ATLANTA (GenomeWeb) – Combining DNA and RNA sequencing data has proven to be beneficial for researchers seeking to understand more about the biology of adult cancers. Just as the advent of genomics testing helped to make cancer care more personalized for adults, the addition of transcriptomics testing and deep bioinformatics analysis to genomics may generate even more detailed information that clinicians may use to potentially determine diagnosis, prognosis, or make treatment decisions.
Similarly, this paradigm may be coming into play in pediatric cancer care. Pediatric cancers are often problematic for researchers looking for targetable somatic mutations as they're lacking in druggable DNA targets. In this context, transcriptomics analysis can help to fill in the gaps.
Researchers with the Treehouse Childhood Cancer Initiative are particularly focused on using RNA sequencing data to analyze entire genetic pathways, with the hypothesis that because cancer drugs are aimed at these specific pathways, they could be effective in treating pediatric cancers, even if they don't have somatic mutations.
Even more specifically, researchers from the University of California, Santa Cruz — which is part of the Treehouse Initiative — have developed what they're calling gene expression outlier analysis to see if they can identify overexpressed genes that can then be targeted with available cancer treatments. They're also aiming to determine if this kind of RNA-based analysis can bolster efforts to match patients to drugs as opposed to using tumor mutation analysis only.
At the AACR annual meeting in Atlanta yesterday, Co-Executive Director of the Institute for Genomic Medicine at Nationwide Children's Hospital Elaine Mardis detailed her center's efforts to combine DNA and RNA sequencing in the clinical cancer care setting in order to help patients.
The NCH cancer genomic profiling protocol includes tumor and germline whole-exome sequencing, with enhanced coverage of cancer-associated genes and copy-number probes across chromosomes at 250-fold coverage; RNA sequencing; targeted RNAseq assays, including ArcherDx assays to looks for driver fusions; and liquid biopsy testing to monitor disease changes.
Once a patient is diagnosed by a clinician, the researchers use a set of seven bioinformatic tools to search for hundreds of predicted driver fusions, Mardis said. They then look to see if there are any overlaps in fusions predicted by two or more tools, annotate and rank them, and confirm their presence with assays. They also use RNAseq to deconvolute the tumor microenvironment and use a cancer immunotherapy pipeline called pVac to identify and prioritize neoantigens from a list of tumor mutations.
The investigators are also taking advantage of the data being produced by their colleagues at the Treehouse Initiative and UCSC, using the thousands of other cancer patients' RNAseq profiles in the Treehouse database to make comparisons to their own data. By doing this, "You can see where your patient is grouping with other patients with a similar cancer," Mardis said. "This is especially valuable for rare cancers." In turn, the NCH team is contributing its data to the Treehouse database.
When pediatric cancer patients come to NCH, they may be eligible to participate in this research protocol, if their clinicians feel they need additional information to treat them. The hospital — which is part of the international collaborative REDCap Consortium research network — has set up a REDCap database to capture information on patients whose oncologists think they might be suitable for the protocol, either because their disease doesn't have a standard of care, because they've phased out of the standard of care, or because they've tried treatment multiple times. Once the data is collected, Mardis said, researchers at the institute look to determine if the patient is suitable for participation in the protocol.
Mardis detailed one case of a patient whose oncologist submitted him for participation in the protocol after he'd had what appeared to be a second recurrence of medulloblastoma in 2018. The patient had originally been diagnosed in 2012 and been diagnosed with his first recurrence in 2015.
The researchers evaluated tumor samples that had been taken from the original diagnosis in 2012 and from the second recurrence in 2018, as well as germline samples from the patient. They found variants in BRCA2 and RET of unknown significance, and the somatic mutation analysis uncovered 65 variants in the primary tumor and 231 variants in the recurrence. Of all these variants, however, only one was pathogenic and it was unique to the recurrence — a mutation in the PTPN11 gene.
Through a search of the literature and through a differential expression analysis, the team found that this variant was statistically significantly overexpressed in this type of tumor and determined that it might be a druggable target for this patient. But when they compared their data to the RNAseq information in the Treehouse database on medulloblastomas, the researchers saw that the RNA profiles between the primary tumor and the recurrence were distinct from one another and determined that although the primary tumor was indeed medullobslatoma, the recurrent tumor was actually a glioma.
Based on these analyses, this patient's 2018 tumor was reclassified as a secondary malignancy, Mardis said. In fact, studies have found that very few patients with medulloblastoma will relapse post-diagnosis, but these patients are at risk for secondary tumors, many of which are malignant gliomas.
So, this combined DNA and RNA sequencing analysis, along with the comparison to the larger Treehouse database, not only helped the clinician treat the patient, it also confirmed previous research on this type of pediatric cancer.
In pediatric cancer a combination of DNA and RNA sequencing is critical to fully characterizing the tumor and the microenvironment for therapeutic decision-making, Mardis concluded. Further, the rapid communication of new findings is critical to making progress in pediatric cancer research.
"For about 25 percent of the kids, we don't find anything informative. But that means we have a 75 percent batting average," Mardis said. "The RNA really adds to the batting average, which really adds to my enthusiasm for it."
At a media event later in the evening, Mardis told GenomeWeb that she believes the combined DNA/RNA sequencing paradigm will eventually become the norm in pediatric cancer research. The trick will be figuring out what level of information is needed and useful, she added. Is whole-exome sequencing necessary? What kind of targeted RNA panels will work best? These are the types of questions that can be answered by groups like hers and the Treehouse researchers.
She further noted that these studies can help to determine what the costs of such testing are in comparison to how effective and efficient this type of testing paradigm can be for treating patients, which can help to convince payors to provide coverage.