As Technical Director of the Genomics Shared Resource at the University of California, Davis, Comprehensive Cancer Center, Cliff Tepper routinely faces a series of challenges: monitoring new technologies; adapting platforms for translational use; interrogating a broad array of cancers; and tailoring results reports for investigators with diverse expertise ranging from molecular biology to clinical oncology.
To meet these challenges, Tepper works closely with scientists and physicians — both at the cancer center and at other institutions — and keeps an eye on peer-reviewed research for the latest information about technologies and cancer studies. He also invests in leading informatics solutions to get the best results for his clients. Recently, he began using Ingenuity® Variant Analysis™ from QIAGEN, an application that he calls “phenomenal.”
In a recent study that Tepper presented at this year’s annual meeting of the American Association for Cancer Research, his team used Variant Analysis to filter variants found in circulating tumor DNA from patients with pancreatic cancer. The project aimed to generate proof-of-principle data to understand the utility of circulating DNA for this type of cancer in samples from a cohort of nearly 30 patients. To figure out whether KRAS mutations found in circulating DNA — associated with a poor patient prognosis — were truly representative of the tumor, they also sequenced tumor samples from three of the patients.
“In general what we found was that if we manually looked through the data, the assay does pick up the KRAS mutations in all of the samples,” Tepper says. The challenge is that with some analysis tools, standard threshold settings are too high to detect variants at the low levels seen in the data. “Sometimes these mutants weren’t being called even though the reads were there,” he adds.
But loading the data into Variant Analysis revealed the whole picture. “We can see the mutations there,” Tepper says. “We got a good idea of what somatic mutations were present in the tumor just based on the circulating DNA.” The ability to easily adjust thresholds and change filters in the application is a big advantage for the genomics core team. They can set up a filter cascade for various traits they’re interested in, such as depth of coverage, sequencing quality, common variants, as well as more specialized filters for variants implicated in cancer, mutations associated with cancer therapeutics, and expression levels. Essential information, such as gene location and base change, is shown clearly. And the tool’s inclusion of the COSMIC database makes it a cinch to pick out known somatic mutations.
With his translational focus, the real payoff for Tepper is generating results that can be easily understood by all of his clients. A clinical pathologist who looked over the Variant Analysis results “liked the presentation a lot because it is easy to examine the data, and it’s very clear what it means as well,” Tepper says. “The interface is very user-friendly and you can organize the columns based on the things you’re most interested in seeing. That helps us share this data with oncologists.”
To learn more about Tepper’s research, check out this case study.