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Showing papers by "Jennifer M. Kachergus published in 2013"


Journal ArticleDOI
22 Nov 2013-PLOS ONE
TL;DR: The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transcriptome studies from FFPE material will produce reliable expression data.
Abstract: Advantages of RNA-Seq over array based platforms are quantitative gene expression and discovery of expressed single nucleotide variants (eSNVs) and fusion transcripts from a single platform, but the sensitivity for each of these characteristics is unknown. We measured gene expression in a set of manually degraded RNAs, nine pairs of matched fresh-frozen, and FFPE RNA isolated from breast tumor with the hybridization based, NanoString nCounter (226 gene panel) and with whole transcriptome RNA-Seq using RiboZeroGold ScriptSeq V2 library preparation kits. We performed correlation analyses of gene expression between samples and across platforms. We then specifically assessed whole transcriptome expression of lincRNA and discovery of eSNVs and fusion transcripts in the FFPE RNA-Seq data. For gene expression in the manually degraded samples, we observed Pearson correlations of >0.94 and >0.80 with NanoString and ScriptSeq protocols, respectively. Gene expression data for matched fresh-frozen and FFPE samples yielded mean Pearson correlations of 0.874 and 0.783 for NanoString (226 genes) and ScriptSeq whole transcriptome protocols respectively, p<2x10-16. Specifically for lincRNAs, we observed superb Pearson correlation (0.988) between matched fresh-frozen and FFPE pairs. FFPE samples across NanoString and RNA-Seq platforms gave a mean Pearson correlation of 0.838. In FFPE libraries, we detected 53.4% of high confidence SNVs and 24% of high confidence fusion transcripts. Sensitivity of fusion transcript detection was not overcome by an increase in depth of sequencing up to 3-fold (increase from ~56 to ~159 million reads). Both NanoString and ScriptSeq RNA-Seq technologies yield reliable gene expression data for degraded and FFPE material. The high degree of correlation between NanoString and RNA-Seq platforms suggests discovery based whole transcriptome studies from FFPE material will produce reliable expression data. The RiboZeroGold ScriptSeq protocol performed particularly well for lincRNA expression from FFPE libraries, but detection of eSNV and fusion transcripts was less sensitive.

52 citations


Journal ArticleDOI
01 Nov 2013-PLOS ONE
TL;DR: Genomic features from a test set of primary breast tumors are used to build an integrated transcriptome landscape model that makes relevant hypothetical predictions about the biological and/or clinical behavior of HER2-positive breast cancer and indicate that this subtype has potential for predicting outcome and for identifying novel potential therapeutic strategies.
Abstract: 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.

21 citations


Journal ArticleDOI
TL;DR: A large number of breast cancer tumors including 4 benign, 33 ER+, 26 HER2+, and 68 triple negative (TN) were constructed into tissue microarrays (TMAs) and FRA expression was analyzed by immunohistochemistry using a high affinity FRA antibody.
Abstract: 1037 Background: Folate receptor alpha (FRA the product of the FOLR1 gene) has been identified as a potential prognostic and therapeutic target in a number of cancers. A correlation has been shown ...

2 citations


Proceedings ArticleDOI
TL;DR: The nanoString platform provides reliable data from highly degraded and FFPE material and correlates with sequence analysis of both expression and copy number from NGS platforms demonstrating potential for large-scale replication studies in FFPe material.
Abstract: Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Next Generation Sequencing (NGS) technologies provide rapid genomic analyses of single nucleotide variants, RNA expression and DNA copy number. Application of these technologies to material isolated from formalin fixed paraffin embedded (FFPE) tissue and even degraded frozen material could provide powerful replication samples but remains challenging. We tested the nanoString platform to validate deep sequence analysis of gene expression and DNA copy number in degraded and FFPE material. Firstly, RNA from the Universal Human Reference RNA and a breast cancer cell line (MDA-MB-436) was artificially degraded to different degrees (RIN 1.2-6.8). We used the nanoString platform to simultaneously measure RNA expression across 226 genes in each degraded sample and the corresponding undegraded RNA. Secondly we isolated RNA and DNA from matched fresh frozen and FFPE tissues from nine breast cancer patients (3 HER2+/ER+/PR+, 2 HER2+/ER-/PR-, 2 HER2+/ER+/PR-, 2 HER2-/ER+/PR+) using the nanoString platform to compare expression and copy number across 226 and 86 genes respectively. Finally, we correlated expression and copy number data generated by nanoString with Illumina transcriptome and whole genome sequencing (WGS). NanoString log2 expression fold-change between all artificially degraded samples and their undegraded counterpart showed extremely high correlation (r2>0.91). NanoString DNA copy number between matched fresh-frozen and FFPE showed a high degree of correlation (r2=0.71). All gene amplifications with copy number ≥ 5 in DNA from fresh-frozen material (N=9) were successfully identified in DNA from FFPE material. We also observed good correlation of gene expression between whole transcriptome sequencing and the nanoString platform (r2 0.59 - 0.72) in FFPE and artificially degraded material and for DNA copy number between WGS and nanoString in DNA isolated from cancer cell lines (r2=0.96). The nanoString platform provides reliable data from highly degraded and FFPE material and correlates with sequence analysis of both expression and copy number from NGS platforms demonstrating potential for large-scale replication studies in FFPE material. Citation Format: Nadine Norton, Edith A. Perez, Yan W. Asmann, Jennifer M. Carr, Brian M. Necela, Jennifer M. Kachergus, Jin Jen, Bruce W. Eckloff, E Aubrey Thompson. Analysis of gene expression and copy number variation in breast tumors using both sequencing and hybridization-based platforms. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2005. doi:10.1158/1538-7445.AM2013-2005

1 citations