Deepak Nagrath

Three-dimensional primary hepatocyte culture in synthetic self-assembling peptide hydrogel.

Drug metabolism studies and liver tissue engineering necessitate stable hepatocyte cultures that express liver functions for a minimum of 4 days to 3 weeks. Current techniques, using different biomaterials and geometries, that maintain hepatocellular function in vitro exhibit a low cell density and functional capacity per unit volume. Herein we investigated a well-defined synthetic peptide that can self-assemble into three-dimensional interweaving nanofiber scaffolds to form a hydrogel, PuraMatrix, as a substrate for hepatocyte culture. Freshly isolated primary rat hepatocytes attached, migrated, and formed spheroids within 3 days after seeding on PuraMatrix. Hepatocytes expressed the apical membrane marker dipeptidyl peptidase IV at cell-cell contacts. Compared to the collagen sandwich, albumin and urea secretion on PuraMatrix were higher for the first week, and cytochrome P450IA1 activity was higher throughout the culture period. Mitochondrial membrane potential 1 day after seeding was higher on PuraMatrix than in the collagen sandwich, suggesting better preservation of the metabolic machinery. PuraMatrix and Matrigel showed similar albumin and urea production. PuraMatrix is an attractive system for generating hepatocyte spheroids that quickly restore liver functions after seeding. This system is also amenable to scale-up, which makes it suitable for in vitro toxicity, hepatocyte transplantation, and bioartificial liver development studies.

Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism

Cancer-associated fibroblasts (CAFs) are a major cellular component of tumor microenvironment in most solid cancers. Altered cellular metabolism is a hallmark of cancer, and much of the published literature has focused on neoplastic cell-autonomous processes for these adaptations. We demonstrate that exosomes secreted by patient-derived CAFs can strikingly reprogram the metabolic machinery following their uptake by cancer cells. We find that CAF-derived exosomes (CDEs) inhibit mitochondrial oxidative phosphorylation, thereby increasing glycolysis and glutamine-dependent reductive carboxylation in cancer cells. Through 13C-labeled isotope labeling experiments we elucidate that exosomes supply amino acids to nutrient-deprived cancer cells in a mechanism similar to macropinocytosis, albeit without the previously described dependence on oncogenic-Kras signaling. Using intra-exosomal metabolomics, we provide compelling evidence that CDEs contain intact metabolites, including amino acids, lipids, and TCA-cycle intermediates that are avidly utilized by cancer cells for central carbon metabolism and promoting tumor growth under nutrient deprivation or nutrient stressed conditions. DOI: http://dx.doi.org/10.7554/eLife.10250.001

Metabolic shifts toward glutamine regulate tumor growth, invasion and bioenergetics in ovarian cancer

Glutamine can play a critical role in cellular growth in multiple cancers. Glutamine‐addicted cancer cells are dependent on glutamine for viability, and their metabolism is reprogrammed for glutamine utilization through the tricarboxylic acid (TCA) cycle. Here, we have uncovered a missing link between cancer invasiveness and glutamine dependence. Using isotope tracer and bioenergetic analysis, we found that low‐invasive ovarian cancer (OVCA) cells are glutamine independent, whereas high‐invasive OVCA cells are markedly glutamine dependent. Consistent with our findings, OVCA patients’ microarray data suggest that glutaminolysis correlates with poor survival. Notably, the ratio of gene expression associated with glutamine anabolism versus catabolism has emerged as a novel biomarker for patient prognosis. Significantly, we found that glutamine regulates the activation of STAT3, a mediator of signaling pathways which regulates cancer hallmarks in invasive OVCA cells. Our findings suggest that a combined approach of targeting high‐invasive OVCA cells by blocking glutamines entry into the TCA cycle, along with targeting low‐invasive OVCA cells by inhibiting glutamine synthesis and STAT3 may lead to potential therapeutic approaches for treating OVCAs.

The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells

Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network‐based computational analysis of global gene expression data from matched sensitive and acquired drug‐resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2‐positive breast cancer patients. Further, forcing drug‐sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.

Metabolic preconditioning of donor organs: Defatting fatty livers by normothermic perfusion ex vivo

Fatty liver is a significant risk factor for liver transplantation, and accounts for nearly half of the livers rejected from the donor pool. We hypothesized that metabolic preconditioning via ex vivo perfusion of the liver graft can reduce fat content and increase post-transplant survival to an acceptable range. We describe a perfusate medium containing agents that promote the defatting of hepatocytes and explanted livers. Defatting agents were screened on cultured hepatocytes made fatty by pre-incubation with fatty acids. The most effective agents were then used on fatty livers. Fatty livers were isolated from obese Zucker rats and normothermically perfused with medium containing a combination of defatting agents. This combination decreased the intracellular lipid content of cultured hepatocytes by 35% over 24h, and of perfused livers by 50% over 3h. Metabolite analysis suggests that the defatting cocktail upregulated both lipid oxidation and export. Furthermore, gene expression analysis for several enzymes and transcription factors involved in fatty acid oxidation and triglyceride clearance were elevated. We conclude that a cocktail of defatting agents can be used to rapidly clear excess lipid storage in fatty livers, thus providing a new means to recondition donor livers deemed unacceptable or marginally acceptable for transplantation.

Integrated energy and flux balance based multiobjective framework for large-scale metabolic networks.

Flux balance analysis (FBA) provides a framework for the estimation of intracellular fluxes and energy balance analysis (EBA) ensures the thermodynamic feasibility of the computed optimal fluxes. Previously, these techniques have been used to obtain optimal fluxes that maximize a single objective. Because mammalian systems perform various functions, a multi-objective approach is needed when seeking optimal flux distributions in such systems. For example, hepatocytes perform several metabolic functions at various levels depending on environmental conditions; furthermore, there is a potential benefit to enhance some of these functions for applications such as bioartificial liver (BAL) support devices. Herein we developed a multi-objective optimization approach that couples the normalized Normal Constraint (NC) with both FBA and EBA to obtain multi-objective Pareto-optimal solutions. We investigated the Pareto frontiers in gluconeogenic and glycolytic hepatocytes for various combinations of liver-specific objectives (albumin synthesis, glutathione synthesis, NADPH synthesis, ATP generation, and urea secretion). Next, we evaluated the impact of experimental flux measurements on the Pareto frontiers. We found that measurements induce dramatic changes in Pareto frontiers and further constrain the network fluxes. This multi-objective optimality analysis may help explain certain features of the metabolic control of hepatocytes, which is relevant to the response to hepatocytes and liver to various physiological stimuli and disease states.

Metabolomics for mitochondrial and cancer studies.

Metabolomics, a high-throughput global metabolite analysis, is a burgeoning field, and in recent times has shown substantial evidence to support its emerging role in cancer diagnosis, cancer recurrence, and prognosis, as well as its impact in identifying novel cancer biomarkers and developing cancer therapeutics. Newly evolving advances in disease diagnostics and therapy will further facilitate future growth in the field of metabolomics, especially in cancer, where there is a dire need for sensitive and more affordable diagnostic tools and an urgency to develop effective therapies and identify reliable biomarkers to predict accurately the response to a therapy. Here, we review the application of metabolomics in cancer and mitochondrial studies and its role in enabling the understanding of altered metabolism and malignant transformation during cancer growth and metastasis. The recent developments in the area of metabolic flux analysis may help to close the gap between clinical metabolomics research and the development of cancer metabolome. In the era of personalized medicine with more and more patient specific targeted therapies being used, we need reliable, dynamic, faster, and yet sensitive biomarkers both to track the disease and to develop and evolve therapies during the course of treatment. Recent advances in metabolomics along with the novel strategies to analyze, understand, and construct the metabolic pathways opens this window of opportunity in a very cost-effective manner.

Genomic deletion of malic enzyme 2 confers collateral lethality in pancreatic cancer

The genome of pancreatic ductal adenocarcinoma (PDAC) frequently contains deletions of tumour suppressor gene loci, most notably SMAD4, which is homozygously deleted in nearly one-third of cases. As loss of neighbouring housekeeping genes can confer collateral lethality, we sought to determine whether loss of the metabolic gene malic enzyme 2 (ME2) in the SMAD4 locus would create cancer-specific metabolic vulnerability upon targeting of its paralogous isoform ME3. The mitochondrial malic enzymes (ME2 and ME3) are oxidative decarboxylases that catalyse the conversion of malate to pyruvate and are essential for NADPH regeneration and reactive oxygen species homeostasis. Here we show that ME3 depletion selectively kills ME2-null PDAC cells in a manner consistent with an essential function for ME3 in ME2-null cancer cells. Mechanistically, integrated metabolomic and molecular investigation of cells deficient in mitochondrial malic enzymes revealed diminished NADPH production and consequent high levels of reactive oxygen species. These changes activate AMP activated protein kinase (AMPK), which in turn directly suppresses sterol regulatory element-binding protein 1 (SREBP1)-directed transcription of its direct targets including the BCAT2 branched-chain amino acid transaminase 2) gene. BCAT2 catalyses the transfer of the amino group from branched-chain amino acids to α-ketoglutarate (α-KG) thereby regenerating glutamate, which functions in part to support de novo nucleotide synthesis. Thus, mitochondrial malic enzyme deficiency, which results in impaired NADPH production, provides a prime ‘collateral lethality’ therapeutic strategy for the treatment of a substantial fraction of patients diagnosed with this intractable disease.

Human Omental-Derived Adipose Stem Cells Increase Ovarian Cancer Proliferation, Migration, and Chemoresistance

Objectives Adipose tissue contains a population of multipotent adipose stem cells (ASCs) that form tumor stroma and can promote tumor progression. Given the high rate of ovarian cancer metastasis to the omental adipose, we hypothesized that omental-derived ASC may contribute to ovarian cancer growth and dissemination. Materials and Methods We isolated ASCs from the omentum of three patients with ovarian cancer, with (O-ASC4, O-ASC5) and without (O-ASC1) omental metastasis. BM-MSCs, SQ-ASCs, O-ASCs were characterized with gene expression arrays and metabolic analysis. Stromal cells effects on ovarian cancer cells proliferation, chemoresistance and radiation resistance was evaluated using co-culture assays with luciferase-labeled human ovarian cancer cell lines. Transwell migration assays were performed with conditioned media from O-ASCs and control cell lines. SKOV3 cells were intraperitionally injected with or without O-ASC1 to track in-vivo engraftment. Results O-ASCs significantly promoted in vitro proliferation, migration chemotherapy and radiation response of ovarian cancer cell lines. O-ASC4 had more marked effects on migration and chemotherapy response on OVCA 429 and OVCA 433 cells than O-ASC1. Analysis of microarray data revealed that O-ASC4 and O-ASC5 have similar gene expression profiles, in contrast to O-ASC1, which was more similar to BM-MSCs and subcutaneous ASCs in hierarchical clustering. Human O-ASCs were detected in the stroma of human ovarian cancer murine xenografts but not uninvolved ovaries. Conclusions ASCs derived from the human omentum can promote ovarian cancer proliferation, migration, chemoresistance and radiation resistance in-vitro. Furthermore, clinical O-ASCs isolates demonstrate heterogenous effects on ovarian cancer in-vitro.

Use and Optimization of a Dual-Flowrate Loading Strategy To Maximize Throughput in Protein-A Affinity Chromatography

The effect of an alternate strategy employing two different flowrates during loading was explored as a means of increasing system productivity in Protein‐A chromatography. The effect of such a loading strategy was evaluated using a chromatographic model that was able to accurately predict experimental breakthrough curves for this Protein‐A system. A gradient‐based optimization routine is carried out to establish the optimal loading conditions (initial and final flowrates and switching time). The two‐step loading strategy (using a higher flowrate during the initial stages followed by a lower flowrate) was evaluated for an Fc‐fusion protein and was found to result in significant improvements in process throughput. In an extension of this optimization routine, dynamic loading capacity and productivity were simultaneously optimized using a weighted objective function, and this result was compared to that obtained with the single flowrate. Again, the dual‐flowrate strategy was found to be superior.