Journal
SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41598-021-87486-3
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Funding
- National Research Foundation of Korea (NRF) - Korea government (Ministry of Science and ICT) [2019R1F1A1062367]
- National Research Foundation of Korea [2019R1F1A1062367] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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Targeted NGS technology can detect specific mutations in CRC patients, with TP53 and ATM mutations showing significant associations with clinicopathological characteristics and survival outcomes.
Targeted next-generation sequencing (NGS) technology detects specific mutations that can provide treatment opportunities for colorectal cancer (CRC) patients. We included 145 CRC patients who underwent surgery. We analyzed the mutation frequencies of common actionable genes and their association with clinicopathological characteristics and oncologic outcomes using targeted NGS. Approximately 97.9% (142) of patients showed somatic mutations. Frequent mutations were observed in TP53 (70%), APC (60%), and KRAS (49%). TP53 mutations were significantly linked to higher overall stage (p=0.038) and lower disease-free survival (DFS) (p=0.039). ATM mutation was significantly associated with higher tumor stage (p=0.012) and shorter overall survival (OS) (p=0.041). Stage 3 and 4 patients with ATM mutations (p=0.023) had shorter OS, and FBXW7 mutation was significantly associated with shorter DFS (p=0.002). However, the OS of patients with or without TP53, RAS, APC, PIK3CA, and SMAD4 mutations did not differ significantly (p=0.59, 0.72, 0.059, 0.25, and 0.12, respectively). Similarly, the DFS between patients with RAS, APC, PIK3CA, and SMAD4 mutations and those with wild-type were not statistically different (p=0.3, 0.79, 0.13, and 0.59, respectively). In multivariate Cox regression analysis, ATM mutation was an independent biomarker for poor prognosis of OS (p=0.043). A comprehensive analysis of the molecular markers for CRC can provide insights into the mechanisms underlying disease progression and help optimize a personalized therapy.
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