Jeffrey S. Buguliskis Ph.D. Technical Editor Genetic Engineering & Biotechnology News

The Synergy of Two Burgeoning Fields Will Lead to Improved Precision Medicine

In 1928, H.B. Reese, a former dairy farmer working as a shipping foreman for Milton S. Hershey, became inspired and decided to strike out on his own, opening The Harry Burnett Reese Candy Company in the basement of his house. Mr. Reese created one the most popular and beloved confectionery treats—Reese’s Peanut Butter Cups—through the combination of two simple, yet coveted ingredients. By 1970, just under a decade after the merger of Reese’s with Hershey Chocolate Corporation, advertisers developed a marketing campaign that epitomized the brand, culminating with the slogan: “Two great tastes, that taste great together.”

Now you’re probably wondering what this historical anecdote has to do with genomics. Rest assured it won’t morph into a Wonka-esque account of morality sung by dozens of oppressed, orange-faced little people. Put simply—the tale is to highlight the idea that there are many great combinations in the world and when put together the results can be ethereal, such as chocolate and peanut butter or something more pragmatic and invaluable such as the merger of powerful ideas like genomics and immunotherapy.

“The use of genomics in immuno-oncology is really exploding,” remarked Richard Chen, M.D., chief scientific officer at Personalis, a precision medicine company utilizing next–generation sequencing–based clinical diagnostics. “Every tumor is genetically and immunologically different in ways that can significantly affect how it responds to immunotherapy.” Personalis offers researchers and clinicians DNA sequencing and interpretation of human exomes and genomes using its Accuracy and Content Enhanced (ACE) platform. “Genomic approaches like our ACE ImmunoID platform can be used to more comprehensively to characterize the immune genetics of tumors, including neoantigens, tumor escape mechanisms, and tumor immune microenvironment,” Dr. Chen added.

With the approval of several immunotherapy drugs over the past few years, the immunotherapeutics field has enjoyed its share of successes and disappointments. For instance, checkpoint inhibitor drugs—those that target the various pathways related to T-cell activation, proliferation, and induction of tumor cell death—have been effective in treating melanoma, non-small cell lung cancer (NSCLC), and ovarian cancer. Yet, a significant fraction of patients fail to respond to these therapies, which frequently lead to severe complications—a major factor in these therapies often being used as last resort treatments. However, scientists are hopeful that new and ongoing genomic studies will be able to provide insights into better treatment options. The pharmacogenomic efforts could identify specific genetic backgrounds that are sensitive to immunotherapy drugs, as similar efforts have for other chemotherapy regimens.

“Genomics, mRNA expression analysis, and next-generation sequencing (NGS) in particular have accelerated our understanding of how the immune system can influence the outcome of treatments,” explained John Leite, Ph.D., vice president of oncology, market development, and product marketing at Illumina. “It is becoming clearer that a tumor must have the potential to create an immune response complete with an arsenal of active immune cells capable of generating an inflammatory response. Moreover, a body of evidence is emerging that demonstrates somatic sequence variants expressed by a broad spectrum of cancers, can provide a means to predict success of certain immune therapies.”

Fiona Hyland, director of R&D for clinical next generation sequencing at Thermo Fisher Scientific, added that “genomics has enabled direct interrogation of the tumor microenvironment, facilitating the investigation of the types and abundance of cells present and the expression of genes and proteins associated with immune cells and of the tumor.” 


Everything Old Is New Again

The immune checkpoint pathways are but one promising area where genomic intervention is starting to shape drug development and usage. For decades scientists have known that due to mutations present within the genome of tumor cells—and not the surrounding normal tissue—cancer cells produce novel sets of antigens that are expressed on their surface. These so-called neoantigens have been attractive drug and vaccine targets for quite some time. However, due to inefficient isolation and sequencing techniques, neoantigens were “shelved” for more rapid and cost-effective therapeutic approaches.

To truly appreciate the important role genomics plays in identifying key DNA alternations, a brief overview of how the immune system addresses antigens is necessary. T cells obtain their “education” within the thymus gland and, through a process called negative selection, are prevented from recognizing autoantigens, which most often includes tumor antigens. However, since tumors develop new genetic mutations that are not present in the thymus, the neoepitope-specific T-cell repertoire is not affected by the negative selection process. Moreover, since tumors are not homogenous in their mutational profile, i.e., various cells develop new mutations within the tumor often making them genotypically distinct from their neighbor, one tumor could contain thousands of potential neoantigens for the immune system to target. Finally, as mutated antigens are only expressed on cancer cells, T cells specific to these targets should not have negative effects on healthy tissue—thus rendering the mutated antigens ideal targets for therapeutic vaccination.

As a result of the exponential decline in sequencing costs and the concomitant rise in advanced NGS technologies, identification of tumor neoantigens has not only become a practical option, but a highly sought after personalized medicine approach. Clinical evidence in mouse models of cancer using neoantigen targeting strategies has shown this approach to be extremely efficacious and provides the appropriate proof of concept validation for NGS- identified tumor antigens as a potential precision medicine tool. Innovations to single cell sequencing methodologies have allowed investigators to identify neoantigen markers from heterogenous tumor tissues. Additionally, the use of in silico epitope prediction algorithms is moving a once labor-intensive process to one that could see routine clinical use as a diagnostic tool.

“We are working on improving the accuracy of neoantigen prediction because it can ultimately improve the efficacy of vaccines synthesized based on those neoantigens, or any diagnostics that use it as a predictive biomarker,” Dr. Chen noted. “To improve neoantigen predictions, we are innovating on sequencing, informatics, machine learning, and validation strategies.”


Cancer Immunotherapy: A pseudo-colored scanning electron micrograph of an oral squamous cancer cell (white) being attacked by two cytotoxic T cells (red), part of a natural immune response. Nanomedicine researchers are creating personalized cancer vaccines by loading neoantigens identified from the patient’s tumor into nanoparticles. When presented with immune stimulants, the patient’s own immune system is activated, leading to expansion of tumor-specific cytotoxic T cells. [Rita Elena Serda, Duncan Comprehensive Cancer Center at Baylor College of Medicine, NCI, NIH]

Roadblocks Destined to Be Cleared

Integral as genomics has been for recent advances in immunotherapy, the merger of these two heady approaches comes with its own set of challenges. For instance, computational approaches for analyzing sequencing data as well as epitope identification, have not evolved as rapidly as sequencing technology—ultimately creating an information logjam that considerably slows down the research and development pipeline. To their credit, bioinformatists have been up to the task of unjamming the chute by developing new software that has made neoantigen identification a less labor intensive, and even approachable, process for potential routine clinical use. Moreover, since a patient’s HLA type can be extracted from NGS information with high accuracy, that data can now be analyzed with new software to enable epitope prediction of candidate antigens for drug or cancer vaccine development.    

“Developing robust and reproducible technologies that are easy to use, automatable, reproducible, and produce consistent results across labs and operators is critical,” Hyland stated. “Assays need to be affordable, with available easy-to-use analysis tools, and interpretable results.”

Hyland’s statement touches on two critical points that are often taken for granted in the research realm: reproducibility and sample size. When performing in vitro experiments at the bench, it’s fairly simple to work in replicate samples in order to get a hold on sample error rates and experimental variance. However, when attempting to translate basic research findings to clinically useful data, experimental parameters are a significant detail, as replicate numbers of humans are a limiting factor, to say the least.

“Oncology is a rapidly evolving space creating challenges for clinicians, and researchers to keep up with the pace of discovery.” Dr. Leite remarked. “As in any new branch of clinical investigation, processing enough samples to generate statistically significant trends while managing the myriad of confounding clinical variables will always be the main challenges.” 


Hope Remains While Company Is True

The fight against cancer has seen its share of highs and lows over the past several decades, yet there has been an undeniable commonality that has remained consistent—the driving force of innovation. Often set to task on a seemingly simple solution to a minor problem, investigators stumble upon new methodologies that can transform and shape entire fields of research. Because much of the infrastructure for innovation already exists through NGS technology and extensive immunotherapy research, it’s not difficult to envision rapid developments over the next several years.

“We are developing a roadmap that is aligned to a vision where exome/transcriptome analysis will make its way to clinical standard of care,” Dr. Leite stated. “We have great expectations for the NovaSeq platforms to enable exome and transcriptome analysis at higher throughputs and lower costs that will support clinical studies powered with more and more subjects.”  

Yet, sequencing platforms are only one aspect of Illumina’s genomic approach to immunotherapy. Dr. Leite told Clinical OMICs that the company is “developing library preparation tools that are on a regulatory path and have the potential to become a standard methodology for tumor assessment in the future. The first market introduction of these tools is with TruSight Tumor 170, which is a tool for tumor profiling, inclusive of the tumor-driving genes and variants that are relevant for therapeutic research and development.”

Recognizing that NGS is a key technology driver, Hyland said that Thermo Fisher is looking to develop “amplicon-based panels that work well on low input amounts of DNA or RNA, and can be massively multiplex—with the Oncomine series of assays, built on AmpliSeq technology, being a critical enabler.” Hyland continued stating that “the first Oncomine IO assay is the Oncomine Immune Response Research Assay, a single pool that sensitively measures gene expression of approximately 400 genes involved in the immune system, tumor progression, and response.”

Being a precision medicine company, when Personalis looks toward the future it can’t help but stare in the face of the patient within the clinic. “Our feeling is that better immuno-oncology diagnostics and personalized therapeutics like neoantigen-based vaccines powered by genomics platforms like ours will help usher in this future,” said Dr. Chen. “We, as a society, need smarter methods for identifying patients that are likely to respond, and we need ways to boost overall response. We think the future of genomics and immune-oncology are inextricably intertwined.”

Kind of like chocolate and peanut butter. 







































This article was originally published in the March/April 2017 issue of Clinical OMICs. For more content like this and details on how to get a free subscription to this digital publication, go to www.clinicalomics.com.

This site uses Akismet to reduce spam. Learn how your comment data is processed.