Enhancing the landscape of colorectal cancer using targeted deep sequencing

Abstract 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 associ...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Chul Seung Lee, In Hye Song, Ahwon Lee, Jun Kang, Yoon Suk Lee, In Kyu Lee, Young Soo Song, Sung Hak Lee
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/bc1682915852470cb11b41551d5a7ba5
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Abstract 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.