PURPOSE: Although the majority of patients with small cell lung cancer (SCLC) respond to initial chemotherapy, those with disease progression at first response assessment (chemoresistance) have inferior outcomes. There is a need for predictive biomarkers to aid investigators in designing future clinical trials that better stratify patients beyond standard clinical and laboratory parameters and to identify new treatments for this patient subpopulation. We hypothesized that tumor microRNAs (miRNAs) could serve as predictive biomarkers for chemoresistance and prognostic biomarkers for survival of patients with SCLC treated with systemic chemotherapy. PATIENTS AND METHODS: SCLC samples annotated with clinical characteristics and baseline comorbidities were available. miRNA microarray profiling was performed on diagnostic SCLC tumor samples, and analysis was performed using XenoBase, a data integration and discovery tool. Confirmation of the top 16 miRNA candidates was performed using quantitative real-time polymerase chain reaction followed by analyses to determine clinical and miRNA biomarkers associated with chemoresistance and survival. RESULTS: miRNAs significantly associated with chemoresistance were miR-92a-2* (p = 0.010), miR-147 (p = 0.018), and miR-574-5p (p = 0.039). By stepwise multivariate analysis, only gender and miR-92a-2* contributed significantly to survival (p = 0.023) and (p = 0.015), respectively. Baseline comorbidities were not associated with chemoresistance or survival. CONCLUSIONS: Higher tumor miR-92a-2* levels are associated with chemoresistance and with decreased survival in patients with SCLC. Tumor miR-92a-2* may have application in screening patients with SCLC at risk for de novo chemoresistance in an effort to design more tailored clinical trials for this subpopulation. Further validation in independent sample sets is warranted.
PURPOSE: Although the majority of patients with small cell lung cancer (SCLC) respond to initial chemotherapy, those with disease progression at first response assessment (chemoresistance) have inferior outcomes. There is a need for predictive biomarkers to aid investigators in designing future clinical trials that better stratify patients beyond standard clinical and laboratory parameters and to identify new treatments for this patient subpopulation. We hypothesized that tumor microRNAs (miRNAs) could serve as predictive biomarkers for chemoresistance and prognostic biomarkers for survival of patients with SCLC treated with systemic chemotherapy. PATIENTS AND METHODS: SCLC samples annotated with clinical characteristics and baseline comorbidities were available. miRNA microarray profiling was performed on diagnostic SCLC tumor samples, and analysis was performed using XenoBase, a data integration and discovery tool. Confirmation of the top 16 miRNA candidates was performed using quantitative real-time polymerase chain reaction followed by analyses to determine clinical and miRNA biomarkers associated with chemoresistance and survival. RESULTS: miRNAs significantly associated with chemoresistance were miR-92a-2* (p = 0.010), miR-147 (p = 0.018), and miR-574-5p (p = 0.039). By stepwise multivariate analysis, only gender and miR-92a-2* contributed significantly to survival (p = 0.023) and (p = 0.015), respectively. Baseline comorbidities were not associated with chemoresistance or survival. CONCLUSIONS: Higher tumormiR-92a-2* levels are associated with chemoresistance and with decreased survival in patients with SCLC. TumormiR-92a-2* may have application in screening patients with SCLC at risk for de novo chemoresistance in an effort to design more tailored clinical trials for this subpopulation. Further validation in independent sample sets is warranted.
Authors: Xi Liu; Lorenzo F Sempere; Yongli Guo; Murray Korc; Sakari Kauppinen; Sarah J Freemantle; Ethan Dmitrovsky Journal: Transl Res Date: 2011-02-04 Impact factor: 7.012
Authors: Shilpi Arora; Aarati R Ranade; Nhan L Tran; Sara Nasser; Shravan Sridhar; Ronald L Korn; Julianna T D Ross; Harshil Dhruv; Kristen M Foss; Zita Sibenaller; Timothy Ryken; Michael B Gotway; Seungchan Kim; Glen J Weiss Journal: Int J Cancer Date: 2011-03-29 Impact factor: 7.396