Prospective enterprise-level molecular genotyping of a cohort of cancer patients

Abstract

Ongoing cancer genome characterization studies continue to elucidate the spectrum of genomic abnormalities that drive many cancers, and in the clinical arena assessment of the driver genetic alterations in patients is playing an increasingly important diagnostic and/or prognostic role for many cancer types. However, the landscape of genomic abnormalities is still unknown for less common cancers, and the influence of specific genotypes on clinical behavior is often still unclear. To address some of these deficiencies, we developed Profile, a prospective cohort study to obtain genomic information on all patients at a large tertiary care medical center for cancer-related care. We enrolled patients with any cancer diagnosis, and, for each patient (unselected for cancer site or type) we applied mass spectrometric genotyping (OncoMap) of 471 common recurrent mutations in 41 cancer-related genes. We report the results of the first 5000 patients, of which 26% exhibited potentially actionable somatic mutations. These observations indicate the utility of genotyping in advancing the field of precision oncology.

Figure 1

Technical and bioinformatics steps in the clinical diagnostics pipeline. The timeline from receipt of specimen to generation of a report is 3 to 4 weeks. hMe, homogenous mass-extend; QC, quality control.

Figure 2

Incidence of mutations by gene in our cancer cohort. Of the 2890 mutations detected in 5118 patients, approximately 19% were KRAS mutations, followed by PIK3CA (17% of mutations), TP53 (11%), and BRAF (7%).

Figure 3

Landscape of mutations by gene in our cancer cohort. The frequency of gene mutation (normalized by the number of samples in each category) is indicated on the y axis, genes mutated on the x axis, and cancer type on the z axis. GI, gastrointestinal.