The Role of In-Office Next Generation Sequencing to Advance Precision Medicine in Community Oncology

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Targeted Therapies in Oncology, May 2021, Volume 10, Issue 7
Pages: 23

The goal of precision medicine is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize the health benefits for patients.

Precision Medicine (PM) is “an approach to disease prevention and treatment that seeks to maximize effectiveness by considering individual variability in genes, environment, and lifestyle,” according to the Precision Medicine Initiative (PMI).1 After former President Obama announced the PMI in his State of the Union address on January 20, 2015—“to bring us closer to curing diseases like cancer and diabetes and to give all of us access to the personalized information we need to keep ourselves and our families healthier”—the National Health Institute and other global agencies commenced a group under the PMI called the PMI Cohort Program.

The goal of PM is to advance medical and scientific discoveries to offer more tailored, precise, and accurate health interventions to maximize the health benefits for patients.2,3 Essential components of PM include the integration of information from several different sources, including genetic and genomic profiles, imaging data, records from wearable health-tracking devices and lifestyle choices, germline data, and pharmacogenomics. The access and application of these data and associated bioinformatics, using computing power and technological expertise to translate PM into personalized health care, are key.

For community practices, using PM will be greatly beneficial to patients and the practice. To maximize these benefits, PM needs to be integrated into the fabric of the community setting. All professionals in a practice will have to be involved in the development of a PM system, including physicians, pharmacists, lab personnel, nurses, and the patients. Although there have been obstacles to implementing diagnostic and screening tests, these can be overcome and will provide more options for patients with cancer.

Next-generation sequencing (NGS), which is rapidly replacing Sanger sequencing, has matured enough as a technology and found its place both in clinical practice and research. In addition, whole exome sequencing (WES) and/or whole genome sequencing (WGS) are becoming part of daily operation for oncologists and hematologists for exploring clinical trials and drug development for malignancies. The cost efficiency of NGS has improved significantly due to technological, scientific, and operational advances. The cost of deciphering the entire human genome has dropped from $10,000 in 2011 to approximately $1000 in 2021.4 Other drivers of PM include more accurate sequencing, a growing number of targeted therapies, and the recognition of biodiversity in the human genome— especially in oncology and rheumatic illnesses.

Even in monetary aspects, the global market for PM is growing rapidly. Market research estimated the 2016 global market at $44 billion in revenue, and this revenue is forecast to more than triple to $140 billion by 2026.5

The rapid strides in sequencing techniques, bioinformatics, and PM have not been matched with efforts of implementation in day-to-day practice. Factors like integration into practice guidelines, lack of consensus and standardization between different stakeholders regarding minimum number of mutational analysis, germline studies, platforms for testing, and payer coverage threaten realization of PM.6

Challenges for PM Adoption

In addition to factors mentioned above, the biggest challenge for success in PM adoption is lack of diversity in the knowledge of genomics and bioinformatics in research and studies. Minority communities often face discrimination in health care and receive poor medical treatment.7 Outreach to these communities, especially in the research field, has also been characterized by a long history of exploitation, abuse, and marginalization.8 Although hesitancy from ethnic minorities is frequently cited as an excuse for the lack of representative data in PM and clinical trials, real-life observation is somewhat different, with researchers observing that willingness to participate did not differ significantly between ethno-racial groups.9 They also argued that underrepresentation of minority populations is more likely due to the research design of the study or limited accessibility.

Results from genome-wide association studies (GWAS) representing 1.7 million samples conducted in 2009 showed that 96% of participants were of European ancestry. Seven years later, the same GWAS analysis revealed that despite the colossal 35 million samples collected, 81% of participants were still of European ancestry. Clearly, racial and ethnic diversity of the samples still had a long way to go.10 The successful implementation of PM requires the clinical integration of the following (FIGURE 1):

  • Molecular testing of patients for actionable mutations
  • Interpretation of molecular profiling results and identification of matched therapies
  • Identification of patients for clinical trials
  • The creation of a longitudinal journey to understand pharmacogenomics
  • Support for drug development
  • Equitable access to genomic and genetic as well as treatment data

With so many testing options, including NGS, WES, WGS, and whole transcriptome sequencing, healthcare providers now face a complex decision: whether to outsource this testing to centralized laboratories, implement it in their own labs, or create a hybrid model bringing part of the testing in house and using tertiary labs with full bioinformatics and sophisticated testing for thousands of genes for support. With the advent of NGS panels, genomic profiling has become leaner, cheaper, and more user friendly. Everything is quicker in house, with much less chance of losing important material or information. One of the best arguments for in-house genomic profiling is the control it affords over the preanalytical parameters, tissue specimen selection, and sample quality.

For many community oncologists, the latter option to create a collaborative model may enhance the uptake of appropriate molecular testing and address an unmet need, as most of the underserved, marginalized population is served by small- to medium-sized community cancer clinics. We must focus on doing those routine tests quickly, cost effectively, and as locally as possible in collaboration with tertiary labs that have additional testing capabilities and bioinformatics.

Additionally, centralized testing in a collaborative model is another very valuable option. When an FDA-approved treatment option is not available based on local minipanel testing results, additional testing with a much larger panel may provide options for clinical trials for new drug development. This testing may also identify germline mutations, such as BRCA1/2 or other homologous repair defects, and identify other family members at risk. This would allow others to implement appropriate clinical interventions to monitor their risk for disease. A bioinformatics platform will enhance assimilation of genomic, pharmacogenomics, and germline data to create a longitudinal journey and ultimately bring health care equity, address disparities, and enhance new drug developments. Benefits of insourcing NGS include the following (FIGURE 2):

  • Improved patient care
  • Rapid turn around
  • Implementation of PM to the fullest
  • New revenue streams
  • Operational cost savings
  • Ongoing cost control of acute care
  • Better ethnic representation
  • Cost avoidance

In summary, even though the field of PM is still evolving and changing, driver mutation and biomarker-guided therapies have already improved treatment options for thousands of patients with cancer and thousands more are eligible for clinical trials. Because of limitations in access to overall testing, limited uptake of testing—at the most, 25% in non–small cell lung cancer in Caucasians and 14% in ethnic minorities—and skewed data disproportionately representative of Caucasians, the success of PM is not likely to be accomplished unless we explore different ways to approach testing. These include:

  1. Making widespread testing accessible locally;
  2. Improving access to testing for minorities;
  3. Performing additional testing at tertiary centers when an actionable mutation is not identified; and
  4. Adding germline testing (if NGS panel only includes somatic testing)

References:

1. National Institutes of Health. The Precision Medicine Initiative Cohort Program —building a research foundation for 21st century medicine. September 17, 2015. Accessed April 19, 2021. https://bit.ly/2S4v8mF

2. Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793-795. doi:10.1056/NEJMp1500523

3. Ashley EA. Towards precision medicine. Nat Rev Genet. 2016;17(9):507-522.doi:10.1038/nrg.2016.86

4. Thermo Fisher Ion 520 DNA sequencing chip comparison and cost analysis report. ResearchAndMarkets.com. News release. February 9, 2018. Accessed April 27, 2021. https://bit.ly/3vimZcC

5. Global precision medicine market to reach $141.70 billion by 2026, reports BIS Research. BIS Research. News release. December 15, 2017. Accessed April 18, 2021. https://prn.to/3sYEwF6

6. Sholl LM, Aisner DL, Varella-Garcia M, et al; LCMC Investigators. Multi-institutional oncogenic driver mutation analysis in lung adenocarcinoma: the lung cancer mutation consortium experience. J Thorac Oncol. 2015;10(5):768-777. doi:10.1097/JTO.0000000000000516

7. Bhopal RS. Racism in health and health care in Europe: reality or mirage? Eur J Pub Health. 2007;17(3):238-241. doi:10.1093/eurpub/ckm039

8. Cohn EG, Henderson GE, Appelbaum PS. Distributive justice, diversity, and inclusion in precision medicine: what will success look like? Genet Med. 2017;19(2):157-159. doi:10.1038/gim.2016.92

9. Wendler D, Kington R, Madans J, et al. Are racial and ethnic minorities less willing to participate in health research? PLoS Med. 2006;3(2):e19. doi:10.1371/journal.pmed.0030019

10. Popejoy AB, Fullerton SM. Genomics is failing on diversity. Nature. 2016;538(7624):161-164. doi:10.1038/538161a