Whole genome amplification and its impact on CGH array profiles

Early Hereditary Diffuse Gastric Cancer (eHDGC) is Characterized by Subtle Genomic Instability and Active DNA Damage Response

Diffuse gastric cancer (DGC) is one of the two primary types of stomach cancer. Carriers of germline mutations in the gene encoding E-cadherin are predisposed to DGC. The primary aim of the present study was to determine if genomic instability is an early event in DGC and how it may lead to disease progression. Chromosomal aberrations in early intramucosal hereditary diffuse gastric cancer (eHDGC) were assessed using array comparative genomic hybridization (array CGH). Notably, no aneuploidy or other large-scale chromosomal rearrangements were detected. Instead, all aberrations affected small regions (< 4.8 Mb) and were predominantly deletions. Analysis of DNA sequence patterns revealed that essentially all aberrations possessed the characteristics of common fragile sites. These results and the results of subsequent immunohistochemical examinations demonstrated that unlike advanced DGC, eHDGCs is characterized by low levels of genomic instability at fragile sites. Furthermore, they express an active DNA damage response, providing a molecular basis for the observed indolence of eHDGC. This finding is an important step to understanding the pathology underlying natural history of DGC and supports a revision of the current definition of eHDGC as a malignant disease.

Copy number analysis by low coverage whole genome sequencing using ultra low-input DNA from formalin-fixed paraffin embedded tumor tissue

Unlocking clinically translatable genomic information, including copy number alterations (CNA), from formalin-fixed paraffin-embedded (FFPE) tissue is challenging due to low yields and degraded DNA. We describe a robust, cost-effective low-coverage whole genome sequencing (LC WGS) method for CNA detection using 5 ng of FFPE-derived DNA. CN profiles using 100 ng or 5 ng input DNA were highly concordant and comparable with molecular inversion probe (MIP) array profiles. LC WGS improved CN profiles of samples that performed poorly using MIP arrays. Our technique enables identification of driver and prognostic CNAs in archival patient samples previously deemed unsuitable for genomic analysis due to DNA limitations.

Comparative study of whole genome amplification and next generation sequencing performance of single cancer cells

BACKGROUND

Whole genome amplification (WGA) is required for single cell genotyping. Effectiveness of currently available WGA technologies in combination with next generation sequencing (NGS) and material preservation is still elusive.

RESULTS

In respect to the accuracy of SNP/mutation, indel, and copy number aberrations (CNA) calling, the HiSeq2000 platform outperformed IonProton in all aspects. Furthermore, more accurate SNP/mutation and indel calling was demonstrated using single tumor cells obtained from EDTA-collected blood in respect to CellSave-preserved blood, whereas CNA analysis in our study was not detectably affected by fixation. Although MDA-based WGA yielded the highest DNA amount, DNA quality was not adequate for downstream analysis. PCR-based WGA demonstrates superiority over MDA-PCR combining technique for SNP and indel analysis in single cells. However, SNP calling performance of MDA-PCR WGA improves with increasing amount of input DNA, whereas CNA analysis does not. The performance of PCR-based WGA did not significantly improve with increase of input material. CNA profiles of single cells, amplified with MDA-PCR technique and sequenced on both HiSeq2000 and IonProton platforms, resembled unamplified DNA the most.

MATERIALS AND METHODS

We analyzed the performance of PCR-based, multiple-displacement amplification (MDA)-based, and MDA-PCR combining WGA techniques (WGA kits Ampli1, REPLI-g, and PicoPlex, respectively) on single and pooled tumor cells obtained from EDTA- and CellSave-preserved blood and archival material. Amplified DNA underwent exome-Seq with the Illumina HiSeq2000 and ThermoFisher IonProton platforms.

CONCLUSION

We demonstrate the feasibility of single cell genotyping of differently preserved material, nevertheless, WGA and NGS approaches have to be chosen carefully depending on the study aims.

Cells Comprising the Prostate Cancer Microenvironment Lack Recurrent Clonal Somatic Genomic Aberrations

Prostate cancer-associated stroma (CAS) plays an active role in malignant transformation, tumor progression, and metastasis. Molecular analyses of CAS have demonstrated significant changes in gene expression; however, conflicting evidence exists on whether genomic alterations in benign cells comprising the tumor microenvironment (TME) underlie gene expression changes and oncogenic phenotypes. This study evaluates the nuclear and mitochondrial DNA integrity of prostate carcinoma cells, CAS, matched benign epithelium and benign epithelium-associated stroma by whole-genome copy-number analyses, targeted sequencing of TP53, and FISH. Array comparative genomic hybridization (aCGH) of CAS revealed a copy-neutral diploid genome with only rare and small somatic copy-number aberrations (SCNA). In contrast, several expected recurrent SCNAs were evident in the adjacent prostate carcinoma cells, including gains at 3q, 7p, and 8q, and losses at 8p and 10q. No somatic TP53 mutations were observed in CAS. Mitochondrial DNA (mtDNA) extracted from carcinoma cells and stroma identified 23 somatic mtDNA mutations in neoplastic epithelial cells, but only one mutation in stroma. Finally, genomic analyses identified no SCNAs, LOH, or copy-neutral LOH in cultured cancer-associated fibroblasts, which are known to promote prostate cancer progression in vivo

IMPLICATIONS

The gene expression changes observed in prostate cancer-adjacent stroma and the attendant contribution of the stroma to the development and progression of prostate cancer are not due to frequent or recurrent genomic alterations in the TME.

Whole genome amplification with SurePlex results in better copy number alteration detection using sequencing data compared to the MALBAC method

Current whole genome amplification (WGA) methods lead to amplification bias resulting in over- and under-represented regions in the genome. Nevertheless, certain WGA methods, such as SurePlex and subsequent arrayCGH analysis, make it possible to detect copy number alterations (CNAs) at a 10 Mb resolution. A more uniform WGA combined with massive parallel sequencing (MPS), however, could allow detection at higher resolution and lower cost. Recently, MALBAC, a new WGA method, claims unparalleled performance. Here, we compared the well-established SurePlex and MALBAC WGA for their ability to detect CNAs in MPS generated data and, in addition, compared PCR-free MPS library preparation with the standard enrichment PCR library preparation. Results showed that SurePlex amplification led to more uniformity across the genome, allowing for a better CNA detection with less false positives compared to MALBAC amplified samples. An even more uniform coverage was observed in samples following a PCR-free library preparation. In general, the combination of SurePlex and MPS led to the same chromosomal profile compared to a reference arrayCGH from unamplified genomic DNA, underlining the large potential of MPS techniques in CNA detection from a limited number of DNA material.

Advances and applications of single-cell sequencing technologies

Single-cell sequencing (SCS) has emerged as a powerful new set of technologies for studying rare cells and delineating complex populations. Over the past 5 years, SCS methods for DNA and RNA have had a broad impact on many diverse fields of biology, including microbiology, neurobiology, development, tissue mosaicism, immunology, and cancer research. In this review, we will discuss SCS technologies and applications, as well as translational applications in the clinic.

Cancer genomics: one cell at a time

The study of single cancer cells has transformed from qualitative microscopic images to quantitative genomic datasets. This paradigm shift has been fueled by the development of single-cell sequencing technologies, which provide a powerful new approach to study complex biological processes in human cancers.

Characterising chromosome rearrangements: recent technical advances in molecular cytogenetics

Genomic rearrangements can result in losses, amplifications, translocations and inversions of DNA fragments thereby modifying genome architecture, and potentially having clinical consequences. Many genomic disorders caused by structural variation have initially been uncovered by early cytogenetic methods. The last decade has seen significant progression in molecular cytogenetic techniques, allowing rapid and precise detection of structural rearrangements on a whole-genome scale. The high resolution attainable with these recently developed techniques has also uncovered the role of structural variants in normal genetic variation alongside single-nucleotide polymorphisms (SNPs). We describe how array-based comparative genomic hybridisation, SNP arrays, array painting and next-generation sequencing analytical methods (read depth, read pair and split read) allow the extensive characterisation of chromosome rearrangements in human genomes.

Application of SNP array for rapid prenatal diagnosis: implementation, genetic counselling and diagnostic flow

We report on the validation and implementation of the HumanCytoSNP-12 array (Illumina) (HCS) in prenatal diagnosis. In total, 64 samples were used to validate the Illumina platform (20 with a known (sub) microscopic chromosome abnormality, 5 with known maternal cell contamination (MCC) and 39 normal control samples). There were no false-positive or false-negative results. In addition to the diagnostic possibilities of arrayCGH, the HCS allows detection of regions of homozygosity (ROH), triploidy and helps recognising MCC. Moreover, in two cases of MCC, a deletion was correctly detected. Furthermore we found out that only about 50 ng of DNA is required, which allows a reporting time of only 3 days. We also present a prospective pilot study of 61 fetuses with ultrasound abnormalities and a normal karyotype tested with HCS. In 4 out of 61 (6.5%) fetuses, a clinically relevant abnormality was detected. We designed and present pre-test genetic counselling information on categories of possible test outcomes. On the basis of this information, about 90% of the parents chose to be informed about adverse health outcomes of their future child at infancy and childhood, and 55% also about outcomes at an adult stage. The latter issue regarding the right of the future child itself to decide whether or not to know this information needs to be addressed.

Single-tube linear DNA amplification (LinDA) for robust ChIP-seq

Genome-wide profiling of transcription factors based on massive parallel sequencing of immunoprecipitated chromatin (ChIP-seq) requires nanogram amounts of DNA. Here we describe a high-fidelity, single-tube linear DNA amplification method (LinDA) for ChIP-seq and reChIP-seq with picogram DNA amounts obtained from a few thousand cells. This amplification technology will facilitate global analyses of transcription-factor binding and chromatin with very small cell populations, such as stem or cancer-initiating cells.

Future medical applications of single-cell sequencing in cancer

Advances in whole genome amplification and next-generation sequencing methods have enabled genomic analyses of single cells, and these techniques are now beginning to be used to detect genomic lesions in individual cancer cells. Previous approaches have been unable to resolve genomic differences in complex mixtures of cells, such as heterogeneous tumors, despite the importance of characterizing such tumors for cancer treatment. Sequencing of single cells is likely to improve several aspects of medicine, including the early detection of rare tumor cells, monitoring of circulating tumor cells (CTCs), measuring intratumor heterogeneity, and guiding chemotherapy. In this review we discuss the challenges and technical aspects of single-cell sequencing, with a strong focus on genomic copy number, and discuss how this information can be used to diagnose and treat cancer patients.

Tumour evolution inferred by single-cell sequencing

Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.

Diagnostic, staging, and grading of urothelial carcinomas from urine: performance of BCA-1, a mini-array comparative genomic hybridisation-based test

BACKGROUND

Cytogenetic abnormalities occur at an early stage of bladder urothelial carcinomas (BUC), and their frequency increases as the cancer becomes more advanced.

OBJECTIVE

To assess the diagnostic performance of a test based on cytogenetic abnormalities to diagnose, stage, and grade BUC from the urine.

DESIGN, SETTING, AND PARTICIPANTS

We used a 341 bacterial artificial chromosome (BAC) comparative genomic hybridisation (CGH)-array chip (BCA-1) designed to include loci affected in BUC. The chip was first used on 32 frozen BUC biopsies to design staging (BN0) and grading (BN1 and BN2) prediction models based on Bayesian networks analysis. The models were then validated on external data obtained from 98 tumour samples using a 2464 BAC CGH-array chip. The performance of the test was finally assessed on 44 urine pellets collected, including 22 patients who had BUC and 22 controls.

MEASUREMENTS

We measured sensitivity and specificity to diagnose BUC stage and grade from urine pellets.

RESULTS AND LIMITATIONS

In the urine, BCA-1 test sensitivity was 95%, specificity was 86%, and accuracy was 91%. The BN0 staging model identified T1-4 tumours in the urine with a sensitivity of 90%, a specificity of 83%, and an accuracy of 87%. The BN1 and BN2 grading models detected high-grade disease with a sensitivity, specificity, and accuracy of 86%, 88%, and 87%, respectively, using BN1 and 100%, 63%, and 82%, respectively, using BN2. BN models performed with similar sensitivity but reduced specificity using the external data. BCA-1 failed to produce results for eight additional samples (failure rate: 9%). The test needed high quantities and quality of DNA, and external validation in larger, prospective, and better-designed studies is necessary to confirm feasibility and performance.

CONCLUSIONS

The BCA-1 mini-CGH-array chip detected BUC in urine with a high diagnostic performance. It could also accurately discriminate low-grade from high-grade tumours and, to a lesser extent, lamina propria-invasive tumours from pTa tumours.

Digital transcriptome profiling from attomole-level RNA samples

Accurate profiling of minute quantities of RNA in a global manner can enable key advances in many scientific and clinical disciplines. Here, we present low-quantity RNA sequencing (LQ-RNAseq), a high-throughput sequencing-based technique allowing whole transcriptome surveys from subnanogram RNA quantities in an amplification/ligation-free manner. LQ-RNAseq involves first-strand cDNA synthesis from RNA templates, followed by 3' polyA tailing of the single-stranded cDNA products and direct single molecule sequencing. We applied LQ-RNAseq to profile S. cerevisiae polyA+ transcripts, demonstrate the reproducibility of the approach across different sample preparations and independent instrument runs, and establish the absolute quantitative power of this method through comparisons with other reported transcript profiling techniques and through utilization of RNA spike-in experiments. We demonstrate the practical application of this approach to define the transcriptional landscape of mouse embryonic and induced pluripotent stem cells, observing transcriptional differences, including over 100 genes exhibiting differential expression between these otherwise very similar stem cell populations. This amplification-independent technology, which utilizes small quantities of nucleic acid and provides quantitative measurements of cellular transcripts, enables global gene expression measurements from minute amounts of materials and offers broad utility in both basic research and translational biology for characterization of rare cells.

Functional viral metagenomics and the next generation of molecular tools

The enzymes of bacteriophages and other viruses have been essential research tools since the first days of molecular biology. However, the current repertoire of viral enzymes only hints at their overall potential. The most commonly used enzymes are derived from a surprisingly small number of cultivated viruses, which is remarkable considering the extreme abundance and diversity of viruses revealed over the past decade by metagenomic analysis. To access the treasure trove of enzymes hidden in the global virosphere and develop them for research, therapeutic and diagnostic uses, improvements are needed in our ability to rapidly and efficiently discover, express and characterize viral genes to produce useful proteins. In this paper, we discuss improvements to sampling and cloning methods, functional and genomics-based screens, and expression systems, which should accelerate discovery of new enzymes and other viral proteins for use in research and medicine.