Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

Abstract

Methods: We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.

Results: Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR. Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.

Conclusion: The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.

Figure 1

Venn Diagramm of significantly regulated genes comparing adenocarcinomas, squamous cell carcinomas and small cell lung cancer to normal lung tissue (NT). The 3 genes that were overexpressed in all 3 tumor types were chromosome condensation protein G (overexpression in AC vs. NT, SCC vs. NT and SCLC vs. NT was 2.2, 2.1 and 3.2-fold, respectively); collagen, type I, alpha 1 (overexpression in AC vs. NT, SCC vs. NT and SCLC vs. NT was 7.98, 3.24 and 2.4-fold, respectively) and mesoderm specific transcript homolog (overexpression in AC vs. NT, SCC vs. NT and SCLC vs. NT was 2.9, 4.5 and 14.8-fold, respectively).

Figure 2

Consensus tree of hierarchical clustering of AC (A1–A10), SCC (P1–P10), SCLC (K1–K10) and lung tissue samples (NT) as a control without cancer (N1–N5) using the genes with the higherst differential expression according to the fold change from the comparison of AC vs. NT, SCC vs. NT and SCLC vs. NT. Data are displayed by a color code. Green, transcript levels below the median; black, equal to the median; red, greater than median. The effective length of the dash after sample separation visualizes the degree of similarity of the different samples.

Figure 3

Corroboration of the results from microarray analysis using RT-PCR. The gene expression levels were normalized to a housekeeping gene (RPS11) for calculating ΔΔCt values. A ΔΔCt value of 1 corresponds to a Fold Change of 2. A) adenocarcinomas (AC), B) squamous cell carcinomas (SCC) and C) small cell lung cancer (SCLC).