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Molecules (Basel, Switzerland) Dec 2021Proliferating cancer cells have high energy demands, which is mainly obtained through glycolysis. The transmembrane trafficking of lactate, a major metabolite produced... (Meta-Analysis)
Meta-Analysis
Proliferating cancer cells have high energy demands, which is mainly obtained through glycolysis. The transmembrane trafficking of lactate, a major metabolite produced by glycolytic cancer cells, relies on monocarboxylate transporters (MCTs). MCT1 optimally imports lactate, although it can work bidirectionally, and its activity has been linked to cancer aggressiveness and poor outcomes. AZD3965, a specific MCT1 inhibitor, was tested both in vitro and in vivo, with encouraging results; a phase I clinical trial has already been undertaken. Thus, analysis of the experimental evidence using AZD3965 in different cancer types could give valuable information for its clinical use. This systematic review aimed to assess the in vivo anticancer activity of AZD3965 either alone (monotherapy) or with other interventions (combination therapy). Study search was performed in nine different databases using the keywords "AZD3965 in vivo" as search terms. The results show that AZD3965 successfully decreased tumor growth and promoted intracellular lactate accumulation, which confirmed its effectiveness, especially in combined therapy. These results support the setup of clinical trials, but other important findings, namely AZD3965 enhanced activity when given in combination with other therapies, or MCT4-induced treatment resistance, should be further considered in the clinical trial design to improve therapy response.
Topics: Animals; Antineoplastic Agents; Cell Line, Tumor; Disease Management; Disease Progression; Drug Evaluation, Preclinical; Energy Metabolism; Glycolysis; Humans; Lactic Acid; Monocarboxylic Acid Transporters; Neoplasms; Pyrimidinones; Signal Transduction; Symporters; Thiophenes; Tumor Microenvironment; Warburg Effect, Oncologic; Xenograft Model Antitumor Assays
PubMed: 35011413
DOI: 10.3390/molecules27010181 -
Journal of Assisted Reproduction and... Aug 2021To study the use of in silica model to better understand and propose new markers of ovarian response to controlled ovarian stimulation before IVF.
PURPOSE
To study the use of in silica model to better understand and propose new markers of ovarian response to controlled ovarian stimulation before IVF.
METHODS
A systematic review and in silica model using bioinformatics. After the selection of 103 papers from a systematic review process, we performed a GRADE qualification of all included papers for evidence-based quality evaluation. We included 57 genes in the silica model using a functional protein network interaction. Moreover, the construction of protein-protein interaction network was done importing these results to Cytoscape. Therefore, a cluster analysis using MCODE was done, which was exported to a plugin BINGO to determine Gene Ontology. A p value of < 0.05 was considered significant, using a Bonferroni correction test.
RESULTS
In silica model was robust, presenting an ovulation-related gene network with 87 nodes (genes) and 348 edges (interactions between the genes). Related to the network centralities, the network has a betweenness mean value = 102.54; closeness mean = 0.007; and degree mean = 8.0. Moreover, the gene with a higher betweenness was PTPN1. Genes with the higher closeness were SRD5A1 and HSD17B3, and the gene with the lowest closeness was GDF9. Finally, the gene with a higher degree value was UBB; this gene participates in the regulation of TP53 activity pathway.
CONCLUSIONS
This systematic review demonstrated that we cannot use any genetic marker before controlled ovarian stimulation for IVF. Moreover, in silica model is a useful tool for understanding and finding new markers for an IVF individualization.
PROSPERO
CRD42020197185.
Topics: Computational Biology; Computer Simulation; Female; Fertilization in Vitro; Gene Regulatory Networks; Humans; Ovary; Ovulation Induction; Prognosis; Protein Interaction Maps
PubMed: 33788133
DOI: 10.1007/s10815-021-02141-0