Identification of Actionable Fusions as an Anti-EGFR Resistance Mechanism Using a Circulating Tumor DNA Assay
Katherine Clifton1, Thereasa A Rich2, Christine Parseghian1
1The University of Texas MD Anderson Cancer Center, Houston, TX.
Purpose:
Gene fusions are established oncogenic drivers and emerging therapeutic targets in advanced colorectal cancer. This study aimed to detail the frequencies and clinicopathological features of gene fusions in colorectal cancer using a circulating tumor DNA assay.
Methods:
Circulating tumor DNA samples in patients with advanced colorectal cancer were analyzed at 4,581 unique time points using a validated plasma-based multigene assay that includes assessment of fusions in FGFR2, FGFR3, RET, ALK, NTRK1, and ROS1. Associations between fusions and clinicopathological features were measured using Fisher's exact test. Relative frequencies of genomic alterations were compared between fusion-present and fusion-absent cases using an unpaired t test.
Results:
Forty-four unique fusions were identified in 40 (1.1%) of the 3,808 patients with circulating tumor DNA detected: RET (n = 6; 36% of all fusions detected), FGFR3 (n = 2; 27%), ALK (n = 10, 23%), NTRK1 (n = 3; 7%), ROS1 (n = 2; 5%), and FGFR2 (n = 1; 2%). Relative to nonfusion variants detected, fusions were more likely to be subclonal (odds ratio, 8.2; 95% CI, 2.94 to 23.00; P < .001). Mutations associated with a previously reported anti-epidermal growth factor receptor (anti-EGFR) therapy resistance signature (subclonal RAS and EGFR mutations) were found with fusions in FGFR3 (10 of 12 patients), RET (nine of 16 patients), and ALK (seven of 10 patients). For the 27 patients with available clinical histories, 21 (78%) had EGFR monoclonal antibody treatment before fusion detection.
Conclusion:
Diverse and potentially actionable fusions can be detected using a circulating tumor DNA assay in patients with advanced colorectal cancer. Distribution of coexisting subclonal mutations in EGFR, KRAS, and NRAS in a subset of the patients with fusion-present colorectal cancer suggests that these fusions may arise as a novel mechanism of resistance to anti-EGFR therapies in patients with metastatic colorectal cancer.
Insights
Gene fusions were detected in 1.1% of advanced colorectal cancer patients using circulating tumor DNA. These fusions, particularly RET, FGFR3, and ALK, may indicate resistance to anti-EGFR therapies.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Gene fusions are recognized as key drivers of oncogenesis and are emerging as therapeutic targets in advanced colorectal cancer.
- Understanding the prevalence and characteristics of these fusions is crucial for developing targeted treatment strategies.
Purpose of the Study:
- To determine the frequencies and clinicopathological features of gene fusions in advanced colorectal cancer.
- To investigate the potential role of gene fusions as a mechanism of resistance to anti-EGFR therapies.
Main Methods:
- Analysis of circulating tumor DNA (ctDNA) from patients with advanced colorectal cancer using a plasma-based multigene assay.
- Assessment for fusions in key genes including FGFR2, FGFR3, RET, ALK, NTRK1, and ROS1.
- Statistical analysis to compare frequencies and correlate fusions with clinicopathological features and genomic alterations.
Main Results:
- Forty-four unique gene fusions were identified in 1.1% of 3,808 patients with detectable ctDNA.
- RET, FGFR3, and ALK fusions were the most prevalent.
- Fusions were significantly more likely to be subclonal compared to non-fusion variants.
- Subclonal mutations associated with anti-EGFR therapy resistance were frequently observed in patients with fusions.
Conclusions:
- Circulating tumor DNA assays can effectively detect diverse and potentially actionable gene fusions in advanced colorectal cancer.
- The co-occurrence of gene fusions and resistance mutations suggests a novel mechanism of resistance to anti-EGFR therapies in metastatic colorectal cancer.
- These findings highlight the importance of comprehensive genomic profiling for guiding treatment decisions.
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