PURPOSE: Cofilin is a cytoskeletal protein whose overexpression has been associated with aggressiveness in several types of malignancies. Here, we established and optimized a simple semi-quantitative immunohistochemistry (SQ-IHC) method for cofilin quantification in tumor biopsies, and applied it in a retrospective cohort of NSCLC patients aiming at validating the use of cofilin-1 as a prognostic biomarker. METHODS: The SQ-IHC method for cofilin-1 quantification was established and applied in a NSCLC cohort. An archival collection of biopsies from 50 patients with clinicopathological information and 5 years follow-up was accessed. Association between cofilin-1 immunocontent and clinical outcome was assessed using standard Kaplan-Meier mortality curves and the log-rank test. To evaluate the robustness of our findings, three different partitional clustering strategies were used to stratify patients into two groups according to the biomarker expression level (hierarchical clustering, Kmeans and median cutoff). RESULTS: In all the three different partitional clustering we used, survival analysis showed that patient with high cofilin-1 immunocontent had a lower overall survival rate (P < 0.05), and could be used to discriminate between good and bad prognosis. No other correlation was found when the variables age, sex or histological type were tested in association with patients outcome or with cofilin immunocontent. CONCLUSIONS: Our method showed good sensitivity/specificity to indicate the outcome of patients according to their cofilin immunocontent in biological samples. Its application in a retrospective cohort and the results presented here are an important step toward the validation process of cofilin-1 as a prognostic biomarker.
PURPOSE:Cofilin is a cytoskeletal protein whose overexpression has been associated with aggressiveness in several types of malignancies. Here, we established and optimized a simple semi-quantitative immunohistochemistry (SQ-IHC) method for cofilin quantification in tumor biopsies, and applied it in a retrospective cohort of NSCLCpatients aiming at validating the use of cofilin-1 as a prognostic biomarker. METHODS: The SQ-IHC method for cofilin-1 quantification was established and applied in a NSCLC cohort. An archival collection of biopsies from 50 patients with clinicopathological information and 5 years follow-up was accessed. Association between cofilin-1 immunocontent and clinical outcome was assessed using standard Kaplan-Meier mortality curves and the log-rank test. To evaluate the robustness of our findings, three different partitional clustering strategies were used to stratify patients into two groups according to the biomarker expression level (hierarchical clustering, Kmeans and median cutoff). RESULTS: In all the three different partitional clustering we used, survival analysis showed that patient with high cofilin-1 immunocontent had a lower overall survival rate (P < 0.05), and could be used to discriminate between good and bad prognosis. No other correlation was found when the variables age, sex or histological type were tested in association with patients outcome or with cofilin immunocontent. CONCLUSIONS: Our method showed good sensitivity/specificity to indicate the outcome of patients according to their cofilin immunocontent in biological samples. Its application in a retrospective cohort and the results presented here are an important step toward the validation process of cofilin-1 as a prognostic biomarker.
Authors: M S Pepe; R Etzioni; Z Feng; J D Potter; M L Thompson; M Thornquist; M Winget; Y Yasui Journal: J Natl Cancer Inst Date: 2001-07-18 Impact factor: 13.506
Authors: Vassilios N Kotiadis; Jane E Leadsham; Emma L Bastow; Aline Gheeraert; Jennafer M Whybrew; Martin Bard; Pekka Lappalainen; Campbell W Gourlay Journal: J Cell Sci Date: 2012-02-17 Impact factor: 5.285
Authors: Stephen T Muth; May Tun Saung; Alex B Blair; MacKenzie G Henderson; Dwayne L Thomas; Lei Zheng Journal: Cancer Lett Date: 2020-11-30 Impact factor: 8.679