scholarly journals Comparative Transcriptomic Response Of Pancreatic And Breast Cancer Cells To Anacardic Acid Ans Olaparib

Author(s):  
Abah Moses Owoicho ◽  
Joseph Luper Tsenum ◽  
Deborah Oganya Ogenyi ◽  
Ogu Stephen ◽  
Ujah Moses Okwori

The study seeks to compare the transcriptomic response of pancreatic and breast cancer cells to Anarcadic Acid and Olaparib via the preparation of Pancreatic Cancer Cell Culture which involves the seeding of PANC-1 cells in 6-well plates (5× 105 cells per well). 24hours later, cells will be untreated or treated by 5mM anacardic acid, 2mM olaparib or a combination of anacardic acid (5mM) and olaparib (2mM) for 48hours; after which Pancreatic Cancer Cell’s mRNA Library will be Prepared and Sequenced using the Illumina TruSeq™ RNA Sample Prep Kit v2. Samples will be sequenced on the Illumina HiSeq 2500, 2× 100bp paired-end reads, to a minimum depth of 30 million reads per sample. Thereafter, the Computational Analyses of Pancreatic Cancer RNA-seq Data will be done by obtaining a total of 240 million obtained reads of high quality clean tags which will then be mapped and annotated via human reference genome using Bioconductor package biomaRt (http://www.bioconductor.org) (Durinck et al 2009). Mapped reads with mapping quality 10 or more will be defined as uniquely mapped reads and used in the downstream analyses. Biological networks and pathways related to anachardic acid, olaparib and the combination will be analyzed with Ingenuity Pathway Analysis (IPA) software (Qiagen, CA, USA). The lists of all genes identified in gene expression analysis will be uploaded into the IPA software. For the analysis of networks and pathways, the cutoff values will be set at P≤ 1× 10−5 and FC≥ |2| respectively.Validation of RNA-seq Results by qRT-PCR via the expression of mRNA which will be determined in all 4 samples using Power SYBR® Green RNA-to-CT™ 1-Step Kit (Life Technologies, CA, USA). The Western blotting for the selected proteins will be performed, as described by Yue (Yue et al 2015). Thereafter, the Breast Cancer Cell Culture will be prepared and treated. Breast Cancer Cell’s mRNA RNA-seq will be prepared. The Truseq Stranded mRNA kit (Illumina) will be used to prepare mRNA libraries from 1 µg total RNA. Libraries will be confirmed on the Agilent 2100 Bioanalyzer and quantitated using the Illumina Library Quantification Kit, ABI Prism qPCR Mix from Kapa Biosystems and the ABI7900HT real-time PCR instrument. The differential Gene Expression will be analysed RNA-seq reads will be assembled according to the hg19.gtf annotation file (downloaded from ENSEMBL) (Flicek et al 2014) using Cufflinks (version 2.2.1) (Trapnell et al 2012). For each comparison, both cufflinks assemblies shall be merged, and the resulting merged gtf file serves as the transcript input for differential gene expression analysis in Gene Ontology and KEGG pathways. For three of the comparisons, a p-value cutoff ≤0.05 shall be used to determine differential expression. In-silico pathway and network analysis of differentially expressed genes shall be performed in MetaCore version 6.27 (GeneGO, Thomson Reuters, New York, N.Y.) (Bolser et al 2012). The results obtained will be statistically analysed. The results of RT-PCR shall be normalized to expression of GAPDH using the formula 2∆ CT. One-way ANOVA shall be used for comparing treatment with the combination of anacardic acid and olaparib to the untreated control. A P value less than 0.05 will be considered statistically significant.

PLoS ONE ◽  
2012 ◽  
Vol 7 (7) ◽  
pp. e41333 ◽  
Author(s):  
Kathryn J. Huber-Keener ◽  
Xiuping Liu ◽  
Zhong Wang ◽  
Yaqun Wang ◽  
Willard Freeman ◽  
...  

2012 ◽  
Vol 30 (30_suppl) ◽  
pp. 56-56
Author(s):  
Byung-In Lee ◽  
Kahuku Oades ◽  
Lien Vo ◽  
Jerry Lee ◽  
Mark Landers ◽  
...  

56 Background: Gene expression profiling has been shown to be effective in analyzing postoperative tumor samples in various cancers. However, in analyzing small specimens such as core biopsies, the limited amount of available material makes multi-gene analyses difficult or impossible. Microarray-based analyses also provide limited dynamic range. We describe the development of targeted RNA-sequencing methodology which combines the power of a universal RNA amplification with NGS for an ultra-deep expression analysis of multiple target genes, enabling <100 ng of sample input for multi-gene analysis in a single tube format. Methods: The gene expression patterns of triple-negative breast cancer FFPE samples were analyzed using a 96-gene breast cancer biomarker panel across three different platforms: Affymetrix Human Gene ST 1.0 microarrays, a pre-developed OncoScore qRT-PCR panel, and targeted RNA-seq. For targeted RNA-seq analysis, the 96-gene panel was amplified using a universal, single-tube “XP-PCR” amplification strategy followed by sequence analysis using the Ion-Torrent Personal Genome Machine. Results: Targeted RNA-seq provided the most sensitivity in terms of detection rates with <100 ng FFPE RNA input and provides unlimited dynamic range with increased sequencing depth. Expression ratio compression issues typically associated with a high number of pre-amplification cycles in standard multiplex-primed methods were not observed here. Low expressing genes, undetectable by qRT-PCR analysis from 1,000 ng input FFPE RNA, were detected and eligible for expression analysis with a significant number of sequencing reads. Alternative transcription/splicing analysis is also possible from sequence analysis of the target transcripts using targeted RNA-seq. Conclusions: By combining universally primed pre-amplification and NGS in multi-gene expression analysis, targeted RNA-seq provides the most sensitive gene expression analysis methodology.


2018 ◽  
Vol 8 (1) ◽  
Author(s):  
David J. Schultz ◽  
Abirami Krishna ◽  
Stephany L. Vittitow ◽  
Negin Alizadeh-Rad ◽  
Penn Muluhngwi ◽  
...  

Endocrine ◽  
2013 ◽  
Vol 44 (2) ◽  
pp. 496-503 ◽  
Author(s):  
Nadine A. Binai ◽  
Gert Carra ◽  
Johannes Löwer ◽  
Roswitha Löwer ◽  
Silja Wessler

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