Growth of RNA sequencing allows physicians and researchers to analyze a patient’s full genetic profile
By David Spetzler, MS, MBA, PhD
In recent years, advances in precision medicine and next generation sequencing have given physicians a deeper understanding of the molecular alterations driving cancer. This information allows them to make more informed decisions when prescribing therapies and develop customized treatment plans that deliver better outcomes for patients without the need to cycle through less effective therapies to find the right fit.
Now, newer advances in molecular profiling offer the ability to analyze a patient’s DNA, RNA, and proteins to determine which treatments are most likely to limit the progression of the disease. Whole transcriptome sequencing (WTS) analysis, also called RNA-based sequencing, is emerging as an essential component to understand a person’s genetic profile, and this technique has benefits over DNA profiling alone. WTS allows physicians and researchers to find targetable gene fusions and determine the global expression levels of each transcript in a cell, including the identification of splicing variants.
Current Treatment Landscape
Biomarker-directed therapies have improved outcomes for many patients with cancer and have reduced the need for potentially toxic chemotherapy. However, these therapies have proven effective only when patients have their tumors profiled to determine if they are eligible to receive the therapy.
Precision medicine helps match patients to the right therapies and can determine if a tumor is likely to respond to a particular treatment before it’s prescribed. Not only does precision medicine help improve health outcomes, it also helps patients avoid unnecessary side effects and can reduce spending on therapies that, ultimately, may not affect the patient’s cancer.
The average treatment course with modern cancer drugs costs an average of $250,000 per patient. Through precision medicine, patients are more likely to be paired up with the appropriate treatment at the appropriate stage in their disease, limiting unnecessary spending, both on the therapy itself and the resulting care that may be required as a result of suboptimal treatment.
Next Generation Sequencing
Next generation sequencing has changed the way clinicians approach cancer treatment, offering more precise results that are delivered faster. Molecular profiling companies can now sequence DNA, RNA, and proteins to determine which treatments are most likely to have a positive impact on patient care.
DNA sequencing can detect DNA point mutations, insertions or deletions, and copy number alterations, as well as effectively identify intronic and intergenic single nucleotide polymorphisms. Some tests can also detect genomic signatures such as tumor mutational burden, microsatellite instability, loss of heterozygosity, and homologous recombination deficiency.
Whole transcriptome sequencing (RNA) can detect clinically relevant aberrations, gene-fusion events, and splice variants. RNA-based sequencing analysis, which complements DNA profiling, is emerging as an essential component to understanding an individual’s genetic profile.
For example, Caris Life Sciences has expanded the amount of RNA profiling, which is able to measure over 61,000 transcripts in the human genomic system, with an average of 60 million reads per patient and a near 100% success rate. Reflecting its value in driving treatment decisions, updated NCCN guidelines for lung cancer (November 2019) now call for RNA sequencing when feasible.
In addition to comprehensive tissue testing, Caris is also developing methods to measure cancer biomarkers in the blood. Caris’ approach to blood-based liquid biopsy is unique because of the propriety methods of extraction, allowing the company to yield sufficient amounts of nucleic acid from all patients, and measure all 22,000 genes.
Human-machine collaboration provides the most comprehensive analysis available today to characterize a patient’s tumor and support treatment decisions. The complexity of the system is too great for humans to decipher alone, and with artificial intelligence (AI) and machine-learning systems, vast amounts of clinical data can be analyzed using custom cohorts defined by clinicians.
By integrating existing datasets of tumor profiling results inclusive of all 22,000 genes, matched with clinical outcomes and comprehensive patient-specific molecular profile information, physicians can better understand a patient’s cancer and provide informed, personalized treatment.
As patient outcomes databases continue to grow, advanced machine-learning capabilities are increasingly being utilized to identify unique molecular signatures. AI-powered tools can be used to inform decision making by analyzing historical clinical and outcome data to learn from the past and provide a better insight into the treatment of cancer by molecular composition. AI has allowed for the identification of a molecular signature that is highly predictive of benefit from first-line chemotherapy with FOLFOX (in combination with bevacizumab), a gold-standard of care, in patients diagnosed with metastatic colorectal cancer.
Cancer is one of the most complex diseases imaginable. The beauty of machine learning and AI is that we can bring equally sophisticated analyses to bear using the hundreds of thousands of patient’s worth of molecular data and longitudinal outcome data already available.
Progress in precision medicine continues to enhance our understanding of cancer and how it affects the entire genome. It is allowing physicians to develop personalized treatment plans for their patients that utilize the most effective therapies available to them.
AI and machine-learning are rapidly transforming the ability to analyze large amounts of molecular and clinical outcome data to provide never before seen insights into the genetic makeup and treatment of cancer by molecular composition, allowing physicians and researchers to truly decode cancer and improve patients’ lives.
David Spetzler, MS, MBA, PhD, is president and chief scientific officer of Caris Life Sciences. He leads the company’s clinical testing service and development of proprietary technologies to aid in the creation of precision medicine strategies for individual cancer patients and noninvasive technologies to identify and predict early-stage cancer. Spetzler has generated more than 330 patent applications across 37 different patent families and authored more than 30 peer-reviewed journal articles.