After years of development, engineering, and enhancement, researchers at St. Jude Children’s Research Hospital in Memphis have made available a software system that enables better detection of gene fusions. The system, called CICERO, offers additional insights into cancers as well as new targets for drug treatments. The latest version of CICERO was published in Genome Biology.1
“In both pediatric and adult cancers, gene fusions can be valuable targets for drug treatment,” said Jinghui Zhang, PhD, Chair of St. Jude’s Department of Computational Biology. “In many pediatric cancers, they are the initiating genomic alterations that drive the tumorigenesis of a cancer, which means drugs targeting that gene fusion can effectively treat the cancer.”
Jinghui Zhang, PhD
Dr. Zhang’s lab programmed CICERO to look for RNA segments in the transcriptome that have partial-match normal DNA segments in the reference human genome but also contain fragments that do not match the reference human genome. Thus, CICERO could distinguish the telltale signatures of gene fusions.
The System at Work
“The key to CICERO’s ability to distinguish cancer-causing fusions from technical artifacts was a set of signal-to-noise-recognition procedures programmed into the system,” said first author Liqing Tian, PhD, a bioinformatic research scientist in Dr. Zhang’s laboratory. “These procedures included assembly of the aberrant reads into a mini-genome representing gene fusion, filtering of technical artifacts, and performance of extensive annotation to prioritize potential cancer-causing fusions.”
Liqing Tian, PhD
In addition to automated analysis, a visualization tool called FusionEditor has been developed. “By visually presenting the predicted gene fusions, FusionEditor enables investigators to incorporate their biologic knowledge about this disease to sort out whether fusions discovered by CICERO are likely to be relevant from the disease point of view,” Dr. Zhang said.
To test CICERO’s ability to detect cancer-causing fusions, researchers conducted benchmark tests in which they applied the system to the transcriptomes of 170 pediatric leukemias, solid tumors, and brain tumors whose driver fusions had been previously analyzed by alternative technologies. CICERO outperformed other commonly used methods of detecting driver fusions, the investigators reported.
To apply CICERO to cancer in adults, the researchers reanalyzed RNA sequence data from a glioblastoma and compared the results with previously reported gene fusions in this disease. “Finding any novel fusions in such a reanalysis would be difficult, but if we did, it would prove that CICERO can also be a useful tool for adult cancer,” Dr. Zhang noted. “We did discover several fusions missed by other methods that are definitely targetable by drugs.” The glioblastoma analysis revealed a surprising number of EGFR fusions, which result in a protein missing one end and could lead to the loss of the protein’s off switch and drive the cancer.
St. Jude researchers have implemented CICERO on St. Jude Cloud, an initiative providing data and analysis resources to the global research community. The fusion-gene detection tool is available at https://platform.stjude.cloud/tools/rapid_rna-seq.
DISCLOSURE: This study was funded in part by the National Institutes of Health and ALSAC, the fundraising and awareness arm of St. Jude. For full disclosures of the study authors, visit genomebiology.biomedcentral.com.
REFERENCE
1. Tian L, Li Y, Edmonson MN, et al: CICERO: A versatile method for detecting complex and diverse driver fusions using cancer RNA sequencing data. Genome Biol 21:126, 2020.
