Broad-scale genome sequencing approaches, including multigene panel testing, whole-exome sequencing (WES), and whole-genome sequencing (WGS), are rapidly being developed and incorporated into a spectrum of clinical oncologic settings, including cancer therapeutics and cancer risk assessment. Several institutions and companies offer tumor sequencing, and institutions are developing "precision medicine" programs that sequence tumor genomes to identify driver genetic alterations that are targetable for therapeutic benefit to patients.[1,2,3] Many of these tumor-based approaches use reference germline DNA sequences to identify pathogenic alterations, which can also provide information on inherited risk of cancers in families. In the genetic counseling and cancer risk assessment -setting, the use of gene panel testing to evaluate inherited cancer risk is becoming more common and may become routine in the near future, with institutions and companies offering gene panel testing to detect alterations in a host of cancer risk-associated genes.
Incidence and Mortality
Estimated new cases and deaths from laryngeal cancer in the United States in 2014:
New cases: 12,630.
The larynx is divided into the following three anatomical regions:
The supraglottic larynx includes the epiglottis, false vocal cords, ventricles, aryepiglottic folds, and arytenoids.
The glottis includes the true vocal cords and the anterior and posterior commissures.
The subglottic region begins about 1 cm below...
These advances in gene sequencing technologies also identify alterations in genes related to the primary indication for ordering genetic sequence testing, along with findings not related to the disorder being tested. The latter genetic findings, termed incidental or secondary findings, are currently a source of significant clinical, ethical, legal, and counseling debate. This section was created to provide information about genomic sequencing technologies in the context of clinical sequencing and highlights additional areas of clinical uncertainty for which further research and approaches are needed.
DNA sequencing technologies have undergone rapid evolution, particularly since 2005 when massively parallel sequencing, or next-generation sequencing (NGS), was introduced.
Automated Sanger sequencing is considered the first generation of sequencing technology. Sanger cancer gene sequencing uses polymerase chain reaction (PCR) amplification of genetic regions of interest followed by sequencing of PCR products using fluorescently labeled terminators, capillary electrophoresis separation of products, and laser signal detection of nucleotide sequence.[6,7] While this is an accurate sequencing technology, the main limitations of Sanger sequencing include low throughput, a limited ability to sequence more than a few genes at a time, and the inability to detect structural rearrangements.
NGS refers to high throughput DNA sequencing technologies that are capable of processing multiple DNA sequences in parallel. Although platforms differ in template generation and sequence interrogation, the overall approach to NGS technologies involves shearing and immobilizing DNA template molecules onto a solid surface, which allows separation of molecules for simultaneous sequencing reactions (millions to billions) to be performed in a parallel fashion.[6,8] Thus, the major advantages of NGS technologies include the ability to sequence thousands of genes at one time, a lower cost, and the ability to detect multiple types of genomic alterations such as insertions, deletions, copy number alterations, and rearrangements. Limitations include the possibility that specific gene regions may be missed, turnaround time can be lengthy (although it is decreasing), and informatics support to handle massive amounts of genetic data has lagged behind the sequencing capability. A well-recognized bottleneck to utilizing NGS data is the need for advanced computational infrastructure to preserve, process, and analyze the vast amount of genetic data. The magnitude of the variants obtained from NGS is exponential; bioinformatics approaches need to evaluate genetic variants for predicted functional consequence in disease biology. There is also a need for user-friendly bioinformatics pipelines to analyze and integrate genetic data to influence the scientific and medical community.[7,9]