Integrative metabolomics and genomics become a popular strategy in cancer research, which facilitate in discovering biomarkers and understanding the molecular mechanisms of carcinogenesis. Since a single metabolomics study with a single analytical platform is hardly able to cover the whole metabolic profile of a disease, systemic reviewing of the published metabolic studies is a convenient way to collect the available differentially expressed metabolites and analyze the metabolism features for a disease. In fact, Li et al. performed similar study, in which seven metabolomics articles and six ESCC mRNA datasets were used for joint-pathway analysis for ESCC(Li et al., 2017). However, only two of the seven studies reviewed in their study were tissue-based metabolomics research article, and the others were from plasma/serum/other fluid -based metabolomics. Metabolite pool in plasma is obviously different from that in tumor. Therefore, the discover from their study can hardly represent the real metabolism features of ESCC. Recently, there is growing number of studies from ESCC tissue-based metabolomics studies available, and it is worthy to conducted a systemic review of ESCC tissue-based metabolomics study to investigate the big metabolic landscape of ESCC. Thus, we performed this study, and screened out 9 relevant articles between 2009 and 2022.
Different analytical tool platforms, including NMR, GC-MS, LC-MS and CE-MS, were used in metabolomics for ESCC. Each platform has its own advantages and limitations, and the reliability of the results obtained from different platforms might have inconsistent result. NMR is non-invasive, rapid, and can detect metabolites in vivo, but has lower sensitivity and limited dynamic range. LC-MS and GC-MS offer improved sensitivity and resolution, while CE-MS is often used for metabolite profiling due to its high sensitivity(Liu and Zhong, 2019). Combinations of multiple analytical techniques, including GC-MS, NMR, and LC-MS, have been widely used to improve the sensitivity, specificity, and selectivity of metabolite detection in recent years(Gao and Xu, 2015). The 9 studies reviewed in this study covered NMR, LC-MS, GC-MS and CE-MS, the combination of multiple analytical techniques provided a comprehensive overview of the differentially expressed metabolites in ESCC. This study revealed that there was a total of 495 unique differential metabolites, 58 high-frequency metabolites with consistent trends.
Based on the results of collected differential metabolites, especially high-frequency metabolites, and the pathway enrichment analysis, dysregulated amino acid metabolism was the most significant metabolic feature in ESCC. The high-frequency metabolite table showed 19 amino acids was reported to altered in ESCC. Most of amino acids, such as L-arginine, glutamate, L-proline, L-aspartic acid, were significantly accumulated in ESCC tissue compared to normal tissue, which indicating an increased uptake of amino acids in ESCC. Glutamine was the only down-regulated amino acid reported in ESCC, and it might be caused by the factor that consumption of arginine was much higher than its absorption from extracellular environment. While glycine and asparagine had inconsistent change trends in different studies. Additionally, the abnormal amino acid metabolism observed in ESCC may serve as a potential biomarker for diagnosis and monitoring of the disease. Targeting amino acid metabolism pathways could be a promising therapeutic strategy, as inhibitors of enzymes involved in amino acid metabolism have shown promising results in inhibiting tumor growth and improving survival. Our previous study(Chen et al., 2021)[22] revealed a significant alteration in amino acid metabolism, such as tryptophan metabolism, was significantly up-regulated in ESCC, and its corresponding amino acid transporters, such as SLC7A5, SLC1A5 and SLC16A10, were evidently over-expressed in ESCC. Some studies have shown that, amino acid transporters, such as SLC7A5 and SLC1A5, are over-expressed in several tumors and essential for cancer cell growth(Wang and Zou, 2020). And the pharmacologic inhibition and knockdown/knockout of these transporters can significantly suppress the proliferation of cancer cells(Kanai, 2022). Therefore, nutritional interventions that target specific amino acids, such as arginine or glutamine, may also be beneficial for patients with ESCC.
Based on the results from enrichment analysis of high-frequency metabolites and joint-pathway analysis, arginine and proline metabolism was illustrated to be a significantly dysregulated pathway in ESCC. Among the top 5 significantly enriched pathways of the high-frequency metabolites, the urea cycle, which was found deregulation in several cancers to maximize the body nitrogen incorporation into tumor growth(Keshet et al., 2018), is included in arginine and proline metabolism. The ammonia recycling exists down stream of arginine and proline metabolism to recover ammonia and keep the balance of nitrogen metabolism in the body, which performs a similar function to the urea cycle. Both of the aspartate metabolism and glycine and serine metabolism have more or less intersection with arginine and proline metabolism through transamination. All of these results hint at the importance of altered arginine and proline metabolism in ESCC.
Arginine, as an important amino acid that plays a critical role in cellular metabolism and immune function(Szefel et al., 2019), was found up-regulated in ESCC in this study. Existing literature reports, altered arginine and proline metabolism has been observed in various tumors, particularly those with chemo resistance and poor prognosis. Arginine is obtained by cells through two pathways under normal physiological conditions: production via the ornithine cycle by ASS1(Szlosarek, 2014) and transport into cells via the CAT1(Satriano, 2004)(Fig. 5). In this study, IHC staining was performed and the result verified the up-regulating expression of CAT1 and the down-regulating expression of ASS1 in ESCC, which implied that CAT1 might be the main cause of increased arginine uptake in ESCC, and targeting this transporter might be a potential therapeutic strategy for this type of cancer. Other reference reported that circulating arginine promotes tumor growth(Poillet-Perez et al., 2018). And this study further supported the concept with CCK8 and clone-formation assays demonstrating that arginine enhances the capacity of proliferation in ESCC cell lines. Therefore, blocking arginine uptake through CAT1 or other means could be a viable therapeutic strategy for ESCC. However, more research is needed to fully understand the role of arginine in ESCC growth and to determine the best approach for targeting arginine and proline metabolism in cancer therapy.
The ornithine is first synthesized from glutamine via glutaminase (GLS), pyrroline-5-carboxylate synthase (P5CS) and ornithine aminotransferase (OAT), or be generated from proline via proline oxidase (PO). Ornithine then enters the urea cycle (shown in the blue area). The enzyme ornithine carbamoyltransferase (OCT) converts the ornithine to citrulline and the argininosuccinate synthetase1 (ASS1) combines citrulline with aspartate to generate argininosuccinate. After that, the enzyme argininosuccinate lyase (ASL) will remove fumaric acid from argininosuccinate to generate arginine. Extracellular arginine can be transported into cells by the cationic amino acid transporters (CAT1) as well. Arginine then converted into ornithine and urea by arginase I/II (ARGI/II). Subsequently, ornithine can be recycled back into arginine through the urea cycle or further converted to polyamines in spermidine and spermine metabolism through ornithine decarboxylase (ODC1) (showed yellow area). Among the above metabolites, up-regulated differentially expressed metabolites show red, down-regulated differentially expressed metabolites show blue and non-differentially expressed metabolites show grey.
Notably, spermidine and spermine biosynthesis, as a downstream metabolic reaction to arginine and proline metabolism, also shown significant alterations in the results of differential metabolite enrichment analysis, 8 out of 18 metabolites in this pathway were differential metabolites, 7 of which showed up-regulation, including ornithine, pyrophosphate, S-adenosylmethionine, spermine, spermidine, putrescine, and 5 were high-frequency metabolites, including adenosine triphosphate, ornithine, S-adenosylmethionine, spermidine, putrescine. In this study, polyamines, including spermidine, spermine, and putrescine, are up-regulated metabolites and IHC staining results indicated the up-regulation of ODC1, a key enzyme involved in polyamine synthesis (Fig. 3A, Fig. 3B). Studies reported that, polyamines are essential for normal cell growth and their depletion results in cytostasis. Dysregulation of polyamine metabolism is common in many cancers, such as prostate cancer, colorectal cancer and ovarian cancer(Du and Han, 2021; Holbert et al., 2022). Elevated polyamine levels are necessary for transformation and tumor progression and targeting polyamine metabolism with inhibitors such as difluoromethylornithine (DFMO), inhibitor of ODC1(Casero et al., 2018), has shown promising results in phase I trials for various cancers. These findings highlight the metabolic specificity of polyamine synthesis in ESCC and suggest the potential feasibility of polyamine metabolic inhibitors in ESCC treatment, which should be further explored.
In conclusion, the joint-pathway analysis of differential genes and differential metabolites explored a relatively wide metabolic landscape for ESCC, and revealed the amino acid metabolism pathways, such as arginine and proline metabolism pathway and polyamine metabolism, as the potential targets for ESCC. However, further functional studies are needed for investigating the potential clinical significance of these metabolic targets in ESCC.