Effects of Indoor Dust Exposure on Lung Cells: Association of Chemical Composition with Phenotypic and Lipid Changes in a 3D Lung Cancer Cell Model.

Indoor dust is a key contributor to the global human exposome in urban areas since the population develops most of its activities in private and public buildings. To gain insight into the health risks associated with this chronic exposure, it is necessary to characterize the chemical composition of dust and understand its biological impacts using reliable physiological models. The present study investigated the biological effects of chemically characterized indoor dust extracts using three-dimensional (3D) lung cancer cell cultures combining phenotypic and lipidomic analyses. Apart from the assessment of cell viability, reactive oxygen species (ROS) induction, and interleukin-8 release, lipidomics was applied to capture the main lipid changes induced as a cellular response to the extracted dust compounds. The application of chemometric tools enabled the finding of associations between chemical compounds present in dust and lipidic and phenotypic profiles in the cells. This study contributes to a better understanding of the toxicity mechanisms associated with exposure to chemical pollutants present in indoor dust.

Application of chemometric methods to the analysis of multimodal chemical images of biological tissues.

Current histology techniques, such as tissue staining or histochemistry protocols, provide very limited chemical information about the tissues. Chemical imaging technologies such as infrared, Raman, and mass spectrometry imaging, are powerful analytical techniques with a huge potential in describing the chemical composition of sample surfaces. In this work, three images of the same tissue slice using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry, infrared microspectroscopy, and an RGB picture from a conventional hematoxylin/eosin (H/E) staining are simultaneously analyzed. These fused images were analyzed by multivariate curve resolution-alternating least squares (MCR-ALS), which provided, for each component, its distribution within the tissue surface, its IR spectrum fingerprint, its characteristic mass values, and the contribution of the RGB channels of the H/E staining. Compared with the individual analysis of each of the images alone, the fusion of the three images showed the relationship between the different types of chemical/biological information and enabled a better interpretation of the tissue under study. In addition, the least-squares projection of the MCR-ALS resolved spectra of components at low spatial resolution onto the IR and RBG images at high spatial resolution, provided a better delimitation of the sample constituents on the image, giving a more precise description of their distribution on the investigated tissue. The application of this procedure can be of interest in different research areas in which a good description of the spatial distribution of the chemical constituents of the samples is needed, such as in biomedicine, food, or environmental research.

Stoichiometric gene-to-reaction associations enhance model-driven analysis performance: Metabolic response to chronic exposure to Aldrin in prostate cancer.

BACKGROUND: Genome-scale metabolic models (GSMM) integrating transcriptomics have been widely used to study cancer metabolism. This integration is achieved through logical rules that describe the association between genes, proteins, and reactions (GPRs). However, current gene-to-reaction formulation lacks the stoichiometry describing the transcript copies necessary to generate an active catalytic unit, which limits our understanding of how genes modulate metabolism. The present work introduces a new state-of-the-art GPR formulation that considers the stoichiometry of the transcripts (S-GPR). As case of concept, this novel gene-to-reaction formulation was applied to investigate the metabolic effects of the chronic exposure to Aldrin, an endocrine disruptor, on DU145 prostate cancer cells. To this aim we integrated the transcriptomic data from Aldrin-exposed and non-exposed DU145 cells through S-GPR or GPR into a human GSMM by applying different constraint-based-methods. RESULTS: Our study revealed a significant improvement of metabolite consumption/production predictions when S-GPRs are implemented. Furthermore, our computational analysis unveiled important alterations in carnitine shuttle and prostaglandine biosynthesis in Aldrin-exposed DU145 cells that is supported by bibliographic evidences of enhanced malignant phenotype. CONCLUSIONS: The method developed in this work enables a more accurate integration of gene expression data into model-driven methods. Thus, the presented approach is conceptually new and paves the way for more in-depth studies of aberrant cancer metabolism and other diseases with strong metabolic component with important environmental and clinical implications.

Legionella pneumophila S1P-lyase targets host sphingolipid metabolism and restrains autophagy.

Autophagy is an essential component of innate immunity, enabling the detection and elimination of intracellular pathogens. Legionella pneumophila, an intracellular pathogen that can cause a severe pneumonia in humans, is able to modulate autophagy through the action of effector proteins that are translocated into the host cell by the pathogen's Dot/Icm type IV secretion system. Many of these effectors share structural and sequence similarity with eukaryotic proteins. Indeed, phylogenetic analyses have indicated their acquisition by horizontal gene transfer from a eukaryotic host. Here we report that L. pneumophila translocates the effector protein sphingosine-1 phosphate lyase (LpSpl) to target the host sphingosine biosynthesis and to curtail autophagy. Our structural characterization of LpSpl and its comparison with human SPL reveals high structural conservation, thus supporting prior phylogenetic analysis. We show that LpSpl possesses S1P lyase activity that was abrogated by mutation of the catalytic site residues. L. pneumophila triggers the reduction of several sphingolipids critical for macrophage function in an LpSpl-dependent and -independent manner. LpSpl activity alone was sufficient to prevent an increase in sphingosine levels in infected host cells and to inhibit autophagy during macrophage infection. LpSpl was required for efficient infection of A/J mice, highlighting an important virulence role for this effector. Thus, we have uncovered a previously unidentified mechanism used by intracellular pathogens to inhibit autophagy, namely the disruption of host sphingolipid biosynthesis.

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis.

Deciphering the Underlying Metabolomic and Lipidomic Patterns Linked to Thermal Acclimation in Saccharomyces cerevisiae.

Temperature is one of the most critical parameters for yeast growth, and it has deep consequences in many industrial processes where yeast is involved. Nevertheless, the metabolic changes required to accommodate yeast cells at high or low temperatures are still poorly understood. In this work, the ultimate responses of these induced transcriptomic effects have been examined using metabolomics-derived strategies. The yeast metabolome and lipidome have been characterized by 1D proton nuclear magnetic resonance spectroscopy and ultra-high-performance liquid chromatography-mass spectrometry at four temperatures, corresponding to low, optimal, high, and extreme thermal conditions. The underlying pathways that drive the acclimation response of yeast to these nonoptimal temperatures were evaluated using multivariate curve resolution-alternating least-squares. The analysis revealed three different thermal profiles (cold, optimal, and high temperature), which include changes in the lipid composition, secondary metabolic pathways, and energy metabolism, and we propose that they reflect the acclimation strategy of yeast cells to low and high temperatures. The data suggest that yeast adjusts membrane fluidity by changing the relative proportions of the different lipid families (acylglycerides, phospholipids, and ceramides, among others) rather than modifying the average length and unsaturation levels of the corresponding fatty acids.

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Exposure to chlorpyrifos induces morphometric, biochemical and lipidomic alterations in green beans (Phaseolus vulgaris).

Chlorpyrifos (CPF) is a worldwide used pesticide that raises concerns from the environmental and human health perspectives. The presence of pesticides such as CPF in edible vegetables has been already reported, but little is known about the effects induced by this pesticide stress on the morphology, oxidative response and lipid composition of treated plants. In this work, green bean plants (Phaseolus vulgaris) were exposed to increasing concentrations of CPF and the different plant parts (roots, stem bases, stem, leaves, pods and beans) were subjected to different analyses. First, morphometric parameters and the oxidative response caused by CPF were explored. In a second phase of the study, an untargeted lipidomic analysis of the different tissue extracts was performed and MALDI-TOF mass spectrometry images of pods and beans were recorded and analysed to illustrate the spatial distribution of the changes observed. As a result of CPF treatment, plants showed a significant decrease in their height, leaf length, and pod number. The biochemical analysis showed lipid peroxidation and the activation of antioxidant mechanisms in roots, stem and leaves. Regarding the lipidomic results, changes in lipid levels were observed, mainly in leaves, pods and seeds. The main changes observed were a reduction of photosynthetic pigments and lipids in leaves and a decrease of triacylglycerols levels in pods and seeds. This last point was confirmed by the analysis of mass spectrometry images of the pods. These observations suggest that CPF would affect the yield of green bean crops as well as the nutritional value of pods and beans. This work represents a step forward in the knowledge of the effects of CPF, one of the most used pesticides worldwide, in plants.

Assessment of the effects of As(III) treatment on cyanobacteria lipidomic profiles by LC-MS and MCR-ALS.

Cyanobacteria are a group of photosynthetic, nitrogen-fixing bacteria present in a wide variety of habitats such as freshwater, marine, and terrestrial ecosystems. In this work, the effects of As(III), a major toxic environmental pollutant, on the lipidomic profiles of two cyanobacteria species (Anabaena and Planktothrix agardhii) were assessed by means of a recently proposed method based on the concept of regions of interest (ROI) in liquid chromatography mass spectroscopy (LC-MS) together with multivariate curve resolution alternating least squares (MCR-ALS). Cyanobacteria were exposed to two concentrations of As(III) for a week, and lipid extracts were analyzed by ultrahigh-performance liquid chromatography/time-of-flight mass spectrometry in full scan mode. The data obtained were compressed by means of the ROI strategy, and the resulting LC-MS data sets were analyzed by the MCR-ALS method. Comparison of profile peak areas resolved by MCR-ALS in control and exposed samples allowed the discrimination of lipids whose concentrations were changed due to As(III) treatment. The tentative identification of these lipids revealed an important reduction of the levels of some galactolipids such as monogalactosyldiacylglycerol, the pigment chlorophyll a and its degradation product, pheophytin a, as well as carotene compounds such as 3-hydroxycarotene and carotene-3,3'-dione, all of these compounds being essential in the photosynthetic process. These results suggested that As(III) induced important changes in the composition of lipids of cyanobacteria, which were able to compromise their energy production processes. Graphical abstract Steps of the proposed LC-MS + MCR-ALS procedure.

Activity of neutral and alkaline ceramidases on fluorogenic N-acylated coumarin-containing aminodiols.

Ceramidases catalyze the cleavage of ceramides into sphingosine and fatty acids. Previously, we reported on the use of the RBM14 fluorogenic ceramide analogs to determine acidic ceramidase activity. In this work, we investigated the activity of other amidohydrolases on RBM14 compounds. Both bacterial and human purified neutral ceramidases (NCs), as well as ectopically expressed mouse neutral ceramidase hydrolyzed RBM14 with different selectivity, depending on the N-acyl chain length. On the other hand, microsomes from alkaline ceramidase (ACER)3 knockdown cells were less competent at hydrolyzing RBM14C12, RBM12C14, and RBM14C16 than controls, while microsomes from ACER2 and ACER3 overexpressing cells showed no activity toward the RBM14 substrates. Conversely, N-acylethanolamine-hydrolyzing acid amidase (NAAA) overexpressing cells hydrolyzed RBM14C14 and RBM14C16 at acidic pH. Overall, NC, ACER3, and, to a lesser extent, NAAA hydrolyze fluorogenic RBM14 compounds. Although the selectivity of the substrates toward ceramidases can be modulated by the length of the N-acyl chain, none of them was specific for a particular enzyme. Despite the lack of specificity, these substrates should prove useful in library screening programs aimed at identifying potent and selective inhibitors for NC and ACER3.

Phenotypic malignant changes and untargeted lipidomic analysis of long-term exposed prostate cancer cells to endocrine disruptors.

Endocrine disruptors (EDs) are a class of environmental toxic molecules able to interfere with the normal hormone metabolism. Numerous studies involve EDs exposure to initiation and development of cancers, including prostate cancer. In this work, three different EDs (aldrin, aroclor 1254 and chlorpyrifos (CPF)) were investigated as potential inducers of a malignant phenotype in DU145 prostate cancer cells after a chronic exposure. Epithelial to mesenchymal transition (EMT) induction, proliferation, migration, colony formation and release of metalloproteinase 2 (MMP-2) were analyzed in 50-day exposed cells to the selected EDs. As a result, aldrin and CPF exposure led to an EMT induction (loss of 16% and 14% of E-cadherin levels, respectively, compared to the unexposed cells). Aroclor and CPF presented an increased migration (134% and 126%, respectively), colony formation (204% and 144%, respectively) and MMP-2 release (137% in both cases) compared to the unexposed cells. An untargeted lipidomic analysis was performed to decipher the lipids involved in the observed transformations. As general results, aldrin exposure showed a global decrease in phospholipids and sphingolipids, and aroclor and CPF showed an increase of certain phospholipids, glycosphingolipids as well as a remarkable increase of some cardiolipin species. Furthermore, the three exposures resulted in an increase of some triglyceride species. In conclusion, some significant changes in lipids were identified and thus we postulate that some lipid compounds and lipid metabolic pathways could be involved in the acquisition of the malignant phenotype in exposed prostate cancer cells to the selected EDs.

The nonlysosomal ß-glucosidase GBA2 promotes endoplasmic reticulum stress and impairs tumorigenicity of human melanoma cells.

Glycosphingolipids, which are abundant at the surface of melanoma cells, play crucial roles in tumor progression. We investigated whether a newly described glycosphingolipid hydrolase, encoded by the GBA2 gene, can modulate human melanoma cell growth and death. GBA2 expression was quantified on melanoma cells by RT-qPCR. The antiproliferative effects of GBA2 were assessed in tumor cells expressing inducible GBA2 and in established melanoma xenografts. As a control an inducible catalytically inactive GBA2 mutant was generated. Sphingolipid levels were monitored by mass spectrometry; unfolded protein response (UPR) and apoptosis were assessed by Western blot and flow cytometry analyses, respectively. We report that GBA2 is down-regulated in melanoma; inducible expression of GBA2 affects endogenous sphingolipid metabolism by promoting glucosylceramide degradation (decrease by 78%) and ceramide generation; this is followed by a UPR that causes apoptosis, subsequent decreased anchorage-independent cell growth, and reduced in vivo tumor growth (by 40%); and all these events are abrogated when expressing a catalytically inactive GBA2. This study documents for the first time the antitumor activity of GBA2 and provides evidence for the role of nonlysosomal glucosylceramide breakdown as a source of bioactive ceramide and a mechanistic link between glycolipid catabolism and the UPR/death response of melanoma cells.

Genetic disorders of simple sphingolipid metabolism.

A better understanding of the functions sphingolipids play in living organisms can be achieved by analyzing the biochemical and physiological changes that result from genetic alterations of sphingolipid metabolism. This review summarizes the current knowledge gained from studies both on human patients and mutant animals (mice, cats, dogs, and cattle) with genetic disorders of sphingolipid metabolism. Genetic alterations affecting the biosynthesis, transport, or degradation of simple sphingolipids are discussed.

A biochemical and lipidomic approach to perceive Halimione portulacoides (L.) response to mercury: An environmental perspective.

The impact of hazardous materials, such as Hg, on life is far from being understood and due to the high number of polluted sites it has generated great concern. A biochemical and lipidomic approach was used to assess the effects of Hg on the saltmarsh halophyte Halimione portulacoides. Plants were collected at two sites of a Hg contaminated saltmarsh. Hg accumulation and distribution in the plant, biochemical parameters (antioxidant and metabolic) and lipid profiles were determined and compared between plant organs and sites (s1 and s2). Hg did not induce antioxidant enzyme activity. Lipid profiles changed under Hg exposure, especially in leaves, decreasing the unsaturation level, the membrane fluidity and stability, and evidencing that membrane lipid remodeling influences plant tolerance to Hg. This knowledge can help select the most appropriate methodologies for the restoration of Hg polluted hotspots, curtailing a serious environmental problem threatening saltmarshes.

A Multi-Level Systems Biology Analysis of Aldrin's Metabolic Effects on Prostate Cancer Cells.

Although numerous studies support a dose-effect relationship between Endocrine disruptors (EDs) and the progression and malignancy of tumors, the impact of a chronic exposure to non-lethal concentrations of EDs in cancer remains unknown. More specifically, a number of studies have reported the impact of Aldrin on a variety of cancer types, including prostate cancer. In previous studies, we demonstrated the induction of the malignant phenotype in DU145 prostate cancer (PCa) cells after a chronic exposure to Aldrin (an ED). Proteins are pivotal in the regulation and control of a variety of cellular processes. However, the mechanisms responsible for the impact of ED on PCa and the role of proteins in this process are not yet well understood. Here, two complementary computational approaches have been employed to investigate the molecular processes underlying the acquisition of malignancy in prostate cancer. First, the metabolic reprogramming associated with the chronic exposure to Aldrin in DU145 cells was studied by integrating transcriptomics and metabolomics via constraint-based metabolic modeling. Second, gene set enrichment analysis was applied to determine (i) altered regulatory pathways and (ii) the correlation between changes in the transcriptomic profile of Aldrin-exposed cells and tumor progression in various types of cancer. Experimental validation confirmed predictions revealing a disruption in metabolic and regulatory pathways. This alteration results in the modification of protein levels crucial in regulating triacylglyceride/cholesterol, linked to the malignant phenotype observed in Aldrin-exposed cells.

Preclinical Studies with Glioblastoma Brain Organoid Co-Cultures Show Efficient 5-ALA Photodynamic Therapy.

BACKGROUND: The high recurrence of glioblastoma (GB) that occurs adjacent to the resection cavity within two years of diagnosis urges an improvement of therapies oriented to GB local control. Photodynamic therapy (PDT) has been proposed to cleanse infiltrating tumor cells from parenchyma to ameliorate short long-term progression-free survival. We examined 5-aminolevulinic acid (5-ALA)-mediated PDT effects as therapeutical treatment and determined optimal conditions for PDT efficacy without causing phototoxic injury to the normal brain tissue. METHODS: We used a platform of Glioma Initiation Cells (GICs) infiltrating cerebral organoids with two different glioblastoma cells, GIC7 and PG88. We measured GICs-5-ALA uptake and PDT/5-ALA activity in dose-response curves and the efficacy of the treatment by measuring proliferative activity and apoptosis. RESULTS: 5-ALA (50 and 100 µg/mL) was applied, and the release of protoporphyrin IX (PpIX) fluorescence measures demonstrated that the emission of PpIX increases progressively until its stabilization at 24 h. Moreover, decreased proliferation and increased apoptosis corroborated the effect of 5-ALA/PDT on cancer cells without altering normal cells. CONCLUSIONS: We provide evidence about the effectiveness of PDT to treat high proliferative GB cells in a complex in vitro system, which combines normal and cancer cells and is a useful tool to standardize new strategic therapies.

Acid ceramidase expression modulates the sensitivity of A375 melanoma cells to dacarbazine.

Dacarbazine (DTIC) is the treatment of choice for metastatic melanoma, but its response in patients remains very poor. Ceramide has been shown to be a death effector and to play an important role in regulating cancer cell growth upon chemotherapy. Among ceramidases, the enzymes that catabolize ceramide, acid ceramidase (aCDase) has been implicated in cancer progression. Here we show that DTIC elicits a time- and dose-dependent decrease of aCDase activity and an increase of intracellular ceramide levels in human A375 melanoma cells. The loss of enzyme activity occurred as a consequence of reactive oxygen species-dependent activation of cathepsin B-mediated degradation of aCDase. These events preceded autophagic features and loss of cell viability. Down-regulation of acid but not neutral or alkaline ceramidase 2 resulted in elevated levels of ceramide and sensitization to the toxic effects of DTIC. Conversely, inducible overexpression of acid but not neutral ceramidase reduced ceramide levels and conferred resistance to DTIC. In conclusion, we report that increased levels of ceramide, due to enhanced degradation of aCDase, are in part responsible for the cell death effects of DTIC. These results suggest that down-regulation of aCDase alone or in combination with DTIC may represent a useful tool in the treatment of metastatic melanoma.

Lipidomic analysis of single and combined effects of polyethylene microplastics and polychlorinated biphenyls on human hepatoma cells.

Microplastics are an emerging environmental issue as a result of their ubiquity, persistence, and intrinsic toxic potential. In addition, their ability to sorb and transport a wide variety of environmental pollutants (i.e. "Trojan Horse" effect) exerts significant adverse impacts upon ecosystems. The toxicological evaluation of the single and combined effects produced by polyethylene microplastics and two polychlorinated biphenyl congeners was performed on the human hepatoma cell line HepG2 by cell viability assessment and an untargeted lipidomic study. The cell lethality evaluation evinced that MPs did not induce relevant cell lethality at any of the concentration range tested, while both PCBs presented a hormetic behavior. The lipidomic analysis suggested that both single PCB exposures induced significant lipidomic changes, especially for glycerophospholipids and glycerolipids. In contrast, for MPs single exposure, the most remarkable change was the substantial enhancement of triglyceride content. Regarding combined exposures, results showed that MPs could induce even more harmful effects than those produced intrinsically as a result of desorbing previously sorbed toxic pollutants. To the best of our knowledge, this is the first study assessing the toxicity of microplastics and their possible "Trojan Horse" effect by applying an untargeted lipidomic methodology.

Phenotypic and Metabolomic Characterization of 3D Lung Cell Cultures Exposed to Airborne Particulate Matter from Three Air Quality Network Stations in Catalonia.

Air pollution constitutes an environmental problem that it is known to cause many serious adverse effects on the cardiovascular and respiratory systems. The chemical characterization of particulate matter (PM) is key for a better understanding of the associations between chemistry and toxicological effects. In this work, the chemical composition and biological effects of fifteen PM10 air filter samples from three air quality stations in Catalonia with contrasting air quality backgrounds were investigated. Three-dimensional (3D) lung cancer cell cultures were exposed to these sample extracts, and cytotoxicity, reactive oxygen species (ROS) induction, metabolomics, and lipidomics were explored. The factor analysis method Multivariate Curve Resolution-Alternating Least-Squares (MCR-ALS) was employed for an integrated interpretation of the associations between chemical composition and biological effects, which could be related to urban traffic emission, biomass burning smoke, and secondary aerosols. In this pilot study, a novel strategy combining new approach methodologies and chemometrics provided new insights into the biomolecular changes in lung cells associated with different sources of air pollution. This approach can be applied in further research on air pollution toxicity to improve our understanding of the causality between chemistry and its effects.

Untargeted metabolomics of prostate cancer zwitterionic and positively charged compounds in urine.

Prostate cancer, a leading cause of cancer-related deaths worldwide, principally occurs in over 50-year-old men. Nowadays there is urgency to discover biomarkers alternative to prostate-specific antigen, as it cannot discriminate patients with benign prostatic hyperplasia from clinically significant forms of prostatic cancer. In the present paper, 32 benign prostatic hyperplasia and 41 prostatic cancer urine samples were collected and analyzed. Polar and positively charged metabolites were therein investigated using an analytical platform comprising an up to 40-fold analyte enrichment step by graphitized carbon black solid-phase extraction, HILIC separation, and untargeted high-resolution mass spectrometry analysis. These classes of compounds are often neglected in common metabolomics experiments even though previous studies reported their significance in cancer biomarker discovery. The complex metabolomics big datasets, generated by the UHPLC-HRMS, were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest data and their analysis by the Multivariate Curve-Resolution Alternating Least Squares chemometrics method. This approach allowed the resolution and tentative identification of the metabolites differentially expressed by the two data sets. Among these, amino acids and carnitine derivatives were tentatively identified highlighting the importance of the proposed methodology for cancer biomarker research.