCAR-3), supporting the role of this miRNA biogenesis gene in cell proliferation in cancer cells. Expression quantitative trait loci mapping indicated that genetic variation (in the form of both single-nucleotide polymorphisms and copy number variations) that may regulate the expression of AGO2 can have downstream effects on cellular growth-dependent complex phenotypes.

Predicting Response to Histone Deacetylase Inhibitors Using High-Throughput Genomics

BACKGROUND Many disparate biomarkers have been proposed as predictors of response to histone deacetylase inhibitors (HDI); however, all have failed when applied clinically. Rather than this being entirely an issue of reproducibility, response to the HDI vorinostat may be determined by the additive effect of multiple molecular factors, many of which have previously been demonstrated. METHODS We conducted a large-scale gene expression analysis using the Cancer Genome Project for discovery and generated another large independent cancer cell line dataset across different cancers for validation. We compared different approaches in terms of how accurately vorinostat response can be predicted on an independent out-of-batch set of samples and applied the polygenic marker prediction principles in a clinical trial. RESULTS Using machine learning, the small effects that aggregate, resulting in sensitivity or resistance, can be recovered from gene expression data in a large panel of cancer cell lines.This approach can predict vorinostat response accurately, whereas single gene or pathway markers cannot. Our analyses recapitulated and contextualized many previous findings and suggest an important role for processes such as chromatin remodeling, autophagy, and apoptosis. As a proof of concept, we also discovered a novel causative role for CHD4, a helicase involved in the histone deacetylase complex that is associated with poor clinical outcome. As a clinical validation, we demonstrated that a common dose-limiting toxicity of vorinostat, thrombocytopenia, can be predicted (r = 0.55, P = .004) several days before it is detected clinically. CONCLUSION Our work suggests a paradigm shift from single-gene/pathway evaluation to simultaneously evaluating multiple independent high-throughput gene expression datasets, which can be easily extended to other investigational compounds where similar issues are hampering clinical adoption.

Identifying and Validating a Combined mRNA and MicroRNA Signature in Response to Imatinib Treatment in a Chronic Myeloid Leukemia Cell Line

Imatinib, a targeted tyrosine kinase inhibitor, is the gold standard for managing chronic myeloid leukemia (CML). Despite its wide application, imatinib resistance occurs in 20–30% of individuals with CML. Multiple potential biomarkers have been identified to predict imatinib response; however, the majority of them remain externally uncorroborated. In this study, we set out to systematically identify gene/microRNA (miRNA) whose expression changes are related to imatinib response. Through a Gene Expression Omnibus search, we identified two genome-wide expression datasets that contain expression changes in response to imatinib treatment in a CML cell line (K562): one for mRNA and the other for miRNA. Significantly differentially expressed transcripts/miRNAs post imatinib treatment were identified from both datasets. Three additional filtering criteria were applied 1) miRbase/miRanda predictive algorithm; 2) opposite direction of imatinib effect for genes and miRNAs; and 3) literature support. These criteria narrowed our candidate gene-miRNA to a single pair: IL8 and miR-493-5p. Using PCR we confirmed the significant up-regulation and down-regulation of miR-493-5p and IL8 by imatinib treatment, respectively in K562 cells. In addition, IL8 expression was significantly down-regulated in K562 cells 24 hours after miR-493-5p mimic transfection (p = 0.002). Furthermore, we demonstrated significant cellular growth inhibition after IL8 inhibition through either gene silencing or by over-expression of miR-493-5p (p = 0.0005 and p = 0.001 respectively). The IL8 inhibition also further sensitized K562 cells to imatinib cytotoxicity (p<0.0001). Our study combined expression changes in transcriptome and miRNA after imatinib exposure to identify a potential gene-miRNA pair that is a critical target in imatinib response. Experimental validation supports the relationships between IL8 and miR-493-5p and between this gene-miRNA pair and imatinib sensitivity in a CML cell line. Our data suggests integrative analysis of multiple omic level data may provide new insight into biomarker discovery as well as mechanisms of imatinib resistance.

Integrative “Omic” Analysis for Tamoxifen Sensitivity through Cell Based Models

It has long been observed that tamoxifen sensitivity varies among breast cancer patients. Further, ethnic differences of tamoxifen therapy between Caucasian and African American have also been reported. Since most studies have been focused on Caucasian people, we sought to comprehensively evaluate genetic variants related to tamoxifen therapy in African-derived samples. An integrative “omic” approach developed by our group was used to investigate relationships among endoxifen (an active metabolite of tamoxifen) sensitivity, SNP genotype, mRNA and microRNA expressions in 58 HapMap YRI lymphoblastoid cell lines. We identified 50 SNPs that associate with cellular sensitivity to endoxifen through their effects on 34 genes and 30 microRNA expression. Some of these findings are shared in both Caucasian and African samples, while others are unique in the African samples. Among gene/microRNA that were identified in both ethnic groups, the expression of TRAF1 is also correlated with tamoxifen sensitivity in a collection of 44 breast cancer cell lines. Further, knock-down TRAF1 and over-expression of hsa-let-7i confirmed the roles of hsa-let-7i and TRAF1 in increasing tamoxifen sensitivity in the ZR-75-1 breast cancer cell line. Our integrative omic analysis facilitated the discovery of pharmacogenomic biomarkers that potentially affect tamoxifen sensitivity.

Genetic Variation Is the Major Determinant of Individual Differences in Leukocyte Endothelial Adhesion

Objective To determine the genetic contribution to leukocyte endothelial adhesion. Methods Leukocyte endothelial adhesion was assessed through a novel cell-based assay using human lymphoblastoid cell lines. A high-throughput screening method was developed to evaluate the inter-individual variability in leukocyte endothelial adhesion using lymphoblastoid cell lines derived from different donors. To assess heritability, ninety-two lymphoblastoid cell lines derived from twenty-three monozygotic twin pairs and twenty-three sibling pairs were compared. These lymphoblastoid cell lines were plated with the endothelial cell line EA.hy926 and labeled with Calcein AM dye. Fluorescence was assessed to determine endothelial cell adhesion to each lymphoblastoid cell line. Intra-pair similarity was determined for monozygotic twins and siblings using Pearson pairwise correlation coefficients. Results A leukocyte endothelial adhesion assay for lymphoblastoid cell lines was developed and optimized (CV = 8.68, Z′-factor = 0.67, SNR = 18.41). A higher adhesion correlation was found between the twins than that between the siblings. Intra-pair similarity for leukocyte endothelial adhesion in monozygotic twins was 0.60 compared to 0.25 in the siblings. The extent to which these differences are attributable to underlying genetic factors was quantified and the heritability of leukocyte endothelial adhesion was calculated to be 69.66% (p-value<0.0001). Conclusions There is a heritable component to leukocyte endothelial adhesion. Underlying genetic predisposition plays a significant role in inter-individual variability of leukocyte endothelial adhesion.

ID: 26: EXPLORING THE LONGITUDINAL TRANSCRIPTOMIC LANDSCAPE OF TYROSINE KINASE INHIBITOR TREATMENT RESPONSE IN CHRONIC MYELOID LEUKEMIA PATIENTS

The interpretation and implementation of large-scale genetic profiles into clinical practice remains a challenge despite substantial growth in our understanding of genetic contributors to drug response. Most current omic studies focus on identifying genetic features that are distinct between normal and tumor samples, but fail to capture the dynamics of association between omic profiles, treatment response and disease progression over time. The focus of this research is to analyze the longitudinal transcriptomic profile of chronic myeloid leukemia patients (CML) in context of tyrosine kinase inhibitor (TKI) treatment and clinical status. The main objectives were to compare a series of post-TKI treatment transcriptome profiles to their baseline levels, and characterize the impact of TKI treatment and CML disease status on the individuals transcriptome over time. Our ultimate goal is to develop TKI response predictors using the longitudinal expression data collected over the treatment course. Peripheral blood samples, buccal swabs and detailed clinical data were collected from each study participant (screened for BCR-ABL1 translocation) for a period of 6 months, in addition to pre-therapy baseline. RNA was extracted from granulocytes isolated from peripheral blood samples, and profiled using RNA sequencing. RNAseq profiles over TKI treatment course were compared to baseline, as well as against hematologic response (complete blood count), cytogenetic response (FISH), and clinical disease progression. We investigated dynamic trends in RNAseq profiles associated TKI response, as well as with the clinical status of the patient over time. We identified genetic features that were either 1) Differentially expressed between baseline and post-TKI time points; 2) Showed non-random spikes in expression levels at specific time points; 3) Associated with hematological and clinical phenotypes, including white blood cell count, percentage granulocytes and percentage cells with BCR-ABL1 translocation; 4) Demonstrated highly correlated patterns of expression over time. Through clustering and enrichment analysis of the selected transcripts, we identified several pathways and molecular features associated with TKI-response, and altered disease state. Of note, we found mTOR signaling, and pro-apoptotic pathways to be significantly altered between baseline and TKI-responding individuals. In addition, we observed significant changes in transcription regulatory network of several transcription factors, notably AP-1, over the treatment time course. To our knowledge, this is the first study to establish the utility of comprehensive longitudinal multiple transcriptome profile analysis of TKI-response in CML. We believe this study will pave way for future large-scale longitudinal omic profiling of CML and other cancer-types.

Abstract 2039: Exploring the longitudinal transcriptomic landscape of tyrosine kinase inhibitor treatment response in chronic myeloid leukemia patients

The interpretation and implementation of large-scale genetic profiles into clinical practice remains a challenge despite substantial growth in our understanding of genetic contributors to drug response. Most current omic studies focus on identifying genetic features that are distinct between normal and tumor samples, but fail to capture the dynamics of association between omic profiles, treatment response and disease progression over time. The focus of this research is to analyze the longitudinal transcriptomic profile of chronic myeloid leukemia patients (CML) in context of tyrosine kinase inhibitor (TKI) treatment and clinical status. The main objectives were to compare a series of post-TKI treatment transcriptome profiles to their baseline levels, and characterize the impact of TKI treatment and CML disease status on the individual9s transcriptome over time. Our ultimate goal is to develop TKI response predictors using the longitudinal expression data collected over the treatment course. Peripheral blood samples, buccal swabs and detailed clinical data were collected from each study participant (screened for BCR-ABL1 translocation) for a period of 6 months, in addition to pre-therapy baseline. RNA was extracted from granulocytes isolated from peripheral blood samples, and profiled using RNA sequencing. RNAseq profiles over TKI treatment course were compared to baseline, as well as against hematologic response (complete blood count), cytogenetic response (FISH), and clinical disease progression. We investigated dynamic trends in RNAseq profiles associated TKI response, as well as with the clinical status of the patient over time. We identified genetic features that were either 1) Differentially expressed between baseline and post-TKI time points; 2) Showed non-random spikes in expression levels at specific time points; 3) Associated with hematological and clinical phenotypes, including white blood cell count, percentage granulocytes and percentage cells with BCR-ABL1 translocation; 4) Demonstrated highly correlated patterns of expression over time. Through clustering and enrichment analysis of the selected transcripts, we identified several pathways and molecular features associated with TKI-response, and altered disease state. Of note, we found mTOR signaling, and pro-apoptotic pathways to be significantly altered between baseline and TKI-responding individuals. In addition, we observed significant changes in transcription regulatory network of several transcription factors, notably AP-1, over the treatment time course. To our knowledge, this is the first study to establish the utility of comprehensive longitudinal multiple transcriptome profile analysis of TKI-response in CML. We believe this study will pave way for future large-scale longitudinal omic profiling of CML and other cancer-types. Citation Format: Aritro Nath, Fan Wang, Divya Lenkala, Bonnie LaCroix, Nancy Glavin, Kristen Kipping-Johnson, Paul Geeleher, Michael Thirman, Lucy Godley, Gordana Raca, Richard Larson, R. Stephanie Huang. Exploring the longitudinal transcriptomic landscape of tyrosine kinase inhibitor treatment response in chronic myeloid leukemia patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2039.

Abstract 1643: MicroRNA processing genes and implications for complex traits

Given the fundamental role of microRNA (miRNA) expression in physiological, developmental and pathological processes, we hypothesize that genes involved in miRNA biogenesis and processing are also important in human complex traits. We identified fifty two such genes and evaluated their expression for their roles in cellular growth and sensitivity to various chemotherapeutic agents in a set of 120 International HapMap cell lines. Gene expression data were obtained through microarray-based gene expression profiling (Affymetrix GeneChip® Human Exon 1.0 ST array) and high-throughput sequencing of the transcriptome (RNA-Seq); data on sensitivity to chemotherapeutic drugs carboplatin, cisplatin, daunorubicin and etoposide were queried using a publicly available pharmacogenomics resource we developed (www.PACdb.org). We found 14 (27%) and 24 (47%) of these miRNA processing gene expression correlated with cellular growth rate and at least one of the 4 chemotherapeutic sensitivities, respectively. Regression analysis for expression between miRNA processing genes and genome-wide miRNAs (quantified using Exiqon miRCURY TM LNA arrays) suggests that the miRNA processing genes affect miRNAs and downstream target genes, leading to complex traits variability. Furthermore, from the results of genome-wide association studies we conducted between genetic variations (in the form of single nucleotide polymorphisms (SNPs) and copy number variations (CNVs)) and miRNA processing genes, we demonstrated that genetic variations that affect the expression of these miRNA processing genes as potential expression quantitative trait loci (eQTLs) also have downstream effects on human complex phenotypes, including cellular growth, sensitivity to chemotherapy and disease susceptibility. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1643. doi:1538-7445.AM2012-1643