The advent of next generation sequencing (NGS) in the past decade has made a tremendous impact on basic and clinical research. This high-throughput DNA sequencing technology can sequence an entire human genome within a few hours at a cost of just around one thousand US dollars (USD). Only 18 years ago, this feat took the International Human Genome Sequencing Consortium 13 years and three billion USD to accomplish using Sanger sequencing, demonstrating the sheer magnitude in technological development in the last two decades. Advances in NGS have catalyzed progress in countless areas of cancer research, heralding a “molecular age” of cancer. Traditionally, cancer diagnosis rested heavily on histological classification of the tumor. For instance, brain cancers were historically classified by the putative cell of origin, such as astrocytomas or oligodendrogliomas. However, the most recently revised 2016 World Health Organization (WHO) brain tumor guidelines strongly emphasized integration of molecular characteristics into diagnosis, underscoring the mounting importance of tumors’ molecular and genetic properties on clinical practice.
Two facets of NGS in clinical cancer research: diagnostics and treatmentNGS analysis of tumor genomics, transcriptomics, and epigenomics is driving biomarker discovery for cancer diagnostics and tumor stratification. Clinical biomarkers, as defined by the Food and Drug Administration (FDA), can serve diagnostic, prognostic, predictive, and pharmacodynamics purposes in cancer and other diseases. Diagnostic biomarkers are characteristic of a disease and can be used to determine whether an individual has cancer. Prognostic biomarkers forecast the cancer’s natural history without treatment (i.e., aggressive versus less aggressive phenotype by tumor stratification), whereas predictive biomarkers anticipate the patient’s response to therapy. Finally, and importantly for the evaluation of clinical trial success, pharmacodynamics biomarkers indicate a treatment effect.
In addition to biomarker discovery, NGS is ushering in an era of precision oncology, a paradigm shift in cancer management that aims to match a tumor’s molecular characteristics with targeted drugs to improve patients’ prospects. This approach has stimulated a series of new oncological clinical trial designs that employ NGS to identity genetic vulnerabilities in patients’ tumors, which inform treatment options.
NGS of liquid biopsy: A biomarker bonanzaTumors leave evidence of their presence in the human body by shedding circulating cancer cells (CTCs), circulating tumor DNA (ctDNA) and ctRNA, as well as tiny vesicles called exosomes into the circulation. The notion of liquid biopsy for cancer diagnosis by detecting these tumor-derived components has been around a while, but advances were hampered by a lack of sensitivity, specificity, and limitation in the number of genes technologies could analyze. NGS is bringing a swift resolution to this challenge. “The concentration of ctDNA/RNA in blood is extremely low, which means we needed a technology sufficiently sensitive and specific to detect them. NGS made this a reality,” explains Liang Wang MD PhD, professor of Pathology at the Medical College of Wisconsin. He and his team have been using NGS over the past decade to discover novel cancer biomarkers.
“Other nucleic acid detection technologies are limited to known genes, such as microarrays, or are targeted to specific genes, such as digital droplet PCR. But NGS has no limitations. It can detect all nucleic acids from known or unknown genes, short microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), long non-coding RNAs (lncRNAs), and even exotic molecules such as extrachromosomal circular DNAs (eccDNAs),” he elaborated. “When you are seeking diagnostic biomarkers in cancer patients, you do not know initially how nucleic acids in liquid biopsy from cancer patients will differ from healthy individuals. But NGS detects the entire spectrum of nucleic acids, so it is well suited for biomarker discovery.”
Exosomes are extracellular vesicles that contain miRNAs, lncRNAs, messenger RNAs (mRNAs) and other cellular components, and which are actively secreted by living normal and tumor cells. They serve as a method of intercellular communication, and, in cancer cells, promote metastasis, angiogenesis, and immune evasion signaling pathways. Although ctDNA harbors tumor-associated mutations from cancer cells that have undergone apoptosis or necrosis, RNA profiles within exosomes serve as a snap shot of the live tumor cell population. In a series of recent publications, Professor Wang has leveraged NGS for identifying diagnostic and prognostic cancer biomarkers from exosomal RNAs.
“We are using NGS on circulating exosomal RNAs from plasma to identify miRNAs and piRNAs that are differentially expressed in prostate patients versus healthy individuals. These could serve as diagnostic biomarkers for early cancer detection from a simple blood draw,” Professor Wang outlined of the key principles behind his work. “Not only are there differences in circulating RNAs between cancer and healthy patients; we are also finding differences in exosomal miRNA levels among prostate cancer patients with aggressive, metastatic castration-resistant disease versus patients with less aggressive cancer phenotypes. These differentially expressed RNAs could serve as a prognostic biomarker to determine whether the cancer will be less or more aggressive and the anticipated overall of survival of the patient.”
Detection of ctDNA by NGS also has several merits. Since it is a tumor-associated DNA, ctDNA levels can correlate with tumor burden and can be used to monitor disease progression. “After diagnosis, we can use NGS to predict treatment response (predictive biomarker). In advanced prostate cancer patients, we have found that reduced ctDNA content in plasma indicates a promising response to treatment whereas increased ctDNA content following therapy suggests an unfavorable response. NGS can also be leveraged for identifying targetable somatic tumor mutations to guide patient treatment,” Professor Wang explained. “And this concept is extendible in essence to any type of cancer. We and others have used NGS of liquid biopsy to identify biomarkers and/or somatic mutations in lung, breast, ovarian, colon, and metastatic kidney cancer among many others. We do foresee NGS will serve many future applications in cancer diagnostics.”
NGS of patient tumors: Precise drug to patient matchmakerRecent years has seen a mounting interest in molecular characterization of cancers, arising from an increasing appreciation of driver mutations on tumorigenesis. Under the precepts of precision oncology, it is anticipated that targeting actionable (i.e., druggable) driver mutations can produce significant a treatment response and survival benefit in patients, such as the early success of imatinib against Philadelphia chromosome- positive (Ph+) chronic myelogenous leukemia (CML). Some mutations are highly recurrent in specific cancers; for instance, Ph+ occurs in over 90% of CML. However, most driver mutations in the majority of cancers are comparatively rare, raising two challenges for implementation of precision oncology. How to detect rare actionable tumor mutations and how to recruit enough patients to test potential targeted drugs?
“We are performing an NGS profile of each patient enrolled into our LUNG-MAP clinical trial for squamous cell lung cancer,” explained Roy S. Herbst, MD, PhD, professor of Medical Oncology and Pharmacology at the Yale School of Medicine, Chief of Medical Oncology at the Yale Cancer Center and Smilow Cancer Hospital, and associate director for Translational Research at the Yale Cancer Center, Yale-New Haven. “The beauty of NGS is that it is multiplexed. It allows you to detect the full spectrum of genetic alterations present in one tumor biopsy sample. With the patient’s NGS profile in hand, we can then match the right targeted drug to the right actionable tumor mutation at the right time. The trial so far has shown that there are lung cancer mutations that you can target and produce a very profound response in patients.”
LUNG-MAP is one of a number of recent clinical trials that have been launched on the premise of precision oncology and that use NGS to seek actionable tumor mutations. These studies include other umbrella trials, such as ALCHEMIST and BATTLE, and basket trials, such as NCI-MATCH and SUMMIT. Umbrella clinical trials evaluate the efficacy of various targeted agents against several mutations in one cancer type. On the other hand, the basket format of clinical trials performs the same evaluation as an umbrella trial, but on multiple kinds of tumors. “Many actionable mutations are rare, which make it difficult in a traditional trial design to recruit enough patients. Using this newer format of NGS-driven master protocol trial design (i.e., umbrella or basket), patients from all over are recruited into a larger study and profiled by NGS, which serves to funnel patients into the various trial treatment arms based on their actionable mutation(s). Moreover, this trial design enables us to bring these targeted drugs into community practices, to areas all across the country, and to underserved communities through LUNG-MAP,” elaborated Professor Herbst.
The LUNG-MAP trial is testing small molecule drug candidates taselisib, a PIK3CA inhibitor matched to NGS-detected PIK3CA mutations, palbociclib, a CDK4/6 inhibitor matched to CCND1, 2, or 3 mutations or CDK4 amplifications, and AZD4547, an FGFR kinase inhibitor matched to FGFR amplifications, mutations, or fusions. Biologicals are also under evaluation, such as rilotumumab, an antibody against HGF matched to c-MET expression, and MEDI4736, an antibody against PD-L1, which is the nonmatch treatment. These novel NGS-selected agents are pitted against either conventional chemotherapy or an FDA-approved kinase inhibitor erlotinib already indicated for EGFR mutant lung cancer. The trial is designed to assess whether NGS-selected targeted therapy outperforms conventional therapy and to broaden implementation of precision oncology.
This would have important ramifications for how drugs are indicated for cancer treatment. For instance, larotrectinib, a tropomyosin kinase receptor inhibitor, was recently approved by the FDA for indication in any cancer with NTRK fusion, and was the first pan-cancer approval of its kind based on tumor mutation rather than histological type. Will this be a trend in the future? “I would say yes, absolutely,” responded Professor Herbst. “I think we are heading towards personalized care and personalized medicine. And the way to best personalize medicine will be to select the best possible drug against those low frequency mutations detected by NGS.” Will NGS become standard-of-care in the future then? “I think an NGS profile will likely become the standard-of-care, I would agree with that. I think NGS will truly enable personalized medicine in a manner that will bring the greatest benefit for patients through the selection of the optimal treatment option.”