Genome Analytics Tool Could Advance Cancer Precision Medicine
Researchers have developed a genome analytics tool that could identify cancer-causing mutations and accelerate cancer precision medicine.
Source: Thinkstock
By Jessica Kent
- A team from St. Jude’s Children’s Research Hospital have created a genome analytics tool to detect alterations that drive tumor formations, which could help advance cancer precision medicine.
In a study published in Nature Genetics, researchers detailed the development of the method, called cis-expression or cis-X. Cis-X works by identifying abnormal expression of tumor RNA.
Noncoding DNA, which doesn’t encode genes, makes up 98 percent of the human genome, researchers noted. Growing evidence suggests that more than 80 percent of the noncoding genome is functional and may regulate gene expression.
Population studies have identified variants in noncoding DNA that are associated with an elevated cancer risk, but researchers have discovered only a small number of noncoding variants in tumor genomes that contribute to tumor initiation. Finding these variants required whole genome sequencing analysis of a large number of tumor samples.
"Cis-X is a fundamental change from existing approaches that require thousands of tumor samples and only identify noncoding variants that happen recurrently," said Jinghui Zhang, PhD, St. Jude Department of Computational Biology chair.
"By using aberrant gene transcription to reveal the function of noncoding variants, we developed cis-X to enable discovery of noncoding variants driving cancer in individual tumor genomes. Identifying variants that lead to dysregulation of oncogenes can expand the scope of the precision medicine to noncoding regions for identifying therapeutic options to suppress aberrantly activated oncogenes in tumors."
Cis-X works by searching for genes with altered expression in two ways. Researchers used whole genome and RNA sequencing to find genes that are expressed on just one chromosome and expressed at aberrantly high levels.
"It can be noisy when analyzing the imbalance of gene expression between alleles," said Yu Liu, PhD, first author of the study. "This analysis used a novel mathematical model that makes cis-X a robust tool for discovery."
Cis-X then searches for the cause of the abnormal expression by looking for alterations in regulatory regions of noncoding DNA within a 3D genome architecture. The alterations include changes such as chromosomal rearrangements and point mutations.
"Few functional noncoding variations happen at high recurrence, but they are important drivers of tumor initiation and progression," Zhang said. "Without identifying the noncoding variant, we may not have the full picture of what caused the cancer."
Researchers used the cis-X approach to analyze the cancer genomes of 13 T-cell acute lymphoblastic leukemia (T-ALL) patients with the data generated as a collaboration between St. Jude and Shanghai Children’s Medical Center. The algorithm was able to identify known and novel oncogene-activating noncoding variants as well as a possible new T-ALL oncogene, PRLR.
Researchers also found that the method worked in adult and pediatric solid tumors, including neuroblastoma, a childhood cancer of immature nerve cells. Solid tumors presented a greater analytic challenge, however: Unlike leukemia, solid tumors often have an abnormal number of chromosomes that are not uniformly distributed in the tumor.
The new technique holds important implications for precision medicine in cancer.
"Cis-X offers a powerful new approach for investigating the functional role of noncoding variants in cancer, which may expand the scope of precision medicine to treat cancer caused by such variants," Zhang said.
Cis-X is publicly available at no cost to researchers through GitHub software repository and St. Jude Cloud.
