Poulami Barman

The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response

Response to treatment with selective serotonin reuptake inhibitors (SSRIs) varies considerably between patients. The International SSRI Pharmacogenomics Consortium (ISPC) was formed with the primary goal of identifying genetic variation that may contribute to response to SSRI treatment of major depressive disorder. A genome-wide association study of 4-week treatment outcomes, measured using the 17-item Hamilton Rating Scale for Depression (HRSD-17), was performed using data from 865 subjects from seven sites. The primary outcomes were percent change in HRSD-17 score and response, defined as at least 50% reduction in HRSD-17. Data from two prior studies, the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study (PGRN-AMPS) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, were used for replication, and a meta-analysis of the three studies was performed (N=2394). Although many top association signals in the ISPC analysis map to interesting candidate genes, none were significant at the genome-wide level and the associations were not replicated using PGRN-AMPS and STAR*D data. Top association results in the meta-analysis of response included single-nucleotide polymorphisms (SNPs) in the HPRTP4 (hypoxanthine phosphoribosyltransferase pseudogene 4)/VSTM5 (V-set and transmembrane domain containing 5) region, which approached genome-wide significance (P=5.03E−08) and SNPs 5’ upstream of the neuregulin-1 gene, NRG1 (P=1.20E−06). NRG1 is involved in many aspects of brain development, including neuronal maturation and variations in this gene have been shown to be associated with increased risk for mental disorders, particularly schizophrenia. Replication and functional studies of these findings are warranted.

Measure transcript integrity using RNA-seq data

BackgroundStored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substantially degraded. RNA degradation distorts the RNA-seq read coverage in a gene-specific manner, and has profound influences on whole-genome gene expression profiling.ResultWe developed the transcript integrity number (TIN) to measure RNA degradation. When applied to 3 independent RNA-seq datasets, we demonstrated TIN is a reliable and sensitive measure of the RNA degradation at both transcript and sample level. Through comparing 10 prostate cancer clinical samples with lower RNA integrity to 10 samples with higher RNA quality, we demonstrated that calibrating gene expression counts with TIN scores could effectively neutralize RNA degradation effects by reducing false positives and recovering biologically meaningful pathways. When further evaluating the performance of TIN correction using spike-in transcripts in RNA-seq data generated from the Sequencing Quality Control consortium, we found TIN adjustment had better control of false positives and false negatives (sensitivity = 0.89, specificity = 0.91, accuracy = 0.90), as compared to gene expression analysis results without TIN correction (sensitivity = 0.98, specificity = 0.50, accuracy = 0.86).ConclusionTIN is a reliable measurement of RNA integrity and a valuable approach used to neutralize in vitro RNA degradation effect and improve differential gene expression analysis.

Estrogens and their precursors in postmenopausal women with early breast cancer receiving anastrozole.

PURPOSE We determined hormone concentrations (estradiol [E2], estrone [E1], estrone conjugates [E1-C], androstenedione [A], testosterone [T]) before and on anastrozole therapy where we also determined plasma concentrations of anastrozole and its metabolites. EXPERIMENTAL Postmenopausal women who were to receive adjuvant anastrozole for resected early breast cancer were studied. Pretreatment, blood samples were obtained for the acquisition of DNA and for plasma hormone measurements (E2, E1, E1-C, A, and T). A second blood draw was obtained at least 4 weeks after starting anastrozole for hormone, anastrozole and metabolite measurements. For hormone assays, a validated bioanalytical method using gas chromatography negative ionization tandem mass spectrometry was used. Anastrozole and metabolite assays involved extraction of plasma followed by LC/MS/MS assays. RESULTS 649 patients were evaluable. Pretreatment and during anastrozole, there was large inter-individual variability in E2, E1, and E1-C as well as anastrozole and anastrozole metabolite concentrations. E2 and E1 concentrations were below the lower limits of quantitation in 79% and 70%, respectively, of patients on anastrozole therapy, but those with reliable concentrations had a broad range (0.627-234.0 pg/mL, 1.562-183.2 pg/mL, respectively). Considering E2, 8.9% had the same or higher concentration relative to baseline while on anastrozole, documented by the presence of drug. CONCLUSIONS We demonstrated large inter-individual variability in anastrozole and anastrozole metabolite concentrations as well as E1, E2, E1-C, A, and T concentrations before and while on anastrozole. These findings suggest that the standard 1mg daily dose of anastrozole is not optimal for a substantial proportion of women with breast cancer.

Frailty Assessment in Advanced Heart Failure

BACKGROUND Several studies have recently demonstrated the value of frailty assessment in a general heart failure (HF) population; however, it is unknown whether these findings are also applicable in advanced HF. We investigated the utility of frailty assessment and its prognostic value in elderly patients with advanced HF. METHODS Forty consecutive elderly subjects aged ≥65 years, with left ventricular ejection fraction ≤35%, New York Heart Association class III or IV, and a 6-minute walk test <300 m were enrolled from the HF clinic at Montefiore Medical Center between October 2012 and July 2013. Subjects were assessed for frailty with the Fried Frailty Index, consisting of 5 components: hand grip strength, 15-foot walk time, weight loss, physical activity, and exhaustion. All subjects were prospectively followed for death or hospitalization. RESULTS At baseline, the mean age of the cohort was 74.9 ± 6.5 years, 58% female, left ventricular ejection fraction 25.6 ± 6.4%, 6-minute walk test 195.8 ± 74.3 m and length of follow-up 454 ± 186 days. Thirty-five percent were prefrail and 65% were frail. Frailty status was associated with the combined primary endpoint of mortality and all-cause hospitalization (hazard ratio [HR] 1.93, 95% confidence interval [CI] 1.15-3.25, P = .013). On individual analysis, frailty was associated with all-cause hospitalizations (HR 1.92, 95% CI 1.12-3.27, P = .017) and non-HF hospitalizations (HR 3.31, 95% CI 1.14- 9.6, P = .028), but was not associated with HF hospitalizations alone (HR 1.31, 95% CI 0.68-2.49, P = .380). CONCLUSIONS Frailty assessment in patients with advanced HF is feasible and provides prognostic value. These findings warrant validation in a larger cohort.

Determining the frequency of pathogenic germline variants from exome sequencing in patients with castrate-resistant prostate cancer

Objectives To determine the frequency of pathogenic inherited mutations in 157 select genes from patients with metastatic castrate-resistant prostate cancer (mCRPC). Design Observational. Setting Multisite US-based cohort. Participants Seventy-one adult male patients with histological confirmation of prostate cancer, and had progressive disease while on androgen deprivation therapy. Results Twelve patients (17.4%) showed evidence of carrying pathogenic or likely pathogenic germline variants in the ATM, ATR, BRCA2, FANCL, MSR1, MUTYH, RB1, TSHR and WRN genes. All but one patient opted in to receive clinically actionable results at the time of study initiation. We also found that pathogenic germline BRCA2 variants appear to be enriched in mCRPC compared to familial prostate cancers. Conclusions Pathogenic variants in cancer-susceptibility genes are frequently observed in patients with mCRPC. A substantial proportion of patients with mCRPC or their family members would derive clinical utility from mutation screening. Trial registration number NCT01953640; Results.

Genetic polymorphisms in the long noncoding RNA MIR2052HG offer a pharmacogenomic basis for the response of breast cancer patients to aromatase inhibitor therapy

Genetic risks in breast cancer remain only partly understood. Here, we report the results of a genome-wide association study of germline DNA from 4,658 women, including 252 women experiencing a breast cancer recurrence, who were entered on the MA.27 adjuvant trial comparing the aromatase inhibitors (AI) anastrozole and exemestane. Single-nucleotide polymorphisms (SNP) of top significance were identified in the gene encoding MIR2052HG, a long noncoding RNA of unknown function. Heterozygous or homozygous individuals for variant alleles exhibited a ∼40% or ∼63% decrease, respectively, in the hazard of breast cancer recurrence relative to homozygous wild-type individuals. Functional genomic studies in lymphoblastoid cell lines and ERα-positive breast cancer cell lines showed that expression from MIR2052HG and the ESR1 gene encoding estrogen receptor-α (ERα) was induced by estrogen and AI in a SNP-dependent manner. Variant SNP genotypes exhibited increased ERα binding to estrogen response elements, relative to wild-type genotypes, a pattern that was reversed by AI treatment. Further, variant SNPs were associated with lower expression of MIR2052HG and ERα. RNAi-mediated silencing of MIR2052HG in breast cancer cell lines decreased ERα expression, cell proliferation, and anchorage-independent colony formation. Mechanistic investigations revealed that MIR2052HG sustained ERα levels both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated, proteasome-dependent degradation of ERα. Taken together, our results define MIR2052HS as a functionally polymorphic gene that affects risks of breast cancer recurrence in women treated with AI. More broadly, our results offer a pharmacogenomic basis to understand differences in the response of breast cancer patients to AI therapy. Cancer Res; 76(23); 7012-23. ©2016 AACR.

Mutational landscapes of sequential prostate metastases and matched patient derived xenografts during enzalutamide therapy

Developing patient derived models from individual tumors that capture the biological heterogeneity and mutation landscape in advanced prostate cancer is challenging, but essential for understanding tumor progression and delivery of personalized therapy in metastatic castrate resistant prostate cancer stage. To demonstrate the feasibility of developing patient derived xenograft models in this stage, we present a case study wherein xenografts were derived from cancer metastases in a patient progressing on androgen deprivation therapy and prior to initiating pre-chemotherapy enzalutamide treatment. Tissue biopsies from a metastatic rib lesion were obtained for sequencing before and after initiating enzalutamide treatment over a twelve-week period and also implanted subcutaneously as well as under the renal capsule in immuno-deficient mice. The genome and transcriptome landscapes of xenografts and the original patient tumor tissues were compared by performing whole exome and transcriptome sequencing of the metastatic tumor tissues and the xenografts at both time points. After comparing the somatic mutations, copy number variations, gene fusions and gene expression we found that the patient’s genomic and transcriptomic alterations were preserved in the patient derived xenografts with high fidelity. These xenograft models provide an opportunity for predicting efficacy of existing and potentially novel drugs that is based on individual metastatic tumor expression signature and molecular pharmacology for delivery of precision medicine.

An integrated model of the transcriptome of HER2-positive breast cancer.

Our goal in these analyses was to use genomic features from a test set of primary breast tumors to build an integrated transcriptome landscape model that makes relevant hypothetical predictions about the biological and/or clinical behavior of HER2-positive breast cancer. We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel. These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set. The generality of the model was confirmed by the observation that several key pathways were enriched in HER2-positive TCGA breast tumors. The ability of this model to make relevant predictions about the biology of breast cancer cells was established by the observation that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset. Additional modules from the HER2 transcriptome model, including ubiquitin-mediated proteolysis, TGF-beta signaling, RHO-family GTPase signaling, and M-phase progression, were linked to response to lapatinib and paclitaxel in vitro and/or risk of relapse in the N9831 dataset. These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.

Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines

Metformin is currently considered as a promising anticancer agent in addition to its anti-diabetic effect. To better individualize metformin therapy and explore novel molecular mechanisms in cancer treatment, we conducted a pharmacogenomic study using 266 lymphoblastoid cell lines (LCLs). Metformin cytotoxicity assay was performed using the MTS assay. Genome-wide association (GWA) analyses were performed in LCLs using 1.3 million SNPs, 485k DNA methylation probes, 54k mRNA expression probe sets, and metformin cytotoxicity (IC50s). Top candidate genes were functionally validated using siRNA screening, followed by MTS assay in breast cancer cell lines. Further study of one top candidate, STUB1, was performed to elucidate the mechanisms by which STUB1 might contribute to metformin action. GWA analyses in LCLs identified 198 mRNA expression probe sets, 12 SNP loci, and 5 DNA methylation loci associated with metformin IC50 with P-values <10−4 or <10−5. Integrated SNP/methylation loci-expression-IC50 analyses found 3 SNP loci or 5 DNA methylation loci associated with metformin IC50 through trans-regulation of expression of 11 or 26 genes with P-value <10−4. Functional validation of top 61 candidate genes in 4 IPA networks indicated down regulation of 14 genes significantly altered metformin sensitivity in two breast cancer cell lines. Mechanistic studies revealed that the E3 ubiquitin ligase, STUB1, could influence metformin response by facilitating proteasome-mediated degradation of cyclin A. GWAS using a genomic data-enriched LCL model system, together with functional and mechanistic studies using cancer cell lines, help us to identify novel genetic and epigenetic biomarkers involved in metformin anticancer response.

Germline genome-wide association studies in women receiving neoadjuvant chemotherapy with or without bevacizumab

Neoadjuvant chemotherapy (NAC) for breast cancer is widely utilized, and we performed genome-wide association studies (GWAS) to determine whether germ-line genetic variability was associated with benefit in terms of pathological complete response (pCR), disease-free survival, and overall survival in patients entered on the NSABP B-40 NAC trial, wherein patients were randomized to receive, or not, bevacizumab in addition to chemotherapy. Patient DNA samples were genotyped with the Illumina OmniExpress BeadChip. Replication was attempted with genotyping data from 1398 HER2-negative patients entered on the GeparQuinto NAC study in which patients were also randomized to receive, or not, bevacizumab in addition to chemotherapy. A total of 920 women from B-40 were analyzed, and 237 patients achieved a pCR. GWAS with three phenotypes (pCR, disease-free survival, overall survival) revealed no single nucleotide polymorphisms (SNPs) that were genome-wide significant (i.e. P⩽5E−08) signals; P values for top SNPs were 2.04E−07, 5.61E−08, and 5.63E−08, respectively, and these SNPs were not significant in the GeparQuinto data. An ad-hoc GWAS was performed in the patients randomized to bevacizumab (457 patients with 128 pCR) who showed signals on chromosome 6, located within a gene, CDKAL1, that approached, but did not reach, genome-wide significance (top SNP rs7453577, P=2.97E−07). However, this finding was significant when tested in the GeparQuinto data set (P=0.04). In conclusion, we identified no SNPs significantly associated with NAC. The observation, in a hypothesis-generating GWAS, of an SNP in CDKAL1 associated with pCR in the bevacizumab arm of both B-40 and GeparQuinto requires further validation and study.