DEVELOPMENT AND VALIDATION OF UV SPECTROMETRIC METHOD FOR QUANTITATIVE DETERMINATION OF ULIPRISTAL ACETATE

Objective: To develop and validate UV spectrometric method for quantitative determination of ulipristal acetate.Methods: The solvent selected was methanol and detection was carried out at 302 nm.Results: Linearity of the proposed method was found to be between 5–20 μg/ml. LOD and LOQ were found to be 0.0062 μg/ml and 0.0187 μg/ml, respectively. The % recovery of the proposed method was found to be 98.83 %-100.32 %. The method was found to be precise as the values of % RSD obtained for both intraday and interday, precision studies were found to be<2.0 %. The method was robust and can be useful for routine analysis of formulations containing ulipristal acetate.Conclusion: The developed method was found to be simple, sensitive, linear, accurate, precise and robust. The developed and validated method can be used for quantitative determination of ulipristal acetate in bulk drugs and dosage form.Â

Epigenomic profiling of neuroblastoma cell lines.

Understanding the aberrant transcriptional landscape of neuroblastoma is necessary to provide insight to the underlying influences of the initiation, progression and persistence of this developmental cancer. Here, we present chromatin immunoprecipitation sequencing (ChIP-Seq) data for the oncogenic transcription factors, MYCN and MYC, as well as regulatory histone marks H3K4me1, H3K4me3, H3K27Ac, and H3K27me3 in ten commonly used human neuroblastoma-derived cell line models. In addition, for all of the profiled cell lines we provide ATAC-Seq as a measure of open chromatin. We validate specificity of global MYCN occupancy in MYCN amplified cell lines and functional redundancy of MYC occupancy in MYCN non-amplified cell lines. Finally, we show with H3K27Ac ChIP-Seq that these cell lines retain expression of key neuroblastoma super-enhancers (SE). We anticipate this dataset, coupled with available transcriptomic profiling on the same cell lines, will enable the discovery of novel gene regulatory mechanisms in neuroblastoma

Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer

Characterizing The Gene Networks Associated With Non-Coding Elements In Pediatric Cancer Using Integrative Genomics

There is a need to better understand non-coding elements that drive pediatric cancers. Long non-coding RNAs (lncRNAs) play an important role in gene regulation and contribute to tumorigenesis; however, which lncRNAs are expressed in pediatric cancer histotypes and whether any are common drivers still remains unknown. Here, we curate RNA sequencing data for 1,044 pediatric leukemia and solid tumors and integrate paired tumor whole genome sequencing and epigenetic data in relevant cell line models to explore lncRNA expression, regulation, and association with cancer. We report a total of 2,657 robustly expressed lncRNAs across six pediatric cancers, including 1,142 exhibiting histotype-specific expression. Next, a multi-dimensional framework was applied to identify and prioritize lncRNAs impacting gene networks, which revealed that lncRNAs dysregulated in pediatric cancer are associated with proliferation, metabolism, and DNA damage hallmarks. Altogether these analyses were integrated to prioritize lncRNAs for experimental validation, and we showed that silencing of TBX2-AS1, our top-prioritized neuroblastoma-specific lncRNA, resulted in significant growth inhibition of neuroblastoma cells, confirming our computational predictions. Taken together, these data provide a comprehensive characterization of lncRNA regulation and function in pediatric cancers and pave the way for future mechanistic studies. In addition to non-coding RNA, non-coding genetic variation can also play a role in driving pediatric cancer. In a second study, we focus on understanding the impact of non-coding genetic variation in neuroblastoma susceptibility and progression. Neuroblastoma is the most common extra-cranial solid pediatric cancer. Its low somatic mutation burden is thought to be driven, in part, by germline variation. Our neuroblastoma genome wide association study (GWAS) has identified nineteen loci associated with disease and confirmed that the majority of associated variants are non-coding. We analyzed histone ChIP-seq, ATAC-seq, and high resolution promoter Capture C to prioritize variants that are likely to impact regulatory regions including promoters and enhancers. This integrative approach not only revealed new genes associated with neuroblastoma susceptibility, but also nominated several causal variants based on predicted impact on transcription factor binding and gene expression. Altogether our studies provide actionable hypotheses about how non-coding elements such as lncRNAs and common variation can driver pediatric cancer

Figure S5 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Figure S5: Characteristics of lncMod analysis and results</p

Tables S4-S6 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Table S4: Top 10 expressed lncRNAs across TARGET cancers and GTEx tissues, Table S5: Tissue specificity index (tau score) annotation per gene, Table S6: Validation of tissue specific lncRNAs based on tau score analysis in alternate NBL datasets</p

Figure S3 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Figure S3: Regions of somatic copy number aberration across cancers and genes dysregulated due to copy number</p

Tables S10-S12 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Table S10: Statistics for input and output variables of lncMod analysis (xls file), Table S11: Significantly dysregulated lncMod triplets, Table S12: lncRNA TF associations ranked by # target genes</p

Figure S2 from Integrative Genomic Analyses Identify LncRNA Regulatory Networks across Pediatric Leukemias and Solid Tumors

Figure S2: lncRNA expression varies across pediatric cancers</p