Using Genomic Profiling in Oncology Advances Precision Medicine

Precision Oncology and Genetics

At its very core, cancer is a genetic condition characterized by inherited gene mutations, altered DNA from environmental components, or mistakes during DNA replication. Regardless of the root cause of genetic mutations, cancer care is shifting toward personalized medicine and targeted therapies based on genetic mutations.

Evolution of Genetic and Genomic Profiling in Oncology

While genetic testing is not a new phenomenon in oncology, the varying uses of it by healthcare professionals have evolved in recent years.

For a long time, genetic testing was only used to detect the inherited genes, otherwise known as germline mutations, that may put patients at a higher risk for developing cancer.

For example, genetic testing may have been used to assess cancer risk if an individual had close or multiple family members with a particular type of cancer. The most common example is biomarker testing for mutations in the BRCA1 and BRCA2 genes, which detects an increased risk of breast cancer.

Non-small cell lung cancer is also one that may warrant genetic testing. As cancer research has evolved, clinicians have widened the scope of cancer genomics, diving into different types of testing for all cancer types.

Today, biomarker testing is often used throughout cancer treatments to propose specific treatment options or assess the efficacy of current treatment.

The American Cancer Society (ACS) notes that biomarker testing can be used to evaluate a cancer patient’s response to targeted drug therapy, immunotherapy, and other treatment methods. For example, if a patient presents with a mutation in the EGFR gene, their oncologist may be more likely to recommend EGFR inhibitors.

In addition to assessing genetic mutations to determine which chemotherapy drug is the best, comprehensive genomic profiling can be used for tumor profiling to guide healthcare providers toward the appropriate treatment option.

Currently, colorectal cancer treatments have shifted toward tumor-informed circulating tumor DNA testing. This approach requires the genetic sequencing of solid tumors to determine how much ctDNA a patient has and guide ongoing clinical decisions.

Beyond treatment uses, genetic profiling has also revolutionized cancer research, steering the direction of next-generation cancer treatments. Working backward from known genetic variants, clinicians and researchers are developing therapies to target and address specific mutations.

The use of genetics in cancer treatments is endless. The National Cancer Institute notes that cancer genomic research has been and continues to be a critical tool in the fight against cancer.

COTA and GTC Collaboration

Although cancer genomics has come a long way since its initial discovery, there are still many challenges in gathering the appropriate information. Company leaders hope to advance oncogenomics through the collaboration between COTA and the GTC.

“COTA has rich clinical electronic medical records and clinical data that are deeply curated,” said Miruna Sasu, CEO and President of COTA. “We go into the electronic medical record and take everything there. Then, we put it in an electronic file that can be analyzed and interrogated by researchers, drug developers, and anyone interested in understanding the patient's journey and utilizing patient data to inform decisions.”

COTA collects data in larger data sets that are constantly updated. Beyond the large data set, the organization works with pharmaceutical companies to develop focus cohorts. For example, suppose a company approaches COTA looking for a type of patient with specific inclusion and exclusion criteria. In that case, COTA can narrow its data sets based on the points of interest.

“Many times, we get asked for deeper genomic data,” said Sasu. The desire for additional data has encouraged this collaboration.

Drug developers often want insight beyond the clinical perspective. On a superficial level, a patient’s improvement on a particular drug or treatment regimen may be valuable clinical data for drug approvals and funding. However, if a subset of the participants is not responding to the treatment, principal investigators often look for more insightful data on the pharmacogenomics behind the response.

The partnership with the GTC will provide COTA with the insightful data researchers seek.

“We're going to pair the clinical data with the genomic data to provide a much deeper view of the patient,” said Sasu. “It's useful across various cases for drug developers. They can look within their discovery pipeline. They can even in silico test certain molecules against these end-to-end patients in a database instead of doing it in the clinic first.”

Genomic Testing Collaborative

“GTC does very extensive DNA and RNA profiling. The data we include on the clinical report is minimal because the clinical report cannot be more than 20 pages,” noted Maher Albitar, MD, CEO, and CMO of GTC. “The agreement between us and COTA is that we give them even the raw data and much detail beyond what goes on the report.”

The data that GTC generates takes up to nearly one terabyte of storage, substantially more than 20 pages of data. Although the raw data is generally cleaned up, it is still a significant volume that needs to be merged with clinical data.

“All this data is essential when combined with detailed, carefully collected clinical data. This is a goldmine for doing research, especially for pharmaceutical companies and routine clinical research,” added Albitar.

He notes that looking at mutated genes or molecular abnormalities alone is insufficient. Profiling aims to examine the whole genome and determine why a patient resists therapy or develops more side effects. Those are two simple clinical trends that can be identified through genomic sequencing.

“We focus on 1,600 genes that are involved in oncogenesis. Looking at the whole transcriptome, many genes expressed at high levels mask and overshadow the clinically relevant genes,” said Albitar. “The data we generate give us a significantly better dynamic range.”

Data Analytics

Clinicians can conduct detailed statistical analyses that accurately reflect the points associated with clinical outcomes. Beyond accuracy, clinically relevant statistical data, Albitar revealed that GTC collects unique data compared to similar labs. They RNA sequence liquid biopsies, unlike most other labs.

“I've been the buyer of a lot of genomics data in the past, but I haven't seen such a deep genome data set,” said Sasu.

However, a lot of “noise” is irrelevant to clinicians or researchers when looking at whole genome or whole exome data. With such large data sets, clinicians are unlikely to identify patterns in the genetic test results that could impact research or patient care. GTC’s focus on genes relevant to oncogenesis helps eliminate some of the noise associated with large data sets.

Many companies try to get GTC’s clinical data early in the study. They gather a lot of that data during in vitro and in vivo trials. 

“It’s very inefficient. The laboratories that have to do this work at a drug company aren't typically used to doing it. They develop a very costly and time-consuming assay,” said Sasu.

Comparing Data

Clinical researchers are constantly looking for data to support that a drug can be safe in clinical settings. How can they effectively do that while minimizing spending and adverse reactions? One solution is to screen any patient dosed with the same, similar, or peripheral drug. Data on those patients can help a provider infer certain factors.

“For example, if I have a PD-L1 inhibitor that I would like to put on the market. There are already two out there. If we have RNA and DNA sequences on those patients, I can compare what I'm trying to do to what is happening in the existing patient themselves,” proposed Sasu. “Then I will save time for my clinical trial patients with certain biomarkers because they’ll likely not respond. I have the availability to select patients that can benefit from the drug that I am trying to develop.”

Safety Profile and Post-Market Analytics

Beyond being able to recruit participants effectively, using data from whole genome sequencing positions drug developers to have a better safety profile. Like ruling out patients who are not likely to improve on the drug, clinicians can exclude patients with specific comorbidities and biomarkers that correlate with an increased risk of adverse events.

“Within drug development, there are tons of questions that come back. Post-marketing requirements from the FDA and other kinds of health authorities can be answered with the data at the click of a button,” added Sasu.  

Genomic Data and Precision Medicine

As most sectors of healthcare move toward an era of precision medicine, genomic testing will help push oncology in the same direction.

“If we could do this for all oncology patients to begin with and screen them for all of these at different time points within their progression, we may be able to get to a point where the patient doesn't need to be burdened with a biopsy or a surgical procedure. This introduces a lot of novel ways to look at a patient and their information to make decisions for them in the future,” said Sasu.

Integrating pharmacogenomics in cancer centers globally may improve patient survival rates, minimize adverse reactions, and promote the best treatment option for each patient.

“It is not good enough to say that a drug works in 60% or 30% of the patients. GTC aims to reach the point where researchers can say this drug, with specific biomarkers, will work on 80% or 90% of the patient. It would spare the other patients who will not respond to the therapy,” said Albitar

As the field of pharmacogenomics progresses, the collaboration between COTA and GTC may represent a unique opportunity to grow data sets and integrate genomics with clinical data.

“It's a beautiful collaboration between a data company, a platform company, and a company that does molecular sequencing,” concluded Sasu.