Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

Integrative Genomics Viewer

The past 60 years have seen huge advances in many of the scientific, technological and managerial factors that should tend to raise the efficiency of commercial drug research and development (RD). Yet the number of new drugs approved per billion US dollars spent on RD has halved roughly every 9 years since 1950, falling around 80-fold in inflation-adjusted terms. There have been many proposed solutions to the problem of declining RD efficiency. However, their apparent lack of impact so far and the contrast between improving inputs and declining output in terms of the number of new drugs make it sensible to ask whether the underlying problems have been correctly diagnosed. Here, we discuss four factors that we consider to be primary causes, which we call the 'better than the Beatles' problem; the 'cautious regulator' problem; the 'throw money at it' tendency; and the 'basic research-brute force' bias. Our aim is to provoke a more systematic analysis of the causes of the decline in RD efficiency.

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Diagnosing the decline in pharmaceutical R&D efficiency.

BackgroundThe prevalence and spectrum of predisposing mutations among children and adolescents with cancer are largely unknown. Knowledge of such mutations may improve the understanding of tumorigenesis, direct patient care, and enable genetic counseling of patients and families. MethodsIn 1120 patients younger than 20 years of age, we sequenced the whole genomes (in 595 patients), whole exomes (in 456), or both (in 69). We analyzed the DNA sequences of 565 genes, including 60 that have been associated with autosomal dominant cancer-predisposition syndromes, for the presence of germline mutations. The pathogenicity of the mutations was determined by a panel of medical experts with the use of cancer-specific and locus-specific genetic databases, the medical literature, computational predictions, and second hits identified in the tumor genome. The same approach was used to analyze data from 966 persons who did not have known cancer in the 1000 Genomes Project, and a similar approach was used to analyze data...

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Germline Mutations in Predisposition Genes in Pediatric Cancer

Objectives: Next-generation sequencing (NGS) allows for high-throughput sequencing analysis of large regions of the human genome. We explored the use of targeted NGS for simultaneous testing for multiple mutations in thyroid cancer. Design: A custom panel (ThyroSeq) was designed to target 12 cancer genes with 284 mutational hot spots. Sequencing was performed to analyze DNA from 228 thyroid neoplastic and nonneoplastic samples including 105 frozen, 72 formalin-fixed, and 51 fine-needle aspiration samples representing all major types of thyroid cancer. Results: Only 5–10 ng of input DNA was sufficient for successful analysis of 99.6% of samples. The analytical accuracy for mutation detection was 100% with the sensitivity of 3%–5% of mutant allele. ThyroSeq DNA assay identified mutations in 19 of 27 of classic papillary thyroid carcinomas (PTCs) (70%), 25 of 30 follicular variant PTCs (83%), 14 of 18 conventional (78%) and 7 of 18 oncocytic follicular carcinomas (39%), 3 of 10 poorly differentiated carcinom...

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Targeted Next-Generation Sequencing Panel (ThyroSeq) for Detection of Mutations in Thyroid Cancer

The mitochondrial voltage-dependent anion channel 1 in tumor cells.

Next-generation sequencing (NGS) is arguably one of the most significant technological advances in the biological sciences of the last 30 years. The second generation sequencing platforms have advanced rapidly to the point that several genomes can now be sequenced simultaneously in a single instrument run in under two weeks. Targeted DNA enrichment methods allow even higher genome throughput at a reduced cost per sample. Medical research has embraced the technology and the cancer field is at the forefront of these efforts given the genetic aspects of the disease. World-wide efforts to catalogue mutations in multiple cancer types are underway and this is likely to lead to new discoveries that will be translated to new diagnostic, prognostic and therapeutic targets. NGS is now maturing to the point where it is being considered by many laboratories for routine diagnostic use. The sensitivity, speed and reduced cost per sample make it a highly attractive platform compared to other sequencing modalities. Moreover, as we identify more genetic determinants of cancer there is a greater need to adopt multi-gene assays that can quickly and reliably sequence complete genes from individual patient samples. Whilst widespread and routine use of whole genome sequencing is likely to be a few years away, there are immediate opportunities to implement NGS for clinical use. Here we review the technology, methods and applications that can be immediately considered and some of the challenges that lie ahead.

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Cliff Meldrum

Papers

Next-Generation Sequencing for Cancer Diagnostics: a Practical Perspective