Ovarian Cancer and Glutamine Metabolism

Fasoulakis, Zacharias; Koutras, Antonios; Ntounis, Thomas; Prokopakis, Ioannis; Perros, Paraskevas; Chionis, Athanasios; Sapantzoglou, Ioakeim; Katrachouras, Alexandros; Konis, Kyriakos; Samara, Athina A.; Valsamaki, Asimina; Palios, Vasileios-Chrysovalantis; Symeonidis, Panagiotis D.; Nikolettos, Konstantinos; Pagkalos, Athanasios; Sotiriou, Sotirios K.; Theodora, Marianna; Antsaklis, Panagiotis; Daskalakis, Georgios; Kontomanolis, Emmanuel N

doi:10.3390/ijms24055041

Cited by 11 publications

(9 citation statements)

References 47 publications

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“…Besides, in our research, western blotting results also illustrated that HK2 and p‐AKT were all reduced by ARHGAP10. Most importantly, these results were consistent with the metabolic features of cancer 12,33–37 . Previous studies have shown that the PI3K/AKT pathway plays an important role in glycolysis 38–40 .…”

Section: Discussionsupporting

confidence: 88%

SMAD4 inhibits glycolysis in ovarian cancer through PI3K/AKT/HK2 signaling pathway by activating ARHGAP10

Wu,

Gong,

Sun

et al. 2024

Cancer Reports

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BackgroundARHGAP10 is a tumor‐suppressor gene related to ovarian cancer (OC) progression; however, its specific mechanism is unclear.AimsTo investigate the effect of ARHGAP10 on OC cell migration, invasion, and glycolysis.Methods and ResultsQuantitative real‐time PCR (qRT‐PCR) quantified mRNA and protein expressions of AKT, p‐AKT, HK2, and SMAD4 were tested by Western blot. EdU, Wound healing, and Transwell assay were utilized to evaluate OC cell proliferation, migration, and invasion. We used a Seahorse XF24 Extracellular Flux Analyzer to monitor cellular oxygen consumption rates (OCR) and extracellular acidification rates (ECAR). Chromatin immunoprecipitation (ChIP) was used to analyze the transcriptional regulation of ARHGAP10 by SMAD4. ARHGAP10 expression in OC tissues was detected by immunohistochemistry. Our results showed that ARHGAP10 expression was negatively related to lactate levels in human OC tissues. ARHGAP10 overexpression can inhibit the migration, proliferation, and invasion of OC cells, and this function can be blocked by 2‐Deoxy‐D‐glucose. Moreover, we found that ARHGAP10 expression can be rescued with the AKT inhibitor LY294002.ConclusionsThis study revealed that the antitumor effects of ARHGAP10 in vivo and in vitro possibly suppress oncogenic glycolysis through the PI3K/AKT/HK2‐regulated glycolysis metabolism pathway.

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Section: Discussionsupporting

confidence: 88%

SMAD4 inhibits glycolysis in ovarian cancer through PI3K/AKT/HK2 signaling pathway by activating ARHGAP10

Wu,

Gong,

Sun

et al. 2024

Cancer Reports

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“…There is increasing evidence that the expression level of glutamine metabolism-related genes in tumor cells not only re ects the growth and proliferation process of tumor cells but also serves as a predictive indicator for the prognosis of tumor patients. It has been shown in relevant literature that the expression and abnormal alteration of GMRGs have a essential relationship with the prognosis of many malignant tumors, such as bladder cancer [11], neuroblastoma [23,24], ovarian cancer [25], lung adenocarcinoma[26] and hepatocellular carcinoma [27][28][29]. However, the molecular mechanism of glutamine metabolism-related genes on the regulation of colorectal cancer progression and the prognosis prediction of patients have not been further expressed for the time being.…”

Section: Discussionmentioning

confidence: 99%

A Glutamine metabolism-related genes prognosis biomarker for predicting prognosis in colorectal carcinoma

Ma,

Zhang,

et al. 2024

Preprint

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Background Colorectal cancer (CRC) is one of the most common types of tumor in the gastrointestinal tract worldwide. Amino acid metabolism is closely associated with malignant tumor development, infiltration, metastasis and recurrence. More studies are needed to understand the relationship between glutamine metabolic profile and prognosis of colorectal cancer. Methods In our study, we obtained transcriptomic and related clinical information data of CRC patients from The Cancer Genome Atlas (TCGA) database. Consensus clustering analysis was used to classify CRC patients into various molecular subtypes and identify differential expression of genes related to immunity and glutamine metabolism. We applied univariate and multivariate COX regression and lasso regression analyses to construct a risk assessment model incorporating four genes related to glutamine metabolism, and the CRC samples were categorized into high- risk and low-risk groups, and the correlation between the risk model scores and TME, immune cell infiltration, and cellular mutations was investigated. Finally, we validated the correlation of ADIPOQ using immunohistochemistry in colorectal cancer tumor tissues. In addition, this study was externally validated using the GSE39582 dataset from the GEO database. Results By consistent cluster analysis, we identified two different molecular subtypes. It was also found that different GMRG subtypes were associated with patients' clinicopathologic features, prognosis and TME cell infiltration characteristics. Meanwhile, a predictive model on the basis of the GMRGS risk score was developed and the validity of the predictive ability of the model was verified in internal and external datasets. Furthermore, in terms of immune infiltration and cellular mutations, we observed significant variability between high and low risk groups. Conclusion Our study identified four glutamine metabolism-related genes affecting TME, clinicopathological features, immune landscape, and prognosis-related prediction of CRC, and these findings in our study will better understand the mechanisms by which reprogramming of glutamine metabolism is associated with the developmental progression of CRC and will facilitate to improve the treatment of tumors.

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“…The inhibition of glutamine metabolism has been shown to have antitumor effects in preclinical models of these cancers [ 157 , 158 ]. In ovarian cancer, which frequently metastasizes to the peritoneum, glutamine dependency has been shown to promote chemoresistance [ 159 ]. Increased expression of glutaminase and the glutamine transporter SLC1A5/ASCT2 has been observed in cisplatin-resistant ovarian cancer cells, and the inhibition of ASCT2 and glutaminase has been shown to sensitize these cells to cisplatin [ 160 ].…”

Section: Oncometabolites and Precision Cancer Medicinementioning

confidence: 99%

Targeting Oncometabolites in Peritoneal Cancers: Preclinical Insights and Therapeutic Strategies

Nadhan

Kashyap

et al. 2023

Metabolites

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Peritoneal cancers present significant clinical challenges with poor prognosis. Understanding the role of cancer cell metabolism and cancer-promoting metabolites in peritoneal cancers can provide new insights into the mechanisms that drive tumor progression and can identify novel therapeutic targets and biomarkers for early detection, prognosis, and treatment response. Cancer cells dynamically reprogram their metabolism to facilitate tumor growth and overcome metabolic stress, with cancer-promoting metabolites such as kynurenines, lactate, and sphingosine-1-phosphate promoting cell proliferation, angiogenesis, and immune evasion. Targeting cancer-promoting metabolites could also lead to the development of effective combinatorial and adjuvant therapies involving metabolic inhibitors for the treatment of peritoneal cancers. With the observed metabolomic heterogeneity in cancer patients, defining peritoneal cancer metabolome and cancer-promoting metabolites holds great promise for improving outcomes for patients with peritoneal tumors and advancing the field of precision cancer medicine. This review provides an overview of the metabolic signatures of peritoneal cancer cells, explores the role of cancer-promoting metabolites as potential therapeutic targets, and discusses the implications for advancing precision cancer medicine in peritoneal cancers.

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Ovarian Cancer and Glutamine Metabolism

Cited by 11 publications

References 47 publications

SMAD4 inhibits glycolysis in ovarian cancer through PI3K/AKT/HK2 signaling pathway by activating ARHGAP10

SMAD4 inhibits glycolysis in ovarian cancer through PI3K/AKT/HK2 signaling pathway by activating ARHGAP10

A Glutamine metabolism-related genes prognosis biomarker for predicting prognosis in colorectal carcinoma

Targeting Oncometabolites in Peritoneal Cancers: Preclinical Insights and Therapeutic Strategies

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