Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome.

BACKGROUND: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome. RESULTS: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395). CONCLUSIONS: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

Bambino: a variant detector and alignment viewer for next-generation sequencing data in the SAM/BAM format.

SUMMARY: Bambino is a variant detector and graphical alignment viewer for next-generation sequencing data in the SAM/BAM format, which is capable of pooling data from multiple source files. The variant detector takes advantage of SAM-specific annotations, and produces detailed output suitable for genotyping and identification of somatic mutations. The assembly viewer can display reads in the context of either a user-provided or automatically generated reference sequence, retrieve genome annotation features from a UCSC genome annotation database, display histograms of non-reference allele frequencies, and predict protein-coding changes caused by SNPs. AVAILABILITY: Bambino is written in platform-independent Java and available from https://cgwb.nci.nih.gov/goldenPath/bamview/documentation/index.html, along with documentation and example data. Bambino may be launched online via Java Web Start or downloaded and run locally.

Genetic variations at loci involved in the immune response are risk factors for hepatocellular carcinoma.

UNLABELLED: Primary liver cancer is the third most common cause of cancer-related death worldwide, with a rising incidence in Western countries. Little is known about the genetic etiology of this disease. To identify genetic factors associated with hepatocellular carcinoma (HCC) and liver cirrhosis (LC), we conducted a comprehensive, genome-wide variation analysis in a population of unrelated Asian individuals. Copy number variation (CNV) and single nucleotide polymorphisms (SNPs) were assayed in peripheral blood with the high-density Affymetrix SNP6.0 microarray platform. We used a two-stage discovery and replication design to control for overfitting and to validate observed results. We identified a strong association with CNV at the T-cell receptor gamma and alpha loci (P < 1 × 10(-15)) in HCC cases when contrasted with controls. This variation appears to be somatic in origin, reflecting differences between T-cell receptor processing in lymphocytes from individuals with liver disease and healthy individuals that is not attributable to chronic hepatitis virus infection. Analysis of constitutional variation identified three susceptibility loci including the class II MHC complex, whose protein products present antigen to T-cell receptors and mediate immune surveillance. Statistical analysis of biologic networks identified variation in the "antigen presentation and processing" pathway as being highly significantly associated with HCC (P = 1 × 10(-11)). SNP analysis identified two variants whose allele frequencies differ significantly between HCC and LC. One of these (P = 1.74 × 10(-12)) lies in the PTEN homolog TPTE2. CONCLUSION: Combined analysis of CNV, individual SNPs, and pathways suggest that HCC susceptibility is mediated by germline factors affecting the immune response and differences in T-cell receptor processing.

A function-blocking CD47 antibody suppresses stem cell and EGF signaling in triple-negative breast cancer.

CD47 is a signaling receptor for thrombospondin-1 and the counter-receptor for signal-regulatory protein-α (SIRPα). By inducing inhibitory SIRPα signaling, elevated CD47 expression by some cancers prevents macrophage phagocytosis. The anti-human CD47 antibody B6H12 inhibits tumor growth in several xenograft models, presumably by preventing SIRPα engagement. However, CD47 signaling in nontransformed and some malignant cells regulates self-renewal, suggesting that CD47 antibodies may therapeutically target cancer stem cells (CSCs). Treatment of MDA-MB-231 breast CSCs with B6H12 decreased proliferation and asymmetric cell division. Similar effects were observed in T47D CSCs but not in MCF7 breast carcinoma or MCF10A breast epithelial cells. Gene expression analysis in breast CSCs treated with B6H12 showed decreased expression of epidermal growth factor receptor (EGFR) and the stem cell transcription factor KLF4. EGFR and KLF4 mRNAs are known targets of microRNA-7, and B6H12 treatment correspondingly enhanced microRNA-7 expression in breast CSCs. B6H12 treatment also acutely inhibited EGF-induced EGFR tyrosine phosphorylation. Expression of B6H12-responsive genes correlated with CD47 mRNA expression in human breast cancers, suggesting that the CD47 signaling pathways identified in breast CSCs are functional in vivo. These data reveal a novel SIRPα-independent mechanism by which therapeutic CD47 antibodies could control tumor growth by autonomously forcing differentiation of CSC.

Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files.

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview. The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview.

Genome-wide transcriptional sequencing identifies novel mutations in metabolic genes in human hepatocellular carcinoma.

We report on next-generation transcriptome sequencing results of three human hepatocellular carcinoma tumor/tumor-adjacent pairs. This analysis robustly examined ∼12,000 genes for both expression differences and molecular alterations. We observed 4,513 and 1,182 genes demonstrating 2-fold or greater increase or decrease in expression relative to their normal, respectively. Network analysis of expression data identified the Aurora B signaling, FOXM1 transcription factor network and Wnt signaling pathways pairs being altered in HCC. We validated as differential gene expression findings in a large data set containing of 434 liver normal/tumor sample pairs. In addition to known driver mutations in TP53 and CTNNB1, our mutation analysis identified non-synonymous mutations in genes implicated in metabolic diseases, i.e. diabetes and obesity: IRS1, HMGCS1, ATP8B1, PRMT6 and CLU, suggesting a common molecular etiology for HCC of alternative pathogenic origin.

Novel pathway analysis of genomic polymorphism-cancer risk interaction in the Breast Cancer Prevention Trial.

PURPOSE: Tamoxifen was approved for breast cancer risk reduction in high-risk women based on the National Surgical Adjuvant Breast and Bowel Project's Breast Cancer Prevention Trial (P-1:BCPT), which showed 50% fewer breast cancers with tamoxifen versus placebo, supporting tamoxifen's efficacy in preventing breast cancer. Poor metabolizing CYP2D6 variants are currently the subject of intensive scrutiny regarding their impact on clinical outcomes in the adjuvant setting. Our study extends to variants in a wider spectrum of tamoxifen-metabolizing genes and applies to the prevention setting. METHODS: Our case-only study, nested within P-1:BCPT, explored associations of polymorphisms in estrogen/tamoxifen-metabolizing genes with responsiveness to preventive tamoxifen. Thirty-nine candidate polymorphisms in 17 candidate genes were genotyped in 249 P-1:BCPT cases. RESULTS: CVP2D6_C1111T, individually and within a CYP2D6 haplotype, showed borderline significant association with treatment arm. Path analysis of the entire tamoxifen pathway gene network showed that the tamoxifen pathway model was consistent with the pattern of observed genotype variability within the placebo-arm dataset. However, correlation of variations in genes in the tamoxifen arm differed significantly from the predictions of the tamoxifen pathway model. Strong correlations between allelic variation in the tamoxifen pathway at CYP1A1-CYP3A4, CYP3A4-CYP2C9, and CYP2C9-SULT1A2, in addition to CYP2D6 and its adjacent genes, were seen in the placebo-arm but not the tamoxifen-arm. In conclusion, beyond reinforcing a role for CYP2D6 in tamoxifen response, our pathway analysis strongly suggests that specific combinations of allelic variants in other genes make major contributions to the tamoxifen-resistance phenotype.