Abstract
Oncologists are increasingly using information obtained from investigations of the tumor genome to find individualized therapies for patients. They specifically search the hereditary information of cancer cells for mutations that drive malignant growth. Targeted drugs against many of these cancer-typical cellular alterations have already become available.
However, how precisely and reliably do the numerous laboratories that specialize in this search around the globe identify individual cancer mutations? And how does the quality and type of sequencing influence results? A team of experts collaborating within the International Cancer Genome Consortium (ICGC) launched an interlaboratory test to find out. They distributed the DNA of a tumor to five ICGC laboratories and compared the quality of the resulting sequencing data records. The data record that had the highest quality was subsequently sent out to another 17 ICGC institutes for bioinformatic evaluation.
The investigators, led by Ivo Gut, Ph.D., from the Spanish National Center for Genome Analysis, and Roland Eils, Ph.D., from the German Cancer Research Center (DKFZ), found significant variations both in sequencing and evaluation results in some of the cases. Only 40% out of 1,000 small mutations, which each affected the exchange of only a single DNA base, were identified uniformly by all participating teams. The outcome for small DNA losses and insertions was even less favorable: Only a single one out of 337 of these genomic changes was identified by all of the centers.
The DNA sequence from the circular experiment, which the participating ICGC labs have sequenced up to 300 times and analyzed, has now been made available for download. The study (“A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing”), which included over 8o researchers from 78 research centers, is published in Nature Communications.
Centro Nacional de Analisis Genómico, (CNAG-CRG)
Laboratories that start out in the field of genome analysis can use this data as a basis to check whether the bioinformatic methods they are using are capable of detecting all mutations concealed therein. In addition, the team developed evaluation guidelines that stipulate, among others, threshold values for detecting a particular mutation.
“Since tumor genome analysis is becoming increasingly common in cancer medicine, rigorous quality control is necessary, like in any other diagnostic method,” says David Jones, Ph.D., a scientist at the DKFZ. “After all, whether or not a patient survives may depend on the detection of a particular mutation that can be treated efficiently with a drug that is already available.”