The Power of RNA in Detecting Gene Fusions for Cancer Diagnostics
RNA profiling provides an effective and accurate method of gene fusion detection for clinical oncology diagnostics
Kinase gene fusions—key players in cancer
Gene fusions are hybrid genes formed by inter- or intra-chromosomal rearrangements, such as translocations, inversions, interstitial deletions, or duplications. Many of these somatic alterations play an important role in cancer development. The BCR-ABL gene fusion, first detected in chronic myeloid leukemia patients in the 1960s, was the first gene fusion characterized. Since that discovery, researchers have identified more than 10,000 gene fusions in human cancers, with many noted to be strong drivers of tumorigenesis.
Today, the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer lists more than 32,000 unique gene fusions involving more than 14,000 genes.
Kinase gene fusions comprise an important subclass of oncogenes that are associated with a wide range of adult and pediatric cancers. Combining the 5′ promoter and 3′ kinase domain of two genes, these hybrids often retain kinase activity, which can lead to inappropriate or overexpression via ligand-independent activation. In 2017, a study of 10,000 cancer patients found that novel kinase fusions or kinases with novel fusion partners made up 35 percent of all identified fusions.
Accurate detection of gene fusions is critical for accurate diagnosis and identification of potential therapeutic targets. Kinase fusions are of particular interest in cancer diagnostics, as many are actionable targets for treatment with various tyrosine kinase inhibitors, which show great promise as precision treatments.
Overcoming challenges with conventional diagnostics
Detecting gene fusions in a clinical setting remains a challenge. Most traditional diagnostic methods for identifying gene fusions—i.e., FISH probes and real time-qPCR—require prior knowledge of both fusion partners, meaning identifying novel fusions or fusions with multiple partners is not feasible for patient diagnostics, as each potential fusion would require a validated test. Fusion detection from DNA is further complicated by the fact that fusions often have multiple DNA breakpoints across large intronic regions, making clinical testing impractical and expensive.
Using RNA profiling to detect gene fusions
As fusion sequences are highly conserved at the level of RNA, RNA profiling presents a viable alternative to overcome the inherent variability of DNA fusion events. RNA-seq based transcript profiling offers a more accurate and sensitive diagnostic alternative to DNA-based methods, and is capable of identifying both specific and novel gene fusions using a single assay.
Recommendations for comprehensive genomic profiling (CGP) of tumors in clinical labs state that, where possible, testing should look for fusions and be able to detect novel fusions. To support transcriptomic profiling in clinical oncology, there is a strong need for well-characterized cell-based pan-cancer fusion RNA controls. Cell line-derived reference standards provide a renewable source of high-quality, genetically defined material to aid in the development, validation, and routine monitoring of these next-generation sequencing RNA-seq workflows.
The move toward reliable RNA-based NGS testing in oncology screening will provide clinicians with more powerful and accurate tools to detect gene fusions. In turn, this will improve diagnosis and provide a basis for targeted precision therapies that can improve patient outcomes.