Untargeted and stable isotope-assisted metabolomic analysis of MDA-MB-231 cells under hypoxia

Introduction

Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.

Objectives

Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.

Methods

Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.

Results

Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.

Conclusion

The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.

     

WNT and NOTCH signaling pathways as activators for epidermal growth factor receptor in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer, with a poor prognosis. Deregulation of WNT and NOTCH signaling pathways is important in ESCC progression, which can be due to either malfunction of their components or crosstalk with other pathways. Therefore, identification of new crosstalk between such pathways may be effective to introduce new strategies for targeted therapy of cancer. A correlation study was performed to assess the probable interaction between growth factor receptors and WNT/NOTCH pathways via the epidermal growth factor receptor (EGFR) and Musashi1 (MSI1), respectively.

Methods

Levels of MSI1/EGFR mRNA expression in tumor tissues from 48 ESCC patients were compared to their corresponding normal tissues using real-time polymerase chain reaction.

Results

There was a significant correlation between EGFR and MSI1 expression (p?=?0.05). Moreover, there was a significant correlation between EGFR/MSI1 expression and grade of tumor differentiation (p?=?0.02).

Conclusion

This study confirms a direct correlation between MSI1 and EGFR and may support the important role of MSI1 in activation of EGFR through NOTCH/WNT pathways in ESCC.

     

Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based algorithm

Introduction

Metabolomic profiling combines Nuclear Magnetic Resonance spectroscopy with supervised statistical analysis that might allow to better understanding the mechanisms of a disease.

Objectives

In this study, the urinary metabolic profiling of individuals with porphyrias was performed to predict different types of disease, and to propose new pathophysiological hypotheses.

Methods

Urine ¹H-NMR spectra of 73 patients with asymptomatic acute intermittent porphyria (aAIP) and familial or sporadic porphyria cutanea tarda (f/sPCT) were compared using a supervised rule-mining algorithm. NMR spectrum buckets bins, corresponding to rules, were extracted and a logistic regression was trained.

Results

Our rule-mining algorithm generated results were consistent with those obtained using partial least square discriminant analysis (PLS-DA) and the predictive performance of the model was significant. Buckets that were identified by the algorithm corresponded to metabolites involved in glycolysis and energy-conversion pathways, notably acetate, citrate, and pyruvate, which were found in higher concentrations in the urines of aAIP compared with PCT patients. Metabolic profiling did not discriminate sPCT from fPCT patients.

Conclusion

These results suggest that metabolic reprogramming occurs in aAIP individuals, even in the absence of overt symptoms, and supports the relationship that occur between heme synthesis and mitochondrial energetic metabolism.

     

How the chemical features of molecules may have addressed the settlement of metabolic steps

Introduction

While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.

Objectives

Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.

Methods

The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.

Results

Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.

Conclusions

Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.

     

PTEN at the interface of immune tolerance and tumor suppression

Background

PTEN is well known to function as a tumor suppressor that antagonizes oncogenic signaling and maintains genomic stability. The PTEN gene is frequently deleted or mutated in human cancers and the wide cancer spectrum associated with PTEN deficiency has been recapitulated in a variety of mouse models of Pten deletion or mutation. Pten mutations are highly penetrant in causing various types of spontaneous tumors that often exhibit resistance to anticancer therapies including immunotherapy. Recent studies demonstrate that PTEN also regulates immune functionality.

Objective

To understand the multifaceted functions of PTEN as both a tumor suppressor and an immune regulator.

Methods

This review will summarize the emerging knowledge of PTEN function in cancer immunoediting. In addition, the mechanisms underlying functional integration of various PTEN pathways in regulating cancer evolution and tumor immunity will be highlighted.

Results

Recent preclinical and clinical studies revealed the essential role of PTEN in maintaining immune homeostasis, which significantly expands the repertoire of PTEN functions. Mechanistically, aberrant PTEN signaling alters the interplay between the immune system and tumors, leading to immunosuppression and tumor escape.

Conclusion

Rational design of personalized anti-cancer treatment requires mechanistic understanding of diverse PTEN signaling pathways in modulation of the crosstalk between tumor and immune cells.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.

     

DTL reconciliation repair

Background

Maximum parsimony phylogenetic tree reconciliation is an important technique for reconstructing the evolutionary histories of hosts and parasites, genes and species, and other interdependent pairs. Since the problem of finding temporally feasible maximum parsimony reconciliations is NP-complete, current methods use either exact algorithms with exponential worst-case running time or heuristics that do not guarantee optimal solutions.

Results

We offer an efficient new approach that begins with a potentially infeasible maximum parsimony reconciliation and iteratively “repairs” it until it becomes temporally feasible.

Conclusions

In a non-trivial number of cases, this approach finds solutions that are better than those found by the widely-used Jane heuristic.

     

High salt and fat intake,inflammation, and risk of cancer

Background

Inflammatory conditions are involved in the pathophysiology of cancer. Recent findings have revealed that excessive salt and fat intake is involved in the development of severe inflammatory reactions.

Methods

literature search was performed on various online databases (PubMed, Scopus, and Google Scholar) regarding the roles of high salt and fat intake in the induction of inflammatory reactions and their roles in the etiopathogenesis of cancer.

Results

The results indicate that high salt and fat intake can induce severe inflammatory conditions. However, various inflammatory conditions have been strongly linked to the development of cancer. Hence, high salt and fat intake might be involved in the pathogenesis of cancer progression via putative mechanisms related to inflammatory reactions.

Conclusion

Reducing salt and fat intake may decrease the risk of cancer.

     

Best serum biomarker combination for ovarian cancer classification

Background

Screening test using CA-125 is the most common test for detecting ovarian cancer. However, the level of CA-125 is diverse by variable condition other than ovarian cancer. It has led to misdiagnosis of ovarian cancer.

Methods

In this paper, we explore the 16 serum biomarker for finding alternative biomarker combination to reduce misdiagnosis. For experiment, we use the serum samples that contain 101 cancer and 92 healthy samples. We perform two major tasks: Marker selection and Classification. For optimal marker selection, we use genetic algorithm, random forest, T-test and logistic regression. For classification, we compare linear discriminative analysis, K-nearest neighbor and logistic regression.

Results

The final results show that the logistic regression gives high performance for both tasks, and HE4-ELISA, PDGF-AA, Prolactin, TTR is the best biomarker combination for detecting ovarian cancer.

Conclusions

We find the combination which contains TTR and Prolactin gives high performance for cancer detection. Early detection of ovarian cancer can reduce high mortality rates. Finding a combination of multiple biomarkers for diagnostic tests with high sensitivity and specificity is very important.

     

Characterizing biomarkers in osteosarcoma metastasis based on an ego-network

Objectives

To characterize biomarkers that underlie osteosarcoma (OS) metastasis based on an ego-network.

Results

From the microarray data, we obtained 13,326 genes. By combining PPI data and microarray data, 10,520 shared genes were found and constructed into ego-networks. 17 significant ego-networks were identified with p < 0.05. In the pathway enrichment analysis, seven ego-networks were identified with the most significant pathway.

Conclusions

These significant ego-modules were potential biomarkers that reveal the potential mechanisms in OS metastasis, which may contribute to understanding cancer prognoses and providing new perspectives in the treatment of cancer.

     

Protein structure determination via an efficient geometric build-up algorithm

Background

A protein structure can be determined by solving a so-called distance geometry problem whenever a set of inter-atomic distances is available and sufficient. However, the problem is intractable in general and has proved to be a NP hard problem. An updated geometric build-up algorithm (UGB) has been developed recently that controls numerical errors and is efficient in protein structure determination for cases where only sparse exact distance data is available. In this paper, the UGB method has been improved and revised with aims at solving distance geometry problems more efficiently and effectively.

Methods

An efficient algorithm (called the revised updated geometric build-up algorithm (RUGB)) to build up a protein structure from atomic distance data is presented and provides an effective way of determining a protein structure with sparse exact distance data. In the algorithm, the condition to determine an unpositioned atom iteratively is relaxed (when compared with the UGB algorithm) and data structure techniques are used to make the algorithm more efficient and effective. The algorithm is tested on a set of proteins selected randomly from the Protein Structure Database-PDB.

Results

We test a set of proteins selected randomly from the Protein Structure Database-PDB. We show that the numerical errors produced by the new RUGB algorithm are smaller when compared with the errors of the UGB algorithm and that the novel RUGB algorithm has a significantly smaller runtime than the UGB algorithm.

Conclusions

The RUGB algorithm relaxes the condition for updating and incorporates the data structure for accessing neighbours of an atom. The revisions result in an improvement over the UGB algorithm in two important areas: a reduction on the overall runtime and decrease of the numeric error.

     

Untargeted polar metabolomics of transformed MDA-MB-231 breast cancer cells expressing varying levels of human arylamine <Emphasis Type="Italic">N</Emphasis>-acetyltransferase 1

Introduction

Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. Expression of NAT1 is elevated in several cancers including breast cancer. However, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear.

Objective

This study explored polar metabolome differences between MDA-MB-231 breast cancer cells expressing varying levels of NAT1 activity using an untargeted approach.

Methods

Three MDA-MB-231 breast adenocarcinoma cell lines that stably express wild-type, increased, and decreased levels of human NAT1 were investigated for differences in polar metabolic profile using a comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) system.

Results

Increased levels of human NAT1 in the transformed cell lines resulted in a statistically significant decreased abundance of the metabolite palmitoleic acid (q = 0.0006), when compared to normal and decreased levels of human NAT1. The fatty acid synthesis pathway utilizes acetyl coenzyme A (acetyl-CoA) in the first two reactions of the pathway and eventually leads to the synthesis of palmitoleic acid.

Conclusion

These data suggest a link between increased levels of NAT1 activity and decreased flux of acetyl-CoA through this portion of the fatty acid synthesis pathway.

     

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study

Introduction

Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

Objectives

The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

Methods

A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.

Results

Using partial least squares-discriminant analysis, we observed significant separation between all groups (p?<?0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI)?=?0.940 and 0.929 for HG and LG, respectively.

Conclusion

These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.

     

Male breast cancer: thirteen years experience of a single center

Background

This retrospective study analysed the epidemiological, clinical, and therapeutic profiles of breast cancer in males.

Methods

We report our experience at the Hospital of the University of Baskent, where 20 cases of male breast cancer were observed and treated between 1995–2008.

Results

Median age at presentation was 66,7 ± 10,9 years. Average follow-up was 63 ± 18,5 months. The main presenting symptom was a mass in 65% of cases (13 patients). Ýnvasive ductal carcinoma was the most frequent pathologic type (70% of cases).

Conclusion

Male breast cancer patients have an incidence of prostate cancer higher than would be predicted in the general population. Cause of men have a higher rate of ER positivity the responses with hormonal agents are good.

     

Influence of media selection on NMR based metabolic profiling of human cell lines

Introduction

Comparative metabolic profiling of different human cancer cell lines can reveal metabolic pathways up-regulated or down-regulated in each cell line, potentially providing insight into distinct metabolism taking place in different types of cancer cells. It is noteworthy, however, that human cell lines available from public repositories are deposited with recommended media for optimal growth, and if cell lines to be compared are cultured on different growth media, this introduces a potentially serious confounding variable in metabolic profiling studies designed to identify intrinsic metabolic pathways active in each cell line.

Objectives

The goal of this study was to determine if the culture media used to grow human cell lines had a significant impact on the measured metabolic profiles.

Methods

NMR-based metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, AsPC-1, MiaPaCa-2 and Panc-1, were compared after culture on Dulbecco’s Modified Eagle Medium (DMEM) or Roswell Park Memorial Institute (RPMI-1640) medium.

Results

Comparisons of the same cell lines cultured on different media revealed that the concentrations of many metabolites depended strongly on the choice of culture media. Analyses of different cell lines grown on the same media revealed insight into their metabolic differences.

Conclusion

The choice of culture media can significantly impact metabolic profiles of human cell lines and should be considered an important variable when designing metabolic profiling studies. Also, the metabolic differences of cells cultured on media recommended for optimal growth in comparison to a second growth medium can reveal critical insight into metabolic pathways active in each cell line.

     

Triterpenoid-rich loquat leaf extract induces growth inhibition and apoptosis of pancreatic cancer cells through altering key flux ratios of glucose metabolism

Introduction

Loquat leaf extract (LLE) is a mixture rich in terpenoids, and has broad biological activities including the inhibition of cancer cell growth. The exact metabolic mechanism of this growth inhibiting effect is not known.

Objectives

We investigated the cellular metabolic effect of LLE, and ursolic acid (UA) on pancreatic cancer cells using a ¹³C carbon tracing technology.

Methods

MIA PaCa-2 cells were cultured in medium containing [1, 2 ¹³C₂]-glucose in the presence of either LLE (50 µg/ml), UA (50 µM), or metformin (1 mM). The mass isotopomer distribution of glucose, lactate, ribose, glutamate and palmitate in medium was determined. Based on the mass isotopomer distribution in metabolites we were able to determine individual ¹³C enrichment (∑M?×?n) and the minimum fraction of new synthesis?(1-M0) in each metabolite. Several flux ratios of energy metabolic pathways were calculated from the mass isotopomer ratios of these metabolites.

Results

We found that tumor viability was suppressed by LLE and UA in a dose dependent manner, and the tumor-inhibiting effect was associated with the changes in oxidative/non-oxidative pentose (Ox/Non-ox) and pyruvate dehydrogenase/isocitrate dehydrogenase (PDH/ICDH) flux ratios resulting in decreased new syntheses of ribose and fatty acids.

Conclusion

Metabolic homeostasis (balance of fluxes) in cancer cells is maintained through the regulation of metabolic fluxes by oncogenes and tumor-suppressor genes. Treatment of MIA PaCa-2 cells by LLE, UA and metformin likely altered key metabolic flux ratios affecting metabolic homeostasis required for energy and macromolecular production in tumor growth.

     

Metastatic tumor cells – genotypes and phenotypes

Background

Metastasis is the primary cause of mortality in cancer patients. Therefore, elucidating the genetics and epigenetics of metastatic tumor cells and the mechanisms by which tumor cells acquire metastatic properties constitute significant challenges in cancer research.

Objective

To summarize the current understandings of the specific genotype and phenotype of the metastatic tumor cells.

Method and Result

In-depth genetic analysis of tumor cells, especially with advances in the next-generation sequencing, have revealed insights of the genotypes of metastatic tumor cells. Also, studies have shown that the cancer stem cell (CSC) and epithelial to mesenchymal transition (EMT) phenotypes are associated with the metastatic cascade.

Conclusion

In this review, we will discuss recent advances in the field by focusing on the genomic instability and phenotypic dynamics of metastatic tumor cells.

     

A novel trichosanthin fusion protein with increased cytotoxicity to tumor cells

Objective

To evaluate the anti-tumor effects of trichosanthin after fusion with a cell penetrating peptide, heparin-binding peptide (HBP), derived from human heparin-binding EGF-like growth factor (HB-EGF).

Results

The fusion protein of trichosanthin-HBP was expressed in Escherichia coli BL21 and purified by Ni–NTA affinity chromatography. The HBP domain had no influence on the topological inactivation activity and N-glycosidase activity of trichosanthin. Trichosanthin-HBP significantly inhibited the growth of tested cancer cells which are impervious to trichosanthin. Tumor cell apoptosis and both the mitochondrial- and death receptor-mediated apoptotic signaling pathways induced by trichosanthin-HBP were more significant than those induced by trichosanthin in HeLa cells.

Conclusion

HBP is an efficient intracellular delivery vehicle for trichosanthin and makes trichosanthin-HBP become a promising agent for cancer therapy.