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

Nan Ye; Yijin Li; Xin Li; Tao Su; Sisheng Wang; Wen Zheng; Hao Yang; Jingqiu Cheng; Meng Gong

doi:10.31083/j.fbl2803053

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

Front Biosci (Landmark Ed). 2023 Mar 16;28(3):53. doi: 10.31083/j.fbl2803053.

Authors

Nan Ye^{1

2}, Yijin Li¹, Xin Li^{1

2}, Tao Su³, Sisheng Wang³, Wen Zheng³, Hao Yang², Jingqiu Cheng^{1

2}, Meng Gong¹

Affiliations

¹ Laboratory of Clinical Proteomics and Metabolomics, Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan, China.
² Key Laboratory of Transplant Engineering and Immunology of the National Health Commission, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan, China.
³ Metabolomics and Proteomics Technology Platform, West China Hospital, Sichuan University, 610041 Chengdu, Sichuan, China.

PMID: 37005747
DOI: 10.31083/j.fbl2803053

Abstract

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.

Keywords: ES-2 cell line; data independed acquisition; sequence-specific data analysis; severe immunodeficiency mouse; tumor organ-specific metastasis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Carcinoma* / genetics
Cell Line, Tumor
Female
Gene Expression Regulation, Neoplastic
Heterografts
Humans
Liver Neoplasms* / genetics
Liver Neoplasms* / pathology
Mice
Proteomics / methods
Tumor Microenvironment