The power of NGS technologies to delineate the genome organization in cancer: from mutations to structural variations and epigenetic alterations

Leveraging the fundamentals of heat transfer and fluid mechanics in microscale geometries for automated next-generation sequencing library preparation

Next-generation sequencing (NGS) is emerging as a powerful tool for molecular diagnostics but remains limited by cumbersome and inefficient sample preparation. We present an innovative automated NGS library preparation system with a simplified mechanical design that exploits both macro- and microfluidic properties for optimizing heat transfer, reaction kinetics, mass transfer, fluid mechanics, adsorption-desorption rates, and molecular thermodynamics. Our approach introduces a unique two-cannula cylindrical capillary system connected to a programmable syringe pump and a Peltier heating element able to execute all steps with high efficiency. Automatic reagent movement, mixing, and magnetic bead-based washing with capillary-based thermal cycling (capillary-PCR) are completely integrated into a single platform. The manual 3-h library preparation process is reduced to less than 15 min of hands-on time via optimally pre-plated reagent plates, followed by less than 6 h of instrument run time during which no user interaction is required. We applied this method to two library preparation assays with different DNA fragmentation requirements (mechanical vs. enzymatic fragmentation), sufficiently limiting consumable use to one cartridge and one 384 well-plate per run. Our platform successfully prepared eight libraries in parallel, generating sequencing data for both human and Escherichia coli DNA libraries with negligible coverage bias compared to positive controls. All sequencing data from our libraries attained Phred (Q) scores > 30, mapping to reference genomes at 99% confidence. The method achieved final library concentrations and size distributions comparable with the conventional manual approach, demonstrating compatibility with downstream sequencing and subsequent data analysis. Our engineering design offers repeatability and consistency in the quality of sequence-able libraries, asserting the importance of mechanical design considerations that employ and optimize fundamental fluid mechanics and heat transfer properties. Furthermore in this work, we provide unique insights into the mechanisms of sample loss within NGS library preparation assays compared with automated adaptations and pinpoint areas in which the principles of thermodynamics, fluid mechanics, and heat transfer can improve future mechanical design iterations.

Advancements in Biotechnology and Stem Cell Therapies for Breast Cancer Patients

This comprehensive review article examines the integration of biotechnology and stem cell therapy in breast cancer diagnosis and treatment. It discusses the use of biotechnological tools such as liquid biopsies, genomic profiling, and imaging technologies for accurate diagnosis and monitoring of treatment response. Stem cell-based approaches, their role in modeling breast cancer progression, and their potential for breast reconstruction post-mastectomy are explored. The review highlights the importance of personalized treatment strategies that combine biotechnological tools and stem cell therapies. Ethical considerations, challenges in clinical translation, and regulatory frameworks are also addressed. The article concludes by emphasizing the potential of integrating biotechnology and stem cell therapy to improve breast cancer outcomes, highlighting the need for continued research and collaboration in this field.

Identification of differentially methylated genes for severe acne by genome-wide DNA methylation and gene expression analysis

Severe acne is a chronic inflammatory skin condition that is affected by both genetic and environmental factors. DNA methylation is associated with a variety of inflammatory skin diseases, but its role in severe acne is unclear. In this study, we conducted a two-stage epigenome correlation study using 88 blood samples to identify disease-related differential methylation sites. We found close associations between the DNA methylation at 23 differentially methylated sites (DMSs) and severe acne, including PDGFD, ARHGEF10, etc. Further analysis revealed that differentially methylated genes (PARP8 and MAPKAPK2) were also expressed differently between severe acne and health control groups. These findings lead us to speculation that epigenetic mechanisms may play an important role in the pathogenesis of severe acne.

Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing

Nanopore sequencing has brought the technology to the next generation in the science of sequencing. This is achieved through research advancing on: pore efficiency, creating mechanisms to control DNA translocation, enhancing signal-to-noise ratio, and expanding to long-read ranges. Heterogeneity regarding epigenetics would be broad as mutations in the epigenome are sensitive to cause new challenges in cancer research. Epigenetic enzymes which catalyze DNA methylation and histone modification are dysregulated in cancer cells and cause numerous heterogeneous clones to evolve. Detection of this heterogeneity in these clones plays an indispensable role in the treatment of various cancer types. With single-cell profiling, the nanopore sequencing technology could provide a simple sequence at long reads and is expected to be used soon at the bedside or doctor's office. Here, we review the advancements of nanopore sequencing and its use in the detection of epigenetic heterogeneity in cancer.

Nano-omics: nanotechnology-based multidimensional harvesting of the blood-circulating cancerome

Over the past decade, the development of 'simple' blood tests that enable cancer screening, diagnosis or monitoring and facilitate the design of personalized therapies without the need for invasive tumour biopsy sampling has been a core ambition in cancer research. Data emerging from ongoing biomarker development efforts indicate that multiple markers, used individually or as part of a multimodal panel, are required to enhance the sensitivity and specificity of assays for early stage cancer detection. The discovery of cancer-associated molecular alterations that are reflected in blood at multiple dimensions (genome, epigenome, transcriptome, proteome and metabolome) and integration of the resultant multi-omics data have the potential to uncover novel biomarkers as well as to further elucidate the underlying molecular pathways. Herein, we review key advances in multi-omics liquid biopsy approaches and introduce the 'nano-omics' paradigm: the development and utilization of nanotechnology tools for the enrichment and subsequent omics analysis of the blood-circulating cancerome.

OUP accepted manuscript

Summary

Next-Generation Sequencing is widely used as a tool for identifying and quantifying microorganisms pooled together in either natural or designed samples. However, a prominent obstacle is achieving correct quantification when the pooled microbes are genetically related. In such cases, the outcome mostly depends on the method used for assigning reads to the individual targets. To address this challenge, we have developed Exodus—a reference-based Python algorithm for quantification of genomes, including those that are highly similar, when they are sequenced together in a single mix. To test Exodus’ performance, we generated both empirical and in silico next-generation sequencing data of mixed genomes. When applying Exodus to these data, we observed median error rates varying between 0% and 0.21% as a function of the complexity of the mix. Importantly, no false negatives were recorded, demonstrating that Exodus’ likelihood of missing an existing genome is very low, even if the genome’s relative abundance is low and similar genomes are present in the same mix. Taken together, these data position Exodus as a reliable tool for identifying and quantifying genomes in mixed samples. Exodus is open source and free to use at: https://github.com/ilyavs/exodus.

Availability and implementation

Exodus is implemented in Python within a Snakemake framework. It is available on GitHub alongside a docker containing the required dependencies: https://github.com/ilyavs/exodus. The data underlying this article will be shared on reasonable request to the corresponding author.

Supplementary information

Supplementary data are available at Bioinformatics online.

Characterization and comparison of genomic profiles between primary cancer cell lines and parent atypical meningioma tumors

Background

Meningiomas are the second most common primary tumors of the central nervous system. However, there is a paucity of data on meningioma biology due to the lack of suitable preclinical in vitro and in vivo models. In this study, we report the establishment and characterization of patient-derived, spontaneously immortalized cancer cell lines derived from World Health Organization (WHO) grade I and atypical WHO grade II meningiomas.

Methods

We evaluated high-resolution 3T MRI neuroimaging findings in meningioma patients which were followed by histological analysis. RT-qPCR and immunostaining analyses were performed to determine the expression levels of meningioma-related factors. Additionally, flow cytometry and sorting assays were conducted to investigate and isolate the CD133 and CD44 positive cells from primary atypical meningioma cells. Further, we compared the gene expression profiles of meningiomas and cell lines derived from them by performing whole-exome sequencing of the blood and tumor samples from the patients, and the primary cancer cell lines established from the meningioma tumor.

Results

Our results were consistent with earlier studies that reported mutations in NF2, SMO, and AKT1 genes in atypical meningiomas, and we also observed mutations in MYBL2, a gene that was recently discovered. Significantly, the genomic signature was consistent between the atypical meningioma cancer cell lines and the tumor and blood samples from the patient.

Conclusion

Our results lead us to conclude that established meningioma cell lines with a genomic signature identical to tumors might be a valuable tool for understanding meningioma tumor biology, and for screening therapeutic agents to treat recurrent meningiomas.

Genomic DNA methylation in HLA-Cw*0602 carriers and non-carriers of psoriasis

BACKGROUND

HLA-Cw*0602 has long been established as one of the most important genetic biomarkers in psoriasis. However, the epigenetic and gene expression differences between HLA-Cw*0602 carriers and non-carriers has not yet been investigated.

OBJECTIVE

We aim to explore the whole-genome methylation and gene expression differences between HLA-Cw*0602 carriers and non-carriers.

METHODS

HLA imputation was performed to get landscape of variants in this region. Genome-wide DNA methylation was compared between positive and negative HLA-Cw*0602 groups. Eleven methylation loci were selected for further validation in additional 43 cases. For differentially methylated genes, GO and KEGG were used to annotate gene functions.

RESULTS

We imputed 29,948 variants based on the constructed HLA reference panels, and obtained 42 HLA-Cw*0602 carriers and 72 non-carriers. Significant methylation differences were detected at 4321 sites (811 hypo- and 3510 hypermethylated). The cg02607779 (KLF7, P = 0.001), cg06936779 (PIP5K1A, P = 0.002), cg03860400 (BTBD10, P = 0.017) and cg26112390 (GOLGA2P5, P = 0.019) were identified and validated to be the significant CpGs contributed to different HLA-C*0602 groups. Among the hypo- and hypermethylated sites, the top CpGs were in gene body and CpG island.

CONCLUSION

We performed the first whole-genome study on methylation differences between psoriatic individuals with or without HLA-Cw*0602, and found the key methylation sites which may contribute to the carrying status of HLA-Cw*0602. Methylation loci located in gene body and CpG island are more likely to affect the methylation levels in HLA-Cw*0602 carriers. This integrated analysis shed light on novel insights into the pathogenic mechanisms of genomic methylation in different HLA genotypes of psoriasis.

Differential Expression Profile of miR-27b, miR-29a, and miR-155 in Chronic Lymphocytic Leukemia and Breast Cancer Patients

Over the past decade, studies on microRNA (miRNA) and cancer quickly became known. miRNAs are small non-coding RNAs that play a vital role in regulation of gene expression. In the present study, the expression of miR-27b, miR-29a, and miR-155, their prognostic roles, and their potential targets in chronic lymphocytic leukemia (CLL) and breast cancer (BC) by qRT-PCR were investigated. In two case-control studies, qRT-PCR was used to analyze the peripheral blood serum of 15 CLL patients and tissue samples of 15 BC patients for the expression of miR-27b, miR-29a, and miR-155. miRNA expression levels were calculated using the qRT-PCR method. The results revealed a significant increase in the expression of all miRNAs in patients with BC and CLL compared with respective healthy groups (p < 0.001). In BC patients, there was a significant difference between the expression of miR-155 and miR-29a (p < 0.05), miR-155 and miR-27b (p < 0.01), and miR-27b and miR-29a (p < 0.001). In CLL patients, a significant difference between expression of both miR-27b and miR-29a compared with expression of miR-155 (p < 0.001) was found. Furthermore, a significant association between miR-155 and prevascular invasion was found. Significantly, elevated circulating miRNAs were shown to be BC specific and could differentiate BC tissues from the controls. It was demonstrated that miRNAs used in this study and their expression profiles can be developed as biomarkers for early diagnosis and prognosis of CLL and BC. Further studies utilizing a larger test group of patients would provide identification of miRNAs as key players in intercellular interactions.

Identification of DNA-Methylated CpG Islands Associated With Gene Silencing in the Adult Body Tissues of the Ogye Chicken Using RNA-Seq and Reduced Representation Bisulfite Sequencing

DNA methylation is an epigenetic mark that plays an essential role in regulating gene expression. CpG islands are DNA methylations regions in promoters known to regulate gene expression through transcriptional silencing of the corresponding gene. DNA methylation at CpG islands is crucial for gene expression and tissue-specific processes. At the current time, a limited number of studies have reported on gene expression associated with DNA methylation in diverse adult tissues at the genome-wide level. Expression levels are rarely affected by DNA methylation in normal adult tissues; however, statistical differences in gene expression level correlated with DNA methylation have recently been revealed. In this study, we examined 20 pairs of DNA methylomes and transcriptomes from RNA-seq and reduced representation bisulfite sequencing (RRBS) data using adult Ogye chicken tissues. A total of 3,133 CpG islands were identified from 20 tissue data in a single chicken sample which could affect downstream genes. Analyzing these CpG island and gene pairs, 121 significant units were statistically correlated. Among them, six genes (CLDN3, DECR2, EVA1B, NME4, NTSR1, and XPNPEP2) were highly significantly changed by altered DNA methylation. Finally, our data demonstrated how DNA methylation correlated to gene expression in normal adult tissues. Our source codes can be found at https://github.com/wjlim/correlation-between-rna-seq-and-RRBS.

The reliable assurance of detecting somatic mutations in cancer-related genes by next-generation sequencing: the results of external quality assessment in China

To evaluate the proficiencies of laboratories utilizing next-generation sequencing (NGS) to detect somatic mutations in cancer-related genes, an external quality assessment (EQA) was implemented by the National Center for Clinical Laboratories of China in 2015. We prepared a panel of samples that comprised eight samples made by mixing synthetic mutated DNA fragments with normal human genomic DNA and one reference sample containing only genomic DNA. We validated our sample panel, and then distributed it to laboratories across China. We received complete results from 64 laboratories. The performances of 51.6 % (33/64) respondent labs were acceptable and 26.6 % (17/64) of the labs returned perfect results. In total, 449 mistakes were reported, including 201 false-negatives (201/449, 44.8 %) and 222 false-positives (222/449, 49.4 %) and 26 slightly discordant results (26/449, 5.8 %). We believe these unsatisfactory results and varied performances are mainly due to the enrichment methods used, the diverse sequencing chemistries of the different NGS platforms, and other errors within the sequencing process. The results indicate that our sample panel is suitable for use in EQA studies, and that further laboratory training in targeted NGS testing is urgently required. To address this, we propose a targeted NGS workflow with details on quality assurance procedures according to the current guidelines.

microRNAs Make the Call in Cancer Personalized Medicine

Since their discovery and the advent of RNA interference, microRNAs have drawn enormous attention because of their ubiquitous involvement in cellular pathways from life to death, from metabolism to communication. It is also widely accepted that they possess an undeniable role in cancer both as tumor suppressors and tumor promoters modulating cell proliferation and migration, epithelial-mesenchymal transition and tumor cell invasion and metastasis. Moreover, microRNAs can even affect the tumor surrounding environment influencing angiogenesis and immune system activation and recruitment. The tight association of microRNAs with several cancer-related processes makes them undoubtedly connected to the effect of specific cancer drugs inducing either resistance or sensitization. In this context, personalized medicine through microRNAs arose recently with the discovery of single nucleotide polymorphisms in the target binding sites, in the sequence of the microRNA itself or in microRNA biogenesis related genes, increasing risk, susceptibility and progression of multiple types of cancer in different sets of the population. The depicted scenario implies that the overall variation displayed by these small non-coding RNAs have an impact on patient-specific pharmacokinetics and pharmacodynamics of cancer drugs, pushing on a rising need of personalized treatment. Indeed, microRNAs from either tissues or liquid biopsies are also extensively studied as valuable biomarkers for disease early recognition, progression and prognosis. Despite microRNAs being intensively studied in recent years, a comprehensive review describing these topics all in one is missing. Here we report an up-to-date and critical summary of microRNAs as tools for better understanding personalized cancer biogenesis, evolution, diagnosis and treatment.

Piecing together the puzzle: nanopore technology in detection and quantification of cancer biomarkers

This mini-review paper is a comprehensive outline of nanopore technology applications in the detection and study of various cancer causal factors.

Epigenome-wide association data implicates DNA methylation-mediated genetic risk in psoriasis

BACKGROUND

Psoriasis is a chronic inflammatory skin disease characterized by epidermal hyperproliferation and altered keratinocyte differentiation and inflammation and is caused by the interplay of genetic and environmental factors. Previous studies have revealed that DNA methylation (DNAm) and genetic makers are closely associated with psoriasis, and strong evidences have shown that DNAm can be controlled by genetic factors, which attracted us to evaluate the relationship among DNAm, genetic makers, and disease status.

METHODS

We utilized the genome-wide methylation data of psoriatic skin (PP, N = 114) and unaffected control skin (NN, N = 62) tissue samples in our previous study, and we performed whole-genome genotyping with peripheral blood of the same samples to evaluate the underlying genetic effect on skin DNA methylation. Causal inference test (CIT) was used to assess whether DNAm regulate genetic variation and gain a better understanding of the epigenetic basis of psoriasis susceptibility.

RESULTS

We identified 129 SNP-CpG pairs achieving the significant association threshold, which constituted 28 unique methylation quantitative trait loci (MethQTL) and 34 unique CpGs. There are 18 SNPs were associated with psoriasis at a Bonferoni-corrected P < 0.05, and these 18 SNPs formed 93 SNP-CpG pairs with 17 unique CpG sites. We found that 11 of 93 SNP-CpG pairs, composed of 5 unique SNPs and 3 CpG sites, presented a methylation-mediated relationship between SNPs and psoriasis. The 3 CpG sites were located on the body of C1orf106, the TSS1500 promoter region of DMBX1 and the body of SIK3.

CONCLUSIONS

This study revealed that DNAm of some genes can be controlled by genetic factors and also mediate risk variation for psoriasis in Chinese Han population and provided novel molecular insights into the pathogenesis of psoriasis.

Analysis of Important Gene Ontology Terms and Biological Pathways Related to Pancreatic Cancer

Pancreatic cancer is a serious disease that results in more than thirty thousand deaths around the world per year. To design effective treatments, many investigators have devoted themselves to the study of biological processes and mechanisms underlying this disease. However, it is far from complete. In this study, we tried to extract important gene ontology (GO) terms and KEGG pathways for pancreatic cancer by adopting some existing computational methods. Genes that have been validated to be related to pancreatic cancer and have not been validated were represented by features derived from GO terms and KEGG pathways using the enrichment theory. A popular feature selection method, minimum redundancy maximum relevance, was employed to analyze these features and extract important GO terms and KEGG pathways. An extensive analysis of the obtained GO terms and KEGG pathways was provided to confirm the correlations between them and pancreatic cancer.

Next-Generation Sequencing and Result Interpretation in Clinical Oncology: Challenges of Personalized Cancer Therapy

The tools of next-generation sequencing (NGS) technology, such as targeted sequencing of candidate cancer genes and whole-exome and -genome sequencing, coupled with encouraging clinical results based on the use of targeted therapeutics and biomarker-guided clinical trials, are fueling further technological advancements of NGS technology. However, NGS data interpretation is associated with challenges that must be overcome to promote the techniques' effective integration into clinical oncology practice. Specifically, sequencing of a patient's tumor often yields 30-65 somatic variants, but most of these variants are "passenger" mutations that are phenotypically neutral and thus not targetable. Therefore, NGS data must be interpreted by multidisciplinary decision-support teams to determine mutation actionability and identify potential "drivers," so that the treating physician can prioritize what clinical decisions can be pursued in order to provide cancer therapy that is personalized to the patient and his or her unique genome.

Performance comparison of two commercial human whole-exome capture systems on formalin-fixed paraffin-embedded lung adenocarcinoma samples

Background

Next Generation Sequencing (NGS) has become a valuable tool for molecular landscape characterization of cancer genomes, leading to a better understanding of tumor onset and progression, and opening new avenues in translational oncology. Formalin-fixed paraffin-embedded (FFPE) tissue is the method of choice for storage of clinical samples, however low quality of FFPE genomic DNA (gDNA) can limit its use for downstream applications.

Methods

To investigate the FFPE specimen suitability for NGS analysis and to establish the performance of two solution-based exome capture technologies, we compared the whole-exome sequencing (WES) data of gDNA extracted from 5 fresh frozen (FF) and 5 matched FFPE lung adenocarcinoma tissues using: SeqCap EZ Human Exome v.3.0 (Roche NimbleGen) and SureSelect XT Human All Exon v.5 (Agilent Technologies).

Results

Sequencing metrics on Illumina HiSeq were optimal for both exome systems and comparable among FFPE and FF samples, with a slight increase of PCR duplicates in FFPE, mainly in Roche NimbleGen libraries. Comparison of single nucleotide variants (SNVs) between FFPE-FF pairs reached overlapping values >90 % in both systems. Both WES showed high concordance with target re-sequencing data by Ion PGM™ in 22 lung-cancer genes, regardless the source of samples. Exon coverage of 623 cancer-related genes revealed high coverage efficiency of both kits, proposing WES as a valid alternative to target re-sequencing.

Conclusions

High-quality and reliable data can be successfully obtained from WES of FFPE samples starting from a relatively low amount of input gDNA, suggesting the inclusion of NGS-based tests into clinical contest. In conclusion, our analysis suggests that the WES approach could be extended to a translational research context as well as to the clinic (e.g. to study rare malignancies), where the simultaneous analysis of the whole coding region of the genome may help in the detection of cancer-linked variants.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2720-4) contains supplementary material, which is available to authorized users.

Molecular Pathology and Personalized Medicine: The Dawn of a New Era in Companion Diagnostics-Practical Considerations about Companion Diagnostics for Non-Small-Cell-Lung-Cancer

Companion diagnostics (CDx) have become a major tool in molecular pathology and assist in therapy decisions in an increasing number of various cancers. Particularly, the developments in lung cancer have been most impressing in the last decade and consequently lung cancer mutation testing and molecular profiling has become a major business of diagnostic laboratories. However, it has become difficult to decide which biomarkers are currently relevant for therapy decisions, as many of the new biomarkers are not yet approved as therapy targets, remain in the status of clinical studies, or still have not left the experimental phase. The current review is focussed on those markers that do have current therapy implications, practical implications arising from the respective companion diagnostics, and thus is focused on daily practice.

Personalized medicine approaches for colon cancer driven by genomics and systems biology: OncoTrack

The post-genomic era promises to pave the way to a personalized understanding of disease processes, with technological and analytical advances helping to solve some of the world's health challenges. Despite extraordinary progress in our understanding of cancer pathogenesis, the disease remains one of the world's major medical problems. New therapies and diagnostic procedures to guide their clinical application are urgently required. OncoTrack, a consortium between industry and academia, supported by the Innovative Medicines Initiative, signifies a new era in personalized medicine, which synthesizes current technological advances in omics techniques, systems biology approaches, and mathematical modeling. A truly personalized molecular imprint of the tumor micro-environment and subsequent diagnostic and therapeutic insight is gained, with the ultimate goal of matching the "right" patient to the "right" drug and identifying predictive biomarkers for clinical application. This comprehensive mapping of the colon cancer molecular landscape in tandem with crucial, clinical functional annotation for systems biology analysis provides unprecedented insight and predictive power for colon cancer management. Overall, we show that major biotechnological developments in tandem with changes in clinical thinking have laid the foundations for the OncoTrack approach and the future clinical application of a truly personalized approach to colon cancer theranostics.

Distinct isoform of FABP7 revealed by screening for retroelement-activated genes in diffuse large B-cell lymphoma

Remnants of ancient transposable elements (TEs) are abundant in mammalian genomes. These sequences harbor multiple regulatory motifs and hence are capable of influencing expression of host genes. In response to environmental changes, TEs are known to be released from epigenetic repression and to become transcriptionally active. Such activation could also lead to lineage-inappropriate activation of oncogenes, as one study described in Hodgkin lymphoma. However, little further evidence for this mechanism in other cancers has been reported. Here, we reanalyzed whole transcriptome data from a large cohort of patients with diffuse large B-cell lymphoma (DLBCL) compared with normal B-cell centroblasts to detect genes ectopically expressed through activation of TE promoters. We have identified 98 such TE-gene chimeric transcripts that were exclusively expressed in primary DLBCL cases and confirmed several in DLBCL-derived cell lines. We further characterized a TE-gene chimeric transcript involving a fatty acid-binding protein gene (LTR2-FABP7), normally expressed in brain, that was ectopically expressed in a subset of DLBCL patients through the use of an endogenous retroviral LTR promoter of the LTR2 family. The LTR2-FABP7 chimeric transcript encodes a novel chimeric isoform of the protein with characteristics distinct from native FABP7. In vitro studies reveal a dependency for DLBCL cell line proliferation and growth on LTR2-FABP7 chimeric protein expression. Taken together, these data demonstrate the significance of TEs as regulators of aberrant gene expression in cancer and suggest that LTR2-FABP7 may contribute to the pathogenesis of DLBCL in a subgroup of patients.

How does the Mediterranean diet promote cardiovascular health? Current progress toward molecular mechanisms: gene-diet interactions at the genomic, transcriptomic, and epigenomic levels provide novel insights into new mechanisms

Epidemiological evidence supports a health-promoting effect of the Mediterranean Diet (MedDiet), especially in the prevention of cardiovascular diseases. These cardiovascular benefits have been attributed to a number of components of the MedDiet such as monounsaturated fatty acids, antioxidant vitamins and phytochemicals. However, the underlying mechanisms remain unknown. Likewise, little is known about the genes that define inter-individual variation in response to the MedDiet, although the TCF7L2 gene is emerging as an illustrative candidate for determining relative risk of cardiovascular events in response to the MedDiet. Moreover, omics technologies are providing evidence supporting potential mechanisms, some of them implicating epigenetics (i.e. microRNAs, methylation), and certain data suggest that some traditional foods could contribute via microRNAs possibly acting as exogenous regulators of gene expression. Future research should aim at increasing and consolidating the nutrigenetic and nutrigenomic knowledge of the MedDiet in order to provide sound, personalized and optimized nutritional recommendations.

Harnessing massively parallel sequencing in personalized head and neck oncology

Advances in the management of patients with head and neck squamous cell carcinoma (HNSCC) have not significantly changed the prognosis of this tumor over the past five decades. Molecular heterogeneity of HNSCC and its association with HPV, in addition to the increase in the number of cancers arising in traditionally low-risk patients, are among some of the obstacles to the successful management of this group of tumors. Massively parallel sequencing, otherwise known as next-generation sequencing (NGS), is rapidly changing conventional patient management by providing detailed information about each patient's genome and transcriptome. Despite major advances in technology and a significant reduction in the cost of sequencing, NGS remains mainly limited to research facilities. In addition, there are only a few published studies that have utilized this technology in HNSCC. This paper aims to report briefly on current commercially available NGS platforms and discuss their clinical applications, ethical considerations, and utilization in personalized patient care, particularly as this relates to head and neck cancer.

SInC: an accurate and fast error-model based simulator for SNPs, Indels and CNVs coupled with a read generator for short-read sequence data

Background

The rapid advancements in the field of genome sequencing are aiding our understanding on many biological systems. In the last five years, computational biologists and bioinformatics specialists have come up with newer, better and more efficient tools towards the discovery, analysis and interpretation of different genomic variants from high-throughput sequencing data. Availability of reliable simulated dataset is essential and is the first step towards testing any newly developed analytical tools for variant discovery. Although there are tools currently available that can simulate variants, none present the possibility of simulating all the three major types of variations (Single Nucleotide Polymorphisms, Insertions and Deletions and Copy Number Variations) and can generate reads taking a realistic error-model into consideration. Therefore, an efficient simulator and read generator is needed that can simulate variants taking the error rates of true biological samples into consideration.

Results

We report SInC (Snp, Indel and Cnv) an open-source variant simulator and read generator capable of simulating all the three common types of biological variants taking into account a distribution of base quality score from a most commonly used next-generation sequencing instrument from Illumina. SInC is capable of generating single- and paired-end reads with user-defined insert size and with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes.

Conclusions

We have come up with a user-friendly multi-variant simulator and read-generator tools called SInC. SInC can be downloaded from http://sourceforge.net/projects/sincsimulator.

Clinical application of amplicon-based next-generation sequencing in cancer

Next-generation sequencing (NGS) technology has revolutionized genomic research by decreasing the cost of sequencing while increasing the throughput. The focus now is on potential clinical applications of NGS technology for diagnostics and therapeutics. Clinical applications of NGS in cancer can detect clinically actionable genetic/genomic alterations that are critical for cancer care. These alterations can be of diagnostic, prognostic, or therapeutic significance. In certain cancers, patient risk and prognosis can be predicted based on the mutation profile identified by NGS. Many targeted therapies have been developed for cancer patients who bear specific mutations; however, choosing the right NGS technique for the appropriate clinical application can be challenging, especially in clinical oncology, where the material for NGS tests is often limited and the turnaround time (TAT) for cancer tests is constrained to a few days. Currently, amplicon-based NGS approaches have emerged as the best fit for clinical oncology. In this review, we focus on amplicon-based library preparation, sequencing, sequence data alignment and annotation, and post-analytic interpretation and reporting.

Genome aberrations in canine mammary carcinomas and their detection in cell-free plasma DNA

Mammary tumors are the most frequent cancers in female dogs exhibiting a variety of histopathological differences. There is lack of knowledge about the genomes of these common dog tumors. Five tumors of three different histological subtypes were evaluated. Massive parallel sequencing (MPS) was performed in comparison to the respective somatic genome of each animal. Copy number and structural aberrations were validated using droplet digital PCR (ddPCR). Using mate-pair sequencing chromosomal aneuploidies were found in two tumors, frequent smaller deletions were found in one, inter-chromosomal fusions in one other, whereas one tumor was almost normal. These aberrations affect several known cancer associated genes such as cMYC, and KIT. One common deletion of the proximal end of CFA27, harboring the tumor suppressor gene PFDN5 was detected in four tumors. Using ddPCR, this deletion was validated and detected in 50% of tumors (N = 20). Breakpoint specific dPCRs were established for four tumors and tumor specific cell-free DNA (cfDNA) was detected in the plasma. In one animal tumor-specific cfDNA was found >1 year after surgery, attributable to a lung metastasis. Paired-end sequencing proved that copy-number imbalances of the tumor are reflected by the cfDNA. This report on chromosomal instability of canine mammary cancers reveals similarities to human breast cancers as well as special canine alterations. This animal model provides a framework for using MPS for screening for individual cancer biomarkers with cost effective confirmation and monitoring using ddPCR. The possibility exists that ddPCR can be expanded to screening for common cancer related variants.

Harnessing virtual machines to simplify next-generation DNA sequencing analysis

MOTIVATION

The growth of next-generation sequencing (NGS) has not only dramatically accelerated the pace of research in the field of genomics, but it has also opened the door to personalized medicine and diagnostics. The resulting flood of data has led to the rapid development of large numbers of bioinformatic tools for data analysis, creating a challenging situation for researchers when choosing and configuring a variety of software for their analysis, and for other researchers trying to replicate their analysis. As NGS technology continues to expand from the research environment into clinical laboratories, the challenges associated with data analysis have the potential to slow the adoption of this technology.

RESULTS

Here we discuss the potential of virtual machines (VMs) to be used as a method for sharing entire installations of NGS software (bioinformatic 'pipelines'). VMs are created by programs designed to allow multiple operating systems to co-exist on a single physical machine, and they can be made following the object-oriented paradigm of encapsulating data and methods together. This allows NGS data to be distributed within a VM, along with the pre-configured software for its analysis. Although VMs have historically suffered from poor performance relative to native operating systems, we present benchmarking results demonstrating that this reduced performance can now be minimized. We further discuss the many potential benefits of VMs as a solution for NGS analysis and describe several published examples. Lastly, we consider the benefits of VMs in facilitating the introduction of NGS technology into the clinical environment.

CONTACT

brian.wilhelm@umontreal.ca.

Single-variant and multi-variant trend tests for genetic association with next-generation sequencing that are robust to sequencing error

As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci.

Genomics and epigenomics of colorectal cancer

Colorectal cancer is one of the most common cancer types worldwide and accounts for approximately 600,000 deaths annually. Work over the last decades has uncovered a number of tumor-suppressor and oncogenes which are frequently mutated and might thus be responsible for the malignant transformation. However, only with the development of new high-throughput technologies systematic analyses of the genome and epigenomes became feasible. While data generation has increased exponential, we are now faced with new challenges to transform these data into useful models that help predicting the outcome of genomic aberrations and to develop novel diagnostic and therapeutic strategies. As a basis for the modeling it is essential to understand and integrate current knowledge. We review previous and current ideas in colorectal cancer development and focus on a pathway oriented view. We show that colorectal cancer is a multilayer complex disease affecting the genome as well as the epigenome with direct consequences on the gene and microRNA (miRNA) expression signatures. The goal is to illustrate the current principles of colorectal cancer pathogenesis and to illustrate the need for elaborate computer modeling systems.

Discovery of posttranscriptional regulatory RNAs using next generation sequencing technologies

Next generation sequencing (NGS) has revolutionized the way by which we engineer metabolism by radically altering the path to genome-wide inquiries. This is due to the fact that NGS approaches offer several powerful advantages over traditional methods that include the ability to fully sequence hundreds to thousands of genes in a single experiment and simultaneously detect homozygous and heterozygous deletions, alterations in gene copy number, insertions, translocations, and exome-wide substitutions that include "hot-spot mutations." This chapter describes the use of these technologies as a sequencing technique for transcriptome analysis and discovery of regulatory RNA elements in the context of three main platforms: Illumina HiSeq, 454 pyrosequencing, and SOLiD sequencing. Specifically, this chapter focuses on the use of Illumina HiSeq, since it is the most widely used platform for RNA discovery and transcriptome analysis. Regulatory RNAs have now been found in all branches of life. In bacteria, noncoding small RNAs (sRNAs) are involved in highly sophisticated regulatory circuits that include quorum sensing, carbon metabolism, stress responses, and virulence (Gorke and Vogel, Gene Dev 22:2914-2925, 2008; Gottesman, Trends Genet 21:399-404, 2005; Romby et al., Curr Opin Microbiol 9:229-236, 2006). Further characterization of the underlying regulation of gene expression remains poorly understood given that it is estimated that over 60% of all predicted genes remain hypothetical and the 5' and 3' untranslated regions are unknown for more than 90% of the genes (Siegel et al., Trends Parasitol 27:434-441, 2011). Importantly, manipulation of the posttranscriptional regulation that occurs at the level of RNA stability and export, trans-splicing, polyadenylation, protein translation, and protein stability via untranslated regions (Clayton, EMBO J 21:1881-1888, 2002; Haile and Papadopoulou, Curr Opin Microbiol 10:569-577, 2007) could be highly beneficial to metabolic engineering.

Translating genomics to the clinic: implications of cancer heterogeneity

BACKGROUND

Sequencing of cancer genomes has become a pivotal method for uncovering and understanding the deregulated cellular processes driving tumor initiation and progression. Whole-genome sequencing is evolving toward becoming less costly and more feasible on a large scale; consequently, thousands of tumors are being analyzed with these technologies. Interpreting these data in the context of tumor complexity poses a challenge for cancer genomics.

CONTENT

The sequencing of large numbers of tumors has revealed novel insights into oncogenic mechanisms. In particular, we highlight the remarkable insight into the pathogenesis of breast cancers that has been gained through comprehensive and integrated sequencing analysis. The analysis and interpretation of sequencing data, however, must be considered in the context of heterogeneity within and among tumor samples. Only by adequately accounting for the underlying complexity of cancer genomes will the potential of genome sequencing be understood and subsequently translated into improved management of patients.

SUMMARY

The paradigm of personalized medicine holds promise if patient tumors are thoroughly studied as unique and heterogeneous entities and clinical decisions are made accordingly. Associated challenges will be ameliorated by continued collaborative efforts among research centers that coordinate the sharing of mutation, intervention, and outcomes data to assist in the interpretation of genomic data and to support clinical decision-making.

Next generation sequencing in clinical medicine: Challenges and lessons for pathology and biomedical informatics

The Human Genome Project (HGP) provided the initial draft of mankind's DNA sequence in 2001. The HGP was produced by 23 collaborating laboratories using Sanger sequencing of mapped regions as well as shotgun sequencing techniques in a process that occupied 13 years at a cost of ~$3 billion. Today, Next Generation Sequencing (NGS) techniques represent the next phase in the evolution of DNA sequencing technology at dramatically reduced cost compared to traditional Sanger sequencing. A single laboratory today can sequence the entire human genome in a few days for a few thousand dollars in reagents and staff time. Routine whole exome or even whole genome sequencing of clinical patients is well within the realm of affordability for many academic institutions across the country. This paper reviews current sequencing technology methods and upcoming advancements in sequencing technology as well as challenges associated with data generation, data manipulation and data storage. Implementation of routine NGS data in cancer genomics is discussed along with potential pitfalls in the interpretation of the NGS data. The overarching importance of bioinformatics in the clinical implementation of NGS is emphasized.[7] We also review the issue of physician education which also is an important consideration for the successful implementation of NGS in the clinical workplace. NGS technologies represent a golden opportunity for the next generation of pathologists to be at the leading edge of the personalized medicine approaches coming our way. Often under-emphasized issues of data access and control as well as potential ethical implications of whole genome NGS sequencing are also discussed. Despite some challenges, it's hard not to be optimistic about the future of personalized genome sequencing and its potential impact on patient care and the advancement of knowledge of human biology and disease in the near future.

Human papillomavirus DNA methylation as a potential biomarker for cervical cancer

Sexually transmitted carcinogenic human papillomavirus (HPV) infections are extraordinarily prevalent worldwide. However, most incident HPV infections clear within a few years, whereas a small minority persists to invasive cancer. Recent studies indicate that detection of methylated viral DNA may distinguish women with cervical intraepithelial neoplasia grade 2+ (CIN2+) from those with a carcinogenic HPV-type infection that shows no evidence of CIN2+. Several studies have reported a positive association between methylation of CpG sites in the L1 gene and CIN2+, although there are inconclusive results about methylation of CpG sites in the upstream regulatory region (URR). In this review, we summarize the current state of knowledge on HPV DNA methylation in cervical carcinogenesis, and discuss the merits of different methods used to measure HPV DNA methylation. To follow the promising leads, we suggest future studies to validate the use of methylated carcinogenic HPV DNA as a predictive and/or diagnostic biomarker for risk of cervical cancer among HPV-positive women.

PCR amplification and high throughput sequencing of immunoglobulin heavy chain genes from formalin-fixed paraffin-embedded human biopsies

The use of high throughput sequencing (HTS) technologies in biomedicine is expanding in a variety of fields in recent years. The 454 system is an HTS platform that is ideally suited to characterize B cell receptor (BCR) repertoires by sequencing of immunoglobulin (Ig) genes, as it is able to sequence stretches of several hundred nucleotides. Most studies that used this platform for antibody repertoire analyses have started from fresh or frozen tissues or peripheral blood samples, and rely on starting with optimal quality DNA. In this paper we demonstrate that BCR repertoire analysis can be done using DNA from formalin-fixed paraffin-embedded (FFPE) human tissue samples. The heterogeneity of BCR repertoires we obtained confirms the plausibility of HTS of DNA from FFPE specimens. The establishment of experimental protocols and computational tools that enable sequence data analysis from the low quality DNA of FFPE tissues is important for enabling research, as it would enable the use of the rich source of preserved samples in clinical biobanks and biopsy archives.

Alternative transcription and alternative splicing in cancer

In recent years, the notion of "one gene makes one protein that functions in one signaling pathway" in mammalian cells has been shown to be overly simplistic. Recent genome-wide studies suggest that at least half of the human genes, including many therapeutic target genes, produce multiple protein isoforms through alternative splicing and alternative usage of transcription initiation and/or termination. For example, alternative splicing of the vascular endothelial growth factor gene (VEGFA) produces multiple protein isoforms, which display either pro-angiogenic or anti-angiogenic activities. Similarly, for the majority of human genes, the inclusion or exclusion of exonic sequences enhances the generation of transcript variants and/or protein isoforms that can vary in structure and functional properties. Many of the isoforms produced in this manner are tightly regulated during normal development but are misregulated in cancer cells. Altered expression of transcript variants and protein isoforms for numerous genes is linked with disease and its prognosis, and cancer cells manipulate regulatory mechanisms to express specific isoforms that confer drug resistance and survival advantages. Emerging insights indicate that modulating the expression of transcript and protein isoforms of a gene may hold the key to impeding tumor growth and act as a model for efficient targeting of disease-associated genes at the isoform level. This review highlights the role and regulation of alternative transcription and splicing mechanisms in generating the transcriptome, and the misuse and diagnostic/prognostic potential of alternative transcription and splicing in cancer.

Exome enrichment and SOLiD sequencing of formalin fixed paraffin embedded (FFPE) prostate cancer tissue

Next generation sequencing (NGS) technologies have revolutionized cancer research allowing the comprehensive study of cancer using high throughput deep sequencing methodologies. These methods detect genomic alterations, nucleotide substitutions, insertions, deletions and copy number alterations. SOLiD (Sequencing by Oligonucleotide Ligation and Detection, Life Technologies) is a promising technology generating billions of 50 bp sequencing reads. This robust technique, successfully applied in gene identification, might be helpful in detecting novel genes associated with cancer initiation and progression using formalin fixed paraffin embedded (FFPE) tissue. This study’s aim was to compare the validity of whole exome sequencing of fresh-frozen vs. FFPE tumor tissue by normalization to normal prostatic FFPE tissue, obtained from the same patient. One primary fresh-frozen sample, corresponding FFPE prostate cancer sample and matched adjacent normal prostatic tissue was subjected to exome sequencing. The sequenced reads were mapped and compared. Our study was the first to show comparable exome sequencing results between FFPE and corresponding fresh-frozen cancer tissues using SOLiD sequencing. A prior study has been conducted comparing the validity of sequencing of FFPE vs. fresh frozen samples using other NGS platforms. Our validation further proves that FFPE material is a reliable source of material for whole exome sequencing.

Pharmacogenetics and pharmacogenomics: role of mutational analysis in anti-cancer targeted therapy

The goal of cancer pharmacogenomics is to obtain benefit from personalized approaches of cancer treatment and prevention. Recent advances in genomic research have shed light on the crucial role of genetic variants, mainly involving genes encoding drug-metabolizing enzymes, drug transporters and targets, in driving different treatment responses among individuals, in terms of therapeutic efficacy and safety. Although a considerable amount of new targeted agents have been designed based on a finely understanding of molecular alterations in cancer, a wide gap between pharmacogenomic knowledge and clinical application still persists. This review focuses on the relevance of mutational analyses in predicting individual response to antitumor therapy, in order to improve the translational impact of genetic information on clinical practice.

A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease

Background

Transcriptomic studies in clinical research are essential tools for deciphering the functional elements of the genome and unraveling underlying disease mechanisms. Various technologies have been developed to deduce and quantify the transcriptome including hybridization and sequencing-based approaches. Recently, high density exon microarrays have been successfully employed for detecting differentially expressed genes and alternative splicing events for biomarker discovery and disease diagnostics. The field of transcriptomics is currently being revolutionized by high throughput DNA sequencing methodologies to map, characterize, and quantify the transcriptome.

Methods

In an effort to understand the merits and limitations of each of these tools, we undertook a study of the transcriptome in sickle cell disease, a monogenic disease comparing the Affymetrix Human Exon 1.0 ST microarray (Exon array) and Illumina’s deep sequencing technology (RNA-seq) on whole blood clinical specimens.

Results

Analysis indicated a strong concordance (R = 0.64) between Exon array and RNA-seq data at both gene level and exon level transcript expression. The magnitude of differential expression was found to be generally higher in RNA-seq than in the Exon microarrays. We also demonstrate for the first time the ability of RNA-seq technology to discover novel transcript variants and differential expression in previously unannotated genomic regions in sickle cell disease. In addition to detecting expression level changes, RNA-seq technology was also able to identify sequence variation in the expressed transcripts.

Conclusions

Our findings suggest that microarrays remain useful and accurate for transcriptomic analysis of clinical samples with low input requirements, while RNA-seq technology complements and extends microarray measurements for novel discoveries.

Separating the wheat from the chaff: mitigating the effects of noise in a plastome phylogenomic data set from Pinus L. (Pinaceae)

BACKGROUND

Through next-generation sequencing, the amount of sequence data potentially available for phylogenetic analyses has increased exponentially in recent years. Simultaneously, the risk of incorporating 'noisy' data with misleading phylogenetic signal has also increased, and may disproportionately influence the topology of weakly supported nodes and lineages featuring rapid radiations and/or elevated rates of evolution.

RESULTS

We investigated the influence of phylogenetic noise in large data sets by applying two fundamental strategies, variable site removal and long-branch exclusion, to the phylogenetic analysis of a full plastome alignment of 107 species of Pinus and six Pinaceae outgroups. While high overall phylogenetic resolution resulted from inclusion of all data, three historically recalcitrant nodes remained conflicted with previous analyses. Close investigation of these nodes revealed dramatically different responses to data removal. Whereas topological resolution and bootstrap support for two clades peaked with removal of highly variable sites, the third clade resolved most strongly when all sites were included. Similar trends were observed using long-branch exclusion, but patterns were neither as strong nor as clear. When compared to previous phylogenetic analyses of nuclear loci and morphological data, the most highly supported topologies seen in Pinus plastome analysis are congruent for the two clades gaining support from variable site removal and long-branch exclusion, but in conflict for the clade with highest support from the full data set.

CONCLUSIONS

These results suggest that removal of misleading signal in phylogenomic datasets can result not only in increased resolution for poorly supported nodes, but may serve as a tool for identifying erroneous yet highly supported topologies. For Pinus chloroplast genomes, removal of variable sites appears to be more effective than long-branch exclusion for clarifying phylogenetic hypotheses.

Next-generation sequencing and large genome assemblies

The next-generation sequencing (NGS) revolution has drastically reduced time and cost requirements for sequencing of large genomes, and also qualitatively changed the problem of assembly. This article reviews the state of the art in de novo genome assembly, paying particular attention to mammalian-sized genomes. The strengths and weaknesses of the main sequencing platforms are highlighted, leading to a discussion of assembly and the new challenges associated with NGS data. Current approaches to assembly are outlined and the various software packages available are introduced and compared. The question of whether quality assemblies can be produced using short-read NGS data alone, or whether it must be combined with more expensive sequencing techniques, is considered. Prospects for future assemblers and tests of assembly performance are also discussed.

Rep-Seq: uncovering the immunological repertoire through next-generation sequencing

Recent scientific discoveries fuelled by the application of next-generation DNA and RNA sequencing technologies highlight the striking impact of these platforms in characterizing multiple aspects in genomics research. This technology has been used in the study of the B-cell and T-cell receptor repertoire. The novelty of immunosequencing comes from the recent rapid development of techniques and the exponential reduction in cost of sequencing. Here, we describe some of the technologies, which we collectively refer to as Rep-Seq (repertoire sequencing), to portray achievements in the field and to present the essential and inseparable role of next-generation sequencing to the understanding of entities in immune response. The large Rep-Seq data sets that should be available in the near future call for new computational algorithms to segue the transition from 'classic' molecular-based analysis to system-wide analysis. The combination of new algorithms with high-throughput data will form the basis for possible new clinical implications in personalized medicine and deeper understanding of immune behaviour and immune response.

Targeted sequence capture as a powerful tool for evolutionary analysis

Next-generation sequencing technologies (NGS) have revolutionized biological research by significantly increasing data generation while simultaneously decreasing the time to data output. For many ecologists and evolutionary biologists, the research opportunities afforded by NGS are substantial; even for taxa lacking genomic resources, large-scale genome-level questions can now be addressed, opening up many new avenues of research. While rapid and massive sequencing afforded by NGS increases the scope and scale of many research objectives, whole genome sequencing is often unwarranted and unnecessarily complex for specific research questions. Recently developed targeted sequence enrichment, coupled with NGS, represents a beneficial strategy for enhancing data generation to answer questions in ecology and evolutionary biology. This marriage of technologies offers researchers a simple method to isolate and analyze a few to hundreds, or even thousands, of genes or genomic regions from few to many samples in a relatively efficient and effective manner. These strategies can be applied to questions at both the infra- and interspecific levels, including those involving parentage, gene flow, divergence, phylogenetics, reticulate evolution, and many more. Here we provide a brief overview of targeted sequence enrichment, and emphasize the power of this technology to increase our ability to address a wide range of questions of interest to ecologists and evolutionary biologists, particularly for those working with taxa for which few genomic resources are available.

Whole cancer genome sequencing by next-generation methods

Traditional approaches to sequence analysis are widely used to guide therapy for patients with lung and colorectal cancer and for patients with melanoma, sarcomas (eg, gastrointestinal stromal tumor), and subtypes of leukemia and lymphoma. The next-generation sequencing (NGS) approach holds a number of potential advantages over traditional methods, including the ability to fully sequence large numbers of genes (hundreds to thousands) in a single test and simultaneously detect deletions, insertions, copy number alterations, translocations, and exome-wide base substitutions (including known "hot-spot mutations") in all known cancer-related genes. Adoption of clinical NGS testing will place significant demands on laboratory infrastructure and will require extensive computational expertise and a deep knowledge of cancer medicine and biology to generate truly useful "clinically actionable" reports. It is anticipated that continuing advances in NGS technology will lower the overall cost, speed the turnaround time, increase the breadth of genome sequencing, detect epigenetic markers and other important genomic parameters, and become applicable to smaller and smaller specimens, including circulating tumor cells and circulating free DNA in plasma.

Targeted high throughput sequencing in clinical cancer settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity

Background

Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings.

Methods

Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.

Results

We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance.

Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations.

Conclusions

The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - in the long term - result in a more reliable prediction of individual cancer therapies.

Update on HER2 testing for breast and upper gastrointestinal tract cancers

With the regulatory approvals in Europe and the USA of trastuzumab-based anti-HER2 targeted therapy for upper gastrointestinal cancers in 2010, HER2 testing has now become universal for newly diagnosed cases of both breast cancer and adenocarcinomas of esophagus, stomach and gastroesophageal origin. In the 12 years or more since the approval of trastuzumab for breast cancer, general refinements in approaches to HER2 testing, including a greater understanding of the implications of preanalytic factors impacting the test results and the application of standardization of reporting of HER2 test results, have taken place. There has also been continuing development in breast cancer with the introduction of new HER2 tests, including non-FISH tests, dimerization assays, phosphorylated HER2 receptor tests, mRNA-based tests, HER2 gene sequencing tests and the application of HER2 testing to circulating tumor cells. Most recently, the introduction of HER2 testing for upper gastrointentinal malignancies has emphasized the need for performing and interpreting slide-based assays in a manner unique to these specimens and not to apply the breast cancer testing protocols to esophageal and gastric adenocarcinomas.

Comprehensive next-generation cancer genome sequencing in the era of targeted therapy and personalized oncology

DNA sequence analysis has become a significant laboratory test in oncology, permitting treatment to become increasingly personalized for both solid tumors and hematologic malignancies. Traditional approaches to sequence analysis, including Sanger sequencing, pyrosequencing and allele-specific PCR, are now widely used to guide therapy for patients diagnosed with lung and colorectal cancer as well as for melanoma, sarcomas (e.g., gastrointestinal stromal tumors) and subtypes of leukemia and lymphoma. Traditional sequence analysis has been limited in bandwidth and throughput and as a result, has been focused exclusively on testing the most common aberrations in key genes or fully sequencing single genes. The massively parallel or next-generation sequencing (NGS) approach to DNA analysis holds a number of potential advantages over the traditional methods, including the ability to fully sequence large numbers of genes (hundreds to thousands) in a single test. Furthermore, NGS can simultaneously detect deletions, insertions, copy number alterations, translocations and exome-wide base substitutions (including known hot-spot mutations) in all known cancer-related genes. However, significant challenges, particularly with respect to demands on expertise and infrastructure, will have to be overcome to translate NGS to the bedside of the cancer patient. Extensive computational expertise is required to bring NGS into clinical context, and a deep knowledge of cancer medicine and cancer biology will be required to generate truly useful, so-called 'clinically actionable' reports for clinicians. While NGS is on the cusp of being launched as a clinical test, it may be expected that the near future will continue to bring major advances in the technology that will lower the overall cost, speed up the turnaround time, increase the breadth of genome sequencing, and detect epigenetic markers and other important genomic parameters, while becoming applicable to smaller and smaller specimens, including circulating tumor cells and circulating free DNA in plasma.