A quantitative analysis of rate-limiting steps in the metastatic cascade using human-specific real-time polymerase chain reaction

Abstract

A quantitative assessment of rate-limiting steps in metastasis has always been challenging because of the difficulty of detecting small tumor cell populations. We have developed a highly sensitive assay for monitoring the metastatic dissemination of human tumor cells in the chick embryo and used this assay to investigate the relative efficacy of sequential stages in the metastatic cascade for two malignant human tumor cells lines, HEp3 and HT1080. This assay is based on the real-time PCR amplification of human alu sequences and exhibits a high sensitivity (25 cells/lung) with a large linear range (50-100,000 cell/lung). The assay is optimized for a high number of replicate in vivo assays (50-100 animals/assay) and can be applied in both experimental and spontaneous metastasis models. Using quantitative alu PCR, we determined that HEp3 spontaneously metastasizes very efficiently and rapidly, generating secondary growth in the lung exceeding 1-2 x 10(4) cells/lung in 7 days. In contrast, spontaneous HT1080 metastasis is 50-100-fold less efficient, resulting in only 200-400 cells/lung in 7 days. By taking advantage of the sensitivity and specificity of the real-time alu PCR assay we were also able to quantitatively assess multiple steps in metastasis including intravasation, arrest of tumor cells in secondary organs of the embryo, and the initial growth and expansion of the arrested tumor cells. A comparative analysis of HEp3 and HT1080 metastasis demonstrates that the relatively low-to-moderate metastatic rate of HT1080 is caused by two distinct deficiencies, an 8-10-fold lower rate of intravasation and a delayed onset of HT1080 growth expansion in the secondary organ. Thus, a very facile metastasis model system coupled with the sensitive, real-time PCR-based assay allows for the identification and quantification of rate-limiting steps in the metastatic cascade for select human tumor cell lines.