Concordance and Discordance in Tumor Genomic Profiling

Abstract

Systematic tumor genomic profiling has the following two overarching objectives in clinical oncology: the matching of a cancer drug to a specific tumor genetic context and the identification of tumors for which use of a specific therapy would prove futile or harmful. The impact of KRAS-oncogene mutations on cetuxumab response in colorectal cancer (CRC) comprises an instructive example of the latter, whereas BRAF and PIK3CA mutations (among many others) are being used to assign patients with cancer to clinical trials of exciting new targeted agents. However, the extent to which genetic heterogeneity modifies both the spectrum of actionable genetic alterations during tumor evolution and their diagnostic evaluation before patient stratification remains a subject of debate. In the article that accompanies this editorial, Vakiani et al present a genomic profiling study of 736 frozen CRC specimens obtained from more than 600 patients. The authors used mass spectrometric genotyping to identify known activating mutations in KRAS, NRAS, BRAF, and PIK3CA oncogenes, which are commonly mutated in CRC. The mutational status of TP53, which is the most common CRC tumor-suppressor gene, was determined by using Sanger sequencing. A subset of tumors was analyzed by using array-based comparative genomic hybridization. The spectrum of genomic aberrations identified was characteristic of CRC. RAS and PIK3CA mutation frequencies (43% and 12%, respectively) were virtually identical in primary and metastatic tumors. BRAF mutations were notably less frequent in metastatic specimens, which may have been related to the aggressive disease course that is typical of this subtype (eg, comparatively few patients with BRAF mutatations may have survived or been candidates for a rebiopsy). TP53 mutation frequencies increased steadily from 8% of adenomas to 53% of metastases. The key findings were derived from the following two subgroups: a set of 84 patients for whom both primary and metastatic specimens were available and a second group of 31 metastatic pairs obtained from the same patient. An initial analysis of these subgroups uncovered the following pivotal observation of the study: the mutational concordance between matched pairs across the five cancer genes analyzed ranged from 89% to 95%. At one level, this result could be interpreted favorably because it provided reassurance against major technical variances in sample preparation or mutation detection. In contrast, a 5% to 10% discordance rate raised two worrisome possibilities that either the genetic testing platforms rendered inaccurate mutation calls in some instance, or patient-matched specimens occasionally harbored distinct mutation profiles. The approach of the authors to sort through the basis for discordant mutational spectra provided a generally instructive framework for clinicians and translational investigators who seek to apply mutational profiling more broadly in the cancer genomic era. Clearly, a 5% to 10% discordance rate between assay results and the ground truth of the lethal tumor fraction could prove highly detrimental to treatment or clinical trials on the basis of genetic criteria. The failure of a diagnostic assay to detect KRAS or NRAS mutations present in CRC tumors (false-negative results) may lead to the futile use of cetuximab (ie, several weeks of ineffective and costly treatment and the potential for unwarranted adverse effects). Conversely, false-positive KRAS results could result in the failure to administer cetuximab-based therapy, which affords clinical benefit in some KRAS wild-type tumors. In other solid tumor contexts (eg, EGFR mutations and erlotinib treatment in non–small-cell lung cancer), mutational false positives might also lead to the erroneous use of anticancer agents. Assortments of methodologic and biologic factors influence the likelihood of false-positive or false-negative tumor genomic profiling results (Fig 1). Certain technical aspects are germane to the genetic assay itself, such as the robustness and reproducibility of the technology used. Another procedural component relates to the quality of the tumor DNA obtained for analysis. In the study by Vakiani et al, fresh or frozen tumor material was used for the primary analysis, which generally yields high-quality tumor genomic DNA. More often, archival specimens stored as formalin-fixed, paraffin-embedded (FFPE) tissue comprise the most accessible clinical option. However, formalin can fragment the genomic DNA and introduce chemical modifications during the fixation and storage process that lead to false-positive mutation calls. The latter effect poses a particular risk when polymerase chain reaction (PCR) followed by Sanger sequencing is applied to small quantities of degraded genomic DNA from FFPE material. Techniques that augment the quantity of genetic material (such as whole-genome amplification) can also produce false-positive mutation calls. Similarly, false-negative results may occur when heavily degraded FFPE DNA is used in small quantities. Known as the allele dropout phenomenon, these mistakes arise when the mutant allele fails to be sampled during PCR amplification. The likelihood of allele dropout JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 30 NUMBER 24 AUGUST 2