Role of Next Generation Sequencing in Oncology

What is Next Generation Sequencing?

Next-Generation Sequencing (NGS) is also referred to as “deep sequencing” or “massive parallel sequencing”. NGS is a broad term that encompasses a number of broad sequencing technique, such as whole genome sequencing (for sequencing the whole human genome), whole exome sequencing (for sequencing the exome, the protein-coding regions of the human genome that constitute about 1% of the human genome), RNA sequencing (for transcriptome analysis), and bisulfite sequencing (for epigenomic profiling).

All the genetic and epigenetic alterations in the cancer cells can be identified by NGS techniques rather than the identification of a few targeted alterations by targeted panels. This technique enables the identification of various individual-specific genetic/epigenetic alterations besides the common genetic alteration observed in a particular cancer type, and thus, have a potential role to play in the development of personalized medicine, a futuristic perspective of cancer therapy.

How Next Generation Sequencing Works?

NSG utilized different solid supports (commonly known as chips or flow cells) to immobilize millions of DNA fragments to be sequenced in parallel. Each DNA strand is uniquely placed on the array of solid support and sequenced in parallel. Thus, this technique enables the parallel sequencing of millions of DNA fragments representatives of the whole genome.

The number of times an individual base is sequenced is known as depth of coverage (DOC). High DOC is generally required for the sequencing cancer genome due to high heterogeneity in cancer cells. Although an increase in the DOC increases the reliability of the sequencing or the chances of all mutation getting identified, it also increases the cost of analysis and the amount of data generated per analysis.

Two types of methods are most widely used for NGS of the DNA, Ion Torrent and MiSeq. In Ion Torrent method, the sequencing is achieved by measuring the change in pH due to the release of a hydrogen ion during DNA polymerase reaction using an integrated semiconductor array for non-optical sequencing.

In MiSeq method, a “sequencing by synthesis” approach is utilized wherein sequencing is done by serial additions of fluorescent-labeled nucleotides to immobilized products across a two-dimensional array that allows for parallel sequencing of thousands of nucleotide strands.

Different studies have demonstrated a high degree of concordance between the two systems. Also, some studies have advocated the use of both systems simultaneously with one confirming the mutations found by another technique.

NGS technologies as powerful cancer diagnostic and prognostic tools

Cancer is a complex disease that results from the accumulation of many DNA mutations that leads to the disruption of cell function, particularly cell cycle control. Understanding the underlying mutations is necessary to cure cancer or manage the deleterious downstream consequences. Next Generation Sequencing (NGS) tools provide a powerful way of understanding cancer genetics and biology. However, due the amount of data these platforms generate the ability to analyze and screen efficiently necessitates some powerful software for NGS analysis. Here we give a short account of sample case studies on NGS application in cancer research and clinical diagnosis, as well as some examples on NGS software tools used to study cancer genetic profiles using NGS and how the outcomes compare to traditional techniques such as FISH.

Case studies

NGS assays target the genome at different scales depending on the purpose of application. These assays can be used to study the complex mutations, gene copy number changes and rearrangements often associated with different types of cancers. For these purposes, NGS assays can be aimed at whole genome, whole exomes and targeted panels studies. One drawback is that because of information overload (thousands and thousands of variable regions) identifying the variant responsible for the disease being studied may be difficult and require a massive dataset (many genomes) to identify the collection of mutations consistently found in affected subjects. However, it is the best option for detecting rare mutations associated with hereditary cancers (Guan et al. 2012) and software for NGS analysis are becoming more and more user-friendly.

Using NGS for translocation detection is superior over conventional detection methods, since it more accurately defines breakpoints, allows for the identification of other partner genes and detection of some cryptic rearrangements (Abel et al. 2014), all in one reaction and dataset. NGS technologies makes it possible to track translocation partners for promiscuous genes such as KMT2A. However, FISH relies on highly trained individuals to score rearrangements by fluorescent microscopy and is an inherently low-resolution method that may be confounded by complex, multiway rearrangements and may require numerous probes to fully elucidate translocation partners for promiscuous genes, such as the mixed-lineage leukemia gene, KMT2A. In this regard, NGS tools become the superior option for disease study.

Role of precision medicine in clinical trials

Cancer precision medicine focuses on adjusting treatment choice and dosage based on the specific genetic profile of the cancer and of the individual (Low et al. 2018). Pharmacogenomics studies investigates how genetic variants in the regions coding for drug metabolism and transportation proteins impact drug target receptors, enzymes and signaling proteins and, in turn, affect the drug efficacy and patient’s response to it (Low et al. 2018). For example, the effect of genomic alterations in cancer drug targets such as EGFR and CDK4/6 (Esfahani et al. 2014, Xu et al. 2017) can be studied in drug trials in order to ascertain treatment adjustments needed to optimize the efficacy of the treatment. The role of NGS platforms in personalized medicine has become increasingly important particularly in the development of laboratory-developed protocols (LDPs) optimized to accommodate as wide a range of the different cancer profiles (Cheng et al. 2015).

Comparing Next-Generation Sequencing Platforms in Oncology

The FoundationOne (F1; Foundation Medicine) test is an NGS test designed to detect the exons of 315 genes associated with cancer and introns from 28 genes known to be involved in rearrangements (Heath 2017). The Guardant360(G360; Guardant Health) NGS test can sequence 70 genes found in DNA circulating in the blood (Heath 2017). Heath (2017) tested the congruency in results of both tests when used in the same patients (n = 9). The results from both tests were also used to compare the treatment routes recommended to patients. The tests identified 45 changes in the genes tested, only 10 of which were shared between both tests and of the 36 drugs appearing in the cases only 9 were shared between the 2 groups. These differences are very important and have major implications in the clinical setting since these tests are performed in thousands of patients.

For NGS technologies to become embedded in clinical practice, they must be rigorously tested for regulatory approval, accepted as routine diagnostic tools, and implemented into clinical trials to ultimately improve patient outcomes.

Pros of Next Generation Sequencing

Cancer is believed to be a genetic disease i.e. various genetic mutations build-up to give rise to cancer. These mutations may be inherited in some cases or in most cases developed due to exposure to different environmental risk factors. This is why most cancers affect old age individuals.

Although similar cancer types share some common characteristics and prognosis, each individual is unique and have a unique set of genetic mutation leading to the disease. NSG has high sensitivity for the identification of all of the concomitant genetic mutations along with the most common mutations previously reported for the disease. This enables the physician to select the most appropriate existing therapy for the patient.

A few cancer types are particularly susceptible to targeted therapy. In such cases, the role of NSG is indispensable for the selection of most appropriate targeted therapy among the various available options with minimal side effects for the patient. Also, in a few cases when the disease is not responding to the available standard therapy, the role of NSG become crucial to identify the driver mutations, and thus, the appropriate targeted therapy.

With the advancement in technology, various new aspects of NGS are evolving that have a potential role in the development of precision medicines. Various applications of the newly available NSG methods include gene fusion detection by sequencing RNA/cDNA, micro microsatellite instability detection by sequencing repeated regions or by evaluating the mutational signatures, detection of cancer (or recurrence in case of treated patients) by sequencing circulating tumor DNA, and others.

Cons of Next Generation Sequencing

it is imperative to note that whole-genome sequencing of many cancers has revealed several thousands of mutations, out of that only a few mutations are responsible for the development of cancer (known as driver mutations) while most of them do not have any role in the development of cancer (known as passenger mutations). Also, due to the heterogenicity of cancer, all cancer cells do not contain the same mutations, which means the mutations detected in the sample might not represent the mutation in all existing cancer cells.

Moreover, mutations in cancer cells might evolve over time, that is, mutations detected at one particular time might not represent the mutation present after some time. All these factors limit the use of NSG for designing a robust targeted medicine that can be beneficial for all patients with a particular cancer type.

Many targeted drugs beneficial at a particular time generally become useless after some time due to the evolution of cancer cells with different mutations. Last but not least, NSG may detect sporadic mutations for which there is no targeted therapy available. Thus, patients would have the only choice to continue the available standard therapy. In such cases, participating in a clinical trial testing an investigational drug may prove to be beneficial.

Challenges and Conclusion

The possibilities of what could be achieved with the rise of next-generation technologies are endless and very exciting. However, filtering, analyzing and storing the high throughput generated data currently requires some powerful NGS software and thus high-performance computers. Storing the large data sets is also very taxing for long-term storage. In addition, there is an urgent need to streamline and ensure congruency in outputs of different NGS software tools. The more data generated the harder it becomes to sift through it all and make sense of what is and is not relevant for whatever question is at hand. This creates the needle in a haystack (or perhaps, needle stack) dilemma. Even when data has been shifted to only include variants found in afflicted subjects that were not present in the controls, it is still very difficult to identify the subset of variants associated with the disease of interest. In addition, tumor-promoting mutations can be found with passenger mutations and distinguishing these may be hard and further complicated with the fact that roles of some of these variants can change depending on the development stage of said tumor. Given the complexity of most cancers and the varieties that may exist the size of the sample size required will also bring with it a plethora of noise variants that may hinder the filtering process. In addition, the amount of data sharing that may be required to make this a fruitful endeavor has huge ethical implications. The level of disclosure that this undertaking will require will also increase the risk of the information being intentionally or unintentionally used introduce biases related to genetic information.

Nonetheless, when considering the age of META-OMICS purely on the research and clinical standpoint, we are living in an exciting age where personalized medicine is progressing towards being an answer to treating a wide range of cancers. In instances where treatment is yet to be discovered, NGS technologies are providing key insights to genetic and epigenetic causes of some of the most debilitating ailments of this era.

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