Guanglong Jiang

Genome-Wide Association Studies for Taxane-Induced Peripheral Neuropathy in ECOG-5103 and ECOG-1199

Purpose: Taxane-induced peripheral neuropathy (TIPN) is an important survivorship issue for many cancer patients. Currently, there are no clinically implemented biomarkers to predict which patients might be at increased risk for TIPN. We present a comprehensive approach to identification of genetic variants to predict TIPN. Experimental Design: We performed a genome-wide association study (GWAS) in 3,431 patients from the phase III adjuvant breast cancer trial, ECOG-5103 to compare genotypes with TIPN. We performed candidate validation of top SNPs for TIPN in another phase III adjuvant breast cancer trial, ECOG-1199. Results: When evaluating for grade 3–4 TIPN, 120 SNPs had a P value of <10−4 from patients of European descent (EA) in ECOG-5103. Thirty candidate SNPs were subsequently tested in ECOG-1199 and SNP rs3125923 was found to be significantly associated with grade 3–4 TIPN (P = 1.7 × 10−3; OR, 1.8). Race was also a major predictor of TIPN, with patients of African descent (AA) experiencing increased risk of grade 2–4 TIPN (HR, 2.1; P = 5.6 × 10−16) and grade 3–4 TIPN (HR, 2.6; P = 1.1 × 10−11) compared with others. An SNP in FCAMR, rs1856746, had a trend toward an association with grade 2–4 TIPN in AA patients from the GWAS in ECOG-5103 (OR, 5.5; P = 1.6 × 10−7). Conclusions: rs3125923 represents a validated SNP to predict grade 3-4 TIPN. Genetically determined AA race represents the most significant predictor of TIPN. Clin Cancer Res; 21(22); 5082–91. ©2015 AACR.

Prognostic and predictive value of tumor vascular endothelial growth factor gene amplification in metastatic breast cancer treated with paclitaxel with and without bevacizumab; results from ECOG 2100 trial.

Purpose: Clinically validated biomarkers for anti-angiogenesis agents are not available. We have previously reported associations between candidate VEGFA single-nucleotide polymorphisms (SNP) and overall survival (OS) in E2100. The associations between tumor VEGFA amplification and outcome are evaluated here. Experimental Design: E2100 was a phase III trial comparing paclitaxel with or without bevacizumab for patients with metastatic breast cancer. FISH to assess gene amplification status for VEGFA was conducted on paraffin-embedded tumors from 363 patients in E2100. Evaluation for association between amplification status and outcomes was conducted. Results: Estrogen receptor (ER)+ or progesterone receptor (PR)+ tumors were less likely to have VEGFA amplification than ER/PR− tumors (P = 0.020). VEGFA amplification was associated with worse OS (20.2 vs. 25.3 months; P = 0.013) in univariate analysis with a trend for worse OS in multivariate analysis (P = 0.08). There was a significant interaction between VEGFA amplification, hormone receptor status, and study arm. Patients with VEGFA amplification and triple-negative breast cancers (TNBC) or HER2 amplification had inferior OS (P = 0.047); amplification did not affect OS for those who were ER+ or PR+ and HER2−. Those who received bevacizumab with VEGFA amplification had inferior progression-free survival (PFS; P = 0.010) and OS (P = 0.042); no association was seen in the control arm. Test for interaction between study arm and VEGFA amplification with OS was not significant. Conclusion: VEGFA amplification in univariate analysis was associated with poor outcomes; this was particularly prominent in HER2+ or TNBCs. Additional studies are necessary to confirm the trend for poor OS seen on multivariate analysis for patients treated with bevacizumab. Clin Cancer Res; 19(5); 1281–9. ©2012 AACR.

Clinical benefit of a precision medicine based approach for guiding treatment of refractory cancers

Patients and Methods Patients with metastatic solid tumors who had progressed on at least one line of standard of care therapy were referred to the Indiana University Health Precision Genomics Program. Tumor samples were submitted for DNA & RNA next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry for actionable targets. A multi-disciplinary tumor board reviewed all results. For each patient, the ratio of progression-free survival (PFS) of the genomically guided line of therapy divided by the PFS of their prior line was calculated. Patients whose PFS ratio was ≥ 1.3 were deemed to have a meaningful improvement in PFS. Results From April 2014–October 2015, 168 patients were evaluated and 101 patients achieved adequate clinical follow-up for analysis. 19 of 44 (43.2%) patients treated with genomically guided therapy attained a PFS ratio ≥ 1.3 vs. 3 of 57 (5.3%) treated with non-genomically guided therapy (p < 0.0001). Similarly, overall PFS ratios (irrespective of cutoff) were higher for patients with genomically guided therapy vs non-genomically guided therapy (p = 0.05). Further, patients treated with genomically guided therapy had a superior median PFS compared to those treated with non-genomically guided therapy (86 days vs. 49 days, p = 0.005, H.R. = 0.55, 95% C.I.:0.37-0.84). Conclusion Patients with refractory metastatic cancer who receive genomically guided therapy have improved PFS ratios and longer median PFS compared to patients who do not receive genomically guided therapy.

Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer.

BackgroundProper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented.ResultsUsing whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors.ConclusionsThe integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research.

Genome-wide association study for anthracycline-induced congestive heart failure

Purpose: Anthracycline-induced congestive heart failure (CHF) is a rare but serious toxicity associated with this commonly employed anticancer therapy. The ability to predict which patients might be at increased risk prior to exposure would be valuable to optimally counsel risk-to-benefit ratio for each patient. Herein, we present a genome-wide approach for biomarker discovery with two validation cohorts to predict CHF from adult patients planning to receive anthracycline. Experimental Design: We performed a genome-wide association study in 3,431 patients from the randomized phase III adjuvant breast cancer trial E5103 to identify single nucleotide polymorphism (SNP) genotypes associated with an increased risk of anthracycline-induced CHF. We further attempted candidate validation in two independent phase III adjuvant trials, E1199 and BEATRICE. Results: When evaluating for cardiologist-adjudicated CHF, 11 SNPs had a P value <10−5, of which nine independent chromosomal regions were associated with increased risk. Validation of the top two SNPs in E1199 revealed one SNP rs28714259 that demonstrated a borderline increased CHF risk (P = 0.04, OR = 1.9). rs28714259 was subsequently tested in BEATRICE and was significantly associated with a decreased left ventricular ejection fraction (P = 0.018, OR = 4.2). Conclusions: rs28714259 represents a validated SNP that is associated with anthracycline-induced CHF in three independent, phase III adjuvant breast cancer clinical trials. Clin Cancer Res; 23(1); 43–51. ©2016 AACR.

Simultaneous inferences based on empirical Bayes methods and false discovery rates ineQTL data analysis

BackgroundGenome-wide association studies (GWAS) have identified hundreds of genetic variants associated with complex human diseases, clinical conditions and traits. Genetic mapping of expression quantitative trait loci (eQTLs) is providing us with novel functional effects of thousands of single nucleotide polymorphisms (SNPs). In a classical quantitative trail loci (QTL) mapping problem multiple tests are done to assess whether one trait is associated with a number of loci. In contrast to QTL studies, thousands of traits are measured alongwith thousands of gene expressions in an eQTL study. For such a study, a huge number of tests have to be performed (~106). This extreme multiplicity gives rise to many computational and statistical problems. In this paper we have tried to address these issues using two closely related inferential approaches: an empirical Bayes method that bears the Bayesian flavor without having much a priori knowledge and the frequentist method of false discovery rates. A three-component t-mixture model has been used for the parametric empirical Bayes (PEB) method. Inferences have been obtained using Expectation/Conditional Maximization Either (ECME) algorithm. A simulation study has also been performed and has been compared with a nonparametric empirical Bayes (NPEB) alternative.ResultsThe results show that PEB has an edge over NPEB. The proposed methodology has been applied to human liver cohort (LHC) data. Our method enables to discover more significant SNPs with FDR<10% compared to the previous study done by Yang et al. (Genome Research, 2010).ConclusionsIn contrast to previously available methods based on p-values, the empirical Bayes method uses local false discovery rate (lfdr) as the threshold. This method controls false positive rate.

New aQTL SNPs for the CYP2D6 Identified by a Novel Mediation Analysis of Genome-Wide SNP Arrays, Gene Expression Arrays, and CYP2D6 Activity

Background. The genome-wide association studies (GWAS) have been successful during the last few years. A key challenge is that the interpretation of the results is not straightforward, especially for transacting SNPs. Integration of transcriptome data into GWAS may provide clues elucidating the mechanisms by which a genetic variant leads to a disease. Methods. Here, we developed a novel mediation analysis approach to identify new expression quantitative trait loci (eQTL) driving CYP2D6 activity by combining genotype, gene expression, and enzyme activity data. Results. 389,573 and 1,214,416 SNP-transcript-CYP2D6 activity trios are found strongly associated (P < 10−5, FDR = 16.6% and 11.7%) for two different genotype platforms, namely, Affymetrix and Illumina, respectively. The majority of eQTLs are trans-SNPs. A single polymorphism leads to widespread downstream changes in the expression of distant genes by affecting major regulators or transcription factors (TFs), which would be visible as an eQTL hotspot and can lead to large and consistent biological effects. Overlapped eQTL hotspots with the mediators lead to the discovery of 64 TFs. Conclusions. Our mediation analysis is a powerful approach in identifying the trans-QTL-phenotype associations. It improves our understanding of the functional genetic variations for the liver metabolism mechanisms.

A modulator based regulatory network for ERα signaling pathway.

BackgroundEstrogens control multiple functions of hormone-responsive breast cancer cells. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. ERα requires distinct co-regulator or modulators for efficient transcriptional regulation, and they form a regulatory network. Knowing this regulatory network will enable systematic study of the effect of ERα on breast cancer.MethodsTo investigate the regulatory network of ERα and discover novel modulators of ERα functions, we proposed an analytical method based on a linear regression model to identify translational modulators and their network relationships. In the network analysis, a group of specific modulator and target genes were selected according to the functionality of modulator and the ERα binding. Network formed from targets genes with ERα binding was called ERα genomic regulatory network; while network formed from targets genes without ERα binding was called ERα non-genomic regulatory network. Considering the active or repressive function of ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on ERα, the ERα/modulator/target relationships were categorized into 27 classes.ResultsUsing the gene expression data and ERα Chip-seq data from the MCF-7 cell line, the ERα genomic/non-genomic regulatory networks were built by merging ERα/ modulator/target triplets (TF, M, T), where TF refers to the ERα, M refers to the modulator, and T refers to the target. Comparing these two networks, ERα non-genomic network has lower FDR than the genomic network. In order to validate these two networks, the same network analysis was performed in the gene expression data from the ZR-75.1 cell. The network overlap analysis between two cancer cells showed 1% overlap for the ERα genomic regulatory network, but 4% overlap for the non-genomic regulatory network.ConclusionsWe proposed a novel approach to infer the ERα/modulator/target relationships, and construct the genomic/non-genomic regulatory networks in two cancer cells. We found that the non-genomic regulatory network is more reliable than the genomic regulatory network.

Charcot-Marie-Tooth gene, SBF2, associated with taxane-induced peripheral neuropathy in African Americans.

Purpose Taxane-induced peripheral neuropathy (TIPN) is one of the most important survivorship issues for cancer patients. African Americans (AA) have previously been shown to have an increased risk for this toxicity. Germline predictive biomarkers were evaluated to help identify a priori which patients might be at extraordinarily high risk for this toxicity. Experimental design Whole exome sequencing was performed using germline DNA from 213 AA patients who received a standard dose and schedule of paclitaxel in the adjuvant, randomized phase III breast cancer trial, E5103. Cases were defined as those with either grade 3-4 (n=64) or grade 2-4 (n=151) TIPN and were compared to controls (n=62) that were not reported to have experienced TIPN. We retained for analysis rare variants with a minor allele frequency <3% and which were predicted to be deleterious by protein prediction programs. 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 TIPN. Results Five genes had a p-value < 10−4 for grade 3-4 TIPN analysis and three genes had a p-value < 10−4 for the grade 2-4 TIPN analysis. For the grade 3-4 TIPN analysis, SET binding factor 2 (SBF2) was significantly associated with TIPN (p-value=4.35 x10−6). Five variants were predicted to be deleterious in SBF2. Inherited mutations in SBF2 have previously been associated with autosomal recessive, Type 4B2 Charcot-Marie-Tooth (CMT) disease. Conclusion Rare variants in SBF2, a CMT gene, predict an increased risk of TIPN in AA patients receiving paclitaxel.

An ERα/modulator regulatory network in the breast cancer cells

Estrogens control multiple functions of hormone-responsive breast cancer (BC) cells [1]. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer [2]. However, ERα requires distinct co-regulator complex or modulators for efficient transcriptional regulation. To have insight into the regulatory network of ERα and discover the novel modulators of ERα which acted by distinct mechanisms, we proposed an analytical method based on a linear regression model to identify translational modulators and the relationship between genes for network. To comprehend the network associated with ERα, a dynamic gene expression profile and ChIP-Seq data shown to characterize the breast cancer cell response to estrogens are utilized. The role of modulators within molecular mechanism can be learned from the exploration of these two data sets. Based on the active or repressive function of the ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on the ERα, the ERα/modulator/target relationships were categorized into 27 classes.