Systematic analyses of glutamine and glutamate metabolisms across different cancer types

The molecular mechanism responsible for HbSC retinopathy may depend on the action of the angiogenesis-related genes ROBO1 and SLC38A5

HbSC disease, a less severe form of sickle cell disease, affects the retina more frequently and patients have higher rates of proliferative retinopathy that can progress to vision loss. This study aimed to identify differences in the expression of endothelial cell-derived molecules associated with the pathophysiology of proliferative sickle cell retinopathy (PSCR). RNAseq was used to compare the gene expression profile of circulating endothelial colony-forming cells from patients with SC hemoglobinopathy and proliferative retinopathy (n = 5), versus SC patients without retinopathy (n = 3). Real-time polymerase chain reaction (qRT-PCR) was used to validate the RNAseq results. A total of 134 differentially expressed genes (DEGs) were found. DEGs were mainly associated with vasodilatation, type I interferon signaling, innate immunity and angiogenesis. Among the DEGs identified, we highlight the most up-regulated genes ROBO1 (log2FoldChange = 4.32, FDR = 1.35E-11) and SLC38A5 (log2FoldChange = 3.36 FDR = 1.59E-07). ROBO1, an axon-guided receptor, promotes endothelial cell migration and contributes to the development of retinal angiogenesis and pathological ocular neovascularization. Endothelial SLC38A5, an amino acid (AA) transporter, regulates developmental and pathological retinal angiogenesis by controlling the uptake of AA nutrient, which may serve as metabolic fuel for the proliferation of endothelial cells (ECs) and consequent promotion of angiogenesis. Our data provide an important step towards elucidating the molecular pathophysiology of PSCR that may explain the differences in ocular manifestations between individuals with hemoglobinopathies and afford insights for new alternative strategies to inhibit pathological angiogenesis.

Largescale multicenter study of a serum metabolite biomarker panel for the diagnosis of breast cancer

Breast cancer (BC) is currently the most prevalent malignancy worldwide, and finding effective non-invasive biomarkers for routine clinical detection of BC remains a significant challenge. Here, we performed non-targeted and targeted metabolomics analysis on the screening, training and validation cohorts of serum samples from 1,947 participants. A metabolite biomarker model including glutamate, erythronate, docosahexaenoate, propionylcarnitine, and patient's age was established for detecting BC. This model demonstrated better diagnostic performance than carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA) alone in discriminating BC from healthy controls both in the training and validation cohorts [area under the curve (AUC), 0.954; sensitivity, 87.1% and specificity, 93.5% for the training cohort and 0.834, 68.3%, and 85.2%, respectively, for the validation cohort 1]. This study has established a noninvasive approach for the detection of BC, which shows potential as a suitable supplement to the clinical screening methods currently employed for BC.

Development of a prognostic model for muscle-invasive bladder cancer using glutamine metabolism

BACKGROUND

Muscle-invasive bladder cancer (MIBC) is distinguished by its pronounced invasiveness and unfavorable prognosis. Immunotherapy and targeted therapy have emerged as key treatment options for various types of cancer. Altered metabolism is a defining characteristic of cancer cells, and there is mounting evidence suggesting the important role of glutamine metabolism (GM) in tumor metabolism. Nevertheless, the relationship between GM and clinical outcomes, immune microenvironment, and immunotherapy in MIBC remains unknown.

METHODS

This study employed Mendelian randomization to explore the causal relationship between blood metabolites and bladder tumors. We systematically evaluated 373 glutamine metabolism-related genes and identified prognostic-related genes, leading to the construction of a glutamine-associated prognostic model. Further analysis confirmed the correlation between high and low-risk groups with the tumor microenvironment, immune cell infiltration, and tumor mutation burden. Subsequently, we assessed the relationship between the risk score and the sensitivity to various immunotherapies and anticancer drugs.

RESULTS

We identified 14 blood metabolites at the molecular level that have a causal relationship with bladder tumors. At the gene level, the study discussed differentially expressed GM genes in MIBC. First, we established a risk model predicting overall survival (OS) based on GM genes, confirming its reliable predictive ability in MIBC patients and validated it in a GEO cohort. Additionally, a reliable column line chart was created. Secondly, two distinct molecular subtypes were identified, and the associations between different risk groups and tumor microenvironment and immune infiltration were observed. In addition, the predicted risk values correlated with responses to a broad range of pharmaceutical agents.

CONCLUSION

In summary, we confirmed the causal relationship between blood metabolites and bladder tumors. Furthermore, a risk scoring model related to glutamine metabolism consisting of 9 genes was developed. This model could potentially serve as a useful tool for predicting prognosis and guiding the treatment of MIBC patients.

Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

The SLC38A5/SNAT5 amino acid transporter: from pathophysiology to pro-cancer roles in the tumor microenvironment

SLC38A5/SNAT5 is a system N transporter that can mediate net inward or outward transmembrane fluxes of neutral amino acids coupled with Na+ (symport) and H+ (antiport). Its preferential substrates are not only amino acids with side chains containing amide (glutamine and asparagine) or imidazole (histidine) groups, but also serine, glycine, and alanine are transported by the carrier. Expressed in the pancreas, intestinal tract, brain, liver, bone marrow, and placenta, it is regulated at mRNA and protein levels by mTORC1 and WNT/β-catenin pathways, and it is sensitive to pH, nutritional stress, inflammation, and hypoxia. SNAT5 expression has been found to be altered in pathological conditions such as chronic inflammatory diseases, gestational complications, chronic metabolic acidosis, and malnutrition. Growing experimental evidence shows that SNAT5 is overexpressed in several types of cancer cells. Moreover, recently published results indicate that SNAT5 expression in stromal cells can support the metabolic exchanges occurring in the tumor microenvironment of asparagine-auxotroph tumors. We review the functional role of the SNAT5 transporter in pathophysiology and propose that, due to its peculiar operational and regulatory features, SNAT5 may play important pro-cancer roles when expressed either in neoplastic or in stromal cells of glutamine-auxotroph tumors.NEW & NOTEWORTHY The transporter SLC38A5/SNAT5 provides net influx or efflux of glutamine, asparagine, and serine. These amino acids are of particular metabolic relevance in several conditions. Changes in transporter expression or activity have been described in selected types of human cancers, where SNAT5 can mediate amino acid exchanges between tumor and stromal cells, thus providing a potential therapeutic target. This is the first review that recapitulates the characteristics and roles of the transporter in physiology and pathology.

LC-MS-based serum metabolomics analysis for the screening and monitoring of colorectal cancer

Background

Colorectal Cancer (CRC) is a prevalent digestive system tumour with significant mortality and recurrence rates. Serum metabolomics, with its high sensitivity and high throughput, has shown potential as a tool to discover biomarkers for clinical screening and monitoring of the CRC patients.

Methods

Serum metabolites of 61 sex and age-matched healthy controls and 62 CRC patients (before and after surgical intervention) were analyzed using a ultra-performance liquid chromatography-high resolution mass spectrometer (UPLC-MS). Statistical methods and pathway enrichment analysis were used to identify potential biomarkers and altered metabolic pathways.

Results

Our analysis revealed a clear distinction in the serum metabolic profile between CRC patients and healthy controls (HCs). Pathway analysis indicated a significant association with arginine biosynthesis, pyrimidine metabolism, pantothenate, and CoA biosynthesis. Univariate and multivariate statistical analysis showed that 9 metabolites had significant diagnostic value for CRC, among them, Guanosine with Area Under the Curve (AUC) values of 0.951 for the training group and0.998 for the validation group. Furthermore, analysis of four specific metabolites (N-Phenylacetylasparticacid, Tyrosyl-Gamma-glutamate, Tyr-Ser and Sphingosine) in serum samples of CRC patients before and after surgery indicated a return to healthy levels after an intervention.

Conclusion

Our results suggest that serum metabolomics may be a valuable tool for the screening and monitoring of CRC patients.

Ovarian Cancer and Glutamine Metabolism

Cancer cells are known to have a distinct metabolic profile and to exhibit significant changes in a variety of metabolic mechanisms compared to normal cells, particularly glycolysis and glutaminolysis, in order to cover their increased energy requirements. There is mounting evidence that there is a link between glutamine metabolism and the proliferation of cancer cells, demonstrating that glutamine metabolism is a vital mechanism for all cellular processes, including the development of cancer. Detailed knowledge regarding its degree of engagement in numerous biological processes across distinct cancer types is still lacking, despite the fact that such knowledge is necessary for comprehending the differentiating characteristics of many forms of cancer. This review aims to examine data on glutamine metabolism and ovarian cancer and identify possible therapeutic targets for ovarian cancer treatment.

Cell Metabolomics Reveals the Potential Mechanism of Aloe Emodin and Emodin Inhibiting Breast Cancer Metastasis

Metastasis is one of the main obstacles for the treatment and prognosis of breast cancer. In this study, the effects and possible mechanisms of aloe emodin (AE) and emodin (EMD) for inhibiting breast cancer metastasis were investigated via cell metabolomics. First, a co-culture model of MCF-7 and HUVEC cells was established and compared with a traditional single culture of MCF-7 cells. The results showed that HUVEC cells could promote the development of cancer cells to a malignant phenotype. Moreover, AE and EMD could inhibit adhesion, invasion, and angiogenesis and induce anoikis of MCF-7 cells in co-culture model. Then, the potential mechanisms behind AE and EMD inhibition of MCF-7 cell metastasis were explored using a metabolomics method based on UPLC-Q-TOF/MS multivariate statistical analysis. Consequently, 27 and 13 biomarkers were identified in AE and EMD groups, respectively, including polyamine metabolism, methionine cycle, TCA cycle, glutathione metabolism, purine metabolism, and aspartate synthesis. The typical metabolites were quantitatively analyzed, and the results showed that the inhibitory effect of AE was significantly better than EMD. All results confirmed that AE and EMD could inhibit metastasis of breast cancer cells through different pathways. Our study provides an overall view of the underlying mechanisms of AE and EMD against breast cancer metastasis.

Integrative analysis of plasma metabolomics and proteomics reveals the metabolic landscape of breast cancer

BACKGROUND

Breast cancer (BC) is the most commonly diagnosed cancer. Currently, mammography and breast ultrasonography are the main clinical screening methods for BC. Our study aimed to reveal the specific metabolic profiles of BC patients and explore the specific metabolic signatures in human plasma for BC diagnosis.

METHODS

This study enrolled 216 participants, including BC patients, benign patients, and healthy controls (HC) and formed two cohorts, one training cohort and one testing cohort. Plasma samples were collected from each participant and subjected to perform nontargeted metabolomics and proteomics. The metabolic signatures for BC diagnosis were identified through machine learning.

RESULTS

Metabolomics analysis revealed that BC patients showed a significant change of metabolic profiles compared to HC individuals. The alanine, aspartate and glutamate pathways, glutamine and glutamate metabolic pathways, and arginine biosynthesis pathways were the critical biological metabolic pathways in BC. Proteomics identified 29 upregulated and 2 downregulated proteins in BC. Our integrative analysis found that aspartate aminotransferase (GOT1), L-lactate dehydrogenase B chain (LDHB), glutathione synthetase (GSS), and glutathione peroxidase 3 (GPX3) were closely involved in these metabolic pathways. Support vector machine (SVM) demonstrated a predictive model with 47 metabolites, and this model achieved a high accuracy in BC prediction (AUC = 1). Besides, this panel of metabolites also showed a fairly high predictive power in the testing cohort between BC vs HC (AUC = 0.794), and benign vs HC (AUC = 0.879).

CONCLUSIONS

This study uncovered specific changes in the metabolic and proteomic profiling of breast cancer patients and identified a panel of 47 plasma metabolites, including sphingomyelins, glutamate, and cysteine could be potential diagnostic biomarkers for breast cancer.

13C Natural Isotope Abundance in Urothelium as a New Marker in the Follow-Up of Patients with Bladder Cancer

Bladder cancer (BC) is the most common urological malignancy and has a high incidence of recurrence. BC cells alter their nutrient uptake and metabolic pathways in order to continue the production of sufficient levels of ATP and metabolic intermediates for proliferation and survival. Changes in metabolic pathways regarding the rate of the enzymatic reaction and transport lead to differences in the content of natural isotopes (13C, 15N, 34S) between normal and cancerous tissues. The assessment of the stable isotopes of carbon, nitrogen, and sulfur in normal urothelium and bladder cancer samples was performed using Isotope Ratio Mass Spectrometry (IRMS). The natural abundance of 15N and 13C was decreased in bladder cancer samples when compared to normal urothelium. No significant correlation was observed in BC specimens depending on the tumor grade and stage. Samples derived from bladder tumors and normal urothelium had a different pattern of 15N and 13C isotope abundance. Decreased 13C natural isotopes in the normal urothelium of BC patients were significantly associated with a shorter DFS. Our results suggest that isotopic analysis of normal urothelium of BC patients can be used to predict bladder cancer recurrence.

Correlation between amino acid metabolism and self-renewal of cancer stem cells: Perspectives in cancer therapy

Cancer stem cells (CSCs) possess self-renewal and differentiation potential, which may be related to recurrence, metastasis, and radiochemotherapy resistance during tumor treatment. Understanding the mechanisms via which CSCs maintain self-renewal may reveal new therapeutic targets for attenuating CSC resistance and extending patient life-span. Recent studies have shown that amino acid metabolism plays an important role in maintaining the self-renewal of CSCs and is involved in regulating their tumorigenicity characteristics. This review summarizes the relationship between CSCs and amino acid metabolism, and discusses the possible mechanisms by which amino acid metabolism regulates CSC characteristics particularly self-renewal, survival and stemness. The ultimate goal is to identify new targets and research directions for elimination of CSCs.

The Role of Cystine/Glutamate Antiporter SLC7A11/xCT in the Pathophysiology of Cancer

SLC7A11/xCT is an antiporter that mediates the uptake of extracellular cystine in exchange for glutamate. Cystine is reduced to cysteine, which is a rate-limiting precursor in glutathione synthesis; a process that protects cells from oxidative stress and is, therefore, critical to cell growth, proliferation, and metabolism. SLC7A11 is expressed in different tissues and plays diverse functional roles in the pathophysiology of various diseases, including cancer, by regulating the processes of redox homeostasis, metabolic flexibility/nutrient dependency, immune system function, and ferroptosis. SLC7A11 expression is associated with poor prognosis and drug resistance in cancer and, therefore, represents an important therapeutic target. In this review, we discuss the molecular functions of SLC7A11 in normal versus diseased tissues, with a special focus on how it regulates gastrointestinal cancers. Further, we summarize current therapeutic strategies targeting SLC7A11 as well as novel avenues for treatment.

The effect of amino acids on the bladder cycle: a concise review

The human bladder maintains a cycle of filling, storing, and micturating throughout an individual's lifespan. The cycle relies on the ability of the bladder to expand without increasing the intravesical pressure, which is only possible with the controlled relaxation of well-complaint muscles and the congruously organized construction of the bladder wall. A competent bladder outlet, which functions in a synchronous fashion with the bladder, is also necessary for this cycle to be completed successfully without deterioration. In this paper, we aimed to review the contemporary physiological findings on bladder physiology and examine the effects of amino acids on clinical conditions affecting the bladder, with special emphasis on the available therapeutic evidence and possible future roles of the amino acids in the treatment of the bladder-related disorders.

NMR Spectroscopy-Based Metabolomics of Platelets to Analyze Brain Tumors

“Tumor-educated platelets” have recently generated substantial interest for the diagnosis of cancer. We hypothesized that tumor educated platelets from patients with brain tumors will reflect altered metabolism compared to platelets from healthy volunteers. Here, in a pilot study, we have employed nuclear magnetic resonance (NMR) spectroscopy in platelets from brain tumor patients to demonstrate altered metabolism compared to the platelets obtained from healthy volunteers.

The Multifaceted Role of Aldehyde Dehydrogenases in Prostate Cancer Stem Cells

Cancer stem cells (CSCs) are the only tumor cells possessing self-renewal and differentiation properties, making them an engine of tumor progression and a source of tumor regrowth after treatment. Conventional therapies eliminate most non-CSCs, while CSCs often remain radiation and drug resistant, leading to tumor relapse and metastases. Thus, targeting CSCs might be a powerful tool to overcome tumor resistance and increase the efficiency of current cancer treatment strategies. The identification and isolation of the CSC population based on its high aldehyde dehydrogenase activity (ALDH) is widely accepted for prostate cancer (PCa) and many other solid tumors. In PCa, several ALDH genes contribute to the ALDH activity, which can be measured in the enzymatic assay by converting 4, 4-difluoro-4-bora-3a, 4a-diaza-s-indacene (BODIPY) aminoacetaldehyde (BAAA) into the fluorescent product BODIPY-aminoacetate (BAA). Although each ALDH isoform plays an individual role in PCa biology, their mutual functional interplay also contributes to PCa progression. Thus, ALDH proteins are markers and functional regulators of CSC properties, representing an attractive target for cancer treatment. In this review, we discuss the current state of research regarding the role of individual ALDH isoforms in PCa development and progression, their possible therapeutic targeting, and provide an outlook for the future advances in this field.

Diamond Nanofilm Normalizes Proliferation and Metabolism in Liver Cancer Cells

Purpose

Surgical resection of hepatocellular carcinoma can be associated with recurrence resulting from the degeneration of residual volume of the liver. The objective was to assess the possibility of using a biocompatible nanofilm, made of a colloid of diamond nanoparticles (nfND), to fill the side after tumour resection and optimize its contact with proliferating liver cells, minimizing their cancerous transformation.

Methods

HepG2 and C3A liver cancer cells and HS-5 non-cancer cells were used. An aqueous colloid of diamond nanoparticles, which covered the cell culture plate, was used to create the nanofilm. The roughness of the resulting nanofilm was measured by atomic force microscopy. Mitochondrial activity and cell proliferation were measured by XTT and BrdU assays. Cell morphology and a scratch test were used to evaluate the invasiveness of cells. Flow cytometry determined the number of cells within the cell cycle. Protein expression in was measured by mass spectrometry.

Results

The nfND created a surface with increased roughness and exposed oxygen groups compared with a standard plate. All cell lines were prone to settling on the nanofilm, but cancer cells formed more relaxed clusters. The surface compatibility was dependent on the cell type and decreased in the order C3A >HepG2 >HS-5. The invasion was reduced in cancer lines with the greatest effect on the C3A line, reducing proliferation and increasing the G2/M cell population. Among the proteins with altered expression, membrane and nuclear proteins dominated.

Conclusion

In vitro studies demonstrated the antiproliferative properties of nfND against C3A liver cancer cells. At the same time, the need to personalize potential therapy was indicated due to the differential protein synthetic responses in C3A vs HepG2 cells. We documented that nfND is a source of signals capable of normalizing the expression of many intracellular proteins involved in the transformation to non-cancerous cells.

Dietary supplementary glutamine and L-carnitine enhanced the anti-cold stress of Arbor Acres broilers

Newborn poultry in cold regions often suffer from cold stress, causing a series of changes in their physiology and metabolism, leading to slow growth and decreased production performance. However, a single anti-stress substance cannot completely or maximally eliminate or alleviate the various effects of cold stress on animals. Therefore, the effects of the supplemented glutamine and L-carnitine on broilers under low temperature were evaluated in this study. Broilers were randomly allocated into 16 groups which were respectively fed with different levels of glutamine and L-carnitine according to the L16 (45) orthogonal experimental design for 3 weeks (the first week is the adaptive feeding period; the second and third weeks are the cold exposure period). Growth performance was recorded, and blood samples were collected during cold exposure. The results showed the supplementation had altered the plasma parameters, growth performance and cold-induced oxidative stress. The increase of corticosterone and suppression of thyroid hormone was ameliorated. Supplemented groups had lower daily feed intake and feed-to-gain ratio, higher daily weight gain and better relative weights of immune organs. Plasma glucose, total protein, blood urea nitrogen and alkaline phosphatase changed as well. Oxidative stress was mollified due to the improved activities of superoxide dismutase and glutathione peroxidase, heightened total antioxidant capacity and stable malondialdehyde. Dietary glutamine and L-carnitine improve the growth performance, nutritional status and cold stress response of broilers at low temperature, and their interaction occurred.

NADPH homeostasis in cancer: functions, mechanisms and therapeutic implications

Nicotinamide adenine dinucleotide phosphate (NADPH) is an essential electron donor in all organisms, and provides the reducing power for anabolic reactions and redox balance. NADPH homeostasis is regulated by varied signaling pathways and several metabolic enzymes that undergo adaptive alteration in cancer cells. The metabolic reprogramming of NADPH renders cancer cells both highly dependent on this metabolic network for antioxidant capacity and more susceptible to oxidative stress. Modulating the unique NADPH homeostasis of cancer cells might be an effective strategy to eliminate these cells. In this review, we summarize the current existing literatures on NADPH homeostasis, including its biological functions, regulatory mechanisms and the corresponding therapeutic interventions in human cancers, providing insights into therapeutic implications of targeting NADPH metabolism and the associated mechanism for cancer therapy.

Global metabolomic profiling of trastuzumab resistant gastric cancer cells reveals major metabolic pathways and metabolic signatures based on UHPLC-Q exactive-MS/MS

Resistance mechanism exploration has become an urgent need owing to the widespread trastuzumab resistance in gastric cancer. In this study, UHPLC-Q exactive MS/MS was carried out to characterize the metabolic profiles of human gastric cancer cell lines NCI N87, MKN45 (trastuzumab-sensitive) and NCI N87/R, MKN45/R (trastuzumab-resistant), respectively. Metabolic signatures and different metabolites were identified using multivariate in combination with univariate analysis. Integrated pathway enrichment analysis was executed using MetaboAnalyst and KEGG metabolic libraries to analyze the altered metabolic pathways in trastuzumab resistant cells. A total of 79 and 75 different metabolites were positively identified by utilizing authentic standards in NCI N87/R and MKN45/R cells, respectively. Furthermore, enrichment analysis demonstrated that seven metabolic pathways in NCI N87/R cells and five in MKN45/R cells were significantly changed. These pathways are involved in amino acid, nucleotide, carbohydrate, cofactor and vitamin metabolism, of which alanine, aspartate and glutamate metabolism displayed the highest pathway impact and lower P value both in NCI N87/R and MKN45/R cells. Moreover, we constructed a metabolomics-proteomics network between substantially altered metabolites and target genes which revealed citrate being regulated by citrate synthase and ACLY, while proline regulation was due to EPRS, PYCRL and PYCR1/2, respectively. Overall, our findings disclose prominent alterations of metabolic signatures in NCI N87/R and MKN45/R cells when compared with the parent cells which are crucial for understanding of underlying mechanisms of resistance and for developing strategies to overcome trastuzumab resistance.

Using Machine Learning to Measure Relatedness Between Genes: A Multi-Features Model

Measuring conditional relatedness between a pair of genes is a fundamental technique and still a significant challenge in computational biology. Such relatedness can be assessed by gene expression similarities while suffering high false discovery rates. Meanwhile, other types of features, e.g., prior-knowledge based similarities, is only viable for measuring global relatedness. In this paper, we propose a novel machine learning model, named Multi-Features Relatedness (MFR), for accurately measuring conditional relatedness between a pair of genes by incorporating expression similarities with prior-knowledge based similarities in an assessment criterion. MFR is used to predict gene-gene interactions extracted from the COXPRESdb, KEGG, HPRD, and TRRUST databases by the 10-fold cross validation and test verification, and to identify gene-gene interactions collected from the GeneFriends and DIP databases for further verification. The results show that MFR achieves the highest area under curve (AUC) values for identifying gene-gene interactions in the development, test, and DIP datasets. Specifically, it obtains an improvement of 1.1% on average of precision for detecting gene pairs with both high expression similarities and high prior-knowledge based similarities in all datasets, comparing to other linear models and coexpression analysis methods. Regarding cancer gene networks construction and gene function prediction, MFR also obtains the results with more biological significances and higher average prediction accuracy, than other compared models and methods. A website of the MFR model and relevant datasets can be accessed from http://bmbl.sdstate.edu/MFR.

Cell proliferation in kidney carcinoma is inhibited by lncRNA GASL1

Long noncoding RNA (lncRNA) GASL1 was identified as a novel lncRNA, which plays an important role in the proliferation and apoptosis of cells. This study aimed to compare the expression of GASL1 mRNA in kidney cancer cells and normal cells and detect the biological role of GASL1 in kidney cancer cell line A498. Polymerase chain reaction (PCR) was performed to examine the expression of GASL1 mRNA in kidney cancer tissues, normal tissues, and the cell lines. GASL1 overexpression was achieved in kidney cancer cell lines A498 through transfection. MTT was used to detect the effects of GASL1 overexpression in A498 cells. GASL1 mRNA was significantly overexpressed in adjacent normal tissues compared with renal cell carcinoma. The expression of GASL1 is lower in kidney cancer cell lines than in normal kidney epithelium cell line HREpiC. Overexpression of GASL1 inhibits the proliferation of renal carcinoma cell lines. GASL1 mRNA was down-regulated in kidney cancer tissues and may play a role in kidney cancer cell proliferation.

Amino acid transporter SLC7A11/xCT at the crossroads of regulating redox homeostasis and nutrient dependency of cancer

Cancer cells often upregulate nutrient transporters to fulfill their increased biosynthetic and bioenergetic needs, and to maintain redox homeostasis. One nutrient transporter frequently overexpressed in human cancers is the cystine/glutamate antiporter solute carrier family 7 member 11 (SLC7A11; also known as xCT). SLC7A11 promotes cystine uptake and glutathione biosynthesis, resulting in protection from oxidative stress and ferroptotic cell death. Recent studies have unexpectedly revealed that SLC7A11 also plays critical roles in glutamine metabolism and regulates the glucose and glutamine dependency of cancer cells. This review discusses the roles of SLC7A11 in regulating the antioxidant response and nutrient dependency of cancer cells, explores our current understanding of SLC7A11 regulation in cancer metabolism, and highlights key open questions for future studies in this emerging research area. A deeper understanding of SLC7A11 in cancer metabolism may identify new therapeutic opportunities to target this important amino acid transporter for cancer treatment.

Bioinformatics and functional analyses of key genes and pathways in human clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. The present study was conducted to explore the mechanisms and identify the potential target genes for ccRCC using bioinformatics analysis. The microarray data of GSE15641 were screened on Gene-Cloud of Biotechnology Information (GCBI). A total of 32 ccRCC samples and 23 normal kidney samples were used to identify differentially expressed genes (DEGs) between them. Subsequently, the clustering analysis and functional enrichment analysis of these DEGs were performed, followed by protein-protein interaction (PPI) network, and pathway relation network. Additionally, the most significant module based on PPI network was selected, and the genes in the module were identified as hub genes. Furthermore, transcriptional level, translational level and survival analyses of hub genes were performed to verify the results. A total of 805 genes, 403 upregulated and 402 downregulated, were differentially expressed in ccRCC samples compared with normal controls. The subsequent bioinformatics analysis indicated that the small molecule metabolic process and the metabolic pathway were significantly enriched. A total of 7 genes, including membrane metallo-endopeptidase (MME), albumin (ALB), cadherin 1 (CDH1), prominin 1 (ROM1), chemokine (C-X-C motif) ligand 12 (CXCL12), protein tyrosine phosphatase receptor type C (PTPRC) and intercellular adhesion molecule 1 (ICAM1) were identified as hub genes. In brief, the present study indicated that these candidate genes and pathways may aid in deciphering the molecular mechanisms underlying the development of ccRCC, and may be used as therapeutic targets and diagnostic biomarkers of ccRCC.