Revealing Colon Cancer Resistance with Identification of Glutamate Metabolites by Proton MR Spectroscopy In Vivo and the Molecular Mechanism

Abstract

This study aimed to investigate the ability of 1H-MRS to evaluate drug-resistant colon cancer in vivo. Xenograft tumour mouse models were generated by parental SW480 cells (5-FU-responsive) or SW480/5-FU cells (5-FU-resistant). After 1H-MRS was performed on these Xenograft tumour mouse models, the tumour lesions were resected for the in vitro assessment of the expression of drug resistance-related proteins and glutathione metabolism-related enzymes. The tumours from SW480/5-FU mice showed significantly higher levels of choline, Glx1, and Glx2 detected by 1H-MRS than the tumours from SW480 mice (P < 0.05). The SW480/5-FU tumours also showed higher expression of glutathione metabolism-related enzymes (P < 0.05). The 1H-MRS-detected metabolites showed positive correlations with the expression levels of drug resistance-related proteins and glutathione metabolism-related enzymes. Glx1 and Glx2 metabolites detected in vivo by 1H-MRS may be biomarkers of 5-FU drug resistance in colon cancer.

1. Introduction

The most common treatment for patients with advanced colorectal cancer (CRC) is palliative chemotherapy with a 5-fluorouracil (5-FU)-based regimen [1]. Unfortunately, the progression-free survival period is only 8.7–12.3 months [2]. Multidrug resistance (MDR) occurs frequently and remains the major obstacle in CRC treatment [2, 3, 4].

For patients with CRC, knowledge of the drug resistance status of their tumour(s) is very important because this information will serve as the basis for the therapeutic strategy and adjusting this strategy as the treatment progresses. At present, drug sensitivity/resistance testing relies on in vitro assays [5]. The tumour is a heterogeneous and pleomorphic cell group with irregular differentiation. Because a biopsy is required to obtain tumour tissue for testing via the in vitro method, the drug resistance status detected is representative of only the biopsy area, and that of the remaining tumour in situ is unknown. The invasive biopsy procedure itself is a major drawback. Moreover, the time needed for obtaining a clinical sample and laboratory testing is long. Undoubtedly, an in vivo method that will accurately and conveniently evaluate the drug resistance status of a tumour is urgently needed.

Studies have identified multiple factors involved in MDR, and the biological processes affected by these factors vary widely, including but not limited to the efflux pump system [6], epigenetic modification [7], cell protection pathways [8, 9], oxidative stress [10], and anti-apoptotic signalling [11]. Obviously, the aetiology of MDR can be multifactorial and potentially cross-level.

One of the most common methods through which tumours acquire drug resistance involves the induction and activation of efflux transporters such as P-glycoprotein (P-gp), which affect the drug transmembrane balance at the plasma membrane [12]. Increased expression of P-gp leads to a decrease in drug accumulation in cells [13, 14]. P-gp activity can be regulated by protein phosphorylation catalysed by protein kinase C (PKC). Thus, the absorption of drugs by cancer cells is reduced [15, 16, 17].

The second mechanism that imparts drug resistance to cancer cells occurs at the intracellular level. This genetic system involves CYP3A4 [18] and glutathione-S-transferase (GST) [19], both of which are enzymes that contribute to cell detoxification and hinder the accumulation of potentially heterologous organisms in cancer cells [5]. The detoxification function of glutathione has also been shown to play an important role in the development of colon cancer resistance to 5-FU.

Magnetic resonance spectroscopy (MRS) is a noninvasive magnetic resonance imaging (MRI) technique that indirectly reflects changes in the metabolic state of living tissues and organs by measuring changes in the chemical composition of a certain area of the human body [20]. 1H-MRS is sufficiently sensitive to detect changes in key metabolites of the metabolic pathway related to the glutathione (i.e., GSH) system in the tumour [20].

Studies on gliomas (the most common type of brain tumour) have found that tumour cells increase glutamine through metabolic reprogramming to provide an abnormally depleted energy source [21, 22], suggesting that an increase in glutamine concentration is related to therapeutic resistance and proliferation of tumour [23]. MRS has been used to quantify changes in metabolites induced by metabolic reprogramming, distinguishing between proliferative gliomas and brain metastases [24, 25]. Clinical longitudinal studies in patients with glioblastomas suggested that pretreatment glutamine and glutamate levels detected by 1H-MRS in glioblastomas were correlated with tumour proliferation and poor prognosis [26].

Our study first demonstrated that 1H-MRS can detect increases in the glutamate metabolism complex (Glx1 and Glx2) in vivo in 5-FU-resistant xenograft tumours, which reflect increased glutathione biological synthesis [27]. Therefore, 1H-MRS may play an important role in the detection of molecular markers of changes in tumour resistance in vivo. In the present study, we opted to investigate the changes in GSH metabolites between 5-FU-responsive and 5-FU-resistant colon cancer tissue via in vivo 1H-MRS with 3.0 T MRI. This preliminary investigation aims to provide knowledge on the characteristic metabolites and molecular mechanisms of the drug resistance of CRC.

2. Research process

2.1 Methods

2.1.1 Cell lines and resistance index

The human colorectal adenocarcinoma cell line SW480 was obtained from the Experimental Animal Center of Sun Yat-sen University (Guangzhou, China). Its 5-FU-resistant subline, SW480/5-FU, was developed by the high-dose impact method with 5-FU (Xudong Haipu Pharmaceutical Co., Ltd., Shanghai, China) [28]. SW480/5-FU cells that were capable of stable growth in 6 μg/mL 5-FU were regarded as a 5-FU-resistant strain and named SW480/5-FU cells. Both SW480 and SW480/5-FU cells were cultured in RPMI 1640 medium (HyClone Laboratories, Logan, UT, United States) supplemented with 10% foetal bovine serum (Gibco, Invitrogen, Waltham, MA, United States) and 100 U/mL penicillin (Solarbio Life Science, Beijing, China) at 37°C in a humidified 5% CO₂ atmosphere and passaged twice a week.

MTT assays were performed to determine the relative cell viability of the parental SW480 and SW480/5-FU cells. For this assay, the cell lines were grown in RPMI 1640 medium as described above and seeded in 96-well plates at a density of 3000 cells of each cell line per well [28]. The cells were treated with 5-FU at various concentrations (0.5, 1.25, 2.5, 5, 10, 50, or 250 μg/mL) for 48 h. MTT (10 μL of 0.5 mg/mL) was added to each well, and the cells were incubated for 4 h. All liquid was removed, and 150 μL of dimethyl sulfoxide was added to each well. The absorbance at 490 nm was read using a multifunction microplate reader (Boteng Instrumentation Co., Ltd., Beijing, China).

The half-maximal inhibitory concentration (IC₅₀) of the SW480 and SW480/5-FU cells was determined using SPSS v13.0 statistical software (IBM Corp., Armonk, NY, United States). The resistance index (RI) of the SW480/5-FU cells was calculated as (SW480/5-FU IC₅₀)/SW480 IC₅₀ = 4.44.

2.1.2 Tumour xenograft model

All animal experiments conformed to the internationally accepted principles for the care and use of laboratory animals (Licence No. 2017-007, Ethical Committee for Animal Research of Guangzhou Medical University, China).

Five- to six-week-old BALB/c nude mice were purchased from the Guangdong Provincial Animal Experiment Center (15–17 g, females, No. 44007200046136). Ten healthy BALB/c nude mice (female, aged 5–6 weeks, 16–18 g) were randomly divided into a resistant tumour group and a responsive tumour group (5 mice in each group). Tumour xenograft models were prepared as previously described [28, 29]. Briefly, 0.2 mL of a suspension (4 × 10⁷ cells/mL) of SW480 cells (responsive tumour group) or SW480/5-FU cells (resistant tumour group) was injected subcutaneously into the bilateral hind leg root to reduce the amount of mouse used. The animals were housed in the specific pathogen-free facility at the Animal Experimental Center of Guangzhou Medical University. Based on the ethical standard of tumor burden on mice in the “Guidelines for the welfare and use of animals in cancer research, 2010” [30], the maximal diameter of tumours on mice was limited to less than 1.5 cm.

2.1.3 In vivo MRI/1H-MRS

Immediately before the MR examination, each tumour-bearing mouse was wrapped in plastic material to provide warmth and prevent curling artifact [28]. In addition, increasing the volume of the imaged subjects can fill the coil imaging space and improve the reliability of the data collection.

MR was performed using the MAGNETOM Skyra 3 T Siemens MR Imaging System (Erlangen, Germany) equipped with an 8-channel mouse coil (Chenguang Medical Technology Co., Shanghai, China). Axial, coronal, and sagittal T2WI (TSE) images (repetition time/echo time = 4500 ms/110 ms, slice thickness = 2 mm, interval = 0, field of vision = 128 mm, NSA = 4, SENSE = 2, acquisition matrix = 128 × 128, reconstruction matrix = 512 × 512, scan time = 2 min 2 s) were acquired to determine the spectroscopic volume of interest in the cancer lesion (i.e., the hyperintense region in the images) (Figure 1).

Figure 1.

Metabolic profiles of SW480/5-fluorouracil cancer tissue in vivo.

1H-MRS was performed using the multivoxel three-dimensional volume acquisition editing MEGA-PRESS sequence with previously described procedures and parameters (repetition time = 1700 ms, echo time = 40 ms, slice thickness = 2 mm, interval = 0, field of vision = 60 mm, volume of interest = 30 mm, collection voxel size = 4–9 mm, acquisition number = 8, acquisition matrix = 128 × 128, scan time = 9 min 13 s) [28].

The acquired spectral data were processed using the device software (Siemens), as previously described [28], and then independently reviewed by two radiologists (Yang YM and Wu MY), who were blinded to the sample grouping [28]. Any discrepancies were resolved by discussion and consensus. The two reviewers independently determined the semiquantitative value (area under the peak) from three different voxels of the tumour while avoiding necrotic areas on T2 images; the two values were then averaged, and the resultant single value was used for the subsequent statistical analysis.

Choline (Cho; 3.21 ppm) and the glutamate and glutamine complex (Glx1; 2.05–2.35 ppm and Glx2; 3.75–3.8 ppm, respectively) were the target metabolites investigated in this study (Figure 1).

2.1.4 Cancer tissue analysis

After MRI, the tumour-bearing mice were sacrificed via the intraperitoneal injection of 10% chloral hydrate. The tumours were removed completely and prepared for histological analysis [haematoxylin-eosin (HE) staining], western blotting, and MTT assays [28].

The histopathological evaluations were performed by a pathologist with 25 years of work experience (Zhang J). Tumour necrosis was assessed using the HE-stained sections (magnification × 400). The degree of necrosis was rated on a 5-point scale: 1 (light) indicated necrosis in 1/5 of the tumour tissue, 2 (moderate) indicated necrosis in 2/5 of the tumour tissue, 3 (severe) indicated necrosis in 3/5 of the tumour tissue, 4 (very severe) indicated necrosis in 4/5 of the tumour tissue, and 5 (total) indicated necrosis throughout the entirety of the tumour tissue. The necrotic area was denoted as extremely small by a rating of 0.5 points.

Western blotting was performed to detect the expression of P-gp, multidrug resistance pump (MRP)1, PKC, γ-GCSh, γ-GCSl, glutathione synthetase (GSHS), and GST-π. Western blot testing was performed by Jie Tewei Biotechnology Co., Ltd. (Guangzhou, China) according to the instruction manual provided with the Phototope®-HRP western blot kit (Cell Signaling Technology, Danvers, MA, United States). The following antibodies were used: goat anti-mouse IgG/HRP (ABclonal, Woburn, MA, United States), MDR1 (ABclonal), MRP1 (ABclonal), PKC (ABclonal), γ-GCSh (ABclonal), γ-GCSl (ABclonal), GSHS (ABclonal), and GST-π (Cell Signaling Technology). The detected protein bands were scanned into a computer in JPG format and analysed using ImagePro-Plus 6.0 software for automatic determination of the integral optical density (IOD) of the band intensities. The IOD of the expression of each respective protein of interest was then divided by the IOD of the internal reference (GAPDH) to obtain the relative (R)IOD.

MTT assays were performed to determine the relative cell viability of cancer tissue with different concentrations of 5-FU [28]. Briefly, the tumour tissue was minced (to a size of 1–2 mm³), suspended in 1 mL of trypsin-EDTA (Gibco), and allowed to digest for 50 min in a 37°C incubator. After the addition of 2 mL of RPMI 1640 medium (HyClone Laboratories, Logan, UT, United States) to terminate digestion, the cell suspension was separated by centrifugation (5 min at a rotation speed of 1000 r/min), resuspended in fresh RPMI 1640 medium (2–3 mL), and filtered through a 200-mesh sieve into a 25-cm² culture flask. The IC₅₀ was measured by the MTT assay.

2.1.5 Statistical analysis

The SPSS v13.1 statistical software package was used for all the calculations. The data are summarized as the means and standard deviations. Due to the small sample size, the Mann-Whitney U test was selected for the comparison of metabolites and protein expression between the 5-FU-responsive group and the 5-FU-resistance group. The correlations between metabolites and P-gp, PKC, MRP1, γ-GCSl, γ-GCSh, GSHS, and GST-π protein expression were assessed by Spearman’s correlation test. A P-value less than 0.05 was considered to indicate statistical significance.

2.2 Results

Two tumours smaller than 1 cm were removed from each group. A total of 16 tumours were included in this study: 8 from the 5-FU-responsive (SW480) mice (maximum diameter range: 1. 21–1.48 cm) and 8 from the 5-FU-resistant (SW480/5-FU) mice (maximum diameter range: 1.15–1.46 cm).

2.2.1 Evaluation of resistance to 5-FU

2.2.1.1 SW480/5-FU cells exhibit higher survivability in cancer tissue in vivo than the parental SW480 cells

The viability of both the parental SW480 cells and SW480/5-FU cells decreased with increases in the concentrations of 5-FU (Figure 2, MTT). The SW480/5-FU tumours exhibited a significantly higher survival rate than the SW480 tumours (P < 0.05) when the 5-FU concentration was higher than 2.5 μg/mL. The RI of SW480/5-FU cells was calculated as follows: (SW480/5-FU IC₅₀)/SW480 IC₅₀ = 42.914 μg/mL/9.516 μg/mL = 4.508.

Figure 2.

Drug resistance curves of SW480/5-fluorouracil and SW480 xenograft tumours.

2.2.1.2 The SW480/5-FU xenograft tumours showed significantly higher expression of resistance-related proteins

The SW480/5-FU xenograft tumours showed higher expression of P-gp, MRP1, and PKC than the SW480 xenograft tumours (Figures 3 and 4). A statistical comparison of the RIOD values obtained for the expression of these proteins between the two groups revealed that the difference was significant; the Mann-Whitney U test Z and P values for P-gp, MRP1, and KPC were 2.611 and 0.003, 2.785 and 0.005, and 2.668 and 0.008, respectively.

Figure 3.

Expression of P-glycoprotein, multidrug resistance pump 1, and protein kinase C in SW480/5-fluorouracil xenograft tumours and SW480 xenograft tumours.

Figure 4.

Relative integral optical density values for the expression levels of P-glycoprotein, multidrug resistance pump 1, and protein kinase C in SW480/5-fluorouracil xenograft tumours and SW480 xenograft tumours.

2.2.2 1H-MRS analysis

The SW480 (5-FU responsive) and SW480/5-FU (5-FU resistant) tumour tissues were assessed by 1H-MRS for the in vivo detection of Cho, Glx1, and Glx2 peaks. The areas under the peak values for each of these metabolites are summarized in Figure 5. All three metabolites were found at significantly higher levels in the 5-FU-resistant tumours, as determined by the Mann-Whitney U test.

Figure 5.

Peak areas of choline, glutamate, and glutamine complex in the SW480/5-fluorouracil xenograft tumours and SW480 xenograft tumours.

2.2.3 Cancer tissue analysis

2.2.3.1 Tumour necrosis

No significant difference in the degree of necrosis was observed between the HE-stained tumour tissues of the SW480 (5-FU responsive) and SW480/5-FU (5-FU resistant) xenografts (Figure 6; T tests, t = 1.76, P = 0.109). However, differences in other histological features were observed. The SW480/5-FU (5-FU resistant) tumour tissues showed larger cell nuclei, a closer cell arrangement, and a greater cell density (Figure 7).

Figure 6.

Degree of necrosis in the SW480/5-fluorouracil xenograft tumours and SW480 xenograft tumours.

Figure 7.

Haematoxylin-eosin staining analysis of tumour tissues. Haematoxylin-eosin staining analysis of tumour tissues (magnification: 400×).

2.2.3.2 Expression of γ-GCSh, γ-GCSl, GSHS, and GST-π proteins in tumour tissues

The SW480/5-FU (5-FU resistant) tumour tissues showed higher expression of glutamate-metabolizing enzyme proteins than the SW480 (5-FU responsive) tumour tissues (Figures 8 and 9). A statistical comparison of the RIOD values for the expression levels of these proteins between the two groups revealed that the difference was significant; specifically, the Mann-Whitney U test Z and P values for γ-GCSh, γ-GCSl, GSHS, and GST-π were 2.643 and 0.008, 2.712 and 0.007, 2.635 and 0.008, and 2.627 and 0.008, respectively.

Figure 8.

Expression of γ-GCSh, γ-GCSl, glutathione synthetase, and glutathione-π in SW480/5-fluorouracil xenograft tumours and SW480 xenograft tumours.

Figure 9.

Relative integral optical density values for the expression levels of γ-GCSh, γ-GCSl, glutathione synthetase, and glutathione-π in SW480/5-fluorouracil xenograft tumours and SW480 xenograft tumours.

2.2.4 Correlation between metabolites detected by 1H-MRS and protein expression in tumour cells

The Cho peak area was positively correlated with the expression of P-gp (r = 0.636, P = 0.048), MRP1 (r = 0.821, P = 0.004), γ-GCSh (r = 0.841, P = 0.002), and γ-GCSl (r = 0.799, P = 0.006). The Glx1 peak area was positively correlated with the expression of MRP1 (r = 0.880, P = 0.021) and GST-π (r = 0.888, P = 0.018), and the Glx2 peak area exhibited positive correlations with the expression of MRP1 (r = 0.847, P = 0.002), γ-GCSh (r = 0.644, P = 0.044), γ-GCShl (r = 0.780, P = 0.008), and GSHS (r = 0.661, P = 0.038).

2.3 Discussion

In this study, the high-dose shock method was used to obtain 5-FU-resistant cells from 5-FU-responsive cells, i.e., SW480/5-FU cells from parental SW480 cells. The RI of the SW480/5-FU cells in vitro was very close to that of cancer tissue created with these cells in a xenograft mouse model. The SW480/5-FU tumour tissues showed significantly increased expression of P-gp, MRP1, and PKC, which indicated the reliable features of these cells for the in vivo study of 5-FU resistance. At the same time, it was also observed that there was no difference in the necrotic range between 5-FU-resistant and 5-FU-responsive colon cancer tissues before being attacked by 50-FU. However, 5-FU-resistant colon cancer tissues had larger nuclei and higher cell density, indicating a significant difference in their proliferative ability. It is speculated that the related metabolites supporting the stronger proliferative ability of 5-FU-resistant colon cancer are higher.

During the development of drug resistance, a harsh microenvironment containing chemotherapeutic drugs will induce tumour cells to undergo metabolic reorganization at the genetic level (i.e., gene mutations in the cell cycle pathway) [31, 32, 33] up to the protein level (i.e., mutation of metabolic enzymes) [34]. This reorganization results in changes in the metabolite composition of the tumor and surrounding tissues [33, 35]. Eventually, the microenvironment itself may become beneficial to tumour survival. The related changes in the levels of certain metabolites will then differentiate chemotherapy-responsive tumours from chemotherapy-resistant tumours. Such metabolites represent the last step in the biological process of the tumour towards immortality, but the clinical measurement of such metabolites can provide insight into the case and its prognosis and/or management.

Compounds in human tissues can produce quantifiable chemical shifts under specific conditions. The peak value generated by these shifts can be determined by 1H-MRS, and the area or peak height of compound resonance peaks can be calculated to quantify the content of compounds in a tissue [36, 37, 38, 39]. Thus, 1H-MRS can detect metabolite changes before and after the development of multidrug resistance in tumour tissues in vivo and is particularly useful for screening metabolites with detoxification functions that can improve the tumour microenvironment. We based our study on this speculation that 1H-MRS has potential value for detecting tumour resistance in vivo.

GSH is a small-molecule peptide composed of three amino acids (tripeptide thiol). Its main function is to detoxify and remove xenobiotics and other endogenous compounds from the cell [27]. As such, its antioxidant function is closely related to tumour MDR, which is an important feature of the drug resistance of malignant tumours [40]. A large amount of reactive oxygen species (ROS) is produced during tumour metabolism. High levels of ROS are cytotoxic and can cause apoptosis. Due to the growth characteristics of tumour cells, these cells exist in a state of low oxygen stress for a long time, which should sensitize the cells to death under the action of ROS [21, 40, 41]. Indeed, this feature serves as the basis of many chemotherapeutic drugs used in clinical practice (i.e., the achievement of an antitumour effect by generating a large amount of ROS). However, the main role of GSH is to reduce potentially toxic oxidants, such as ROS, to produce oxidized GSH in the form of glutathione disulfide (GSSG) [27] and thereby directly remove ROS from tumour cells, which unfortunately leads to drug resistance [21, 41].

In addition, anticancer drugs in tumour tissues can interact with GSH via GST and then be exported from the cells through MRP [40, 42]. MRP is a relatively large transmembrane protein and is an ATP-driven outlet pump that excludes GSSG and various glutathione-S conjugates [40, 42, 43]. Therefore, GSH improves the unfavourable microenvironment for tumour cells and increases the chances of tumour survival.

Glutamine is converted into glutamic acid under the action of glutaminase, and glutamic acid then combines with glycine to produce glutamylcysteine. This product is further combined with cysteine to form GSH by a reaction catalysed by GSHS [27]. Therefore, two key enzyme-catalysed reactions occur upstream of GSH biosynthesis.

γ-GCS is the key enzyme of the first step of GSH biosynthesis and is composed of a γ-GCSh heavy chain subunit (73 kDa) and a γ-GCSl light chain subunit (27.7 kDa) [27, 44]. γ-GCSh harbours all functions of the complete catalytic enzyme and can independently catalyse GSH synthesis without the γ-GCSl subunit, which is regulated by GSH feedback [45]. In contrast, the γ-GCSl subunit harbours no enzymatic activity but can combine with the γ-GCSh subunit through noncovalent bonds to form a holoenzyme, which changes the spatial structure of γ-GCSh and enhances its catalytic activity [46]. Compared with the results obtained with γ-GCSh alone, the catalytic activity of γ-GCSh combined with γ-GCSl is higher and is less suppressed by GSH feedback [47].

GSHS is the second key enzyme in GSH biosynthesis [27]. GSHS, which is composed of two subunits and has the same molecular weight as γ-glutamylcysteine synthetase, is not subject to feedback regulation by GSH [27]. It has been reported that GSHS is less important in GSH biosynthesis than γ-GCS [47]. However, another study demonstrated that GSHS plays a decisive role in GSH synthesis under certain tissue hypoxia conditions [48]. Hamdoum et al. [49] reported that the synthesis of GSH is reduced in response to treatment with GSHS inhibitors, which benefits leukaemia patients by increasing their sensitivity to chemotherapy drugs.

GST represents a group of isozymes that exists in a broad array of organisms, is encoded by multiple genes, and has myriad physiological functions [40]. Some studies have shown that the abnormal expression of GST isoenzymes is related to the metabolism of anticancer drugs that results in tumour drug resistance [50, 51, 52, 53]. The GST gene family is a huge supergene family. In terms of phenotype, each type of isozyme includes many subtypes, and there are five subtypes [54]. Some studies have found that GST-π exhibits the closest relationship with tumour MDR [54]. GST-π is a phase II metabolic enzyme that is expressed at high levels in most tumour cells [55, 56, 57, 58]. GST-π can catalyse the binding of harmful biological ions from internal and external sources to GSH, which protects cells from damage. The GSH-chemotherapeutic drug conjugate is actively pumped out of cells through MRP1, which reduces the accumulation of chemotherapeutic drugs in cells [40, 43]. GST-π can also be combined with some anticancer drugs to form a complex with higher water solubility and easier excretion. The complex is excreted through the kidneys, which reduces the cytotoxicity of antitumour drugs but can also cause MDR [21]. In addition, the combination of GST-π and c-Jun N-terminal kinase impedes tumour cell apoptosis by blocking the mitogen-activated protein kinase pathway, which ultimately leads to tumour drug resistance [21].

GSH has three spin systems generated from three amino acid residues, i.e., γ-glutamyl, cysteine, and glycine. These systems are tightly coupled second-order γ-glutamyl αCH, βCH2 and γCH2, cysteine αCH and βCH2, and glycine αCH2 [59, 60]. The GSH spectrum consists of a series of resonances from the peptide components, which are more or less transferred from the separated peptide resonances. In the central nervous system, all signals from GSH overlap with resonance from other neurochemicals. These chemicals include N-acetylaspartate (at 2.02 ppm and 2.45 ppm), polyglutamate recombination (centred at 2.05 ppm and 2.35 ppm), creatine plus creatine phosphate (at 3.03 ppm and 3.96 ppm), and amino acids such as glutamic acid, glutamine, and aspartic acid (at 3.75–3.8 ppm) [27].

In the current study, the 1H-MRS spectrum collected by clinical medical MR mainly reflects GSH and upstream metabolites, i.e., glutamine and the glutamate complex (Glx) at 2.1–2.5 ppm (CH2-CH2β-γ peak) and 3.7–3.9 ppm (α peak of amino acid CH). These complexes include the glutamate complex centred at 2.05 ppm and 2.35 ppm (Glx1) and amino acids such as glutamic acid, glutamine, and aspartic acid at 3.75–3.8 ppm (Glx2). The GLX peak detected in vivo using 1H-MRS indirectly reflects the metabolic changes of GSH [27].

This study found that γ-GCSh, γ-GCSl, GSHS, and GST were significantly increased in SW480/5-FU tumour tissues compared with SW480 tumour tissues, which indicated that the functions of GSH synthesis, detoxification, and removal of xenobiotics and other endogenous compounds increased and resulted in tumour tissue resistance to 5-FU. In addition, the peak areas of Glx1 and Glx2 detected by 1H-MRS in vivo in the SW480/5-FU tumour tissues were significantly higher than those found in the SW480 tumour tissues. The area of Glx1 was highly positively correlated with the expression of MRP1 and GST-π, and the area of Glx2 was highly positively correlated with the expression of MRP1, γ-GCSh, γ-GCShl, and GSHS. Therefore, the biological processes of GSH synthesis and detoxification can be reproduced in vivo, which suggests the formation of tumour resistance.

This study also showed that the cell nuclei of SW480/5-FU tumour cells were larger than those of SW480 tumour cells (by HE histology); in addition, the former cells were arranged more closely and exhibited a higher cell density. These findings indicate that drug-resistant tumour cells proliferate more actively. The area of the Cho peak detected with 1H-MRS in vivo was also significantly higher with SW480/5-FU tumour cells and was positively correlated with the expression of tumour P-gp, MRP1, γ-GCSh, and γ-GCSl. The level of Cho is closely related to Cho and phospholipid metabolic activities, and the phospholipid bilayer is the basis of the cell membrane. Thus, the Cho levels can indirectly reflect the activity of cell membrane metabolism [61, 62]. We hypothesize that Cho may be able to promote or synergize with GSH synthetic biological processes.

Our study has inherent limitations that must be considered when interpreting our findings. First, only eight samples per group were included in this study. Further study with a larger sample size is needed to determine the stability and repeatability of the observed indicators. Second, the collection of 1H-MRS data for tumours in xenograft models with clinical medical MRI systems may lead to a low signal-to-noise ratio and result in bias. In addition, MRS remains a limited research tool. The relatively long acquisition time is currently difficult to standardize and complicates the accurate quantification of the metabolite tissue concentration [27]. This study constitutes preliminary exploratory research using a 3 T MRI system equipped with an 8-channel mouse coil, and we found a preliminary experimental result. Therefore, an ultra-high field small animal MRI system with higher than 7 T is needed to verify the repeatability and reliability of 1H-MRS for metabolite data acquisition. Finally, we only studied 5-FU-resistant colon cancer, but other clinical chemotherapeutic drugs for colon cancer were not included. The addition of an experimental exploration of resistance to other clinical chemotherapeutic drugs for colon cancer, such as FOLFOX, 5-FU/LV, and other treatment regimens at the preclinical stage, is needed.

3. Conclusion

1H-MRS can detect increases in Glx1 and Glx2 metabolites, reflecting an increase in the GSH biological synthesis process, which is a cause of drug resistance in tumours. Active membrane metabolism of tumours, tumour acidification, and GSH synthesis biological processes have a promoting or synergistic effect, and the possible mechanisms and connections need to be explored further. Therefore, 1H-MRS is expected to provide biomarkers for the evaluation of colon cancer drug resistance by detecting changes in tumour metabolites in vivo.

Acknowledgments

This work was supported by the Natural Science Foundation of Guangdong [No. 2015A030313732] and the Guangzhou Science and Technology Plan Project (No. 201907010020).

The authors would like to express their gratitude to Wei-Ling Huang and Qi-Feng Pan for the technical assistance provided with the MRI.

Conflict of interest

The authors declare no conflict of interest.