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. 2024 Jul 9;9(29):31335–31343. doi: 10.1021/acsomega.3c08610

Zeolite Functionalized with Magnesium/Aluminum/Lanthanum Ternary Hydroxide for the Phosphometabolite Profiling of Malignant Neoplastic Serum Samples

Tasbiha Malik †, Batool Fatima †,*, Dilshad Hussain ‡, Fahmida Jabeen §, Shan E Zahra Jawad †, Abrar Mohyuddin ∥, Muhammad Najam-ul-Haq §,*
PMCID: PMC11270549  PMID: 39072089

Abstract

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ATP upregulation is a significant driver of aggressive cancer cell phenotypes. Phosphometabolites participate in metabolic pathways and are overexpressed in cancer cell activity. Therefore, developing novel and accurate methods for detecting phosphometabolites in biological fluids is essential. In this research, a novel zeolite composite comprising magnesium, aluminum, and lanthanum hydroxides (MALZ) is developed and used for the first time to enrich phosphorylated metabolites via its inherent interaction with phosphate groups. SEM micrographs show a crystalline cubic structure with a small diameter of 36.62 nm. FTIR analysis confirms the phosphate adsorption and desorption using AMP and ATP as the standards. XRD analysis of MALZ provides structural information about the synthesized composite. Adsorption–desorption parameters, such as pH, shaking time, and MALZ concentration, are optimized to analyze the binding capacity of the fabricated material for phosphorylated metabolites. A kinetic study reveals the rapid and effective AMP and ATP adsorptions on MALZ. The multiple hydroxyl groups of ternary hydroxides and high affinity of lanthanum toward the phosphate group enrich 26 phosphometabolites from serum samples of malignant neoplastic patients. The LC–MS profile shows characteristic phosphometabolites that may act as signatures of cancer-related abnormal metabolic pathways. This study may provide an experimental pathway for detecting metabolites in human body fluids.

1. Introduction

Energy is necessary for the production and functioning of biomolecules. Therefore, cancer cells need ATP to maintain their growth.1 Several post-translational modifications (PTMs) influence NF-β signaling including phosphorylation. It is the common PTM type in NF-κB signaling and contributes to cancer progression.2 Protein and lipid metabolisms can be altered by a change in energy supply via the AMP-activated protein kinase (AMPK). The clinicopathological significance of AMPK in breast cancer shows that AMPK expression levels in triple-negative breast cancer (TNBC) are higher than those in non-triple-negative breast cancer (NTNBC) cells. Moreover, AMPK is upregulated in TNBC tissues compared to NTNBC.3

The cellular plasma membrane takes up metabolites processed in the cytoplasm. It is then transported to intracellular organelles, i.e., peroxisomes and mitochondria, for further processing as they are considered the central points for cancer cell metabolism.4 Adenosine triphosphate (ATP) and guanosine triphosphate (GTP) are the purine nucleotides for DNA and RNA syntheses and energy metabolism. The biosynthesis of purine nucleotides is increased in malignant tumors because of their high proliferation. Cancer cells upregulate inosine monophosphate dehydrogenase (IMPDH), the rate-limiting enzyme in de novo GTP biosynthesis. De novo synthesis of GMP (guanosine monophosphate) is also regulated by this enzyme. These phosphometabolites are higher in cancer cells than in normal cells.5 Cancer metastasis and angiogenesis are promoted by adenosine diphosphate (ADP), thus being a target to diagnose and treat cancer.6

Liver cancer is the most common cancer leading to death because of poor prognosis, and its prognosis is dismal as it is discovered at a late stage.7 Protein kinase depletion in hepatocytes facilitates liver cancer progression, which promotes autophagy and oxidative phosphorylation.8 Cellular ATP and ADP levels are elevated in liver cancer. The ATP to ADP ratio differs in cancer cells than in normal cells.9,10 Some genes dephosphorylate extracellular ATP to ADP and AMP by extracellularly releasing ATP in liver cancer.11 Cancer cells increase their proliferation as the phosphometabolites build up.12 ATP upregulation in cancer cells enhances several aggressive behaviors, i.e., migration, stemness, anchorage independence, drug resistance, antioxidant capacity, and cell proliferation.13

Various enrichment approaches in phospho-proteomics have been used to enrich phosphoproteins and phospho-peptides selectively. Frequently employed enrichment techniques include immunoprecipitation, coprecipitation, ion exchange chromatography, chemical derivatization, immobilized metal affinity chromatography (IMAC), metal oxide chromatography (MOAC), inorganic salt affinity chromatography, and coprecipitation. IMAC is based on the affinity of phosphate groups for metal ions such as Cu2+, Ni2+, Zn2+, and Fe3+.14 Fe3+ and Ga3+ are often utilized, and TiO2 is often used in MOAC and has a high affinity for p-peptides. Cerium-based nanocomposites allow the simultaneous study of mono- and multipeptides.15 Fe3+, Zr4+, Ti4+, Al3+, La3+, and Ga3+ have distinctive characteristics and better selectivity for phosphorylated biomolecules.16 La2O3 nanoparticles have a powdery nature.17 Enhanced enrichment of monophosphorylated peptides is seen for alumina-zirconia.16

Wang et al. recorded serum metabolic fingerprinting (SMF) by employing nanoparticle-enhance laser desorption/ionization mass spectrometry (NPELDI MS) for the “one-stop shop” diagnosis of polycystic ovary syndrome (PCOS).18 In a comprehensive review by Li et al., the utilization of bionanoparticles, i.e., exosomes, virus nanoparticles, nucleic acid nanoparticles, and protein nanoparticles, as nanomedicine for cancer diagnosis, imaging, and treatment is discussed.19 Lung cancer, kidney cancer, and liver cancer were diagnosed in a recent study by employing Fe-MOF-UL by engineering at the atomic, i.e., metal node of Fe/Co/Ni, and supermolecular level, i.e., ultrathin/bulk. SMF metabolic signals were extracted using 0.1 μL of serum per sample.20 Huang et al. utilized NPELDI MS to record SMF for diagnosis and prognosis of breast cancer (BrCa). SMF machine learning is an efficient readout to differentiate non-BrCa from BrCa.21

In this study, magnesium, aluminum, and lanthanum ternary hydroxides are loaded on zeolite to prepare a MALZ (Mg-Al-La-zeolite) composite and used to enrich phosphorylated metabolites. After parameter optimizations, the comprehensive analysis of phosphorylated metabolites in liver cancer serum samples is carried out via liquid chromatography–mass spectrometry (LC–MS). The MALZ composite can efficiently capture phosphorylated metabolites because of its inherent interaction with the phosphate groups. The main objective of this proposed study is to evaluate the modification of zeolite for efficient phosphometabolite adsorption and desorption. This study may lead to the development of novel detection methods for phosphorylated and other metabolites.

2. Experimental Section

2.1. Reagents and Materials

2.1.1. Preparation of MALZ

A coprecipitation method22 was used to prepare magnesium–aluminum–lanthanum ternary hydroxides loaded on porous zeolite. Magnesium nitrate hexahydrate, aluminum nitrate nanohydrate, and lanthanum nitrate were added to 200 mL of deionized water, wherein magnesium and lanthanum nitrates had twice the molar ratio than aluminum nitrate. In the second step, 10 g of porous zeolite (sodium aluminosilicate hydrate) was added and stirred for 3 h at room temperature. The reaction mixture was added with 28% ammonia solution until the pH reached 9.5 and stirred for 3 h. Precipitates were kept for 24 h at room temperature. The solid was collected and washed using ultrapure water until the filtrate’s pH became neutral. The washed precipitates were dried for 24 h in an oven at 65 °C. Prepared MALZ was pulverized to a fine powder followed by drying and dehydrating at 400 °C.

2.1.2. Solid Phase Extraction (SPE) of Phosphorylated Metabolites

Adsorption–desorption studies were carried out using AMP and ATP as standards. For 0.1 M AMP solution, 1.8 g of AMP was dissolved in 50 mL of deionized water. Similarly, 0.1 M ATP solution was prepared by dissolving 336 mg in 10 mL of deionized water. After dilution, the solutions were sonicated for 20 min, and absorbance was recorded at 259 nm.

2.1.3. Parameter Optimization

The binding capacity of MALZ was optimized for evaluating parameters such as the effect of AMP and ATP concentrations, pH, shaking time, and amount of the enrichment material. Experimental details are provided in the Supporting Information.

2.1.4. Effect of pH on Desorption

Desorption of bound AMP was carried out to estimate the ability of MALZ to enrich phosphate moieties. After desorption, MALZ can be reused for several cycles. The desorption experiment was similar to dephosphorylation, and the effects of pH and shaking time were optimized for the serum analysis. The details are given in the Supporting Information.

2.1.5. LC–MS Analysis

Serum samples of liver cancer patients were taken with the prior consent of the Ethical Committee of Nishtar Hospital Multan, Pakistan, and stored at −20 °C. Proteins were precipitated by acetonitrile and centrifuged at 14,000g, and the protein pellet was removed. The liquid samples were filtered to remove any particulate matter. MALZ (10 mg) was used to enrich under the optimized conditions. The acidic pH was adjusted to 5, and the sample was shaken at 25 °C for 30 min at 140 rpm. After the sample loading, the material was washed and filtered. For elution, the pH was brought to 11 and further shaken for 30 min, and the filtrates were collected and analyzed by LC-ESI-MS analysis.

3. Results and Discussion

Zeolites act as ion exchangers and have a high loading capacity due to their high surface area. Magnesium, aluminum, and lanthanum zeolites are designed to capture phosphorylated molecules from standard and serum samples. Magnesium ions bind phosphate groups at neutral and acidic pH. La has a similar affinity for phosphate as Al3+, and the latter binds with ATP and other phosphorylated molecules more strongly than Mg2+ and Ca2+. The phosphate binds at the terminal phosphate, thus promoting GTP, AMP, and ADP bindings.

3.1. Characterization of MALZ

The phosphate binding potential of MALZ is characterized by FTIR analysis. Figure 1A represents the FTIR spectra of raw zeolite and MALZ before and after adsorption of AMP. Zeolite shows characteristic peaks at 1747, 1249, and 661 cm–1. A similar peak pattern is observed for MALZ with 1247 and 670 cm–1 peaks. MALZ after phosphate adsorption shows peaks at 2925, 1739, 1253, 982, 670, 548, and 464 cm–1. The peaks between 1200 and 1800 cm–1 show hydroxyl groups. Peaks around 464, 548, and 661 cm–1 are attributed to phosphate complexes, i.e., LaPO4 and AlPO4. A bending at 982 cm–1 is due to the asymmetric stretch of the P–O bond. Hence, FTIR spectra confirm AMP enrichment via the hydroxyl groups of MALZ.

Figure 1.

Figure 1

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(A) FTIR spectra of zeolite, MALZ without and with phosphate adsorption, (B) XRD crystallographic analysis of precursor zeolite and MALZ, (C, D) SEM micrographs of MALZ at different magnification levels, and (E) particle size distribution of Zeolite@MALZ represented via histogram.

MALZ and its precursor zeolite are investigated for crystallographic structures and solid-state chemistry through X-ray diffraction. Figure 1B represents the diffraction peaks at 2θ of 12, 21, 23, 25, 26, 29, 34, and 47°, indicating the crystallographic frames of (110) La(OH)3, (210) La2O3, (202) La(OH)3, (111) La2O3, (103) La(OH)3, (113) La(OH)3, (213) La(OH)3, and (503) La2O3, respectively. The data are consistent with the literature and JCPDS database SD card number 01-089-8015. Small peaks show the impurities of salts and other byproducts. The zeolite provides a solid support where lanthanum hydroxide and lanthanum oxide intermediates are impregnated. No diffraction peaks are observed for Al and Mg because of their low stoichiometric quantities and higher dispersion of La in the MALZ.

MALZ’s surface morphology and size are examined using scanning electron microscopy (SEM). Figure 1C,D shows a cubic morphology with uniform adsorption on the zeolite surface. The observed average MALZ size is ∼36.62 nm,23 indicating that a large surface area can bind maximum phosphate molecules. Figure 1E represents a histogram that indicates the particle size distribution of the synthesized zeolite, and the calculated polydispersity index (PDI) is 0.14.

This study aims to attach phosphorylated metabolites because the synthesized composite possesses an inherent interaction capability for phosphate groups. As reported in a recent study, lanthanum on MALZ supports phosphate attachment, as La is a hard electron acceptor with a preference for oxygen-containing anions. Moreover, zeolite, aluminum, and magnesium-based materials have also been reported for phosphate adsorption.23−25

3.2. Adsorption Studies

3.2.1. Effect of AMP and ATP Concentrations on MALZ Enrichment Capacity

Adenosine monophosphate (AMP) and adenosine triphosphate (ATP) are standard phosphorylated metabolites to optimize the enrichment parameters such as analyte concentration, pH, shaking time, and MALZ amount. First, different concentrations of standards are prepared and enriched using the MALZ composite. Figure 2A indicates a linear relationship between the AMP and ATP concentrations and MALZ binding capacity. The concentrations of AMP and ATP vary from 5 to 25 mM at room temperature, pH 5, and the amount of MALZ = 5 mg. Figure 2A describes the adsorptions of ATP and AMP as a function of their concentrations. Increasing the concentration increases the enriched amounts of ATP and AMP from the solution, attributed to the higher availability of exchangeable and active phosphate molecules to combine with surface hydroxyl groups of MALZ, resulting in an elevated desorption efficiency or binding capacity of MALZ.

Figure 2.

Figure 2

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Graphical representation of parameters indicating the binding capacity of Zeolite@MALZ with AMP and ATP at (A) different concentrations, (B) pH, (C) incubation time, (D) amount of Zeolite@MALZ, (E) desorption pH, and (F) desorption time. (Comprehensive exploration of the binding capacity of synthesized material with ATP and AMP provides information about the effects of varying concentration, pH, and incubation times. Zeolite@MALZ concentration, desorption pH, and time provide an understanding of adsorption–desorption dynamics and optimal conditions for removing analytes.)

3.2.2. Effect of pH on the Binding Efficiency of MALZ

The binding capacity of MALZ is then evaluated at different pH values of standard solutions. The binding efficiency of MALZ increases in acidic pH up to 5 and decreases as the pH gets neutral. Results are aligned to the concept of protonation of OH– groups under acidic conditions. In the pH range 2–5, there are more H+ ions in the solution to protonate OH groups on MALZ, introducing a strong positive charge on MALZ. This positive charge attracts the negatively charged phosphate of AMP for adsorption on MALZ through electrostatic interactions. At pH 6–7, H+ ions decrease as maximum phosphate is adsorbed, and OH– groups from the surface are removed and clustered in the solution. A pool of OH– and phosphate ions is created, and competition among negatively charged ions is developed for attachment to the adsorbent. It hinders the overall adsorption capacity of MALZ at a higher pH of 6–7.26,27 Therefore, the binding capacity peaks at pH 5, and this trend is observed in Figure 2B.

3.2.3. Effect of Shaking Time on the Binding Capacity of MALZ

The effect of shaking time on the attachment of AMP (15 mM) and ATP (15 mM) on 5 mg of MALZ is investigated at pH 5 by varying shaking time from 10 to 50 min. Results in Figure 2C indicate that MALZ binding capacity increases from 0.0019 to 0.0291 mg/g for AMP and 0.0599 to 0.10344 mg/g for ATP as the shaking time increases from 10 to 50 min with 10 min intervals. A small decrease in binding capacity is observed at higher shaking times. A possible explanation for the increase is that as the shaking time increases, there is more time for the protonated positively charged surface hydroxyl groups of MALZ to interact with negatively charged phosphates of AMP and ATP in the solution. A slight decrease in binding capacity with increasing shaking time may be due to the saturation of surface OH– groups of MALZ.

3.2.4. Effect of MALZ Amount on Enrichment

Results reflect a uniform decrease in the binding capacity, and this trend shows a negative correlation between the MALZ amount and its binding capacity. MALZ’s surface area is high because of its small size, leading to higher phosphate enrichment. A small MALZ amount is sufficient to adsorb higher phosphate concentration. Only 1 mg MALZ has enough binding sites to adsorb AMP and ATP from the 15 mM solution used in these experiments.28

AMP and ATP concentrations adsorbed on MALZ are calculated using the binding capacity equation:29

3.2.4.

where qe is the binding capacity of MALZ, Co is the AMP and ATP concentrations in the blank before adsorption, Ceq is the AMP and ATP concentrations in the solution after enrichment, m is the mass of MALZ, and V is the volume of AMP solution.

3.3. Desorption Parameters

3.3.1. Effect of pH on Desorption

Desorption is calculated in percentage using the following formula:

3.3.1.

where RD is the percentage desorption, CD is the concentration of desorbed AMP as calculated from absorbance using Beer’s law, VD is the volume used from the desorption procedure, qe is the optimum binding capacity under optimum conditions, and m is the amount of MALZ. Here, VD is 3 mL; qe is constant, i.e., 0.0433; and m is 5 mg.

The pH has an essential role in analyte enrichment and in its elution or desorption. Enrichment is facilitated under acidic conditions, as discussed above. In contrast, desorption occurs under basic conditions as more hydroxyl groups are available in the solution to compete with AMP and ATP phosphate groups in reaching the MALZ surface. At higher pH values, the protonated OH groups are deprotonated, which disturb the electrostatic interactions between MALZ and phosphorylated metabolites. Therefore, these metabolites are released in the solution. Figure 2 (E) shows a linear increase in the desorption of AMP and ATP at higher pH. These results are consistent with the previous studies on phosphorylated biomolecule enrichment using nanomaterials.

3.3.2. Effect of Shaking Time on Desorption

The effect of the shaking time on AMP and ATM desorption is also evaluated. Figure 2E illustrates the linear increase in MALZ desorption efficiency with increasing shaking time. Under basic conditions (pH 11), the desorption efficiency increases by increasing shaking time from 10 to 50 min with 10 min intervals. The increase in the desorption percentage is due to the availability of more time for hydroxyl groups present in the basic solution to interact with MALZ having enriched phosphate groups of AMP and ATP.

3.4. Kinetics and Thermodynamics Studies

3.4.1. Pseudo-First-Order Model

The Lagergren rate equation explains the phosphate enrichment process, which can be presented in the pseudo-first-order. Enriching adsorbate from liquid solution has a proportionality relationship between occupied sites on the adsorbent and unoccupied sites. The equation for this model is given below:

3.4.1.

Taking integrals on both sides of the equation, at times 0 to t and adsorption capacities 0 to qt, the equation is obtained as below:

3.4.1.

where q is the enriched amount of AMP and ATP (mg/g), subscripts t and q denote the state at equilibrium and time t (min), respectively, and k1 is the rate constant. By plotting the graph between the script (t) on the x axis and ln(qe–qt) on the y axis, the slope is described in terms of the rate constant of the pseudo-first-order model as depicted in Figure S1A.

3.4.2. Pseudo-Second-Order Model

The second order describes the adsorption kinetics mechanism, and a general assumption from the pseudo-order model is that the process of adsorption increases at first, decreases with time, and becomes constant. This model best explains chemical equilibrium and nonphysical equilibrium. The rate equation for the pseudo-second-order model is given below:

3.4.2.

Similarly, an integrated linear equation for the pseudo-second-order can be obtained as follows:

3.4.2.

By plotting the graph between time t on the x axis and t/qt on the y-axis, the rate constant for the pseudo-second-order can be calculated, as shown in Figure S1C.

3.4.3. Intraparticle Diffusion Model

The chances of AMP and ATP to travel into MALZ pores are explained by the intraparticle diffusion model. The equation describing this model is given below:

3.4.3.

where kdi [g/(mg·min 0.5)] is the adsorption rate constant of the intraparticle diffusion model and Ci (mg/g) is a constant related to boundary layer thickness. The graph is plotted between t1/2 on the x axis, qt on the y axis, and kdi is the slope for the intraparticle diffusion model.

The graph is linearly plotted if intraparticle diffusion is involved in the enrichment. If the plotted line does not pass through the origin, it indicates that some other mechanism is involved in the enrichment. The graph suggests that the plot does not pass through the origin, and some other mechanism controls the enrichment process.30Table S1 indicates that the R2 trend is as follows: intraparticle diffusion (R2) < pseudo-first-order (R2) < pseudo-second-order (R2).

The trend suggests that the enrichment of both AMP and ATP is of pseudo-second-order. The pseudo-second-order model describes that the adsorption of AMP and ATP is parallel to the number of free active sites on MALZ and gives the maximum value at complete saturation and formation of one complete layer of AMP and ATP on the MALZ surface.31

3.4.4. Freundlich Isothermal Adsorption Model

The Freundlich isothermal adsorption model is an empirical equation based on heterogeneous surfaces of materials. The linear equation is expressed as

3.4.4.

where Ce is the concentration at equilibrium (mg/L), n is the exponential constant for the Freundlich equation expressing energy heterogeneity of enriched surface, and k is the Freundlich constant showing the relative enrichment capacity of MALZ.

The results of AMP and ATP enrichment by MALZ using the Freundlich adsorption isothermal model are shown in Figure 3A,B.

Figure 3.

Figure 3

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Adsorption kinetics for MALZ at initial AMP and ATP concentrations. Freundlich model for (A) AMP and (B) ATP and Langmuir model for (C) ATP and (D) AMP. (Investigation of adsorption kinetics coupled with Langmuir and Freundlich models of MALZ for ATP and AMP provides a comprehensive understanding of sorption activity, resulting in valuable details of adsorption mechanisms and surface interaction characteristics between modified zeolite material and adsorbate molecules.)

3.4.5. Langmuir Adsorption Isothermal Model

The enrichment isotherms of ATP and AMP on MALZ at 25 °C and pH 5 are shown in Figure 3C,D, respectively, using the following formula:

3.4.5.

where qm (mg/g) is the enrichment capacity and KL (L/mg) is the Langmuir constant.

From Table S2, R2 values for the Langmuir model are higher than those of Freundlich for both AMP and ATP; thus, experimental results best fit the Langmuir isothermal model.

3.5. Serum Phosphometabolite Analysis

The metabolic traits of malignant liver cancer focus on three metabolic alterations: glycolysis, lipid metabolism, and glutamine addiction. As serum metabolome reflects the patient’s body response to cancer, characteristic phosphometabolites contribute to altered glycolysis, lipid metabolism, and glutamine addiction. MALZ-based detection using SPE followed by LC–MS is developed to separate and profile phosphorylated metabolites from serum samples. A comparison of the metabolite control (Figure S3) and cancer sample (Figure 4) shows different metabolic MS profiles having 26 metabolites, including fucose 1-phosphate, glucose 6-phosphate, glyceric acid 1,3-biphosphate, fructose 1,6-bisphosphate, adenosine monophosphate, ADP, ATP, NADPH, and FADH. They are overexpressed in cancer, contribute toward high glycolysis, and are an exhaustive energy source for cancer cells.

Figure 4.

Figure 4

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MS profile of detected phosphometabolites enriched from malignant neoplastic samples by MALZ via SPE followed by LC–MS. (Mass spectrometry profiles of phosphometabolites indicate the presence of specific phosphorus-containing compounds, providing a specific and targeted approach for discovering potential biomarkers and deeper insights into metabolic changes associated with malignancy.)

Phospholipids such as sphingosine 1-phosphate LysoPE (20:0/0:0), LysoPC (20:1(11Z)/0:0), phosphatidic acid (10:0/17:0), and phosphatidyl ethanolamine (32:4) belong to lipid metabolism, and their expression is linked to cancer. Table 1 lists detected phosphometabolites from cancer serum samples, HMDB ID, m/z, and involved metabolic pathways.

Table 1. Identified Phosphorylated Metabolites after Enrichment with MALZ followed by LC–MS Analysis of Control and Malignant Neoplastic Serum Samplesa.

sr. no. monoisotopic mass phosphorylated metabolite HMDB ID metabolic pathway Involved
1 149.1 O-phosphoethanolamine HMDB0000224 accumulation in cancer cells during glutamine deprivation correlated with tumor growth under nutrient starvation
2 169.1 phosphoenol pyruvate HMDB0000263 inhibited cell growth, proliferation, migration, invasion, and induced robust apoptosis activation
3 200.1 4-O-phosphono-d-erythrose HMDB0001321 involved in a metabolic disorder called glucose-6-phosphate dehydrogenase deficiency pathway
4 244.03 fucose 1-phosphate HMDB0001265 hyperactivity of glycolysis
5 257.10 glycerophosphocholine HMDB0000086 overexpression in cancer cells
6 260.02 glucose 6-phosphate HMDB0001401 hyperactivity of glycolysis
7 265.95 glyceric acid 1,3-biphosphate HMDB0001270 involved in the Warburg effect (aerobic glycolysis), a metabolic shift as a cancer hallmark
8 300.1 2-trans,-6-trans-farnesyl monophosphate HMDB0304088  
9 313.4 5′-phosphoribosyl-N-formyl glycin amidine HMDB0002305 biochemical intermediate in forming purine nucleotides via inosine-5-monophosphate
10 331.4 deoxyadenosine monophosphate HMDB0000905 overexpression in cancer cells
11 335.4 fructose 1,6-bisphosphate HMDB0003973 hyperactivity of glycolysis
12 347 adenosine monophosphate HMDB0000045 overexpression
13 353.9 (2S,4R,5S)-4,5,6-trihydroxy-2-[hydroxyl (phosphonooxy) phosphoryl]oxy-3-oxohexanoic acid HMDB0260134 part of human exposome
14 379.24 sphingosine1-phosphate HMDB0000277 S1P controls numerous aspects of cell physiology, survival, and mammalian inflammatory responses
15 391 phosphoribosyl pyrophosphate HMDB0000280 it was formed from ribose 5-phosphate by the enzyme ribose-phosphate diphosphokinase; it has a role in transferring phosphate groups.
16 427.21 adenosine diphosphate (ADP) HMDB0001341 glucose metabolism
17 506.9 adenosine 5′-triphosphate (ATP) HMDB0000538 hyperactivity of glycolysis
18 509.3 LysoPE (20:0/0:0) HMDB0011515 sphingosine-1-phosphate (S-1-P) and lysophosphatidylcholine (lysoPC 17:0) are upregulated in HCC sera
19 523.5 guanosine triphosphate (GTP) HMDB0001273 elevated intensity in cancer
20 531 PA (2:0/PGJ2) HMDB0266517 oxidized phosphatidic acids belong to a group of biomolecules having a role as signaling molecules
21 549.3 LysoPC (20:1(11Z)/0:0) HMDB0010391 overexpressed, potential biomarker, lipid metabolism
22 578.3 phosphatidic acid (10:0/17:0) HMDB0114774 intermediates in the biosynthesis of triacylglycerols and phospholipids
23 648.8 PA (16:0/16:0) HMDB0000674 biosynthesis of triacylglycerols and phospholipid
23 683.4 phosphatidylethanolamine (32:4) HMDB0008832 elevated levels of cancer
24 745.4 NADPH HMDB0000221 hyperactivity of glycolysis
25 787.1 FADH HMDB0001197 hyperactivity of glycolysis
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a

Monoisotopic mass, HMDB ID, metabolic pathway information, and a link to cancer/exosomes are provided. The Human Metabolome Database (HMDB) is explored to identify the enriched metabolites

Serum-derived metabolic profiles complement protein cancer biomarkers; however, the phosphometabolite content remains under-researched. This work aims to compare phosphometabolite profiles of cancer patients and healthy controls and observe the difference between normal and altered levels.

4. Conclusions

Phosphometabolites play a role in altered glycolysis and lipid metabolism in cancer. In this study, ternary hydroxides of magnesium, aluminum, and lanthanum loaded onto the porous zeolite (MALZ) are fabricated and optimized for the selective separation of phosphometabolites from serum and identified via LC–MS. Lanthanum, because of its acidic nature, possesses a higher affinity for phosphate, and compared to other transition metals, it shows a prominent role in phospho-proteomics. The utilization of magnesium and aluminum further enhances the affinity for the phosphate. MS profiles of malignant neoplastic and healthy serum samples show differences in the number and expression of phosphometabolites. MALZ with nanodiameter, homogeneous surface morphology, high surface area, available hydroxyl groups, and high affinity to phosphate groups offers SPE separations for phosphometabolite profiling in cancer-based studies.

Acknowledgments

The authors acknowledge the Higher Education Commission (HEC) of Pakistan.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.3c08610.

  • Materials and chemicals for MALZ synthesize; parameter optimization; adsorption kinetics of MALZ at initial AMP and ATP concentrations: (A) pseudo-first-order, (B) intraparticle diffusion, and (C) pseudo-second-order (Figure S1); mechanism of phosphate adsorption in acidic conditions (Figure S2); and MS profile of enriched metabolites from healthy serum sample by MALZ via SPE followed by LC–MS (Figure S3) (PDF)

The authors declare no competing financial interest.

Supplementary Material

ao3c08610_si_001.pdf (330KB, pdf)

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