Genetic fingerprint concerned with lymphatic metastasis of human lung squamous cancer.
BACKGROUND
With the most recent introduction of microarray technology to biology, it becomes possible to perform comprehensive analysis of gene expression in cancer cell. In this study the laser microdissection technique and cDNA microarray analysis were combined to obtain accurate molecular profiles of lymphatic metastasis in patients with lung squamous cell carcinoma.


METHODS
Primary lung squamous cancer tissues and regional lymph nodes were obtained from 10 patients who underwent complete resection of lung cancer. According to the source of lung cancer cells, the samples were classified into three groups: the primary tumor with lymphatic metastasis (TxN+, n=5), the primary tumor without lymphatic metastasis (TxN-, n=5) and matched tumor cells from metastatic lymph nodes (N+, n=5). Total RNA was extracted from laser microdissected tumor samples. Adequate RNA starting material of mRNA from primary tumor or metastatic nodes were labeled and then hybridized into the same microarray containing 6 000 known, named human genes/ESTs. After scanning, data analysis was performed using GeneSpring6.2.


RESULTS
A total of 37 genes were found to be able to separate TxN+ from TxN-. TxN+ have higher levels of genes concerned with structural protein, signal transducer, chaperone and enzyme. TxN- have higher levels of genes coding for cell cycle regulator, transporter, signal transducer and apoptosis regulator. Interestingly, there were no differentially expressed genes between N+ and TxN+.


CONCLUSIONS
The acquisition of the metastatic phenotype might occur early in the development of lung squamous cancer. We raise the hypothesis that the gene-expression signature described herein is valuable to elucidate the molecular mechanisms regarding lymphatic metastasis and to look for novel therapeutic targets.
Ge
Mingjian
M
Department of Thoracic Surgery, the First Affiliated Hospital, Chongqing Medical University, Chongqing 400016, China. mingjian_ge@hotmail.com.
Wang
Mei
M
Wu
Qingchen
Q
Qin
Zhiming
Z
Chen
Li
L
Li
Liangbin
L
Li
Li
L
Zhao
Xiaolong
X