Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer

Juan Ni; Yang Chen; Ningning Li; Diandian Sun; Haixing Ju; Zhongjian Chen

doi:10.21037/tcr-20-3406

Combination of GC-MS based metabolomics analysis with mouse xenograft models reveals a panel of dysregulated circulating metabolites and potential therapeutic targets for colorectal cancer

Transl Cancer Res. 2021 Apr;10(4):1813-1825. doi: 10.21037/tcr-20-3406.

Authors

Juan Ni^{1

2

3}, Yang Chen⁴, Ningning Li^{1

2

3}, Diandian Sun^{1

2

3}, Haixing Ju^{1

2

3}, Zhongjian Chen^{1

2

3}

Affiliations

¹ Institute of Cancer and Basic Medicine (IBMC), Chinese Academy of Sciences, Hangzhou, China.
² Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
³ Experimental Research Centre, Zhejiang Cancer Hospital, Hangzhou, China.
⁴ College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.

Abstract

Background: Colorectal cancer (CRC) is a common gastrointestinal tumor with subtle, often undetectable early symptoms, which means that upon diagnosis, patients often present in the middle or late stages of disease. Therefore, the need for an effective biomarker for the early diagnosis and development of novel therapeutic targets is urgent to prolong patient survival time and reduce mortality.

Methods: Twenty mice were randomly divided into patient-derived xenograft (PDX) model (transplantation of fresh CRC tumor samples) and control groups (10 mice in each group). All the animals were euthanized using isoflurane at the end of the experiment. Gas chromatography-mass spectrometry (GC-MS)-based metabolomic profiling was performed to investigate the differential metabolites in the serum, and publicly available gene expression data (GSE106582) were analyzed to determine dysregulated metabolic pathways. Joint pathway analysis was used to identify potential metabolic targets. Immunohistochemistry analysis was performed to confirm the presence of the identified targets at the protein level.

Results: A total of 96 differential circulating metabolites were identified, which were predominantly involved in amino acid metabolism. In particular, the serum levels of amino acids such as phenylalanine and aspartic acid were significantly downregulated in the PDX group, suggesting an increased consumption of amino acids in CRC. Moreover, both the mRNA and protein levels of the amino acid transporters, SLC7A5 and SLC1A5, were found to be upregulated in CRC.

Conclusions: By combining GC-MS-based metabolomics profiling with a PDX model of CRC our study successfully identified potential diagnostic circulating metabolites. Dysregulated amino acid metabolism was found to be a significant feature of CRC. The amino acid transporters, SLC7A5 and SLC1A5, were identified as potential metabolic therapeutic targets. This study furthers the understanding of the metabolic processes involved in CRC.

Keywords: Gas chromatography-mass spectrometry (GC-MS); amino acid transporter; colorectal cancer (CRC); metabolomics.