Allele-specific disparity in breast cancer

Background

Molecular alterations critical to development of cancer include mutations, copy number alterations (amplifications and deletions) as well as genomic rearrangements resulting in gene fusions. Massively parallel next generation sequencing, which enables the discovery of such changes, uses considerable quantities of genomic DNA (> 5 ug), a serious limitation in ever smaller clinical samples. However, a commonly available microarray platforms such as array comparative genomic hybridization (array CGH) allows the characterization of gene copy number at a single gene resolution using much smaller amounts of genomic DNA. In this study we evaluate the sensitivity of ultra-dense array CGH platforms developed by Agilent, especially that of the 1 million probe array (1 M array), and their application when whole genome amplification is required because of limited sample quantities.

Methods

We performed array CGH on whole genome amplified and not amplified genomic DNA from MCF-7 breast cancer cells, using 244 K and 1 M Agilent arrays. The ADM-2 algorithm was used to identify micro-copy number alterations that measured less than 1 Mb in genomic length.

Results

DNA from MCF-7 breast cancer cells was analyzed for micro-copy number alterations, defined as measuring less than 1 Mb in genomic length. The 4-fold extra resolution of the 1 M array platform relative to the less dense 244 K array platform, led to the improved detection of copy number variations (CNVs) and micro-CNAs. The identification of intra-genic breakpoints in areas of DNA copy number gain signaled the possible presence of gene fusion events. However, the ultra-dense platforms, especially the densest 1 M array, detect artifacts inherent to whole genome amplification and should be used only with non-amplified DNA samples.

Conclusions

This is a first report using 1 M array CGH for the discovery of cancer genes and biomarkers. We show the remarkable capacity of this technology to discover CNVs, micro-copy number alterations and even gene fusions. However, these platforms require excellent genomic DNA quality and do not tolerate relatively small imperfections related to the whole genome amplification.     

Changes in gene expression during the development of mammary tumors in MMTV-Wnt-1 transgenic mice

Background

In human breast cancer normal mammary cells typically develop into hyperplasia, ductal carcinoma in situ, invasive cancer, and metastasis. The changes in gene expression associated with this stepwise progression are unclear. Mice transgenic for mouse mammary tumor virus (MMTV)-Wnt-1 exhibit discrete steps of mammary tumorigenesis, including hyperplasia, invasive ductal carcinoma, and distant metastasis. These mice might therefore be useful models for discovering changes in gene expression during cancer development.

Results

We used cDNA microarrays to determine the expression profiles of five normal mammary glands, seven hyperplastic mammary glands and 23 mammary tumors from MMTV-Wnt-1 transgenic mice, and 12 mammary tumors from MMTV-Neu transgenic mice. Adipose tissues were used to control for fat cells in the vicinity of the mammary glands. In these analyses, we found that the progression of normal virgin mammary glands to hyperplastic tissues and to mammary tumors is accompanied by differences in the expression of several hundred genes at each step. Some of these differences appear to be unique to the effects of Wnt signaling; others seem to be common to tumors induced by both Neu and Wnt-1 oncogenes.

Conclusion

We described gene-expression patterns associated with breast-cancer development in mice, and identified genes that may be significant targets for oncogenic events. The expression data developed provide a resource for illuminating the molecular mechanisms involved in breast cancer development, especially through the identification of genes that are critical in cancer initiation and progression.     

A one-step cloning method for the construction of somatic cell gene targeting vectors: application to production of human knockout cell lines

Background

To facilitate the screening of large quantities of new antimicrobial peptides (AMPs), we describe a cost-effective method for high throughput prokaryotic expression of AMPs. EDDIE, an autoproteolytic mutant of the N-terminal autoprotease, Npro, from classical swine fever virus, was selected as a fusion protein partner. The expression system was used for high-level expression of six antimicrobial peptides with different sizes: Bombinin-like peptide 7, Temporin G, hexapeptide, Combi-1, human Histatin 9, and human Histatin 6. These expressed AMPs were purified and evaluated for antimicrobial activity.

Results

Two or four primers were used to synthesize each AMP gene in a single step PCR. Each synthetic gene was then cloned into the pET30a/His-EDDIE-GFP vector via an in vivo recombination strategy. Each AMP was then expressed as an Npro fusion protein in Escherichia coli. The expressed fusion proteins existed as inclusion bodies in the cytoplasm and the expression levels of the six AMPs reached up to 40% of the total cell protein content. On in vitro refolding, the fusion AMPs was released from the C-terminal end of the autoprotease by self-cleavage, leaving AMPs with an authentic N terminus. The released fusion partner was easily purified by Ni-NTA chromatography. All recombinant AMPs displayed expected antimicrobial activity against E. coli, Micrococcus luteus and S. cerevisia.

Conclusions

The method described in this report allows the fast synthesis of genes that are optimized for over-expression in E. coli and for the production of sufficiently large amounts of peptides for functional and structural characterization. The Npro partner system, without the need for chemical or enzymatic removal of the fusion tag, is a low-cost, efficient way of producing AMPs for characterization. The cloning method, combined with bioinformatic analyses from genome and EST sequence data, will also be useful for screening new AMPs. Plasmid pET30a/His-EDDIE-GFP also provides green/white colony selection for high-throughput recombinant AMP cloning.     

The CAG repeat polymorphism of the androgen receptor gene and breast cancer

Background

Genetic variants in hormone receptor genes may be crucial predisposing factors for breast cancer, and microsatellites in the androgen receptor gene (AR) have been suggested to play a role. The aim of the study was to determine the association between the length of the CAG repeats in the AR gene and the development of breast cancer. Methodology: In total, 75 breast cancer cases and 50 healthy controls were analyzed for CAG repeats in the AR gene by polymerase chain reaction and the GeneScan/Genotyping technique.

Results

CAG repeat genotypes and alleles distribution were found to be significantly different between breast cancer patients and controls (P < 0.05). While the presence of CAG repeats shorter than 22 (classified as short, S) increases the risk of breast cancer, the risk is reduced by the presence of CAG repeats longer than 22. In the group of patients with breast cancer, a high tumor stage was found to have a significant association with genotype S/S of CAG repeats in the AR gene.

Conclusion

Our results suggest that the length of CAG repeats in the androgen receptor gene is associated with the risk of developing breast cancer.     

Mammalian tissues defective in nonsense-mediated mRNA decay display highly aberrant splicing patterns

Background

Nonsense-mediated mRNA decay (NMD) affects the outcome of alternative splicing by degrading mRNA isoforms with premature termination codons. Splicing regulators constitute important NMD targets; however, the extent to which loss of NMD causes extensive deregulation of alternative splicing has not previously been assayed in a global, unbiased manner. Here, we combine mouse genetics and RNA-seq to provide the first in vivo analysis of the global impact of NMD on splicing patterns in two primary mouse tissues ablated for the NMD factor UPF2.

Results

We developed a bioinformatic pipeline that maps RNA-seq data to a combinatorial exon database, predicts NMD-susceptibility for mRNA isoforms and calculates the distribution of major splice isoform classes. We present a catalog of NMD-regulated alternative splicing events, showing that isoforms of 30% of all expressed genes are upregulated in NMD-deficient cells and that NMD targets all major splicing classes. Importantly, NMD-dependent effects are not restricted to premature termination codon+ isoforms but also involve an abundance of splicing events that do not generate premature termination codons. Supporting their functional importance, the latter events are associated with high intronic conservation.

Conclusions

Our data demonstrate that NMD regulates alternative splicing outcomes through an intricate web of splicing regulators and that its loss leads to the deregulation of a panoply of splicing events, providing novel insights into its role in core- and tissue-specific regulation of gene expression. Thus, our study extends the importance of NMD from an mRNA quality pathway to a regulator of several layers of gene expression.     

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

Background

Copy number variants (CNVs), including deletions, amplifications, and other rearrangements, are common in human and cancer genomes. Copy number data from array comparative genome hybridization (aCGH) and next-generation DNA sequencing is widely used to measure copy number variants. Comparison of copy number data from multiple individuals reveals recurrent variants. Typically, the interior of a recurrent CNV is examined for genes or other loci associated with a phenotype. However, in some cases, such as gene truncations and fusion genes, the target of variant lies at the boundary of the variant.

Results

We introduce Neighborhood Breakpoint Conservation (NBC), an algorithm for identifying rearrangement breakpoints that are highly conserved at the same locus in multiple individuals. NBC detects recurrent breakpoints at varying levels of resolution, including breakpoints whose location is exactly conserved and breakpoints whose location varies within a gene. NBC also identifies pairs of recurrent breakpoints such as those that result from fusion genes. We apply NBC to aCGH data from 36 primary prostate tumors and identify 12 novel rearrangements, one of which is the well-known TMPRSS2-ERG fusion gene. We also apply NBC to 227 glioblastoma tumors and predict 93 novel rearrangements which we further classify as gene truncations, germline structural variants, and fusion genes. A number of these variants involve the protein phosphatase PTPN12 suggesting that deregulation of PTPN12, via a variety of rearrangements, is common in glioblastoma.

Conclusions

We demonstrate that NBC is useful for detection of recurrent breakpoints resulting from copy number variants or other structural variants, and in particular identifies recurrent breakpoints that result in gene truncations or fusion genes. Software is available at http://http.//cs.brown.edu/people/braphael/software.html.     

Exploration of the gene fusion landscape of glioblastoma using transcriptome sequencing and copy number data

Background

RNA-seq has spurred important gene fusion discoveries in a number of different cancers, including lung, prostate, breast, brain, thyroid and bladder carcinomas. Gene fusion discovery can potentially lead to the development of novel treatments that target the underlying genetic abnormalities.

Results

In this study, we provide comprehensive view of gene fusion landscape in 185 glioblastoma multiforme patients from two independent cohorts. Fusions occur in approximately 30-50% of GBM patient samples. In the Ivy Center cohort of 24 patients, 33% of samples harbored fusions that were validated by qPCR and Sanger sequencing. We were able to identify high-confidence gene fusions from RNA-seq data in 53% of the samples in a TCGA cohort of 161 patients. We identified 13 cases (8%) with fusions retaining a tyrosine kinase domain in the TCGA cohort and one case in the Ivy Center cohort. Ours is the first study to describe recurrent fusions involving non-coding genes. Genomic locations 7p11 and 12q14-15 harbor majority of the fusions. Fusions on 7p11 are formed in focally amplified EGFR locus whereas 12q14-15 fusions are formed by complex genomic rearrangements. All the fusions detected in this study can be further visualized and analyzed using our website: http://ivygap.swedish.org/fusions.

Conclusions

Our study highlights the prevalence of gene fusions as one of the major genomic abnormalities in GBM. The majority of the fusions are private fusions, and a minority of these recur with low frequency. A small subset of patients with fusions of receptor tyrosine kinases can benefit from existing FDA approved drugs and drugs available in various clinical trials. Due to the low frequency and rarity of clinically relevant fusions, RNA-seq of GBM patient samples will be a vital tool for the identification of patient-specific fusions that can drive personalized therapy.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-818) contains supplementary material, which is available to authorized users.     

Expression analyses of nuclear receptor genes in breast cancer cell lines exposed to soy phytoestrogens after BRCA2 knockdown by TaqMan Low-Density Array (TLDA)

Background

Most of breast cancers are considered sporadic and modulation of the two major genes BRCA1 and BRCA2 expressions caused by tissue-specific somatic mutations lead to this pathology. The nutritional intake of phytoestrogens seems to reduce the risk of breast cancer and investigation of their potential as anticancer agents has increased. However, the possible mechanisms and signalling pathways of phytoestrogen action in breast cancer prevention remains unknown.

Results

Using Taqman Low Density Array technology, we investigated the BRCA2 loss of function role in sporadic breast cancers and the links existing with soy isoflavones on a panel of nuclear receptor expression. Human breast cell lines (MCF-7, MDA-MB-231, and MCF-10a) were transfected by BRCA2-siRNA and treated with genistein (18.5 μM) or daidzein (78.5 μM) for 72 h. Generating the transitory knockdown of BRCA2 oncosuppressor, we observed different modulations in several nuclear receptor genes such as ER, RAR and RXR, as well as PPARs and VDR according to the studied breast cell line. Additional isoflavone treatments showed different nuclear receptor gene modulation profiles.

Conclusion

Our results seemed to implicate the oncosuppressor BRCA2 and the phytoestrogen pathways in different nuclear gene expressions via an ER-independent manner.     

A normalization strategy for comparing tag count data

Background

High-throughput sequencing, such as ribonucleic acid sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) analyses, enables various features of organisms to be compared through tag counts. Recent studies have demonstrated that the normalization step for RNA-seq data is critical for a more accurate subsequent analysis of differential gene expression. Development of a more robust normalization method is desirable for identifying the true difference in tag count data.

Results

We describe a strategy for normalizing tag count data, focusing on RNA-seq. The key concept is to remove data assigned as potential differentially expressed genes (DEGs) before calculating the normalization factor. Several R packages for identifying DEGs are currently available, and each package uses its own normalization method and gene ranking algorithm. We compared a total of eight package combinations: four R packages (edgeR, DESeq, baySeq, and NBPSeq) with their default normalization settings and with our normalization strategy. Many synthetic datasets under various scenarios were evaluated on the basis of the area under the curve (AUC) as a measure for both sensitivity and specificity. We found that packages using our strategy in the data normalization step overall performed well. This result was also observed for a real experimental dataset.

Conclusion

Our results showed that the elimination of potential DEGs is essential for more accurate normalization of RNA-seq data. The concept of this normalization strategy can widely be applied to other types of tag count data and to microarray data.     

An integrated approach of bioinformatic prediction and in vitro analysis identified that miR-34a targets <Emphasis Type="Italic">MET</Emphasis> and <Emphasis Type="Italic">AXL</Emphasis> in triple-negative breast cancer

Background

Breast cancer is the most prevalent cancer among women, and AXL and MET are the key genes in the PI3K/AKT/mTOR pathway as critical elements in proliferation and invasion of cancer cells. MicroRNAs (miRNAs) are small non-coding RNAs regulating the expression of genes.

Methods

Bioinformatic approaches were used to find a miRNA that simultaneously targets both AXL and MET 3′-UTRs. The expression of target miRNA was evaluated in triple-negative (MDA-MB-231) and HER2-overexpressing (SK-BR-3) breast cancer cell lines as well as normal breast cells, MCF-10A, using quantitative real-time PCR. Then, the miRNA was overexpressed in normal and cancer cell lines using a lentiviral vector system. Afterwards, effects of overexpressed miRNA on the expression of AXL and MET genes were evaluated using quantitative real-time PCR.

Results

By applying bioinformatic software and programs, miRNAs that target the 3′-UTR of both AXL and MET mRNAs were determined, and according to the scores, miR-34a was selected for further analyses. The expression level of miR-34a in MDA-MB-231 and SK-BR-3 was lower than that of MCF-10A. Furthermore, AXL and MET expression in SK-BR-3 and MDA-MB-231 was lower and higher, respectively, than that of MCF-10A. After miR-34a overexpression, MET and AXL were downregulated in MDA-MB-231. In addition, MET was downregulated in SK-BR-3, while AXL was upregulated in this cell line.

Conclusions

These findings may indicate that miR-34a is an oncogenic miRNA, downregulated in the distinct breast cancer subtypes. It also targets MET and AXL 3′-UTRs in triple-negative breast cancer. Therefore, it can be considered as a therapeutic target in this type of breast cancer.

     

Quantifying and resolving multiple vector transformants in S. cerevisiae plasmid libraries

Background

Two sequential enzymes in the production of sialic acids, N-acetyl-D-glucosamine 2-epimerase (GlcNAc 2-epimerase) and N-acetyl-D-neuraminic acid aldolase (Neu5Ac aldolase), were overexpressed as double-tagged gene fusions. Both were tagged with glutathione S-transferase (GST) at the N-terminus, but at the C-terminus, one was tagged with five contiguous aspartate residues (5D), and the other with five contiguous arginine residues (5R).

Results

Both fusion proteins were overexpressed in Escherichia coli and retained enzymatic activity. The fusions were designed so their surfaces were charged under enzyme reaction conditions, which allowed isolation and immobilization in a single step, through a simple capture with either an anionic or a cationic exchanger (Sepharose Q or Sepharose SP) that electrostatically bound the 5D or 5R tag. The introduction of double tags only marginally altered the affinity of the enzymes for their substrates, and the double-tagged proteins were enzymatically active in both soluble and immobilized forms. Combined use of the fusion proteins led to the production of N-acetyl-D-neuraminic acid (Neu5Ac) from N-acetyl-D-glucosamine (GlcNAc).

Conclusion

Double-tagged gene fusions were overexpressed to yield two enzymes that perform sequential steps in sialic acid synthesis. The proteins were easily immobilized via ionic tags onto ionic exchange resins and could thus be purified by direct capture from crude protein extracts. The immobilized, double-tagged proteins were effective for one-pot enzymatic production of sialic acid.     

Phenylhexyl isothiocyanate has dual function as histone deacetylase inhibitor and hypomethylating agent and can inhibit myeloma cell growth by targeting critical pathways

Background

Amplification of the ERBB2 (Her-2/neu) oncogene, which occurs in approximately 25% of breast carcinomas, is a known negative prognostic factor. Available data indicate that a variable number of nearby genes on chromosome 17q may be co-amplified or deleted, forming a continuous amplicon of variable size. In approximately 25% of these patients, the amplicon extends to the gene for topoisomerase II alpha (TOP2A), a target for anthracyclines. We sought to understand the significance of these associated genomic changes for breast cancer prognosis and predicting response to therapy.

Methods and patients

Archival tissue samples from 63 breast cancer patients with ERBB2 amplification, stages 0–IV, were previously analyzed with FISH probes for genes located near ERBB2. In the present study, the clinical outcome data were determined for all patients presenting at stages I–III for whom adequate clinical follow up was available.

Results

Four amplicon patterns (Classes) were identified. These were significantly associated with the clinical outcome, specifically, recurrence of breast cancer. The Amplicon class IV with deleted TOP2A had 67% (6/9) cases with recurrence, whereas the other three classes combined had only 12% (3/25) cases (p-value = 0.004) at the time of last follow-up. TOP2A deletion was also significantly associated with time to recurrence (p-value = 0.0002). After adjusting for age in Cox regression analysis, the association between TOP2A deletion and time to recurrence remains strongly significant (p-value = 0.002) whereas the association with survival is marginally significant (p-value = 0.06).

Conclusion

TOP2A deletion is associated with poor prognosis in ERBB2-amplified breast carcinomas. Clarification of the mechanism of this association will require additional study.     

Fusion Peptides from Oncogenic Chimeric Proteins as Putative Specific Biomarkers of Cancer

Chromosomal translocations encoding chimeric fusion proteins constitute one of the most common mechanisms underlying oncogenic transformation in human cancer. Fusion peptides resulting from such oncogenic chimeric fusions, though unique to specific cancer subtypes, are unexplored as cancer biomarkers. Here we show, using an approach termed fusion peptide multiple reaction monitoring mass spectrometry, the direct identification of different cancer-specific fusion peptides arising from protein chimeras that are generated from the juxtaposition of heterologous genes fused by recurrent chromosomal translocations. Using fusion peptide multiple reaction monitoring mass spectrometry in a clinically relevant scenario, we demonstrate the specific, sensitive, and unambiguous detection of a specific diagnostic fusion peptide in clinical samples of anaplastic large cell lymphoma, but not in a diverse array of benign lymph nodes or other forms of primary malignant lymphomas and cancer-derived cell lines. Our studies highlight the utility of fusion peptides as cancer biomarkers and carry broad implications for the use of protein biomarkers in cancer detection and monitoring.A cancer biomarker is generally an analyte that indicates the presence or extent of a specific form of cancer. A useful cancer biomarker should reliably distinguish between benign and malignant states and, ideally, distinguish one form of cancer from other, related differential diagnoses. Many human cancers contain recurrent chromosomal translocations and chimeric gene fusions that could be exploited as cancer-specific biomarkers (1, 2). Indeed, several structural aberrations are specific and pathognomonic for distinct types of cancer (3). Moreover, as new molecular therapies increasingly target oncogenic fusion proteins, the detection and quantitation of these proteins may also provide important, direct therapeutic guidance (4–6). Although genomic techniques targeting fusion partner genes are routinely used for diagnosing cancers, fusion peptides resulting from oncogenic chimeric fusions are unexplored as biomarker candidates for cancer detection. The specificity and qualitative/binary nature (i.e. present or absent) of fusion proteins in specific tumor types make these analytes attractive candidates for cancer detection.Advances in mass spectrometry permit the direct and unbiased interrogation of proteins and peptides in complex mixtures with unambiguous identification of specific proteins (7, 8). Multiple reaction monitoring (MRM)¹ via mass spectrometry is a powerful approach for the targeted detection of biomarker candidates in a complex background (9). MRM involves the focused interrogation of specific m/z windows for the precursor analyte, as well as selected fragment ions, following MS/MS analysis. By focusing only on specific m/z windows, one increases the sensitivity of detection dramatically, and within the context of a complex mixture there is the potential for a reproducible dynamic range spanning ≥4 orders of magnitude (10, 11).Despite their enormous potential as biomarkers, fusion peptides resulting from oncogenic chimeric fusions have not been exploited for the specific and sensitive detection of cancer. Here we demonstrate the detection of unique fusion peptides that are specific for various forms of cancer. To demonstrate applicability in a clinically relevant scenario, we show the utility of our MRM-based MS approach combined with an innovative double stable isotope strategy for the identification of nucleophosmin-anaplastic lymphoma kinase (NPM-ALK) fusion peptide arising from the corresponding chimeric fusion protein for the identification of NPM-ALK-positive anaplastic large cell lymphoma (ALCL). We show the exquisite specificity and sensitivity of this fusion peptide (FP) MRM approach and the extraordinary accuracy of its application with clinical biopsy material.