A new way of capturing the molecular alterations of cancer

Mayo Clinic researchers have a new way of plotting how cancer has progressed deep within a patient’s genetic blueprint. It’s a new graphing method called the Genome U-plot that reveals genetic changes taking place on a molecular level. The Genome U-plot’s two-dimensional layout and high spacial resolution make it possible to show chromosomal deletions, breaks, rearrangements and amplifications – which current data visualization charts can’t capture. That could open the possibility of new, targeted therapies for patients who don’t respond to standard treatment.

Research from George Vasmatzis, Ph.D., finds that compared to conventional visual displays, the U-Plot empowers health care providers to better interpret tumor-related genomic alterations. The paper, Genome U-Plot: A Whole Genome Visualization, is published in the December 16, 2017 edition of Bioinformatics.

George Vasmatzis, Ph.D.

“Until now, scientists and health care providers have not been able to take advantage of complete genomic analysis of tumors,” says Dr. Vasmatzis, the co-director of the Biomarker Discovery Program in the Mayo Clinic Center for Individualized Medicine. “The U-Plot layout is the first tool to provide a full picture of the genetic alterations that contribute to tumor growth. This should make it easier for providers to apply genomic analysis to diagnosing, treating and predicting the course of each patient’s individual disease.”

“Visualization is an important aspect of genome-wide analysis. It offers new insights into the genomic data by providing comprehensive views and also the capability to perform exploratory research. Visualization guarantees a faster inspection of the genome data than analyzing standard data on excel sheets and could identify areas that require further investigation.” says Athanasios Gaitatzes, Ph.D., a visualization expert of the Information Technology program in the Mayo Clinic Center for Individualized Medicine.

The Genome U-Plot presents chromosomes in a U-shape, which research shows improves the readability by at least two-fold over standard linear and circular layouts. None of the conventional displays provided a high enough quality image to perform investigative research. The Genome U-plot has enough space that names and locations of relevant genes can be displayed, making it easier to pinpoint variants.

“The U-Plot’s layered approach is the best platform to explore large, multiple data sets that reveal the tumor alterations. It will help interpret these alterations in a comprehensive way. We anticipate this layout method could transform the practice by making genomic information easier to understand, interpret and apply at the point of care,” says Dr. Vasmatzis.

The Biomarker Discovery Program of the Mayo Clinic Center for Individualized Medicine funded this study.