Integrated classification of lung tumors and cell lines by expression profiling

Abstract

The utility of cancer cell lines depends largely on their accurate classification, commonly based on histopathological diagnosis of the cancers from which they were derived. However, because cancer is often heterogeneous, the cell line, which also has the opportunity to alter in vitro, may not be representative. Yet without the overall architecture used in histopathological diagnosis of fresh samples, reclassification of cell lines has been difficult. Gene-expression profiling accurately reproduces histopathological classification and is readily applicable to cell lines. Here, we compare the gene-expression profiles of 41 cell lines with 44 tumors from lung cancer. These profiles were generated after hybridization of samples to four replicate 7,685-element cDNA microarrays. After removal of genes that were uniformly up- or down-regulated in fresh compared with cell-line samples, cluster analysis produced four major branch groups. Within these major branches, fresh tumor samples essentially clustered according to pathological type, and further subclusters were seen for both adenocarcinoma (AC) and small cell lung carcinoma (SCLC). Four of eight squamous cell carcinoma (SCC) cell lines clustered with fresh SCC, and 11 of 13 SCLC cell lines grouped with fresh SCLC. In contrast, although none of the 11 AC cell lines clustered with AC tumors, three clustered with SCC tumors and six with SCLC tumors. Although it is possible that preexisting SCC or SCLC cells are being selected from AC tumors after establishment of cell lines, we propose that, even in situ, AC will ultimately progress toward one of two poorly differentiated phenotypes with expression profiles resembling SCC or SCLC.

Figures

Fig 1.

Dendrogram of a two-way hierarchical clustering of 6,141 genes. Samples, colored according to type, are indicated to the left: red, AC; green, SCC; purple, normal; blue, SCLC; black, LCC; orange, carcinoids; brown, fibroblasts; and pink, NSLC. Each column represents a particular gene. Squares are colored according to the log mean expression ratios across four replicates. Red indicates expression ratios greater than 1 (overexpression), green less than 1 (underexpression), and black roughly equal to 1 (no expression change) in relation to the reference sample.

Fig 2.

Identification of genes differentially regulated between tumors and cell lines. Expression change across all samples for 905 genes, the expression of which was generally overexpressed in cell-line samples compared with fresh samples (A), and 1,313 genes, the expression of which was generally underexpressed in cell-line samples compared with fresh samples (B). (C) Two-way hierarchical clustering of 1,804 genes that are differentially regulated between fresh samples and cell lines. The left side of the dendrogram shows the clustering of fresh samples with cell-line samples. Branch colors are as indicated for Fig. 1. The upper dendrogram shows the clustering of genes.

Fig 3.

Dendrogram of the reduced data set of 4,253 genes after filtering for commonly regulated genes in either fresh or cell-line samples. Samples are colored as described for Fig. 1. Groupings indicated on the left represent distinct clusters of particular carcinoma types. cl, cell line sample; fr, fresh tumor sample.

Fig 4.

Expression profiles across all samples of eight selected gene clusters from Fig. 3 showing distinct patterns of expression. The dendrogram and highlighted clusters from Fig. 3 are shown along the bottom and between individual gene clusters for reference. (A) Genes up-regulated in carcinoids. (B) Genes up-regulated in normal tissue. (C) Genes up-regulated in AC and LCC. (D and E) Genes up-regulated in SCC. (F–H) Genes up-regulated in SCLC.