Abstract 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
RNA Sequencing Identifies Multiple Fusion Transcripts, Differentially Expressed Genes, and Reduced Expression of Immune Function Genes in BRAF (V600E) Mutant vs BRAF Wild-Type Papillary Thyroid Carcinoma
Context: The BRAF V600E mutation (BRAF-MUT) confers an aggressive phenotype in papillary thyroid carcinoma, but unidentified additional genomic abnormalities may be required for full phenotypic expression. Objective: RNA sequencing (RNA-Seq) was performed to identify genes differentially expressed between BRAF-MUT and BRAF wild-type (BRAF-WT) tumors and to correlate changes to patient clinical status. Design: BRAF-MUT and BRAF-WT tumors were identified in patients with T1N0 and T2–3N1 tumors evaluated in a referral medical center. Gene expression levels were determined (RNA-Seq) and fusion transcripts were detected. Multiplexed capture/detection and digital counting of mRNA transcripts (nCounter, NanoString Technologies) validated RNA-Seq data for immune system-related genes. Patients: BRAF-MUT patients included nine women, three men; nine were TNM stage I and three were stage III. Three (25%) had tumor infiltrating lymphocytes. BRAF-WT included five women, three men; all were stage I, and five (62.5%) had tumor infiltrating lymphocytes. Results: RNA-Seq identified 560 of 13 085 genes differentially expressed between BRAF-MUT and BRAF-WT tumors. Approximately 10% of these genes were related to MetaCore immune function pathways; 51 were underexpressed in BRAF-MUT tumors, whereas 4 (HLAG, CXCL14, TIMP1, IL1RAP) were overexpressed. The four most differentially overexpressed immune genes in BRAF-WT tumors (IL1B; CCL19; CCL21; CXCR4) correlated with lymphocyte infiltration. nCounter confirmed the RNA-Seq expression level data. Eleven different high-confidence fusion transcripts were detected (four interchromosomal; seven intrachromosomal) in 13 of 20 tumors. All in-frame fusions were validated by RT-PCR. Conclusion: BRAF-MUT papillary thyroid cancers have reduced expression of immune/inflammatory response genes compared with BRAF-WT tumors and correlate with lymphocyte infiltration. In contrast, HLA-G and CXCL14 are overexpressed in BRAF-MUT tumors. Sixty-five percent of tumors had between one and three fusion transcripts. Functional studies will be required to determine the potential role of these newly identified genomic abnormalities in contributing to the aggressiveness of BRAF-MUT and BRAF-WT tumors.
AT‐101 downregulates BCL2 and MCL1 and potentiates the cytotoxic effects of lenalidomide and dexamethasone in preclinical models of multiple myeloma and Waldenström macroglobulinaemia
SummaryMultiple myeloma, the second most common haematological malignancy in the U.S., is currently incurable. Disruption of the intrinsic apoptotic pathway by BCL2 and MCL1 upregulation is observed in >80% of myeloma cases and is associated with an aggressive clinical course. Remarkably, there is no approved drug with the ability to target BCL2 or MCL1. Thus, we investigated the anti‐tumour effects of a pan‐BCL2 inhibitor, AT‐101, which has high binding specificity for BCL2 and MCL1 in preclinical models of plasma cell cancers (Multiple myeloma and Waldenström macroglobulinaemia). Gene expression and immunoblot analysis of six plasma cell cancer models showed upregulation of BCL2 family members. AT‐101 was able to downregulate BCL2 and MCL1 in all plasma cell cancer models and induced apoptotic cell death in a caspase‐dependent manner by altering mitochondrial membrane permeability. This cytotoxic effect and BCL2 downregulation were further potentiated when AT‐101 was combined with lenalidomide/dexamethasone (LDA). NanoString nCounter mRNA quantification and Ingenuity Pathways Analysis revealed differential changes in the CCNA2, FRZB, FYN, IRF1, PTPN11 genes in LDA‐treated cells. In summary, we describe for the first time the cellular and molecular events associated with the use of AT‐101 in combination with lenalidomide/dexamethasone in preclinical models of plasma cell malignancy.
Abstract 4926: Modeling the transcriptome landscape of HER2+ breast cancer
Abstract Motivation: Overexpression of HER2 (the product of the ERBB2 gene) occurs in about 15% of all breast tumors. We have undertaken to use next generation transcriptome sequencing technology to identify genomic features that are unique to HER2+ tumors. Interactome mapping was then used to integrate the genes associated with these features into a transcriptome landscape model, with a view towards identifying nodes of interaction that might be targeted in HER2+ tumors. Methods: We performed 50nt paired-end RNA-sequencing for 24 breast tumors: 8 each HER2+, ER+, triple negatives (TN). In addition to breast adenocarcinomas, we also sequenced 8 early passage non-transformed HMEC cell lines as normal controls. Reads from RNA sequencing were aligned to the genome and exon junctions using TopHat software. Gene counts were summarized and annotations were performed using our in-house programs. Tukey's test was used to obtain genes or transcripts that are specific to HER2 tumor group compared to other tumors/normal. A combination of bioinformatics softwares and algorithms were used to identify SNVs. Results: Only 13527 genes with median gene count greater than 16 reads in at least one of the 4 groups were considered for differential gene expression and splicing analysis. Some 696 genes were differentially expressed in HER2+ tumors compared to ER+, TN tumors and HMECs. We identified 272 alternately spliced transcripts for which the HER2+ tumors exhibited a mean transcript expression ratio significantly different from the means of other tumor groups. We also identified 4735 expressed single nucleotide variants that are uniquely associated with HER2+ tumors compared to other tumors/normal groups. Among these 3579/4735 sequence polymorphisms were not present in the 1000 genome germline sequence database or in the dbSNP132 database of naturally occurring germline polymorphisms. Integration of all the genes obtained from genomic feature analyses (differential expression, alternative splicing, single nucleotide variance) has been carried out to indentify biological processes that are specific to the HER2+ tumor subtype. Key nodes and pathways that are specific to HER2+ tumors will be evaluated for association with clinical outcome in a large series of patients who have received HER2-targeted therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4926. doi:1538-7445.AM2012-4926
Abstract 4975: Next generation sequencing reveals a connection between KRAS mutation and the NFkB pathway in lung adenocarcinoma samples
Abstract Motivation: KRAS is commonly mutated in a variety of cancers including lung cancer. The KRAS gene is frequently mutated at codons 12 and 13 in lung adenocarcinomas in patients with a history of smoking. Tumors harboring an activating KRAS mutation are aggressive and are often resistant to available therapies. In the present study, we set out to identify pathways that are specifically altered in lung cancer patients whose tumors harbor a KRAS mutation using next generation sequencing technology. Methods: We performed 50nt paired-end RNA-sequencing in 15 lung adenocarcinoma samples (8 and 7 samples with and without KRAS mutation). Reads were aligned to genome and exon junctions using Illumina's alignment tool ELAND_RNA. CASAVA and Genome Studio data analysis software were used to obtain read counts for genes, exons and exon junctions. We applied a variety of computational methods (Casper R package, Bowtie, TopHat) and softwares (Partek, R statistical software, JMP, Ingenuity Pathway Anlaysis, DAVID) to carry out our analyses. Results: Differential gene expression and splicing analysis were performed between the two groups. We identified 115 genes that were differentially expressed and 112 genes that consist of splicing variants with at least 2 fold changes and p-value < 0.01. We randomly selected 6/15 samples and performed real-time qRT-PCR for 6 differentially expressed genes. Significant correlations were observed ranging from 0.44 to 0.83, when qRT-PCR results were compared with RNA-sequencing expression data. Pathway analysis with 115 differentially expressed genes and 112 splicing variants revealed that the most significant pathway is composed entirely of NFκB focus genes, suggesting that there is a direct connection between oncogenic KRAS and activation of the NFκB signaling pathway. Conclusions: NFκB has been implicated in KRas-mediated formation of early stage lung adenomas in the LSL-Kas mouse model. Our data indicate that this connection also occurs in human lung cancer and establish NFκB activation as a key manifestation of KRAS mutation in human lung cancer. Hence drugs targeting NFκB and NFκB related genes may potentially be helpful for the treatment of patients with oncogenic KRAS mutations. (Supported in part by grants from the 26.2 with Donna Foundation and the Florida Department of Health Bankhead/Coley program.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4975. doi:10.1158/1538-7445.AM2011-4975
Abstract 4908: Deep sequence analysis of the relationship between gene expression, CpG island methylation, and gene copy number in breast cancer cells
Abstract Background: Estrogen receptor (ER) expression in breast caner is an important biomarker for targeted therapy and outcome prediction. Nevertheless, the molecular mechanism that controls the phenotypic difference is little known. We used deep sequence technology to profile the transcriptome, gene copy number, and CpG island methylation simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in ER+ and ER- breast cancer. Materials and methods: Total mRNA sequence (mRNA-seq), gene copy number (DNA-seq), and genomic CpG island methylation (Methyl-seq) were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome (hg18) to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands; differentially expressed genes between ER+ and ER- cell lines were selected and then correlated with methylation status of these genes’ CpG islands within 5kb of transcript start or copy number changes. The genes that appeared controlled by methylation or copy number changes in cell lines were further evaluated for their expression in the dataset of 129 primary breast tumors. Results: ER+ breast cancer cells had very different gene expression pattern from ER- cancer cells. The two cell line types formed two distinct clusters in unsupervised cluster and 1,873 genes were differentially expressed by moderated t statistics. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5’ end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. Eighty nine of these 149 genes were also differentially expressed in the primary tumor samples and 84 of them were consistent with cell line gene expression and methylation data. The set of 149 genes were significantly enriched in the ER+ tumors by Gene Set Enrichment Analysis. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; however, only 9 of these genes were overexpressed in ER+ tumors. Many of the methylation or CNA affected genes were functionally significant and some are known to be associated with breast cancer outcome such as GATA3 and LYN. Conclusions: A global pattern of differential CpG island methylation influences expression of a cohort of genes that contribute to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion in defining the transcriptome landscape of ER+ and ER- cells appears to more modest, although several potentially significant genes appear to be globally regulated by copy number aberrations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4908. doi:10.1158/1538-7445.AM2011-4908
Abstract LB-276: Fusion transcripts in breast cancer cell lines and tumors
Abstract The role of fusion gene transcripts such as BRC-ABL1 has been long appreciated in hematopoietic malignancies. Recent evidence from next generation sequencing projects has suggested that gene fusion events and the resultant chimaeric transcripts may be expressed in solid tumors. We have developed a novel bioinformatics analytical pipeline to detect fusion gene transcripts from paired-end mRNA-seq data. The bioinformatics tool used for fusion transcript discovery employs multiple steps of false positive filtering and nominates the fusion transcript candidates with high confidence (approaching 100%). The screening and validation of the fusion candidates were quickly carried out using the recommended primer design regions as one of the outputs of the SnowShoes-FD pipeline. This pipeline was used to analyze the transcriptome of 22 breast cancer cell lines and 9 non-transformed breast cell populations. Fifty-four fusion candidates were nominated, all of which were validated using reverse transcription PCR and Sanger sequencing. Five fusion products were predicted to have a second fusion junction point between two fusion partners. These 54 fusion transcripts consist of 103 partner genes that are involved in cell cycle and/or nuclear receptor signaling. No fusion transcripts were identified from the non-transformed breast cell lines. We subsequently analyzed a panel of primary breast tumors, 8 each HER2+, triple negative, and ER+. Fifteen novel fusion transcript candidates have been nominated. Validation and functional analysis of these candidates is in progress. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-276. doi:10.1158/1538-7445.AM2011-LB-276
Detection of Redundant Fusion Transcripts as Biomarkers or Disease-Specific Therapeutic Targets in Breast Cancer