Proteomic Study on Multi-Organ Metastases of Human Ovarian Clear Cell Carcinoma Cell Line in a Xenograft Mouse Model Based on a Novel Sequence-Specific Analysis Strategy.

Background: To investigate the gene regulation of tumor cells in the process of different organ metastasis on a xenograft mouse model and screen the genes involved in the organ-target metastasis of tumor cells.

Methods: A multi-organ metastasis model was constructed with a human ovarian clear cell carcinoma cell line (ES-2) based on a severe immunodeficiency mouse strain (NCG). Differentially expressed tumor proteins among multi-organ metastases were successfully characterized by microliter liquid chromatography-high-resolution mass spectrometry, sequence-specific data analysis and multivariate statistical data analysis. Liver metastases were selected as typical for subsequent bioinformatic analysis. Selected liver metastasis-specific genes in ES-2 cells were validated by sequence-specific quantitation including high resolution-multiple reaction monitoring quantification at protein level and quantitative real-time polymerase chain reaction at mRNA level.

Results: From the mass spectrometry data, a total of 4503 human proteins were identified using the sequence-specific data analysis strategy. Of them, 158 proteins were selected as specifically regulated genes in liver metastases for subsequent bioinformatics studies. Based on Ingenuity Pathway Analysis (IPA) pathway analysis and sequence-specific quantitation, Ferritin light chain (FTL), lactate dehydrogenase A (LDHA) and long-chain-fatty-acid-CoA ligase 1 (ACSL1) were finally validated as specifically upregulated proteins in liver metastases.

Conclusions: Our work provides a new approach to analyze gene regulation in tumor metastasis in xenograft mouse model. In presence of a large number of mouse protein interference, we validated the up-regulation of human ACSL1, FTL and LDHA in ES-2 liver metastases, which reflects the adaptive regulation of tumor cells to the liver microenvironment through metabolic reprogramming.