Epidermal growth factor receptor mutations in primary small cell lung cancer:genetic heterogeneity and prognostic impacts
Author(s): TANG Huarong, HU Xiao, YANG Shifeng, XU Yujin, DONG Baiqiang, WANG Jin, KONG Yue, MA Honglian, ZHANG Xiaozuo
Pages: 270-273
Year: 2017 Issue: 3
Journal: Chinese Journal of Radiation Oncology
Keyword: Neoplasm; small cell lung; Epidermal growth factor receptor; Heterogeneity; Prognosis;
Abstract: Objective To conduct a large?scale survey of the epidermal growth factor receptor ( EGFR) mutations among Chinese small cell lung cancer ( SCLC ) patients, and to analyze the genetic heterogeneity and clinical characteristics of EGFR mutations in primary SCLC. Methods From 2009 to 2014, tissue specimens were collected from a total of 557 patients with SCLC.A total of 45 surgery and 512 biopsy samples are included. Dideoxy sequencing was used to determine the EGFR mutations. The chi?square test was used to analyze the correlation between clinical variables and EGFR mutations. Survival analysis was performed using the Kaplan?Meier method. Multivariate prognostic analysis was made by the Cox model. Results In the 557 specimens, 38 had EGFR mutations ( 68%) , containing 3 with E19 deletion, 3 with E21 L858R, 1 with E20 T790M, and others with non?classical mutations. There was no correlation of EGFR mutations with gender, age, or clinical stage. There was no significant difference in proportion of non?smokers between patients with and without EGFR mutations ( 11/36 vs. 86/398, P=0080 ) . After the patient?treatment history matching, patients with EGFR mutations had a significantly longer median overall survival time than those without EGFR mutations ( 24.43± 946 vs. 14.17± 084 months, P= 0020 ) , indicating a better prognosis in patients with EGFR mutations. The Cox regression analysis suggested that limited stage disease, age of<65 years, and EGFR mutations were prognostic predictors ( HR=2610, 1476,0576, P=0000,0010,0039). Conclusions EGFR mutations with high genetic heterogeneity can be found among the patients newly diagnosed with SCLC. EGFR mutations are positively correlated with the survival of patients with SCLC.
Pages: 270-273
Year: 2017 Issue: 3
Journal: Chinese Journal of Radiation Oncology
Keyword: Neoplasm; small cell lung; Epidermal growth factor receptor; Heterogeneity; Prognosis;
Abstract: Objective To conduct a large?scale survey of the epidermal growth factor receptor ( EGFR) mutations among Chinese small cell lung cancer ( SCLC ) patients, and to analyze the genetic heterogeneity and clinical characteristics of EGFR mutations in primary SCLC. Methods From 2009 to 2014, tissue specimens were collected from a total of 557 patients with SCLC.A total of 45 surgery and 512 biopsy samples are included. Dideoxy sequencing was used to determine the EGFR mutations. The chi?square test was used to analyze the correlation between clinical variables and EGFR mutations. Survival analysis was performed using the Kaplan?Meier method. Multivariate prognostic analysis was made by the Cox model. Results In the 557 specimens, 38 had EGFR mutations ( 68%) , containing 3 with E19 deletion, 3 with E21 L858R, 1 with E20 T790M, and others with non?classical mutations. There was no correlation of EGFR mutations with gender, age, or clinical stage. There was no significant difference in proportion of non?smokers between patients with and without EGFR mutations ( 11/36 vs. 86/398, P=0080 ) . After the patient?treatment history matching, patients with EGFR mutations had a significantly longer median overall survival time than those without EGFR mutations ( 24.43± 946 vs. 14.17± 084 months, P= 0020 ) , indicating a better prognosis in patients with EGFR mutations. The Cox regression analysis suggested that limited stage disease, age of<65 years, and EGFR mutations were prognostic predictors ( HR=2610, 1476,0576, P=0000,0010,0039). Conclusions EGFR mutations with high genetic heterogeneity can be found among the patients newly diagnosed with SCLC. EGFR mutations are positively correlated with the survival of patients with SCLC.
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