Cancer is the second-leading cause of death in the United States, with over 600,000 deaths reported in 2020. The American Cancer Society estimated there would be almost 2 million new diagnoses in the US for 2021 — and that’s just for the four most prevalent cancers.
With these elevated diagnostic numbers, clinicians and scientists are always working to find solutions for patients afflicted with cancer. More and more frequently, oncologists turn to the genome for detection, diagnosis, and therapeutic decisions.
Traditionally, cancer researchers have used Sanger sequencing to test for genetic mutations. Sanger sequencing has a few limitations. Most notably, its small sample size only allows researchers to look at a small fragment of DNA at a time. There is no opportunity for massively parallel sequencing. But, cancer care can become targeted and personalized to the patient through next-generation sequencing (NGS).
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In cancer research, NGS is often used to identify genetic variations and mutations. Researchers and clinicians use NGS to look at large portions of DNA and RNA at once. Then, they identify any abnormalities that could be related to the disease.
Sanger sequencing, by contrast, sequences small sections of DNA using electrophoresis. Increasingly, Sanger sequencing is used to validate results after areas of interest are identified using NGS.
Both technologies are still used in cancer diagnosis and treatment; however, NGS offers several benefits over Sanger.
Next-generation sequencing provides more data in a shorter amount of time. It gives researchers the ability to sequence the entire genome, or parts of the genome known to cause disease. Sanger, by comparison, can only sequence small sections of DNA at a time. Sanger sequencing would take years to sequence an entire genome; with NGS, it takes about a week.
Next-generation sequencing can also be combined with signal detection, which previously was a separate process. Most notably, NGS is massively parallel. It allows for greater amounts of data to be read after a single test on one sequencing flow cell.
Using next-generation sequencing to diagnose, assess, and treat cancer lower costs for oncology patients. It is sometimes partially or fully covered by insurance companies, which can save patients thousands of dollars in oncological care, as well as provide faster turnaround times for labs.
Compared to Sanger sequencing, next-generation sequencing has greater throughput. While Sanger sequencing can only sequence about 1,000 base pairs, with NGS the whole genome can be analyzed. Larger quantities of samples are not needed to get more data.
Because of this, more data is generated using fewer samples with high throughput sequencing.
Next-generation sequencing reliably detects genes associated with tumor formation and progression. Its high sensitivity makes it a good choice for detecting rare or infrequent mutations. In a clinical setting, this means that the data is targeted to produce the most accurate results personalized to the patient.
In a study published in BMC Clinical Pathology, researchers sampled breast and ovarian tumor tissue to examine BRCA1 and BRCA2 genes. These areas are known for germline mutations that increase a person's likelihood of developing ovarian or breast cancer. Patients with these mutations are also more likely to benefit from ADP ribose polymerase inhibitors during treatment.
This data proves that NGS can identify BRCA1 and BRCA2 variants if that variant is present in >10% of a tissue sample. These results indicate NGS could be used to make better decisions for treating cancer patients.
When clinical oncology meets patient personalization through the application of next-generation sequencing, targeted diagnosis can be integrated into cancer care. Next-generation sequencing offers a way to target cancer where it begins in the genome. The technology detects variants at a sensitive and ultra precise level, reimagining the standard in cancer diagnosis and care.
Retinoblastoma (RB) diagnosis is a good example of NGS in use. The cancer has many different RB1 gene mutations. Historically, it has been difficult to analyze at the molecular level.
In a 2015 study, researchers sampled genetic material from 33 RB patients and their family members. They developed a process to identify single nucleotide variants, copy number variations, and insertions and deletions. They also were able to differentiate between somatic and germline mutations.
This research showed that NGS is effective in identifying variants of RB in clinical practice. The study also identified nine previously unknown variants, providing further insight into the disease.
As technology advances, next-generation sequencing makes sequencing integral to the future of personalized medicine. Tumor genetic profiling allows clinicians to make more informed treatment choices. It also helps clinicians predict the outcome of treatment.
For example, in a rectal cancer study, 194 alterations were identified in 102 patients’ cancer genes. 42% of participants had KRAS, NRAS, and BRAF mutations. These mutations mean those patients are unlikely to have success with anti-epidermal growth factor receptor therapy. However, many of these alterations are the target of alternative therapies.
If treatment can be designed to target specific tumor genetic profiles, failed responses to therapies and poor prognoses can be avoided.
Cancer treatment and research are constantly evolving. To learn about other other multiomics applications, take a look at our other articles:
The Role of Liquid Biopsy in Clinical Oncology >
Next-Generation Sequencing in Pancreatic Cancer Management >