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Driver genes as predictive indicators of brain metastasis in patients with advanced NSCLC: EGFR, ALK, and RET gene mutations.
- Source :
- Cancer Medicine; Jan2020, Vol. 9 Issue 2, p487-495, 9p
- Publication Year :
- 2020
-
Abstract
- Background: A retrospective analysis verified the role of gene mutations in brain metastasis in patients with non‐small cell lung cancer (NSCLC). Methods: Data from 552 patients with advanced NSCLC treated from January 2015 to June 2017 in the Affiliated Cancer Hospital of Zhengzhou University were retrospectively analyzed. Next‐generation sequencing was used to detect mutations in eight reported driver genes and various risk factors were evaluated. Results: Of the 552 patients with advanced NSCLC, 153 (27.7%) had brain metastases. The univariate analysis showed that age (P =.008), gender (P =.016), smoking history (P =.010), lymph node metastasis (P =.003), and three driver genes, positive epidermal growth factor receptor (EGFR) mutation (P =.001), positive anaplastic lymphoma kinase (ALK) gene fusion (P =.021), and positive rearranged during transfection (RET) gene fusion (P =.003), were the factors influencing the incidence of brain metastasis. Logistic multivariate regression analysis revealed that positive EGFR mutation (P =.012), positive ALK gene fusion (P =.015), positive RET gene fusion (P =.003), pathological type (P =.009), lymph node N2‐3 metastasis (P <.001), and a younger age (P <.001) were independent risk factors for brain metastasis. In addition, a receiver operating characteristic (ROC) curve was plotted with the above factors with an area under the curve = 0.705 (P <.001). Conclusions: An EGFR mutation, ALK gene fusion, and RET gene fusion in advanced NSCLC patients play roles in brain metastasis as positive driver genes. Impact: An EGFR mutation, and ALK and RET gene fusions are risk factors for brain metastasis in advanced NSCLC patients. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20457634
- Volume :
- 9
- Issue :
- 2
- Database :
- Complementary Index
- Journal :
- Cancer Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 141275391
- Full Text :
- https://doi.org/10.1002/cam4.2706