Cancer insights from magnetic resonance spectroscopy of cells and excised tumors.

Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer tissue, and biofluids is a rapidly expanding field that is providing unique insights into cancer. Starting from the 1970s, the field has continued to evolve as a stand-alone technology or as a complement to in vivo MRS to characterize the metabolome of cancer cells, cancer-associated stromal cells, immune cells, tumors, biofluids and, more recently, changes in the metabolome of organs induced by cancers. Here, we review some of the insights into cancer obtained with ex vivo MRS and provide a perspective of future directions. Ex vivo MRS of cells and tumors provides opportunities to understand the role of metabolism in cancer immune surveillance and immunotherapy. With advances in computational capabilities, the integration of artificial intelligence to identify differences in multinuclear spectral patterns, especially in easily accessible biofluids, is providing exciting advances in detection and monitoring response to treatment. Metabolotheranostics to target cancers and to normalize metabolic changes in organs induced by cancers to prevent cancer-induced morbidity are other areas of future development.

Molecular and functional imaging insights into the role of hypoxia in cancer aggression.

Hypoxia in cancers has evoked significant interest since 1955 when Thomlinson and Gray postulated the presence of hypoxia in human lung cancers, based on the observation of necrosis occurring at the diffusion limit of oxygen from the nearest blood vessel, and identified the implication of these observations for radiation therapy. Coupled with discoveries in 1953 by Gray and others that anoxic cells were resistant to radiation damage, these observations have led to an entire field of research focused on exploiting oxygenation and hypoxia to improve the outcome of radiation therapy. Almost 65 years later, tumor heterogeneity of nearly every parameter measured including tumor oxygenation, and the dynamic landscape of cancers and their microenvironments are clearly evident, providing a strong rationale for cancer personalized medicine. Since hypoxia is a major cause of extracellular acidosis in tumors, here, we have focused on the applications of imaging to understand the effects of hypoxia in tumors and to target hypoxia in theranostic strategies. Molecular and functional imaging have critically important roles to play in personalized medicine through the detection of hypoxia, both spatially and temporally, and by providing new understanding of the role of hypoxia in cancer aggressiveness. With the discovery of the hypoxia-inducible factor (HIF), the intervening years have also seen significant progress in understanding the transcriptional regulation of hypoxia-induced genes. These advances have provided the ability to silence HIF and understand the associated molecular and functional consequences to expand our understanding of hypoxia and its role in cancer aggressiveness. Most recently, the development of hypoxia-based theranostic strategies that combine detection and therapy are further establishing imaging-based treatment strategies for precision medicine of cancer.

MRI and MRS of intact perfused cancer cell metabolism, invasion, and stromal cell interactions.

Because of the spatial and temporal heterogeneities of cancers, technologies to investigate cancer cells and the consequences of their interactions with abnormal physiological environments, such as hypoxia and acidic extracellular pH, with stromal cells, and with the extracellular matrix, under controlled conditions, are valuable to gain insights into the functioning of cancers. These insights can lead to an understanding of why cancers invade and metastasize, and identify effective treatment strategies. Here we have provided an overview of the applications of MRI/MRS/MRSI to investigate intact perfused cancer cells, their metabolism and invasion, and their interactions with stromal cells and the extracellular matrix.

Brain Tumor Detection and Classification Using Cycle Generative Adversarial Networks.

Brain cancer ranks tenth on the list of leading causes of death in both men and women. Biopsy is one of the most used methods for diagnosing cancer. However, the biopsy process is quite dangerous and take a long time to reach a decision. Furthermore, as the tumor size is rising quickly, non-invasive, automatic diagnostic equipment is required which can automatically detect the tumor and its stage precisely in a few seconds. In recent years, techniques based on Machine Learning and Deep Learning (DL) for detecting and classifying cancers has gained remarkable success in recent years. This paper suggested an ensemble method for detecting and classifying brain tumor and its stages using brain Magnetic Resonance Imaging (MRI). A modified InceptionResNetV2 pre-trained model is used for tumor detection from MRI image. After tumor detection, a combination of InceptionResNetV2 and Random Forest Tree (RFT) is used to determine the cancer stage, which includes glioma, meningioma, and pituitary cancer. The size of the dataset is small, so C-GAN (Cyclic Generative Adversarial Networks) is used to increase the dataset size. The experiment results demonstrate that the suggested tumor detection and tumor classification models achieve the accuracy of 99% and 98%, respectively.

Characterization of lipomatous tumors with high-resolution 1H MRS at 17.6T: Do benign lipomas, atypical lipomatous tumors and liposarcomas have a distinct metabolic signature?

Background: Distinguishing between some benign lipomas (BLs), atypical lipomatous tumors (ALTs), and dedifferentiated liposarcomas (DDLs) can be challenging due to overlapping magnetic resonance imaging characteristics, and poorly understood molecular mechanisms underlying the malignant transformation of liposarcomas. Purpose: To identify metabolic biomarkers of the lipomatous tumor spectrum by examining human tissue specimens using high-resolution 1H magnetic resonance spectroscopy (MRS). Materials and methods: In this prospective study, human tissue specimens were obtained from participants who underwent surgical resection for radiologically-indeterminate lipomatous tumors between November 2016 and May 2019. Tissue specimens were obtained from normal subcutaneous fat (n=9), BLs (n=10), ALTs (n=7) and DDLs (n=8). Extracts from specimens were examined with high-resolution MRS at 17.6T. Computational modeling of pattern recognition-based cluster analysis was utilized to identify significant differences in metabolic signatures between the lipomatous tumor types. Results: Significant differences between BLs and ALTs were observed for multiple metabolites, including leucine, valine, branched chain amino acids, alanine, acetate, glutamine, and formate. DDLs were distinguished from ALTs by increased glucose and lactate, and increased phosphatidylcholine. Multivariate principal component analysis showed clear clustering identifying distinct metabolic signatures of the tissue types. Conclusion: Metabolic signatures identified in 1H MR spectra of lipomatous tumors provide new insights into malignant progression and metabolic targeting. The metabolic patterns identified provide the foundation of developing noninvasive MRS or PET imaging biomarkers to distinguish between BLs, ALTs, and DDLs.

Text-Based Emotion Recognition Using Deep Learning Approach.

Sentiment analysis is a method to identify people's attitudes, sentiments, and emotions towards a given goal, such as people, activities, organizations, services, subjects, and products. Emotion detection is a subset of sentiment analysis as it predicts the unique emotion rather than just stating positive, negative, or neutral. In recent times, many researchers have already worked on speech and facial expressions for emotion recognition. However, emotion detection in text is a tedious task as cues are missing, unlike in speech, such as tonal stress, facial expression, pitch, etc. To identify emotions from text, several methods have been proposed in the past using natural language processing (NLP) techniques: the keyword approach, the lexicon-based approach, and the machine learning approach. However, there were some limitations with keyword- and lexicon-based approaches as they focus on semantic relations. In this article, we have proposed a hybrid (machine learning + deep learning) model to identify emotions in text. Convolutional neural network (CNN) and Bi-GRU were exploited as deep learning techniques. Support vector machine is used as a machine learning approach. The performance of the proposed approach is evaluated using a combination of three different types of datasets, namely, sentences, tweets, and dialogs, and it attains an accuracy of 80.11%.

Biguanide drugs enhance cytotoxic effects of cisplatin by depleting aspartate and NAD+ in sensitive cancer cells.

Biguanide drugs (metformin and phenformin) have drawn interest for potential cancer treatments, and laboratory studies show that some cancer cells are selectively sensitive to growth-inhibitory effects of biguanides. Examining metabolic pathways affected by biguanide treatments in cancer cells that are highly sensitive to biguanides, we found that biguanide treatment depletes cellular levels of both aspartate and NAD+. Experiments to replenish these metabolites or block steps of the aspartate-malate shuttle suggest that depletion of both metabolites, rather than either aspartate of NAD+ individually, is critical for growth-inhibitory effects of biguanide exposure. Even in sensitive cancer cells, though, biguanide treatment alone over a broad range of doses only inhibits cell replication without significantly affecting cell viability. Noting that clinical observations of biguanide efficacy have used combinations of agents that typically include cisplatin, we found that biguanide treatment at a cytostatic level substantially decreases survival of lung cancer and breast cancer cells when co-treated with cisplatin at doses that alone are also non-cytotoxic. This striking enhancement of cisplatin toxicity by biguanides depends on reductions of levels of NAD+ and aspartate, since addition of either of these metabolites prevented this potentiation of cisplatin cytotoxicity. Thus, biguanide drugs can have cytotoxic effects when used in combination with other cancer drugs, such as cisplatin, and depleting cellular levels of NAD+ and aspartate is critical for enhancing the cytotoxicity of cisplatin by biguanide drugs in sensitive cancer cells.

Hypoxia theranostics of a human prostate cancer xenograft and the resulting effects on the tumor microenvironment.

Hypoxia is frequently observed in human prostate cancer, and is associated with chemoresistance, radioresistance, metastasis, and castrate-resistance. Our purpose in these studies was to perform hypoxia theranostics by combining in vivo hypoxia imaging and hypoxic cancer cell targeting in a human prostate cancer xenograft. This was achieved by engineering PC3 human prostate cancer cells to express luciferase as well as a prodrug enzyme, yeast cytosine deaminase, under control of hypoxic response elements (HREs). Cancer cells display an adaptive response to hypoxia through the activation of several genes mediated by the binding of hypoxia inducible factors (HIFs) to HRE in the promoter region of target gene that results in their increased transcription. HIFs promote key steps in tumorigenesis, including angiogenesis, metabolism, proliferation, metastasis, and differentiation. HRE-driven luciferase expression allowed us to detect hypoxia in vivo to time the administration of the nontoxic prodrug 5-fluorocytosine that was converted by yeast cytosine deaminase, expressed under HRE regulation, to the chemotherapy agent 5-fluorouracil to target hypoxic cells. Conversion of 5-fluorocytosine to 5-fluorouracil was detected in vivo by 19F magnetic resonance spectroscopy. Morphological and immunohistochemical staining and molecular analyses were performed to characterize tumor microenvironment changes in cancer-associated fibroblasts, cell viability, collagen 1 fiber patterns, and HIF-1α. These studies expand our understanding of the effects of eliminating hypoxic cancer cells on the tumor microenvironment and in reducing stromal cell populations such as cancer-associated fibroblasts.

Brain metabolites in cholinergic and glutamatergic pathways are altered by pancreatic cancer cachexia.

BACKGROUND: Cachexia is a major cause of morbidity in pancreatic ductal adenocarcinoma (PDAC) patients. Our purpose was to understand the impact of PDAC-induced cachexia on brain metabolism in PDAC xenograft studies, to gain new insights into the causes of cachexia-induced morbidity. Changes in mouse and human plasma metabolites were characterized to identify underlying causes of brain metabolic changes. METHODS: We quantified metabolites, detected with high-resolution 1 H magnetic resonance spectroscopy, in the brain and plasma of normal mice (n = 10) and mice bearing cachexia (n = 10) or non-cachexia (n = 9) inducing PDAC xenografts as well as in human plasma obtained from normal individuals (n = 24) and from individuals with benign pancreatic disease (n = 20) and PDAC (n = 20). Statistical significance was defined as a P value ≤0.05. RESULTS: The brain metabolic signature of cachexia-inducing PDAC was characterized by a significant depletion of choline of -27% and -21% as well as increases of glutamine of 13% and 9% and formate of 21% and 14%, relative to normal controls and non-cachectic tumour-bearing mice, respectively. Good to moderate correlations with percent weight change were found for choline (r = 0.70), glutamine (r = -0.58), and formate (r = -0.43). Significant choline depletion of -38% and -30%, relative to normal controls and non-cachectic tumour-bearing mice, respectively, detected in the plasma of cachectic mice likely contributed to decreased brain choline in cachectic mice. Similarly, relative to normal controls and patients with benign disease, choline levels in human plasma samples of PDAC patients were significantly lower by -12% and -20% respectively. A comparison of plasma metabolites from PDAC patients with and without weight loss identified significant changes in glutamine metabolism. CONCLUSIONS: Disturbances in metabolites of the choline/cholinergic and glutamine/glutamate/glutamatergic neurotransmitter pathways may contribute to morbidity. Metabolic normalization may provide strategies to reduce morbidity. The human plasma metabolite changes observed may lead to the development of companion diagnostic markers to detect PDAC and PDAC-induced cachexia.

Hypoxia Patterns in Primary and Metastatic Prostate Cancer Environments.

Metastatic dissemination continues to be a major cause of prostate cancer (PCa) mortality, creating a compelling need to understand factors that play a role in the metastatic cascade. Since hypoxia plays an important role in PCa aggressiveness, we characterized patterns of hypoxia in the primary tumor and metastatic environments of a human PCa xenograft. We previously developed and characterized an imaging strategy based on the hypoxia response element (HRE)-driven expression of long-lived enhanced green fluorescent protein (EGFP) and short-lived luciferase (luc) fused to the oxygen-dependent degradation domain in human PCa PC-3 cells. Both reporter proteins were placed under the transcriptional control of a five-tandem repeat HRE sequence. PC-3 cells also constitutively expressed the tdTomato red fluorescent protein, allowing cancer cell detection in vivo. This "timer" strategy can provide information on the temporal evolution of HIF activity and hypoxia in tumors. Here, for the first time, we performed in vivo and ex vivo imaging of this dual HIF reporter system in PC-3 metastatic tumors implanted orthotopically in the prostate and PC-3 nonmetastatic tumors implanted subcutaneously. We observed distinct patterns of EGFP and luc expression in subcutaneous and orthotopic tumors, and in metastatic nodules, that provide new insights into the presence of hypoxia at primary and metastatic tumor sites, and of the role of hypoxia in metastasis.

Hypoxia-Induced Reporter Genes with Different Half-Lives.

The utility of reporter genes has gained significant momentum over the last three decades. Reporter genes are used to understand the transcriptional activity of a gene both in vitro and in vivo, and in pathway analysis and drug screening for diseases involving protozoan parasites, and in anti-cancer drug developments. Here, using a human prostate cancer xenograft model (PC3), we describe a method to construct and validate hypoxia reporter genes with different half-lives. Using molecular biology and optical imaging techniques, we have validated the expression of long half-life enhanced green fluorescence protein (EGFP) expression and short half-life luciferase gene expression to report on the spatial and temporal evolution of hypoxia in vivo.

Metabolic consequences of HIF silencing in a triple negative human breast cancer xenograft.

Hypoxia is frequently encountered in tumors and results in the stabilization of hypoxia inducible factors (HIFs). These factors transcriptionally activate genes that allow cells to adapt to hypoxia. In cancers, hypoxia and HIFs have been associated with increased invasion, metastasis, and resistance to chemo and radiation therapy. Here we have characterized the metabolic consequences of silencing HIF-1α and HIF-2α singly or combined in MDA-MB-231 triple negative human breast cancer xenografts, using non-invasive proton magnetic resonance spectroscopic imaging (1H MRSI) of in vivo tumors, and high-resolution 1H MRS of tumor extracts. Tumors from all three sublines showed a significant reduction of growth rate. We identified new metabolic targets of HIF, and demonstrated the divergent consequences of silencing HIF-1α and HIF-2α individually on some of these targets. These data expand our understanding of the metabolic pathways regulated by HIFs that may provide new insights into the adaptive metabolic response of cancer cells to hypoxia. Such insights may lead to novel metabolism based therapeutic targets for triple negative breast cancer.

Metabolomic characterization of experimental ovarian cancer ascitic fluid.

INTRODUCTION: Malignant ascites (MA) is a major cause of morbidity that occurs in 37% of ovarian cancer patients. The accumulation of MA in the peritoneal cavity due to cancer results in debilitating symptoms and extremely poor quality of life. There is an urgent unmet need to expand the understanding of MA to design effective treatment strategies, and to improve MA diagnosis. OBJECTIVE: Our purpose here is to contribute to a better characterization of MA metabolic composition in ovarian cancer. METHOD: We determined the metabolic composition of ascitic fluids resulting from orthotopic growth of two ovarian cancer cell lines, the mouse ID8-vascular endothelial growth factor (VEGF)-Defb29 cell line and the human OVCAR3 cell line using high-resolution 1H MRS. ID8-VEGF-Defb29 tumors induce large volumes of ascites, while OVCAR3 tumors induce ascites less frequently and at smaller volumes. To better understand the factors driving the metabolic composition of the fluid, we characterized the metabolism of these ovarian cancer cells in culture by analyzing cell lysates and conditioned culture media with 1H NMR. RESULTS: Distinct metabolite patterns were detected in ascitic fluid collected from OVCAR3 and ID8-VEGF-Defb29 tumor bearing mice that were not reflected in the corresponding cell culture or conditioned medium. CONCLUSION: High-resolution 1H NMR metabolic markers of MA can be used to improve characterization and diagnosis of MA. Metabolic characterization of MA can provide new insights into how MA fluid supports cancer cell growth and resistance to treatment, and has the potential to identify metabolic targeting strategies to reduce or eliminate the formation of MA.

Detection of Pancreatic Cancer-Induced Cachexia Using a Fluorescent Myoblast Reporter System and Analysis of Metabolite Abundance.

The dire effects of cancer-induced cachexia undermine treatment and contribute to decreased survival rates. Therapeutic options for this syndrome are limited, and therefore efforts to identify signs of precachexia in cancer patients are necessary for early intervention. The applications of molecular and functional imaging that would enable a whole-body "holistic" approach to this problem may lead to new insights and advances for diagnosis and treatment of this syndrome. Here we have developed a myoblast optical reporter system with the purpose of identifying early cachectic events. We generated a myoblast cell line expressing a dual tdTomato:GFP construct that was grafted onto the muscle of mice-bearing human pancreatic cancer xenografts to provide noninvasive live imaging of events associated with cancer-induced cachexia (i.e., weight loss). Real-time optical imaging detected a strong tdTomato fluorescent signal from skeletal muscle grafts in mice with weight losses of only 1.2% to 2.7% and tumor burdens of only approximately 79 to 170 mm(3). Weight loss in cachectic animals was also associated with a depletion of lipid, cholesterol, valine, and alanine levels, which may provide informative biomarkers of cachexia. Taken together, our findings demonstrate the utility of a reporter system that is capable of tracking tumor-induced weight loss, an early marker of cachexia. Future studies incorporating resected tissue from human pancreatic ductal adenocarcinoma into a reporter-carrying mouse may be able to provide a risk assessment of cachexia, with possible implications for therapeutic development.

Combining Optical Reporter Proteins with Different Half-lives to Detect Temporal Evolution of Hypoxia and Reoxygenation in Tumors.

Here we have developed a hypoxia response element driven imaging strategy that combined the hypoxia-driven expression of two optical reporters with different half-lives to detect temporal changes in hypoxia and hypoxia inducible factor (HIF) activity. For this purpose, human prostate cancer PC3 cells were transfected with the luciferase gene fused with an oxygen-dependent degradation domain (ODD-luc) and a variant of the enhanced green fluorescent protein (EGFP). Both ODD-luciferase and EGFP were under the promotion of a poly-hypoxia-response element sequence (5xHRE). The cells constitutively expressed tdTomato red fluorescent protein. For validating the imaging strategy, cells were incubated under hypoxia (1% O2) for 48 hours and then reoxygenated. The luciferase activity of PC3-HRE-EGFP/HRE-ODD-luc/tdtomato cells detected by bioluminescent imaging rapidly decreased after reoxygenation, whereas EGFP levels in these cells remained stable for several hours. After in vitro validation, PC3-HRE-EGFP/HRE-ODD-luc/tdtomato tumors were implanted subcutaneously and orthotopically in nude male mice and imaged in vivo and ex vivo using optical imaging in proof-of-principle studies to demonstrate differences in optical patterns between EGFP expression and bioluminescence. This novel "timer" imaging strategy of combining the short-lived ODD-luciferase and the long-lived EGFP can provide a time frame of HRE activation in PC3 prostate cancer cells and will be useful to understand the temporal changes in hypoxia and HIF activity during cancer progression and following treatments including HIF targeting strategies.

Metabolic imaging of pancreatic ductal adenocarcinoma detects altered choline metabolism.

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and lethal disease that develops relatively symptom-free and is therefore advanced at the time of diagnosis. The absence of early symptoms and effective treatments has created a critical need for identifying and developing new noninvasive biomarkers and therapeutic targets. EXPERIMENTAL DESIGN: We investigated the metabolism of a panel of PDAC cell lines in culture and noninvasively in vivo with (1)H magnetic resonance spectroscopic imaging (MRSI) to identify noninvasive biomarkers and uncover potential metabolic targets. RESULTS: We observed elevated choline-containing compounds in the PDAC cell lines and tumors. These elevated choline-containing compounds were easily detected by increased total choline (tCho) in vivo, in spectroscopic images obtained from tumors. Principal component analysis of the spectral data identified additional differences in metabolites between immortalized human pancreatic cells and neoplastic PDAC cells. Molecular characterization revealed overexpression of choline kinase (Chk)-α, choline transporter 1 (CHT1), and choline transporter-like protein 1 (CTL1) in the PDAC cell lines and tumors. CONCLUSIONS: Collectively, these data identify new metabolic characteristics of PDAC and reveal potential metabolic targets. Total choline detected with (1)H MRSI may provide an intrinsic, imaging probe-independent biomarker to complement existing techniques in detecting PDAC. The expression of Chk-α, CHT1, and CTL1 may provide additional molecular markers in aspirated cytological samples.

Metabolic profiling of Commiphora wightii (guggul) reveals a potential source for pharmaceuticals and nutraceuticals.

Guggul gum resin from Commiphora wightii (syn. Commiphoramukul) has been used for centuries in Ayurveda to treat a variety of ailments. The NMR and GC-MS based non-targeted metabolite profiling identified 118 chemically diverse metabolites including amino acids, fatty acids, organic acids, phenolic acids, pregnane-derivatives, steroids, sterols, sugars, sugar alcohol, terpenoids, and tocopherol from aqueous and non-aqueous extracts of leaves, stem, roots, latex and fruits of C. wightii. Out of 118, 51 structurally diverse aqueous metabolites were characterized by NMR spectroscopy. For the first time quinic acid and myo-inositol were identified as the major metabolites in C. wightii. Very high concentration of quinic acid was found in fruits (553.5 ± 39.38 mg g(-1) dry wt.) and leaves (212.9 ± 10.37 mg g(-1) dry wt.). Similarly, high concentration of myo-inositol (168.8 ± 13.84 mg g(-1) dry wt.) was observed from fruits. The other metabolites of cosmeceutical, medicinal, nutraceutical and industrial significance such as α-tocopherol, n-methylpyrrolidone (NMP), trans-farnesol, prostaglandin F2, protocatechuic, gallic and cinnamic acids were identified from non-aqueous extracts using GC-MS. These important metabolites have thus far not been reported from this plant. Isolation of a fungal endophyte, (Nigrospora sps.) from this plant is the first report. The fungal endophyte produced a substantial quantity of bostrycin and deoxybostrycin known for their antitumor properties. Very high concentrations of quinic acid and myo-inositol in leaves and fruits; a substantial quantity of α-tocopherol and NMP in leaves, trans-farnesol in fruits, bostrycin and deoxybostrycin from its endophyte makes the taxa distinct, since these metabolites with medicinal properties find immense applications as dietary supplements and nutraceuticals.

Metabolite profiling reveals abiotic stress tolerance in Tn5 mutant of Pseudomonas putida.

Pseudomonas is an efficient plant growth-promoting rhizobacteria (PGPR); however, intolerance to drought and high temperature limit its application in agriculture as a bioinoculant. Transposon 5 (Tn5) mutagenesis was used to generate a stress tolerant mutant from a PGPR Pseudomonas putida NBRI1108 isolated from chickpea rhizosphere. A mutant NBRI1108T, selected after screening of nearly 10,000 transconjugants, exhibited significant tolerance towards high temperature and drought. Southern hybridization analysis of EcoRI and XhoI restricted genomic DNA of NBRI1108T confirmed that it had a single Tn5 insertion. The metabolic changes in the polar and non-polar extracts of NBRI1108 and NBRI1108T were examined using 1H, 31P nuclear magnetic resonance (NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS). Thirty six chemically diverse metabolites consisting of amino acids, fatty acids and phospholipids were identified and quantified. Insertion of Tn5 influenced amino acid and phospholipid metabolism and resulted in significantly higher concentration of aspartic acid, glutamic acid, glycinebetaine, glycerophosphatidylcholine (GPC) and putrescine in NBRI1108T as compared to that in NBRI1108. The concentration of glutamic acid, glycinebetaine and GPC increased by 34%, 95% and 100%, respectively in the NBRI1108T as compared to that in NBRI1108. High concentration of glycerophosphatidylethanolamine (GPE) and undetected GPC in NBRI1108 indicates that biosynthesis of GPE may have taken place via the methylation pathway of phospholipid biosynthesis. However, high GPC and low GPE concentration in NBRI1108T suggest that methylation pathway and phosphatidylcholine synthase (PCS) pathway of phospholipid biosynthesis are being followed in the NBRI1108T. Application of multivariate principal component analysis (PCA) on the quantified metabolites revealed clear variations in NBRI1108 and NBRI1108T in polar and non-polar metabolites. Identification of abiotic stress tolerant metabolites from the NBRI1108T suggest that Tn5 mutagenesis enhanced tolerance towards high temperature and drought. Tolerance to drought was further confirmed in greenhouse experiments with maize as host plant, where NBRI1108T showed relatively high biomass under drought conditions.

Targeting Glutamine Metabolism in Breast Cancer with Aminooxyacetate.

PURPOSE: Glutamine addiction in c-MYC-overexpressing breast cancer is targeted by the aminotransferase inhibitor, aminooxyacetate (AOA). However, the mechanism of ensuing cell death remains unresolved. EXPERIMENTAL DESIGN: A correlation between glutamine dependence for growth and c-MYC expression was studied in breast cancer cell lines. The cytotoxic effects of AOA, its correlation with high c-MYC expression, and effects on enzymes in the glutaminolytic pathway were investigated. AOA-induced cell death was assessed by measuring changes in metabolite levels by magnetic resonance spectroscopy (MRS), the effects of amino acid depletion on nucleotide synthesis by cell-cycle and bromodeoxyuridine (BrdUrd) uptake analysis, and activation of the endoplasmic reticulum (ER) stress-mediated pathway. Antitumor effects of AOA with or without common chemotherapies were determined in breast cancer xenografts in immunodeficient mice and in a transgenic MMTV-rTtA-TetO-myc mouse mammary tumor model. RESULTS: We established a direct correlation between c-MYC overexpression, suppression of glutaminolysis, and AOA sensitivity in most breast cancer cells. MRS, cell-cycle analysis, and BrdUrd uptake measurements indicated depletion of aspartic acid and alanine leading to cell-cycle arrest at S-phase by AOA. Activation of components of the ER stress-mediated pathway, initiated through GRP78, led to apoptotic cell death. AOA inhibited growth of SUM159, SUM149, and MCF-7 xenografts and c-myc-overexpressing transgenic mouse mammary tumors. In MDA-MB-231, AOA was effective only in combination with chemotherapy. CONCLUSIONS: AOA mediates its cytotoxic effects largely through the stress response pathway. The preclinical data of AOA's effectiveness provide a strong rationale for further clinical development, particularly for c-MYC-overexpressing breast cancers.