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1.
Biol Direct ; 18(1): 8, 2023 03 05.
Article in English | MEDLINE | ID: mdl-36872327

ABSTRACT

BACKGROUND: Lung cancer is one of the most frequently diagnosed cancers characterized by high mortality, metastatic potential, and recurrence. Deregulated gene expression of lung cancer, likewise in many other solid tumors, accounts for their cell heterogeneity and plasticity. S-adenosylhomocysteine hydrolase-like protein 1 (AHCYL1), also known as Inositol triphosphate (IP(3)) receptor-binding protein released with IP(3) (IRBIT), plays roles in many cellular functions, including autophagy and apoptosis but AHCYL1 role in lung cancer is largely unknown. RESULTS: Here, we analyzed the expression of AHCYL1 in Non-Small Cell Lung Cancer (NSCLC) cells from RNA-seq public data and surgical specimens, which revealed that AHCYL1 expression is downregulated in tumors and inverse correlated to proliferation marker Ki67 and the stemness signature expression. AHCYL1-silenced NSCLC cells showed enhanced stem-like properties in vitro, which correlated with higher expression levels of stem markers POU5F1 and CD133. Also, the lack of AHCYL1 enhanced tumorigenicity and angiogenesis in mouse xenograft models highlighting stemness features. CONCLUSIONS: These findings indicate that AHCYL1 is a negative regulator in NSCLC tumorigenesis by modulating cell differentiation state and highlighting AHCYL1 as a potential prognostic biomarker for lung cancer.


Subject(s)
Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Humans , Animals , Mice , Adenosylhomocysteinase , Cell Plasticity , Carcinogenesis
3.
J Proteome Res ; 22(1): 1-15, 2023 01 06.
Article in English | MEDLINE | ID: mdl-36484409

ABSTRACT

The ultimate goal of surgical treatment in cancer is to remove the tumor mass for restoring a healthy state. A 16-lipid panel that discriminated healthy controls from clear cell renal cell carcinoma (ccRCC) patients in a prior study was evaluated in the present work in paired-serum samples collected from patients (n = 41) before and after nephrectomy. Changes in the lipid and metabolite fingerprints from ccRCC patients were investigated and compared with fingerprints from healthy individuals obtained by means of ultra-performance liquid chromatography-high-resolution mass spectrometry. The lipid panel differentiated phenotypes associated with metabolic restoration after surgery, representing a serum signature of phenoreversion to a healthy metabolic state. In particular, PC 16:0/0:0, PC 18:2/18:2, and linoleic acid allowed discriminating serum samples from ccRCC patients with poor prognosis from those with an improved outcome during the follow-up period. Ratios of PC 16:0/0:0 and PC 18:2/18:2 with linoleic acid levels may contribute as prognostic tools to support decision-making during the patient follow-up care. The preliminary character of these results should be validated with larger cohorts, including subjects with different ethnicities, life style, and diets. MetaboLights study references: MTBLS1839, MTBLS3838, and MTBLS4629.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Humans , Carcinoma, Renal Cell/surgery , Carcinoma, Renal Cell/metabolism , Kidney Neoplasms/surgery , Linoleic Acid , Prognosis , Biomarkers, Tumor
4.
J Proteome Res ; 20(1): 841-857, 2021 01 01.
Article in English | MEDLINE | ID: mdl-33207877

ABSTRACT

A discovery-based lipid profiling study of serum samples from a cohort that included patients with clear cell renal cell carcinoma (ccRCC) stages I, II, III, and IV (n = 112) and controls (n = 52) was performed using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry and machine learning techniques. Multivariate models based on support vector machines and the LASSO variable selection method yielded two discriminant lipid panels for ccRCC detection and early diagnosis. A 16-lipid panel allowed discriminating ccRCC patients from controls with 95.7% accuracy in a training set under cross-validation and 77.1% accuracy in an independent test set. A second model trained to discriminate early (I and II) from late (III and IV) stage ccRCC yielded a panel of 26 compounds that classified stage I patients from an independent test set with 82.1% accuracy. Thirteen species, including cholic acid, undecylenic acid, lauric acid, LPC(16:0/0:0), and PC(18:2/18:2), identified with level 1 exhibited significantly lower levels in samples from ccRCC patients compared to controls. Moreover, 3α-hydroxy-5α-androstan-17-one 3-sulfate, cis-5-dodecenoic acid, arachidonic acid, cis-13-docosenoic acid, PI(16:0/18:1), PC(16:0/18:2), and PC(O-16:0/20:4) contributed to discriminate early from late ccRCC stage patients. The results are auspicious for early ccRCC diagnosis after validation of the panels in larger and different cohorts.


Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Biomarkers, Tumor , Carcinoma, Renal Cell/diagnosis , Early Diagnosis , Humans , Kidney Neoplasms/diagnosis , Lipidomics , Machine Learning , Mass Spectrometry
5.
J Pharm Biomed Anal ; 178: 112905, 2020 Jan 30.
Article in English | MEDLINE | ID: mdl-31707200

ABSTRACT

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.


Subject(s)
Kidney Neoplasms/diagnosis , Prostatic Neoplasms/diagnosis , Urinary Bladder Neoplasms/diagnosis , Animals , Biomarkers, Tumor/analysis , Female , Humans , Male , Mass Spectrometry/methods , Metabolomics/methods
6.
Biochem Mol Biol Educ ; 46(5): 502-515, 2018 09.
Article in English | MEDLINE | ID: mdl-30281891

ABSTRACT

Metabolic control analysis (MCA) is a promising approach in biochemistry aimed at understanding processes in a quantitative fashion. Here the contribution of enzymes and transporters to the control of a given pathway flux and metabolite concentrations is determined and expressed quantitatively by means of numerical coefficients. Metabolic flux can be influenced by a wide variety of modulators acting on one or more metabolic steps along the pathway. We describe a laboratory exercise to study metabolic regulation of human erythrocytes (RBCs). Within the framework of MCA, students use these cells to determine the sensitivity of the glycolytic flux to two inhibitors (iodoacetic acid: IA, and iodoacetamide: IAA) known to act on the enzyme glyceraldehyde-3-phosphate-dehydrogenase. Glycolytic flux was estimated by determining the concentration of extracellular lactate, the end product of RBC glycolysis. A low-cost colorimetric assay was implemented, that takes advantage of the straightforward quantification of the absorbance signal from the photographic image of the multi-well plate taken with a standard digital camera. Students estimate flux response coefficients for each inhibitor by fitting an empirical function to the experimental data, followed by analytical derivation of this function. IA and IAA exhibit qualitatively different patterns, which are thoroughly analyzed in terms of the physicochemical properties influencing their action on the target enzyme. IA causes highest glycolytic flux inhibition at lower concentration than IAA. This work illustrates the feasibility of using the MCA approach to study key variables of a simple metabolic system, in the context of an upper level biochemistry course. © 2018 International Union of Biochemistry and Molecular Biology, 46(5):502-515, 2018.


Subject(s)
Biochemistry/education , Erythrocytes/metabolism , Glycolysis , Colorimetry , Enzyme Inhibitors/chemistry , Enzyme Inhibitors/pharmacology , Erythrocytes/drug effects , Glyceraldehyde-3-Phosphate Dehydrogenases/antagonists & inhibitors , Glyceraldehyde-3-Phosphate Dehydrogenases/metabolism , Glycolysis/drug effects , Humans , Iodoacetamide/chemistry , Iodoacetamide/pharmacology , Iodoacetic Acid/chemistry , Iodoacetic Acid/pharmacology , Students
7.
J Proteome Res ; 17(11): 3877-3888, 2018 11 02.
Article in English | MEDLINE | ID: mdl-30260228

ABSTRACT

A protocol for harvesting and extracting extracellular metabolites from an in vitro model of human renal cell lines was developed to profile the exometabolome by means of a discovery-based metabolomics approach using ultraperformance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry. Metabolic footprints provided by conditioned media (CM) samples ( n = 66) of two clear cell Renal Cell Carcinoma (ccRCC) cell lines with different genetic backgrounds and a nontumor renal cell line, were compared with the human serum metabolic profile of a pilot cohort ( n = 10) comprised of stage IV ccRCC patients and healthy individuals. Using a cross-validated orthogonal projection to latent structures-discriminant analysis model, a panel of 21 discriminant features selected by iterative multivariate classification, allowed differentiating control from tumor cell lines with 100% specificity, sensitivity, and accuracy. Isoleucine/leucine, phenylalanine, N-lactoyl-leucine, and N-acetyl-phenylalanine, and cysteinegluthatione disulfide (CYSSG) were identified by chemical standards, and hydroxyprolyl-valine was identified with MS and MS/MS experiments. A subset of 9 discriminant features, including the identified metabolites except for CYSSG, produced a fingerprint of classification value that enabled discerning ccRCC patients from healthy individuals. To our knowledge, this is the first time that N-lactoyl-leucine is associated with ccRCC. Results from this study provide a proof of concept that CM can be used as a serum proxy to obtain disease-related metabolic signatures.


Subject(s)
Biomarkers, Tumor/blood , Carcinoma, Renal Cell/blood , Kidney Neoplasms/blood , Leucine/blood , Metabolome , Adult , Aged , Carcinoma, Renal Cell/diagnosis , Carcinoma, Renal Cell/pathology , Case-Control Studies , Cell Line, Tumor , Chromatography, Liquid , Cysteine/analogs & derivatives , Cysteine/blood , Discriminant Analysis , Female , Glutathione/analogs & derivatives , Glutathione/blood , HEK293 Cells , Humans , Kidney Neoplasms/diagnosis , Kidney Neoplasms/pathology , Leucine/analogs & derivatives , Male , Metabolomics/methods , Middle Aged , Neoplasm Staging , Phenylalanine/analogs & derivatives , Phenylalanine/blood , Pilot Projects , Tandem Mass Spectrometry
8.
J Cell Physiol ; 231(7): 1522-33, 2016 Jul.
Article in English | MEDLINE | ID: mdl-26551914

ABSTRACT

Galectin-1 (Gal1), a ß-galactoside-binding protein elevated in hepatocellular carcinoma (HCC), promotes epithelial-mesenchymal transition (EMT) and its expression correlates with HCC growth, invasiveness, and metastasis. During the early stages of HCC, transforming growth factor ß1 (TGF-ß1 ) acts as a tumor suppressor; however in advanced stages, HCC cells lose their cytostatic response to TGF-ß1 and undergo EMT. Here, we investigated the role of Gal1 on liver endothelial cell biology, and the interplay between Gal1 and TGF-ß1 in HCC progression. By Western blot and immunofluorescence, we analyzed Gal1 expression, secretion and localization in HepG2 and HuH-7 human HCC cells, and in SK-HEP-1 human liver sinusoidal endothelial cells (SECs). We used loss-of-function and gain-of-function experiments to down- or up-regulate Gal1 expression, respectively, in HepG2 cells. We cultured SK-HEP-1 cells with conditioned media from HCC cells secreting different levels of Gal1, and demonstrated that Gal1 derived from tumor hepatocytes induced its own expression in SECs. Colorimetric and scratch-wound assays revealed that secretion of Gal1 by HCC cells induced SEC proliferation and migration. Moreover, by fluorescence microscopy we demonstrated that Gal1 promoted glycan-dependent heterotypic adhesion of HepG2 cells to SK-HEP-1 SECs. Furthermore, TGF-ß1 induced Gal1 expression and secretion by HCC cells, and promoted HepG2 cell adhesion to SK-HEP-1 SECs through a Gal1-dependent mechanism. Finally, Gal1 modulated HepG2 cell proliferation and sensitivity to TGF-ß1 -induced growth inhibition. Our results suggest that Gal1 and TGF-ß1 might function coordinately within the HCC microenvironment to regulate tumor growth, invasion, metastasis, and angiogenesis.


Subject(s)
Carcinoma, Hepatocellular/genetics , Galectin 1/genetics , Liver Neoplasms/genetics , Transforming Growth Factor beta1/genetics , Carcinoma, Hepatocellular/pathology , Cell Movement/genetics , Cell Proliferation/genetics , Endothelial Cells , Epithelial-Mesenchymal Transition , Galectin 1/biosynthesis , Gene Expression Regulation, Neoplastic , Hep G2 Cells , Humans , Liver Neoplasms/pathology , Neovascularization, Pathologic/genetics , Transforming Growth Factor beta1/biosynthesis , Tumor Microenvironment
9.
J Cell Physiol ; 230(6): 1298-309, 2015 Jun.
Article in English | MEDLINE | ID: mdl-25469885

ABSTRACT

Galectin-1 (Gal1), a ß-galactoside-binding protein abundantly expressed in tumor microenvironments, is associated with the development of metastasis in hepatocellular carcinomas (HCC). However, the precise roles of Gal1 in HCC cell invasiveness and dissemination are uncertain. Here, we investigated whether Gal1 mediate epithelial-mesenchymal transition (EMT) in HCC cells, a key process during cancer progression. We used the well-differentiated and low invasive HepG2 cells and performed 'gain-of-function' and 'loss-function' experiments by transfecting cells with Gal1 cDNA constructs or by siRNA strategies, respectively. Epithelial and mesenchymal markers expression, changes in apico-basal polarity, independent-anchorage growth, and activation of specific signaling pathways were studied using Western blot, fluorescence microscopy, soft-agar assays, and FOP/TOP flash reporter system. Gal1 up-regulation in HepG2 cells induced down-regulation of the adherens junction protein E-cadherin and increased expression of the transcription factor Snail, one of the main inducers of EMT in HCC. Enhanced Gal1 expression facilitated the transition from epithelial cell morphology towards a fibroblastoid phenotype and favored up-regulation of the mesenchymal marker vimentin in HCC cells. Cells overexpressing Gal1 showed enhanced anchorage-independent growth and loss of apico-basal polarity. Remarkably, Gal1 promoted Akt activation, ß-catenin nuclear translocation, TCF4/LEF1 transcriptional activity and increased cyclin D1 and c-Myc expression, suggesting activation of the Wnt pathway. Furthermore, Gal1 overexpression induced E-cadherin downregulation through a PI3K/Akt-dependent mechanism. Our results provide the first evidence of a role of Gal1 as an inducer of EMT in HCC cells, with critical implications in HCC metastasis.


Subject(s)
Cadherins/metabolism , Carcinoma, Hepatocellular/metabolism , Epithelial-Mesenchymal Transition/physiology , Galectin 1/metabolism , Cell Line, Tumor , Down-Regulation/physiology , Humans , Liver Neoplasms/metabolism , Liver Neoplasms/pathology , Phosphatidylinositol 3-Kinases/metabolism , Up-Regulation , beta Catenin/metabolism
10.
World J Gastroenterol ; 19(47): 8831-49, 2013 Dec 21.
Article in English | MEDLINE | ID: mdl-24379606

ABSTRACT

Hepatocellular carcinoma (HCC) represents a global health problem. Infections with hepatitis B or C virus, non-alcoholic steatohepatitis disease, alcohol abuse, or dietary exposure to aflatoxin are the major risk factors to the development of this tumor. Regardless of the carcinogenic insult, HCC usually develops in a context of cirrhosis due to chronic inflammation and advanced fibrosis. Galectins are a family of evolutionarily-conserved proteins defined by at least one carbohydrate recognition domain with affinity for ß-galactosides and conserved sequence motifs. Here, we summarize the current literature implicating galectins in the pathogenesis of HCC. Expression of "proto-type" galectin-1, "chimera-type" galectin-3 and "tandem repeat-type" galectin-4 is up-regulated in HCC cells compared to their normal counterparts. On the other hand, the "tandem-repeat-type" lectins galectin-8 and galectin-9 are down-regulated in tumor hepatocytes. The abnormal expression of these galectins correlates with tumor growth, HCC cell migration and invasion, tumor aggressiveness, metastasis, postoperative recurrence and poor prognosis. Moreover, these galectins have important roles in other pathological conditions of the liver, where chronic inflammation and/or fibrosis take place. Galectin-based therapies have been proposed to attenuate liver pathologies. Further functional studies are required to delineate the precise molecular mechanisms through which galectins contribute to HCC.


Subject(s)
Carcinoma, Hepatocellular/metabolism , Cell Transformation, Neoplastic/metabolism , Galectins/metabolism , Hepatitis/metabolism , Liver Cirrhosis/metabolism , Liver Neoplasms/metabolism , Animals , Antineoplastic Agents/chemistry , Antineoplastic Agents/pharmacology , Carcinoma, Hepatocellular/drug therapy , Carcinoma, Hepatocellular/pathology , Cell Transformation, Neoplastic/pathology , Drug Design , Galectins/antagonists & inhibitors , Hepatitis/pathology , Humans , Liver Cirrhosis/pathology , Liver Neoplasms/drug therapy , Liver Neoplasms/pathology , Molecular Targeted Therapy , Signal Transduction
11.
Hepatology ; 53(6): 2097-106, 2011 Jun.
Article in English | MEDLINE | ID: mdl-21391228

ABSTRACT

UNLABELLED: Galectin-1 (Gal-1), a widely expressed ß-galactoside-binding protein, exerts pleiotropic biological functions. Gal-1 is up-regulated in hepatocarcinoma cells, although its role in liver pathophysiology remains uncertain. We investigated the effects of Gal-1 on HepG2 hepatocellular carcinoma (HCC) cell adhesion and polarization. Soluble and immobilized recombinant Gal-1 (rGal-1) promoted HepG2 cell adhesion to uncoated plates and also increased adhesion to laminin. Antibody-mediated blockade experiments revealed the involvement of different integrins as critical mediators of these biological effects. In addition, exposure to rGal-1 markedly accelerated the development of apical bile canaliculi as shown by TRITC-phalloidin labeling and immunostaining for multidrug resistance associated-protein 2 (MRP2). Notably, rGal-1 did not interfere with multidrug resistance protein 1/P-glycoprotein or MRP2 apical localization, neither with transfer nor secretion of 5-chloromethylfluorescein diacetate through MRP2. Stimulation of cell adhesion and polarization by rGal-1 was abrogated in the presence of thiodigalactoside, a galectin-specific sugar, suggesting the involvement of protein-carbohydrate interactions in these effects. Additionally, Gal-1 effects were abrogated in the presence of wortmmanin, PD98059 or H89, suggesting involvement of phosphoinositide 3-kinase (PI3K), mitogen-activated protein kinase and cyclic adenosine monophosphate-dependent protein kinase signaling pathways in these functions. Finally, expression levels of this endogenous lectin correlated with HCC cell adhesion and polarization and up-regulation of Gal-1-favored growth of hepatocarcinoma in vivo. CONCLUSION: Our results provide the first evidence of a role of Gal-1 in modulating HCC cell adhesion, polarization, and in vivo tumor growth, with critical implications in liver pathophysiology.


Subject(s)
Carcinoma, Hepatocellular/physiopathology , Cell Polarity/physiology , Cell Proliferation , Galectin 1/physiology , Liver Neoplasms/physiopathology , Cell Adhesion/physiology , Cell Line, Tumor , Cyclic AMP-Dependent Protein Kinases/physiology , Humans , Mitogen-Activated Protein Kinases/physiology , Multidrug Resistance-Associated Protein 2 , Multidrug Resistance-Associated Proteins/physiology , Phosphatidylinositol 3-Kinases/physiology , Signal Transduction/physiology
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