Relevant bibliographies by topics / Cancer cells metabolism

Academic literature on the topic 'Cancer cells metabolism'

Author: Grafiati
Published: 14 March 2023

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Journal articles on the topic "Cancer cells metabolism"

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Pecqueur, Claire, Lisa Oliver, Kristell Oizel, Lisenn Lalier, and François M. Vallette. "Targeting Metabolism to Induce Cell Death in Cancer Cells and Cancer Stem Cells." International Journal of Cell Biology 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/805975.

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Abnormal metabolism and the evasion of apoptosis are considered hallmarks of cancers. Accumulating evidence shows that cancer stem cells are key drivers of tumor formation, progression, and recurrence. A successful therapy must therefore eliminate these cells known to be highly resistant to apoptosis. In this paper, we describe the metabolic changes as well as the mechanisms of resistance to apoptosis occurring in cancer cells and cancer stem cells, underlying the connection between these two processes.
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Annibaldi, Alessandro, and Christian Widmann. "Glucose metabolism in cancer cells." Current Opinion in Clinical Nutrition and Metabolic Care 13, no. 4 (July 2010): 466–70. http://dx.doi.org/10.1097/mco.0b013e32833a5577.

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Bekala, M. I. "ADAPTOR PROTEIN RUK/CIN85 IS INVOLVED IN THE GLUCOSE METABOLISM REPROGRAMMING IN BREAST CANCER CELLS." Biotechnologia Acta 15, no. 2 (April 2022): 47–48. http://dx.doi.org/10.15407/biotech15.02.047.

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Aim. This study aimed to investigate the changes in glucose metabolism in mouse 4T1 breast adenocarcinoma cells with different levels of Ruk/CIN85 expression. Methods. We used 4T1 cells with stable overexpression (subline RukUp) or knockdown (subline RukDown) of Ruk/CIN85, as well as corresponding vector control sublines Mock and Scr. Cells were cultured in the complete RPMI-1640 medium under standard conditions. mRNA expression levels were estimated by RT2-PCR, enzymes activities were measured by spectrophotometric and/or fluorometric assays. Results. Analysis of mRNA expression of glucose metabolism-related genes in RukUp and RukDown cells revealed that glycolysis genes are preferentially overexpressed in RukUp cells, and downregulated in RukDown cells. Thus, RukUp cells were characterized by significantly overexpressed Slc2a1, Gck, Aldoa, and Ldha, while in RukDown cells these genes were either down regulated or not changed. However, the expression of TCA (tricarboxylic acid) cycle enzyme Mdh2 increased dramatically (by 7,8 times) in RukDown cells. In detail, we observed statistically significant changes in the activity of all studied enzymes in RukUp cells (increase by 1,5-1,9 times for glycolysis enzymes and G6PD, and decrease by 1,33-1,69 times for TCA enzymes). However, in RukDown cells we did not find any significant changes in glycolysis enzymes activities, but activities of mitochondrial IDH3 and MDH2 were elevated by 1,65 and 1,59 times, respectively. Conclusions. The results obtained indicate that adaptor protein Ruk/CIN85 is involved in the metabolic reprogramming during breast cancer progression. High level of Ruk/CIN85 expression is associated with potentiation of the Warburg effect.
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Yan, Liang, Priyank Raj, Wantong Yao, and Haoqiang Ying. "Glucose Metabolism in Pancreatic Cancer." Cancers 11, no. 10 (September 29, 2019): 1460. http://dx.doi.org/10.3390/cancers11101460.

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Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal cancers, with a five-year survival rate of around 5% to 8%. To date, very few available drugs have been successfully used to treat PDAC due to the poor understanding of the tumor-specific features. One of the hallmarks of pancreatic cancer cells is the deregulated cellular energetics characterized by the “Warburg effect”. It has been known for decades that cancer cells have a dramatically increased glycolytic flux even in the presence of oxygen and normal mitochondrial function. Glycolytic flux is the central carbon metabolism process in all cells, which not only produces adenosine triphosphate (ATP) but also provides biomass for anabolic processes that support cell proliferation. Expression levels of glucose transporters and rate-limiting enzymes regulate the rate of glycolytic flux. Intermediates that branch out from glycolysis are responsible for redox homeostasis, glycosylation, and biosynthesis. Beyond enhanced glycolytic flux, pancreatic cancer cells activate nutrient salvage pathways, which includes autophagy and micropinocytosis, from which the generated sugars, amino acids, and fatty acids are used to buffer the stresses induced by nutrient deprivation. Further, PDAC is characterized by extensive metabolic crosstalk between tumor cells and cells in the tumor microenvironment (TME). In this review, we will give an overview on recent progresses made in understanding glucose metabolism-related deregulations in PDAC.
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Saunders, F. R., and H. M. Wallace. "Polyamine metabolism and cancer prevention." Biochemical Society Transactions 35, no. 2 (March 20, 2007): 364–68. http://dx.doi.org/10.1042/bst0350364.

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Colorectal cancer is one of a number of cancers that may be amenable to prevention. The NSAIDs (non-steroidal anti-inflammatory drugs) have been shown to be effective chemopreventative agents in humans, but their mechanism of action is not clear. The polyamines are cellular polycations that are essential for cell growth and are overproduced in cancer cells. It is our hypothesis that inhibition of polyamine metabolism is an integral part of the mechanism of cancer prevention mediated by NSAIDs.
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Dutta, Anika, and Neelam Sharma-Walia. "Curbing Lipids: Impacts ON Cancer and Viral Infection." International Journal of Molecular Sciences 20, no. 3 (February 2, 2019): 644. http://dx.doi.org/10.3390/ijms20030644.

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Lipids play a fundamental role in maintaining normal function in healthy cells. Their functions include signaling, storing energy, and acting as the central structural component of cell membranes. Alteration of lipid metabolism is a prominent feature of cancer, as cancer cells must modify their metabolism to fulfill the demands of their accelerated proliferation rate. This aberrant lipid metabolism can affect cellular processes such as cell growth, survival, and migration. Besides the gene mutations, environmental factors, and inheritance, several infectious pathogens are also linked with human cancers worldwide. Tumor viruses are top on the list of infectious pathogens to cause human cancers. These viruses insert their own DNA (or RNA) into that of the host cell and affect host cellular processes such as cell growth, survival, and migration. Several of these cancer-causing viruses are reported to be reprogramming host cell lipid metabolism. The reliance of cancer cells and viruses on lipid metabolism suggests enzymes that can be used as therapeutic targets to exploit the addiction of infected diseased cells on lipids and abrogate tumor growth. This review focuses on normal lipid metabolism, lipid metabolic pathways and their reprogramming in human cancers and viral infection linked cancers and the potential anticancer drugs that target specific lipid metabolic enzymes. Here, we discuss statins and fibrates as drugs to intervene in disordered lipid pathways in cancer cells. Further insight into the dysregulated pathways in lipid metabolism can help create more effective anticancer therapies.
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Zhu, Xuan, Hui-Hui Chen, Chen-Yi Gao, Xin-Xin Zhang, Jing-Xin Jiang, Yi Zhang, Jun Fang, Feng Zhao, and Zhi-Gang Chen. "Energy metabolism in cancer stem cells." World Journal of Stem Cells 12, no. 6 (June 26, 2020): 448–61. http://dx.doi.org/10.4252/wjsc.v12.i6.448.

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Leone, Robert D., and Jonathan D. Powell. "Metabolism of immune cells in cancer." Nature Reviews Cancer 20, no. 9 (July 6, 2020): 516–31. http://dx.doi.org/10.1038/s41568-020-0273-y.

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Gough, N. R. "Rewiring the Metabolism of Cancer Cells." Science Signaling 7, no. 347 (October 14, 2014): ec282-ec282. http://dx.doi.org/10.1126/scisignal.aaa0412.

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Cao, Hui, and Jianbo Xiao. "Metabolism of stilbenoids in cancer cells." Free Radical Biology and Medicine 128 (November 2018): S81. http://dx.doi.org/10.1016/j.freeradbiomed.2018.10.181.

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Dissertations / Theses on the topic "Cancer cells metabolism"

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Simon, Molas Helga. "Exploring the regulation and function of TIGAR in cancer cells." Doctoral thesis, Universitat de Barcelona, 2019. http://hdl.handle.net/10803/667414.

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The TP53-Induced Glycolysis and Apoptosis Regulator (TIGAR) gene was described in 2006 by Dr. Karen Vousden's group in response to the induction of the tumour suppressor gene p53. Since then, numerous studies have focused on clarifying the role of this gene in the metabolism of tumour cells. TIGAR was initially described as an enzyme with bisphosphatase activity on fructose-2,6-bisphosphate, a key metabolite in the positive allosteric regulation of phosphofructokinase-1, which catalyses a key reaction in glycolysis. Through this bisphosphatase activity, TIGAR reduces the levels of fructose-2,6-bisphosphate and, consequently, decreases the glycolytic flux and redirects the metabolites to the pentose phosphate pathway, which is determinant for the antioxidant capacity of cells. Overexpression of TIGAR has been described in multiple tumours, as well as in different cell lines, indicating that this gene confers a growth advantage to these cells. The present doctoral thesis has focused on studying the metabolic function of TIGAR in tumours, as well as the mechanisms that regulate its transcription. The study was carried out on cell lines of cervical cancer and lung cancer in which we have been able to confirm that TIGAR exerts a bisphosphatase function on fructose-2,6-bisphosphate. TIGAR has proven to be key in the response of the cervical cancer cell line HeLa to the blockage of glycolysis, either by inhibiting the expression of the PFKFB3 gene by interfering RNA technology, or by blocking the PFK-2 protein by the drug 3PO. The blockage of glycolysis increases oxidative stress and the phosphorylation of the kinase Akt, which is required for the induction of TIGAR. Furthermore, through metabolomic studies we have been able to describe for the first time the involvement of TIGAR in the entrance of pyruvate to the tricarboxylic acid cycle, in the mitochondria. Finally, and in relation to the mechanisms that regulate the transcription of TIGAR, we have proved that the transcription factor Nrf2, key in the regulation of the antioxidant activity of tumour cells, controls the expression of TIGAR in HeLa cells. In lung cancer cells, where the over activation of Nrf2 is related to chemo resistance and radiotherapy, the relationship between Nrf2 and TIGAR seems to be indirect. With the results presented in this doctoral thesis we have contributed to a better understanding of the role of TIGAR in tumour metabolism and have laid the foundations for future studies aimed at blocking this protein in tumours.
El gen TP53-Induced Glycolysis and Apoptosi Regulator (TIGAR) va ser descrit l'any 2006 pel grup de la Dra. Karen Vousden en resposta a l’activació del supressor tumoral p53. Des de llavors, nombrosos estudis s'han centrat en aclarir el paper d'aquest gen en el metabolisme de les cèl·lules tumorals. Inicialment, la funció atribuïda a TIGAR va ser la de bisfosfatasa de la fructosa-2,6-bisfosfat, metabòlit clau en la regulació al·lostèrica positiva de l’enzim fosfofructoquinasa-1, que catalitza la una reacció clau en la glucòlisi. Mitjançant aquesta activitat bisfosfatasa, TIGAR redueix els nivells de fructosa-2,6-bisfosfat i, en conseqüència, frena en flux glicolític i redirigeix els metabòlits a la via de les pentoses fosfat. És per aquest motiu que TIGAR es va descriure com un gen amb capacitat antioxidant. La present tesi doctoral s'ha centrat en estudiar la funció metabòlica de TIGAR en línies tumorals, així com els mecanismes que regulen la seva transcripció. Amb aquests estudis hem pogut demostrar que TIGAR és clar en la resposta de les cèl·lules al bloqueig de la glucòlisi, ja sigui per la inhibició de l'expressió del gen PFKFB3 mitjançant la tecnologia de RNA d'interferència, com pel bloqueig de la proteïna PFK-2 mitjançant el fàrmac 3PO. El bloqueig de la glucòlisi provoca un augment de l'estrès oxidatiu i de la fosforil·lació de la quinasa Akt, necessària per a la inducció de TIGAR.que al seu torn condueix a una inducció de TIGAR. D’altra banda, estudis metabolòmics ens han permès descriure per primera vegada l’acció de TIGAR en nivells inferiors de la glicòlisi, afectant l’entrada del piruvat al cicle de Krebs. Finalment, hem pogut comprovar que el factor de transcripció Nrf2, clau en la regulació de l'activitat antioxidant de les cèl·lules, controla l'expressió de TIGAR en una línia cel·lular de càncer de cèrvix. En cèl·lules de càncer de pulmó, en canvi, la relació entre Nrf2 i TIGAR sembla ser indirecta. Amb els resultats presentats en aquesta tesi doctoral hem contribuït a entendre millor el paper de TIGAR en el metabolisme tumoral i hem establert les bases per a futurs estudis dirigits al bloqueig d'aquesta proteïna als tumors.
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Board, Mary. "A study of energy metabolism in neoplastic cells." Thesis, University of Oxford, 1990. http://ora.ox.ac.uk/objects/uuid:d3e13e31-3fe8-4cd8-ad71-50d4e7df4d27.

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Vermeersch, Kathleen A. "Systems-level characterization of ovarian cancer metabolism." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54258.

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The purpose of this thesis was to characterize cancer metabolism in vitro using epithelial ovarian cancer as a model on an untargeted, systems-level, basis with particular attention paid to the difference between cancer stem cell metabolism and cancer cell metabolism. Two-dimensional gas chromatography coupled to mass spectrometry was used to measure the metabolite profiles of the ovarian cancer and cancer stem cell lines under normal baseline conditions and also under chemotherapeutic and environmental perturbations. These two cell lines exhibited significant metabolic differences under normal baseline conditions and results demonstrated that metabolism in the ovarian cancer stem cell line was distinct from that of more differentiated isogenic cancer cells, showing similarities to stem cell metabolism that suggest the potential importance of metabolism for the cancer stem cell phenotype. Glucose deprivation, hypoxia, and ischemia all perturbed ovarian cancer and cancer stem cell metabolism, but not in the same ways between the cell types. Chemotherapeutic treatment with docetaxel caused metabolic changes mostly in amino acid and carbohydrate metabolism in ovarian cancer cells, while ovarian cancer stem cell metabolism was not affected by docetaxel. Overall, these metabolic differences between the two cell types will deepen our understanding of the metabolic changes occurring within the in vivo tumor and will help drive development of cancer stem cell targeted therapeutics.
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Hjertman, Magnus. "Protein modification with hydrophobic prenyl groups in malignant cells /." Stockholm, 2001. http://diss.kib.ki.se/2001/91-7349-063-6/.

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Ross, Helen L. "The metabolism of benzo(a)pyrene in human cells." Thesis, University of Nottingham, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.253019.

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Pyne, Emily Seton. "The Impact of Stromal Cells on the Metabolism of Ovarian Cancer Cells in 3D Culture." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/74931.

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Academic: Ovarian cancer is the leading cause of death among female gynecologic cancers. Current treatments include surgical debulking, and chemotherapy. However, better interventions are needed to reduce the mortality rate of metastatic disease. Ovarian cancer cells have displayed the ability to aggregate and form 3D homogeneous and heterogeneous spheroids, which can function as micrometastases. Ovarian cancer spheroids survive independently prior to adhering to an endothelial tissue. Since aggregation has been shown to provide a survival advantage to the spheroids and increased their aggressive phenotype, this study aimed to investigate how the metabolism of ovarian cancer cells change in 3-dimensional (3D) culture. Examining metabolic pathways and identifying markers of metabolic change could provide the scientific base for new, targeted interventions for this disease. Spheroids of both homogeneous and heterogeneous composition demonstrated overall lower metabolic capacity than their adherent counterparts. Spheroids had a lower basal energetic demand than adherent cells, paralleled by lower maximal respiration capacity, glycolytic capacity, and spare respiratory capacity. We conclude that the lower energetic demand of spheroids may be a mechanism to prolong death by reserving energy and metabolic cellular processes; this may render anti-metabolic drug treatment with AICAR or metformin ineffective against disseminating ovarian cancer aggregates. General: Ovarian cancer is currently the leading cause of death among female gynecologic cancers. While treatments exist, better interventions are needed to reduce the mortality rate in this form of cancer. Ovarian cancer cells have displayed the ability to aggregate and form 3D homogeneous and heterogeneous spheroids, which can function as micrometastases. Ovarian cancer spheroids survive independently prior to adhering to an endothelial tissue. Since aggregation has been shown to provide a survival advantage to the spheroids and increased their aggressive phenotype, this study aims to investigate how the metabolism of ovarian cancer cells change in 3-dimensional (3D) culture. Examining metabolic pathways and identifying markers of metabolic change could provide the scientific base for new, targeted interventions for this disease.
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Wang, Feng. "Interaction between pancreatic cancer and beta cells : intraislet significance of islet amyloid polypeptide /." Stockholm, 1998. http://diss.kib.ki.se/1998/91-628-3300-6/.

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Maddula, Sasidhar [Verfasser]. "Cell cycle phase specific metabolism of colon cancer cells: a metabolome study / Sasidhar Maddula." München : Verlag Dr. Hut, 2011. http://d-nb.info/1018980911/34.

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E, Pranzini. "Metabolic reprogramming of colorectal cancer cells resistant to 5-FU." Doctoral thesis, Università di Siena, 2020. http://hdl.handle.net/11365/1095546.

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Metabolic rearrangements are essential to satisfy the different needs of cancer cells during tumorigenesis. Recent studies highlighted a role for such metabolic reprogramming in adaptation to therapies and chemo-resistance development. 5-fluorouracil (5-FU) is an antimetabolite drug widely used as a first-line treatment for colorectal cancer. Despite several advantages of 5-FU, its clinical application is still greatly limited, due to the acquisition of drug resistance. In the first part of this thesis, we illustrate the role of micro RNAs (miRNAs) in reprogramming colon cancer cells toward a resistant phenotype as well as their involvement in the response of resistant cells to acute treatment with 5-FU. We performed a global gene expression profile for the entire miRNA genome, and we found a change in the expression of four miRNAs following acute treatment with 5-FU in cells resistant to this drug. Among them, we focused on miR-210-3p, previously described as a key regulator of DNA damage repair mechanisms and mitochondrial metabolism. Here we show that miR-210-3p downregulation enables resistant cells to counteract the toxic effect of the drug increasing the expression of RAD-52 protein, involved in DNA damage repair. Moreover, miR-210-3p downregulation enhances mitochondrial oxidative metabolism, increasing the expression levels of succinate dehydrogenase subunits D, decreasing intracellular succinate levels and inhibiting HIF-1α expression. These results suggest that miR-210-3p downregulation following 5-FU treatment sustains DNA damage repair and metabolic adaptation to counteract drug treatment, thus supporting the resistant phenotype. In the second part of this thesis, we reveal important adaptations in serine and one-carbon metabolism associated with the acquisition of 5-FU resistance in colorectal cancer cells. 5-FU resistant cells showed an increase in both serine up-take from extracellular medium and de novo serine synthesis pathway. Together with increased serine availability, dynamic labeling experiment after 13C-serine incubation underlined a different utilization of serine-derived carbons in resistant cells with a sustained flux into the mitochondrial compartment supporting increased purine nucleotides synthesis. Accordingly, we found a strong decrease in the expression of the cytosolic isoform of the enzyme serine hydroxy-methyltransferase (SHMT1) and a concomitant increase in the expression of the mitochondrial isoform (SHMT2) in 5-FU resistant cells compared to parental cells, confirming the shift toward mitochondrial one-carbon branch activity. Accordingly, higher expression levels of the mitochondrial serine transporter SFXN1 have been observed in resistant cells with respect to the sensitive ones. Silencing SHMT2 in 5-FU resistant cells increases the efficacy of the treatment with 5-FU against resistant cells confirming the importance of the reported adaptation in the acquisition of resistance to 5-FU. In conclusion, the data shown in this thesis underline different adaptations related to both miRNAs expression and nutrient metabolism carried out by 5-FU resistant cells. This reprogramming supports the response of 5-FU resistant cells to overcome the toxic effect of the drug. The identification of such alterations opens the possibility of new therapeutic approaches to tackle resistant cells and overcome colon cancer relapse.
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Bellio, Chiara. "Cancer stem cells from epithelial ovarian cancer patients privilege oxidative phosphorylation, and resist glucose deprivation." Doctoral thesis, Università degli studi di Padova, 2015. http://hdl.handle.net/11577/3424111.

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Ovarian cancer is the fourth leading cause of cancer-related death in women and the leading cause of gynecologic cancer death. Moreover, it is regarded as a therapy resistant tumor, because it shows the formation of more aggressive recurrence of the primary tumor as a result of chemotherapy. This chemo-resistance is thought to be related to the presence of the Cancer Stem Cells (CSC). Tumor cells are characterized by a high glycolytic metabolism even in the presence of oxygen, the so-called Warburg effect; however, it is unclear whether this condition is also shared by CSC. We identified ovarian CSC, according to their co-expression of CD44 and CD117 markers, in 40 samples of ascitic effusions from ovarian cancer-bearing patients. We have analyzed phenotipic characteristics by investigating stemness marker expression by flow-cytometry, spheroid formation assay, tumorigenicity in vivo and gene expression in RT-PCR. For the analysis of metabolic characteristics, ovarian cancer cells were FACS-sorted in to CD44+CD117+ and CD44+CD117- cell populations and analyzed through specific metabolic gene-cards. Results were confirmed also through Western Blot for specific metabolic enzymes and functional assay of mitochondrial activity. We have demonstrated that CD44+CD117+ EOC cells presented high tumorigenicity and expressed stemness-associated markers and multidrug resistance pumps. Moreover, the CD44+CD117+ cell population overexpressed genes associated with glucose uptake, oxidative phosphorylation (OXPHOS), and fatty acid -oxidation, indicating higher ability to direct pyruvate towards the Krebs cycle. Consistent with a metabolic profile dominated by OXPHOS, the CD44+CD117+ cells showed higher mitochondrial reactive oxygen species (ROS) production and elevated membrane potential, and underwent apoptosis upon inhibition of the mitochondrial respiratory chain. The CSC also had a high rate of pentose phosphate pathway (PPP) activity, which is not typical of cells privileging OXPHOS over glycolysis, and may rather reflect the PPP role in recharging scavenging enzymes. Furthermore, CSC resisted in vitro and in vivo glucose deprivation, while maintaining their CSC phenotype and OXPHOS profile. In this study, we show that a subpopulation of CD44+CD117+ EOC cells fulfilling the canonical properties of CSC does not preferentially exploit a glycolytic metabolism, privileging instead the mitochondrial respiratory pathway. These observations could explain the CSC resistance to anti-angiogenic therapies, and indicate this peculiar metabolic profile as a possible target of novel treatment strategies.
Il cancro all’ovaio viene considerato un tumore resistente alla terapia e questa farmaco-resistenza si pensa sia correlata alla presenza delle cellule staminali tumorali (CSC). Le cellule staminali tumorali sono una rara e piccola popolazione cellulare responsabile dell’insorgenza del tumore, del mantenimento della sua crescita, dei casi di recidive e metastasi, in seguito alla loro proprietà di farmaco-resistenza. Considerando queste premesse, è indispensabile caratterizzare queste cellule in modo da trovare un possibile bersaglio terapeutico e migliorare i risultati delle terapie attuali. Le cellule tumorali sono caratterizzate da un metabolismo altamente glicolitico anche in presenza di ossigeno, denominato “Effetto Warburg”. Poco si conosce riguardo al metabolismo delle cellule staminali tumorali, e soprattutto non è noto se l’effetto Warburg è una condizione condivisa. Questo progetto di ricerca si prefigge di: - caratterizzare le CSC nel campioni primari di liquido ascitico di cancro all’ovaio; - studiare il profilo metabolico delle CSC isolate, per identificare eventuali differenze con la controparte differenziata. RISULTATI: Inizialmente abbiamo identificato le CSC, secondo la co-espressione dei marcatori CD44 (il recettore dell’acido ialuronico), e CD117 [c-kit, recettore della citochina SCF (Stem Cell Factor)] in 40 campioni di liquido ascitico di cancro all’ovaio di pazienti in cura all’ospedale di Padova. Questa rara popolazione cellulare CD44+CD117+ è in grado di formare strutture sferoidali; è altamente tumorigenica in topi immunodeficienti; presenta farmaco-resistenza, dimostrata con trattamenti in vitro con farmaci solitamente utilizzati in clinica; ed è caratterizzata da un’alta espressione di geni codificanti: pathway di staminalità (Nanog, Oct4, Sox2), pompe o enzimi detossificanti, coinvolti nei fenomeni di farmaco-resistenza (ABCG2, MRP1, MRP2 e ALDH1A) e enzimi coinvolti nel fenomeno della transizione epitelio-mesenchimale, importante nei processi di metastasi (SNAIL1, SNAIL2, ZEB1, ZEB2, TWIST1). Complessivamente, questi risultati dimostrano che le cellule CD44+CD117+ rappresentano una popolazione con caratteristiche di staminalità. A seguito di questa caratterizzazione fenotipica, abbiamo studiato il profilo metabolico delle cellule CD44+CD117+, confrontandolo con quello della controparte non-staminale (CD44+CD117-). In primo luogo, abbiamo esaminato l’espressione di geni coinvolti in diverse importanti vie metaboliche, tra cui: il metabolismo del glucosio, il ciclo dell'acido tricarbossilico (TCA), la catena di trasporto degli elettroni (ETC) nel processo della respirazione mitocondriale, la via dei pentoso fosfati (PPP), e la β-ossidazione degli acidi grassi. Le cellule CD44+CD117+ mostrano alti livelli di espressione dei geni associati alla glicolisi, e sono caratterizzate da una forte dipendenza dalla via dei pentoso fosfati e della β-ossidazione degli acidi grassi, dimostrata da una significativa diminuzione della loro vitalità in seguito a trattamento in vitro con due inibitori specifici delle due vie metaboliche (DHEA e Etomoxir rispettivamente). Inoltre le cellule CD44+CD117+ sono caratterizzate da un'alta espressione dei geni codificati enzimi coinvolti nel ciclo di Krebs e nella fosforilazione ossidativa (OXPHOS). Questo risultato ci ha permesso di analizzare l'espressione di un enzima chiave del ciclo di Krebs, la piruvato deidrogenasi (PDH), fondamentale nel trasporto del piruvato dalla glicolisi alla respirazione cellulare. Abbiamo verificato livelli di espressione comparabili dell’enzima PDH nelle due popolazioni cellulari CD44+CD117+ e CD44+CD117-, mentre l’enzima PDHK1, che inattiva la piruvato deidrogenasi tramite fosforilazione, risulta meno espressa nella popolazione CD44+CD117+. Questi dati suggeriscono che nelle cellule staminali tumorali venga privilegiato il trasporto del piruvato verso i mitocondri, per catalizzare il metabolismo della respirazione mitocondriale. Alla luce di questi risultati, abbiamo studiato l’attività mitocondriale nella popolazione staminale e nella controparte non staminale. In particolare le cellule CD44+CD117+ sono caratterizzate da bassi livelli di ROS (specie reattive dell’ossigeno) totali, da alti livelli di ROS mitocondriali, da una iper-polarizzazione del potenziale di membrana mitocondriale in seguito a trattamento con oligomicina (inibitore dell’ATP-sintasi) e da una drammatica diminuzione della vitalità cellulare in seguito a trattamento con inibitori specifici della catena di trasporto degli elettroni (ETC) (oligomicina inibitore dell’ATP-sintasi; rotenone inibitore del complesso I e antimicina inibitore del complesso III). Complessivamente, questi risultati ci hanno suggerito un modello sperimentale del profilo metabolico delle cellule staminali tumorali CD44+CD117+, le quali privilegiano la via della respirazione mitocondriale, a discapito della via glicolitica. Inoltre, abbiamo dimostrato che un trattamento in vitro e in vivo (2DG) di deprivazione di glucosio o blocco della via glicolitica seleziona una popolazione di cellule con caratteristiche di staminalità: incremento dell’espressione dei marcatori CD44 e CD117, farmaco-resistenza, tumorigenicità in vivo, formazion dii sferoidi in vitro ed espressione di geni convolti in pathway tipici delle cellule staminali. Questa popolazione cellulare ha mostrato una down-regolazione della maggior parte delle vie metaboliche, entrando in uno stato di quiescenza pur mantenendo livelli di espressione significativi dei geni codificanti enzimi del metabolismo ossidativo e iper-polarizzazione del potenziale di membrana mitocondriale, nonché dell’attività dei mitocondri. A conclusione del progetto e come ulteriore dimostrazione del profilo metabolico ossidativo delle cellule staminali tumorali, contrario all’effetto Warburg sfruttato dalle cellule tumorali, abbiamo eseguito degli esperimenti in vitro con due farmaci che colpiscono le vie metaboliche della respirazione cellulare: Metformina e CPI-613. Metformina inibisce il complesso I della catena di trasporto degli elettroni ed è attualmente in uso in studi clinici come farmaco antitumorale promettente; CPI-613 è un farmaco innovativo che inibisce due enzimi chiave del ciclo degli acidi tricarbossilici, PDH e α-KGH. Trattamenti in vitro con questi farmaci hanno dimostrato una significativa diminuzione della vitalità delle cellule CD44+CD117+, fondamentale verifica della loro dipendenza da questo profilo metabolico. CONCLUSIONI: In questo studio abbiamo investigato il profilo metabolico delle cellule staminali tumorali, isolate ex-vivo da campioni di liquidi ascitici di pazienti con carcinoma ovarico, dimostrando che le CSC ovariche, a differenza delle cellule differenziate neoplastiche, sfuggono all’effetto Warburg, utilizzando preferibilmente una respirazione ossidativa. Questa osservazione può indicare nuove strade e nuove strategie per approcci di terapie mirate nei confronti delle CSC, alla luce delle peculiari caratteristiche del loro metabolismo.
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Books on the topic "Cancer cells metabolism"

1

Lands, William E. M., 1930-, ed. Biochemistry of arachidonic acid metabolism. Boston: Nijhoff, 1985.

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Dr, Mehta Kapil, and Siddik Zahid H, eds. Drug resistance in cancer cells. New York, NY: Springer, 2009.

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Cancer: Between glycolysis and physical constraint. Berlin: Springer, 2004.

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Benjamin, Bonavida, ed. Sensitization of cancer cells for chemo/immuno/radio-therapy. Totowa, NJ: Humana Press, 2008.

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Ockner, Robert K. Integration of metabolism, energetics, and signal transduction: Unifying foundations in cell growth and death, cancer, atherosclerosis, and Alzheimer disease. New York: Kluwer Academic Publishers, 2004.

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E, Milo George, Casto Bruce C, and Shuler Charles Fredric 1953-, eds. Transformation of human epithelial cells: Molecular and oncogenetic mechanisms. Boca Raton: CRC Press, 1992.

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Bourgeault, Geoffrey A. Energy metabolism of wild type MCF-7 human breast cancer cells and its adriamyacin resistant derivative. Sudbury, Ont: Laurentian University, 1997.

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Sherbet, G. V. Growth factors and their receptors in cell differentiation, cancer and cancer therapy. London: Elsevier, 2011.

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The tumor microenvironment. New York: Springer, 2010.

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T, Galeotti, ed. Cell membranes and cancer: Proceedings of the Second International Workshop on Membranes in Tumour Growth, Rome, Italy, June 17-20, 1985. Amsterdam: Elsevier Science, 1985.

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Book chapters on the topic "Cancer cells metabolism"

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Li, Ting, Christopher Copeland, and Anne Le. "Glutamine Metabolism in Cancer." In The Heterogeneity of Cancer Metabolism, 17–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_2.

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AbstractMetabolism is a fundamental process for all cellular functions. For decades, there has been growing evidence of a relationship between metabolism and malignant cell proliferation. Unlike normal differentiated cells, cancer cells have reprogrammed metabolism in order to fulfill their energy requirements. These cells display crucial modifications in many metabolic pathways, such as glycolysis and glutaminolysis, which include the tricarboxylic acid (TCA) cycle, the electron transport chain (ETC), and the pentose phosphate pathway (PPP) [1]. Since the discovery of the Warburg effect, it has been shown that the metabolism of cancer cells plays a critical role in cancer survival and growth. More recent research suggests that the involvement of glutamine in cancer metabolism is more significant than previously thought. Glutamine, a nonessential amino acid with both amine and amide functional groups, is the most abundant amino acid circulating in the bloodstream [2]. This chapter discusses the characteristic features of glutamine metabolism in cancers and the therapeutic options to target glutamine metabolism for cancer treatment.
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Jung, Jin G., and Anne Le. "Targeting Metabolic Cross Talk Between Cancer Cells and Cancer-Associated Fibroblasts." In The Heterogeneity of Cancer Metabolism, 205–14. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_15.

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AbstractAlthough cancer has classically been regarded as a genetic disease of uncontrolled cell growth, the importance of the tumor microenvironment (TME) [1, 2] is continuously emphasized by the accumulating evidence that cancer growth is not simply dependent on the cancer cells themselves [3, 4] but also dependent on angiogenesis [5–8], inflammation [9, 10], and the supporting roles of cancer-associated fibroblasts (CAFs) [11–13]. After the discovery that CAFs are able to remodel the tumor matrix within the TME and provide the nutrients and chemicals to promote cancer cell growth [14], many studies have aimed to uncover the cross talk between cancer cells and CAFs. Moreover, a new paradigm in cancer metabolism shows how cancer cells act like “metabolic parasites” to take up the high-energy metabolites, such as lactate, ketone bodies, free fatty acids, and glutamine from supporting cells, including CAFs and cancer-associated adipocytes (CAAs) [15, 16]. This chapter provides an overview of the metabolic coupling between CAFs and cancer cells to further define the therapeutic options to disrupt the CAF-cancer cell interactions.
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Sazeides, Christos, and Anne Le. "Metabolic Relationship Between Cancer-Associated Fibroblasts and Cancer Cells." In The Heterogeneity of Cancer Metabolism, 189–204. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_14.

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AbstractCancer-associated fibroblasts (CAFs), a major component of the tumor microenvironment (TME), play an important role in cancer initiation, progression, and metastasis. Recent findings have demonstrated that the TME not only provides physical support for cancer cells but also directs cell-to-cell interactions (in this case, the interaction between cancer cells and CAFs). As cancer progresses, the CAFs also coevolve, transitioning from an inactivated state to an activated state. The elucidation and understanding of the interaction between cancer cells and CAFs will pave the way for new cancer therapies [1–3].
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Jung, Jin G., and Anne Le. "Metabolism of Immune Cells in the Tumor Microenvironment." In The Heterogeneity of Cancer Metabolism, 173–85. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_13.

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AbstractThe tumor microenvironment (TME) is a complex biological structure surrounding tumor cells and includes blood vessels, immune cells, fibroblasts, adipocytes, and extracellular matrix (ECM) [1, 2]. These heterogeneous surrounding structures provide nutrients, metabolites, and signaling molecules to provide a cancer-friendly environment. The metabolic interplay between immune cells and cancer cells in the TME is a key feature not only for understanding tumor biology but also for discovering cancer cells’ vulnerability. As cancer immunotherapy to treat cancer patients and the use of metabolomics technologies become more and more common [3], the importance of the interplay between cancer cells and immune cells in the TME is emerging with respect to not only cell-to-cell interactions but also metabolic pathways. This interaction between immune cells and cancer cells is a complex and dynamic process in which immune cells act as a determinant factor of cancer cells’ fate and vice versa. In this chapter, we provide an overview of the metabolic interplay between immune cells and cancer cells and discuss the therapeutic opportunities as a result of this interplay in order to define targets for cancer treatment. It is important to understand and identify therapeutic targets that interrupt this cancerpromoting relationship between cancer cells and the surrounding immune cells, allowing for maximum efficacy of immune checkpoint inhibitors as well as other genetic and cellular therapies.
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Antonio, Marjorie Justine, Cissy Zhang, and Anne Le. "Different Tumor Microenvironments Lead to Different Metabolic Phenotypes." In The Heterogeneity of Cancer Metabolism, 137–47. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_10.

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AbstractThe beginning of the twenty-first century offered new advances in cancer research, including new knowledge about the tumor microenvironment (TME). Because TMEs provide the niches in which cancer cells, fibroblasts, lymphocytes, and immune cells reside, they play a crucial role in cancer cell development, differentiation, survival, and proliferation. Throughout cancer progression, the TME constantly evolves, causing cancer cells to adapt to the new conditions. The heterogeneity of cancer, evidenced by diverse proliferation rates, cellular structures, metabolisms, and gene expressions, presents challenges for cancer treatment despite the advances in research. This chapter discusses how different TMEs lead to specific metabolic adaptations that drive cancer progression.
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Alvina, Fidelia B., Arvin M. Gouw, and Anne Le. "Cancer Stem Cell Metabolism." In The Heterogeneity of Cancer Metabolism, 161–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_12.

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AbstractCancer stem cells (CSCs), also known as tumorinitiating cells (TICs), are a group of cells found within cancer cells. Like normal stem cells, CSCs can proliferate, engage in self-renewal, and are often implicated in the recurrence of tumors after therapy [1, 2]. The existence of CSCs in various types of cancer has been proven, such as in acute myeloid leukemia (AML) [3], breast [4], pancreatic [5], and lung cancers [6], to name a few. There are two theories regarding the origin of CSCs. First, CSCs may have arisen from normal stem/progenitor cells that experienced changes in their environment or genetic mutations. On the other hand, CSCs may also have originated from differentiated cells that underwent genetic and/or heterotypic modifications [7]. Either way, CSCs reprogram their metabolism in order to support tumorigenesis.
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Camelo, Felipe, and Anne Le. "The Intricate Metabolism of Pancreatic Cancers." In The Heterogeneity of Cancer Metabolism, 77–88. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_5.

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AbstractCurrently, approximately 95% of pancreatic cancers are pancreatic ductal adenocarcinomas (PDAC), which are the most aggressive form and the fourth leading cause of cancer death with extremely poor prognosis [1]. Poor prognosis is primarily attributed to the late diagnosis of the disease when patients are no longer candidates for surgical resection [2]. Cancer cells are dependent on the oncogenes that allow them to proliferate limitlessly. Thus, targeting the expression of known oncogenes in pancreatic cancer has been shown to lead to more effective treatment [3]. This chapter discusses the complexity of metabolic features in pancreatic cancers. In order to comprehend the heterogeneous nature of cancer metabolism fully, we need to take into account the close relationship between cancer metabolism and genetics. Gene expression varies tremendously, not only among different types of cancers but also within the same type of cancer among different patients. Cancer metabolism heterogeneity is often prompted and perpetuated not only by mutations in oncogenes and tumor-suppressor genes but also by the innate diversity of the tumor microenvironment. Much effort has been focused on elucidating the genetic alterations that correlate with disease progression and treatment response [4, 5]. However, the precise mechanisms by which tumor metabolism contributes to cancer growth, survival, mobility, and aggressiveness represent a functional readout of tumor progression (Fig. 1).
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Park, Joshua K., Nathan J. Coffey, Aaron Limoges, and Anne Le. "The Heterogeneity of Lipid Metabolism in Cancer." In The Heterogeneity of Cancer Metabolism, 39–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65768-0_3.

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AbstractThe study of cancer cell metabolism has traditionally focused on glycolysis and glutaminolysis. However, lipidomic technologies have matured considerably over the last decade and broadened our understanding of how lipid metabolism is relevant to cancer biology [1–3]. Studies now suggest that the reprogramming of cellular lipid metabolism contributes directly to malignant transformation and progression [4, 5]. For example, de novo lipid synthesis can supply proliferating tumor cells with phospholipid components that comprise the plasma and organelle membranes of new daughter cells [6, 7]. Moreover, the upregulation of mitochondrial β-oxidation can support tumor cell energetics and redox homeostasis [8], while lipid-derived messengers can regulate major signaling pathways or coordinate immunosuppressive mechanisms [9–11]. Lipid metabolism has, therefore, become implicated in a variety of oncogenic processes, including metastatic colonization, drug resistance, and cell differentiation [10, 12–16]. However, whether we can safely and effectively modulate the underlying mechanisms of lipid metabolism for cancer therapy is still an open question.
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Zheng, Minhua, Wei Wang, Jun Liu, Xiao Zhang, and Rui Zhang. "Lipid Metabolism in Cancer Cells." In Advances in Experimental Medicine and Biology, 49–69. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6785-2_4.

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Aggarwal, Vaishali, Sanjay Rathod, Kanupriya Vashishth, and Arun Upadhyay. "Immune Cell Metabolites as Fuel for Cancer Cells." In Immuno-Oncology Crosstalk and Metabolism, 153–86. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6226-3_6.

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Conference papers on the topic "Cancer cells metabolism"

1

Occhipinti, Annalisa, and Claudio Angione. "A Computational Model of Cancer Metabolism for Personalised Medicine." In Building Bridges in Medical Science 2021. Cambridge Medicine Journal, 2021. http://dx.doi.org/10.7244/cmj.2021.03.001.3.

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Cancer cells must rewrite their ‘‘internal code’’ to satisfy the demand for growth and proliferation. Such changes are driven by a combination of genetic (e.g., genes’ mutations) and non-genetic factors (e.g., tumour microenvironment) that result in an alteration of cellular metabolism. For this reason, understanding the metabolic and genomic changes of a cancer cell can provide useful insight on cancer progression and survival outcomes. In our work, we present a computational framework that uses patient-specific data to investigate cancer metabolism and provide personalised survival predictions and cancer development outcomes. The proposed model integrates patient-specific multi-omics data (i.e., genomic, metabolomic and clinical data) into a metabolic model of cancer to produce a list of metabolic reactions affecting cancer progression. Quantitative and predictive analysis, through survival analysis and machine learning techniques, is then performed on the list of selected reactions. Since our model performs an analysis of patient-specific data, the outcome of our pipeline provides a personalised prediction of survival outcome and cancer development based on a subset of identified multi-omics features (genomic, metabolomic and clinical data). In particular, our work aims to develop a computational pipeline for clinicians that relates the omic profile of each patient to their survival probability, based on a combination of machine learning and metabolic modelling techniques. The model provides patient-specific predictions on cancer development and survival outcomes towards the development of personalised medicine.
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Potma, Eric O., Jue Hou, Elliot Botvinick, and Bruce J. Tromberg. "Kinetics of lipid metabolism in cancer cells (Conference Presentation)." In Biophysics, Biology and Biophotonics III: the Crossroads, edited by Adam Wax and Vadim Backman. SPIE, 2018. http://dx.doi.org/10.1117/12.2290754.

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Behar, Vered, Osnat Bohana-Kashtan, Alina Shitrit, Efrat Ben-Zeev, Alexander Konson, Rachel Ozeri, Tzofit Kehat, et al. "Abstract 3219: Changing the metabolism of cancer cells with PKM2 activators - a path to a cancer metabolism drug." In Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL. American Association for Cancer Research, 2012. http://dx.doi.org/10.1158/1538-7445.am2012-3219.

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Maldonado, Rylee, Chloe Adrienna Talana, Kahealani Uehara, and Michael Weichhaus. "Abstract PO-057: Breast cancer cell metabolism: Effect of beta-hydroxybutyrate on glucose deprived breast cancer cells." In Abstracts: AACR Special Virtual Conference on Epigenetics and Metabolism; October 15-16, 2020. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.epimetab20-po-057.

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Elliott, Robert L., Xian-Peng Jiang, and Jonathan F. Head. "Abstract A89: Glycolytic cancer cell metabolism suppressed by transplantation of exogenous normal mitochondria into human breast cancer cells." In Abstracts: AACR Special Conference: Metabolism and Cancer; June 7-10, 2015; Bellevue, WA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3125.metca15-a89.

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Badgley, Michael A., Carmine F. Palermo, Stephen A. Sastra, Brent R. Stockwell, and Kenneth P. Olive. "Abstract A41: Leveraging metabolic dependencies in cancer: Cysteine addiction in pancreatic cancer cells." In Abstracts: AACR Special Conference: Metabolism and Cancer; June 7-10, 2015; Bellevue, WA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3125.metca15-a41.

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Torga, Gonzalo, Steven Mooney, Jelani C. Zarif, and Kenneth J. Pienta. "Abstract 2939: Induction of apoptosis in prostate cancer cells by altering cell metabolism." In Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.am2015-2939.

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DeBerardinis, Ralph J. "Abstract IA03: Metabolic heterogeneity in cancer cells and tumors." In Abstracts: AACR Special Conference: Metabolism and Cancer; June 7-10, 2015; Bellevue, WA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3125.metca15-ia03.

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Patel, B., Y. Rattigan, E. Ackerstaff, J. Koutcher, G. Sukenick, J. Glod, and D. Banerjee. "P1-03-03: Adaptive Exploitation of Stromal Cell Metabolism by Tumor Cells." In Abstracts: Thirty-Fourth Annual CTRC‐AACR San Antonio Breast Cancer Symposium‐‐ Dec 6‐10, 2011; San Antonio, TX. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/0008-5472.sabcs11-p1-03-03.

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Yan, Cong, Xinchun Ding, Lingyan Wu, and Hong Du. "Abstract A12: Establishment of myeloid lineage cell line that resembles myeloid-derived suppressive cells." In Abstracts: AACR Special Conference: Metabolism and Cancer; June 7-10, 2015; Bellevue, WA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1557-3125.metca15-a12.

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Reports on the topic "Cancer cells metabolism"

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Feng, Pei. Genetic Alteration of Metabolism and Tumorigenicity of Prostate Cancer Cells. Fort Belvoir, VA: Defense Technical Information Center, June 2003. http://dx.doi.org/10.21236/ada417940.

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Kornbluth, Sally. Metabolic Regulation of Ovarian Cancer Cell Death. Fort Belvoir, VA: Defense Technical Information Center, July 2012. http://dx.doi.org/10.21236/ada570124.

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Kornbluth, Sally. Metabolic Regulation of Ovarian Cancer Cell Death. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada597625.

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Frost, Susan C., Art Edison, and Nick Simpson. Metabolic Reorganization in Breast Cancer Epithelial Cells: Role of the Pentose Phosphate Shunt. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada514032.

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Frost, Susan. Metabolic Reorganization in Breast Cancer Epithelial Cells: Role of the Pentose Phosphate Shunt. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada550796.

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Bold, Richard. Metabolic Stress Induced by Arginine Deprivation Induces Autophagy Cell Death in Prostate Cancer. Fort Belvoir, VA: Defense Technical Information Center, August 2009. http://dx.doi.org/10.21236/ada517565.

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Bold, Richard. Metabolic Stress Induced by Arginine Deprivation Induces Autophagy Cell Death in Prostate Cancer. Fort Belvoir, VA: Defense Technical Information Center, August 2010. http://dx.doi.org/10.21236/ada546263.

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Bold, Richard. Metabolic Stress Induced by Arginine Deprivation Induces Autophagy Cell Death in Prostate Cancer. Fort Belvoir, VA: Defense Technical Information Center, August 2011. http://dx.doi.org/10.21236/ada552112.

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