Comprehensive Mutation Profiling of Colorectal Cancer Patients With Lung or Liver Metastasis by Targeted Next-Generation Sequencing.

ABSTRACT

OBJECTIVES: Primary tumor tissue is often analyzed to search for predictive biomarkers and DNA-guided personalized therapies, but there is an incomplete understanding of the discrepancies in the genomic profiles between primary tumors and metastases, such as liver and lung metastases. METHODS: We performed in-depth targeted next-generation sequencing of 520 key cancer-associated genes for 47 matched primary and metastatic tumor samples which were retrospectively collected. RESULTS: A total of 699 mutations were detected in the 47 samples. The coincidence rate of primary tumors and metastases was 51.8% (n = 362), and compared to patients with liver metastases, patients with lung metastases had a significantly greater coincidence rate (P = .021). The number of specific mutations for the primary tumors and liver and lung metastases was 186 (26.6%), 122 (17.5%), and 29 (4.1%), respectively. Analysis of a patient with all three occurrences, including a primary tumor, liver metastasis, and lung metastasis, indicated a possible polyclonal seeding mechanism for liver metastases. Remarkably, multiple samples from patients with primary and metastatic tumors supported a mechanism of synchronous parallel dissemination from primary tumors to metastatic tumors that were not mediated through pre-metastatic tumors. We also found that the PI3K-Akt signaling pathway significantly altered lung metastases compared to matched primary tumors (P = .001). In addition, patients with mutations in CTCF, PIK3CA, or TP53 and LRP1B, AURKA, FGFR1, ATRX, DNMT3B, or GNAS had larger primary tumor sizes and metastases, especially patients with both LRP1B and AURKA mutations. Interestingly, CRC patients with TP53-disruptive mutations were more likely to have liver metastases (P = .016). CONCLUSION: In this study, we demonstrate significant differences in the genomic landscapes of colorectal cancer patients based on the site of metastasis. Notably, we observe a larger genomic variation between primary tumors and liver metastasis compared to primary tumors and lung metastasis. These findings can be used for tailoring treatments based on the specific metastatic site.