Publications

BACKGROUND

Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth.

METHODS

Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES).

RESULTS

cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score<5), 29 had sufficient material to be re-analyzed using a less comprehensive but more sensitive assay, MSK-ACCESS, which revealed somatic mutations in 14/29 (48%). Conversely, 5 patients without alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches.

CONCLUSIONS

cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.