CFL1 expression levels as a prognostic and drug resistance marker in nonsmall cell lung cancer

Abstract

Background: Nonsmall cell lung cancer (NSCLC) is the major determinant of overall cancer mortality worldwide. Despite progress in molecular research, current treatments offer limited benefits. Because NSCLC generates early metastasis, and this behavior requires great cell motility, herein the authors assessed the potential value of CFL1 gene (main member of the invasion/metastasis pathway) as a prognostic and predictive NSCLC biomarker.

Methods: Metadata analysis of tumor tissue microarray was applied to examine expression of CFL1 in archival lung cancer samples from 111 patients, and its clinicopathologic significance was investigated. The robustness of the finding was validated using another independent data set. Finally, the authors assayed in vitro the role of CFL1 levels in tumor invasiveness and drug resistance using 6 human NSCLC cell lines with different basal degrees of CFL1 gene expression.

Results: CFL1 levels in biopsies discriminate between good and bad prognosis at early tumor stages (IA, IB, and IIA/B), where high CFL1 levels are correlated with lower overall survival rate (P<.0001). Biomarker performance was further analyzed by immunohistochemistry, hazard ratio (P<.001), and receiver-operating characteristic curve (area=0.787; P<.001). High CFL1 mRNA levels and protein content are positively correlated with cellular invasiveness (determined by Matrigel Invasion Chamber System) and resistance (2-fold increase in drug 50% growth inhibition dose) against a list of 22 alkylating agents. Hierarchical clustering analysis of the CFL1 gene network had the same robustness for stratified NSCLC patients.

Conclusions: This study indicates that the CFL1 gene and its functional gene network can be used as prognostic biomarkers for NSCLC and could also guide chemotherapeutic interventions.

FIGURE 1. Prognostic value of CFL1 mRNA levels in NSCLC patients

(A) Meta-analysis of cohort data grouped according to the International Staging System for Lung Cancer and CFL1 gene expression level (i.e. upper-fifth vs. lower-fifth), and plotted as survival probabilities using Kaplan-Meier method. Black lines represent patients with low CFL1 expression; red lines with high CFL1 expression. Differences in survival rates were assessed with the log-rank test. Gray lines represent all patients according to tumor staging. P values lower than 0.05 were considered significant. (B) Cox multivariable regression analysis to estimate hazard ratios for cohort clinical covariates and CFL1 expression. Hazard ratios indicate that patients with high CFL1 expression level presented poor outcome.

FIGURE 2. Biomarker performance in early stage NSCLC patients

(A) Kaplan Meier plot are shown for patients in stages I and II (n=85) in the original cohort (testing cohort) stratified by CFL1 expression level and (B) in an independent cohort (validation cohort) obtained from a different set of published NSCLC microarray data (n=67). (C) Biomarker performance estimated by Receiver Operating Characteristic (ROC) analysis. (D) Representative immunohistochemical (IHC) analysis of cofilin immunocontent in tumor biopsies. Healthy human alveolar tissue obtained from tumor margins is mostly negative to cofilin IHC staining (upper left). High staining for cofilin is found within the neoplasic lung cells (asterisks). Original magnification ×200; scale bar = 100 µM.

FIGURE 3. Cofilin immunocontent correlates with tumor invasiveness and resistance against alkylating drugs

Six human NSCLC cell lines composed of adenocarcinomas (H-23, A549, EKVX), large cells (H-460, HOP-92) and squamous-cells carcinomas (H-226) from the NCI-60 panel were selected based on different levels of CFL1 gene expression (http://discover.nci.nih.gov/datasetsNature2000.jsp) to establish the role of CFL1 in tumor aggressiveness, evaluated by assays of cell invasion and drug resistance. (A) Western blot analysis shows that the pattern of CFL1 mRNA (symbols) matches with the level of cofilin immunocontent (bars). (B) Invasion index was obtained by determining the movement of cells through an 8.0 µm pore size, either uncoated (migration) or matrigel-coated (invasion), attracted by a chemotactic gradient of serum. The mean of four fields for each condition in quadruplicates is plotted. *P < 0.02 (Mann Whitney test); **P < 0.0001 (One-way ANOVA).

FIGURE 4. CFL1 mRNA and protein levels vs. drug sensitivity/resistance profile

(A) Microarray meta-data of the cell lines are crossed against GI₅₀ values of 118 standard chemotherapy agents (from NCI-60 drug discovery pipeline). P values have been color coded according to the scale shown; P < 0.05 indicates a significant negative correlation (resistance) while P > 0.95 indicates a significant positive correlation (sensitivity). The major mechanism of drug action is shown (the term “alkylating agents” is used broadly to include platinating agents; Uk: unknown; P90: hsp90 binder; Pi: protein synthesis inhibitor). Each column within the matrix represents the Spearman correlation between gene expression and toxicity of an individual drug. (B) In vitro validation of the citotoxicity for selected drugs assayed by the sulforhodamine B (SRB) method (upper plots). The obtained drug GI₅₀ values were correlated with cofilin immunocontent (lower plots).

FIGURE 5. Prognostic and drug resistance marker of CFL1 functional gene network

(A) Graph model of CFL1 functional gene network vs. alkylating drug sensitivity/resistance profile. Nodes represent gene products; connecting lines indicate physical and/or functional associations according to experimental data (http://string.embl.de/). Gene expression data (http://discover.nci.nih.gov/cellminer/home.do) were crossed against GI₅₀ values of all alkylating agents identified in the resistance panel at Figure 4A. Four CFL1 network partners follow the same resistance profile (red nodes; n = number of drugs for which gene expression showed correlation). Network drawn was built using a spring model algorithm. Further detains in Methods. (B) Two-way hierarchical clustering analysis of NCSLC tumors. This panel presents the NSCLC cohort data (referred to as Testing Cohort in Table 1) arranged according to the gene expression profile of all CFL1 network components. Complete linkage clustering of tumor samples is shown in TREEVIEW format. The color intensity is relative to the log2 ratio of the microarray signal (red: positive values; green: negative values). For visualization purposes, the gene expression values were median centered and normalized using CLUSTER 3.0 software. (c) Kaplan Meier plot of the entire NSCLC cohort data (n=111), where patients are stratified according to the hierarchical clustering analysis of CFL1 functional gene network.