“Next-gen” is short for next-generation sequencing (NGS). It is a type of sequencing technology or a method to determine the order of nucleotides in a particular specimen, such as a DNA molecule. Sometimes the technology is referred to as second-generation sequencing, as it is the newer sequencing technology. Sanger sequencing, which was first described in 1975 by Frederick Sanger,1 is considered first-generation sequencing and is still widely used in clinical testing. It is extremely accurate and is considered the gold standard. However, a major limitation of Sanger sequencing is its throughput. Throughput is the amount of DNA sequence that can be read with each sequencing reaction. It is estimated that sequencing an entire genome with Sanger-based methods on one machine would take approximately 60 years and cost up to $30 million.2 Thus, Sanger-based technology is not practical for analyzing large amounts of data and has limited research and clinical applications. As a result, newer technologies were needed. Such technology emerged in the mid 2000s in the form of NGS.3 Over the last 5 years, this technology has transitioned from the research to the clinical setting and is routinely used for noninvasive prenatal testing, multigene panels, and exome analysis.4
NGS is a term used to refer to the various high-throughput DNA sequencing platforms available that are capable of sequencing large numbers of different DNA sequences in parallel. Thus, NGS is also referred to as massively parallel sequencing. Massively parallel sequencing results in a much higher throughput than Sanger sequencing, and, as a result, multiple genes can be analyzed more quickly and for a lower cost. Additionally, bar coding allows for pooling of patient samples.5 Technological advances, coupled with the US Supreme Court ruling in June 2013 that genes cannot be patented,6 changed the landscape of inherited cancer testing and has resulted in multiple entities offering multigene testing options. Such tests may be targeted for a particular disease type, such as breast or colon cancer, or may encompass a variety of genes with or without overlapping phenotypes. Because of the variety of options available, clinicians may find it helpful to have a basic understanding of the various steps involved in NGS and how variations in each can affect the final product—the patient’s clinical report.
NGS consists of 3 main steps. These are sample preparation, sequencing, and data analysis.5 For a multigene cancer test, the typical specimen is blood or saliva. Most NGS platforms require platform-specific adapters. Thus, when the specimen arrives at the laboratory, genomic DNA must be isolated and then prepared for the NGS platform being utilized. Preparation for a multigene cancer test involves a target enrichment step. This step “targets” the genes of interest included on a particular panel. Different platforms use various sequence enrichment methods and, thus, have different benefits and limitations. All platforms have the ability to sequence millions of DNA fragments in parallel.5 Additionally, sample preparation may involve bar coding and fragmentation of DNA. Each of these nuances allows room for variation.
After a specimen is prepared, sequencing takes place on the designated platform. The final quality and accuracy of the data can be affected by the platform chosen for the task at hand, as each platform differs in its sequence capacity, sequence read length, and run time.5 This step also relies heavily on bioinformatics support, as massive amounts of data are produced.
The sequenced data must then be analyzed. The various bases must be called, and reads must be correctly aligned to the reference sequence. Each base has various short reads that align to it. The number of reads that overlap a particular location is referred to as coverage. The variants (differences in DNA being analyzed compared with the reference sequence) must then be called and annotated. Sufficient coverage is essential for accurate identification and annotation of variants.7 In areas with inadequate coverage, Sanger sequencing is often utilized to ensure accuracy. This information must then be translated into the clinical report. Again, each of these steps allows room for variation.
Compiling and analyzing the massive amount of data produced by NGS require extensive bioinformatics and computing power. The ability to shorten turnaround time and automate steps in analysis is dependent on advances in bioinformatics and computing power. As technology continues to improve, knowledge of gene functions increases, and more variants are characterized, whole exome and genome sequencing are anticipated to replace targeted panels.
NGS cancer panels have been clinically available only since 2012 and have included BRCA since 2013. In this short time period, the impact on diagnosing inherited cancer syndromes has been demonstrated. No longer must a clinician rely on a sequential testing strategy; rather he or she can utilize a concurrent approach via a multigene test. For example, historically, a woman diagnosed with breast cancer at age 34 might have BRCA1/2 testing, and, if the result was negative, TP53 analysis might then occur. Depending on the family history, other genes might be in the differential diagnosis. Assuming that TP53 was negative, these additional genes might then be analyzed.
However, such an approach is often not realistic when a woman and her healthcare team are relying on this information for surgical decision making, and, even when time is not an issue, such an approach is often cost prohibitive. NGS has helped lessen these barriers via the creation of targeted panels. Additionally, through these targeted panels the phenotypic knowledge of cancer syndromes has begun expanding, and there have been increased diagnoses in syndromes previously thought to be rare.4,8,9 NGS and genetics are in their infancy, and the clinical utility of testing will continue to expand.
1. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A. 1977;74(12):5463-5467.
2. Rizzo JM, Buck MJ. Key principles and clinical applications of “next-generation” DNA sequencing. Cancer Prev Res. 2012;5(7):887-900.
3. Pilgrim SM, Pain SJ, Tischkowitz MD. Opportunities and challenges of next-generation DNA sequencing for breast units. Br J Surg. 2014;101(8):889-898.
4. Laduca H, Stuenkel AJ, Dolinsky JS, et al. Utilization of multigene panels in hereditary cancer predisposition testing: analysis of more than 2,000 patients [published online ahead of print April 24, 2014]. Genet Med. doi:10.1038/gim.2014.40.
5. Rehm HL, Bale SJ, Bayrak-Toydemir P, et al; Working Group of the American College of Medical Genetics and Genomics Laboratory Quality Assurance Committee. ACMG clinical laboratory standards for next-generation sequencing. Genet Med. 2013;15(9):733-747.
6. American Civil Liberties Union. BRCA FAQs.https://aclu.org/free-speech/brca-faqs. Accessed June 23, 2014.
7. Zhang J, Chiodini R, Badr A, et al. The impact of next-generation sequencing on genomics. J Genet Genomics. 2011;38(3):95-109.
8. Walsh T, Casadei S, Lee MK, et al. Mutations in 12 genes for inherited ovarian, fallopian tube, and peritoneal carcinoma identified by massively parallel sequencing. Proc Natl Acad Sci U S A. 2011;108(44):18032-18037.
9. Cragun D, Radford C, Dolinsky JS, et al. Panel-based testing for inherited colorectal cancer: a descriptive study of clinical testing performed by a US laboratory [published online ahead of print February 9, 2014]. Clin Genet. doi:10.1111/cge.12359.