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by claude@2026-06, 2026-06-21
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The study investigated how pyruvate carboxylase (PC) affects glycolysis and endometriosis progression using quasi-targeted metabolomics in immortalized human endometrial stromal cells (IhESCs), comparing cells transfected with PC knockdown versus controls. Cells were metabolite-extracted with aqueous methanol and analyzed by LC-MS/MS (QTRAP 6500+) with Q3-based quantification and bioinformatics using PCA, differential metabolite testing, and KEGG pathway analysis. The key finding was that PC knockdown altered cellular metabolite profiles consistent with reduced glycolysis and that PC promotes endometriosis progression by activating the AKT pathway. This paper’s limitation, as reflected in its design, is that it relies on a cellular model and metabolomic analyses rather than in vivo confirmation. This paper is centrally about endometriosis—specifically, how pyruvate carboxylase promotes endometriosis progression via AKT pathway activation and glycolysis modulation.
Abstract
Quasi-targeted metabolomics was employed to investigate the effects of PC knockdown (si#1) on cellular metabolite profiles, with experimental analysis performed by Novogene. The workflow consisted of four main phases: sample collection, metabolite extraction, mass spectrometry analysis, and bioinformatics processing. IhESCs in NC or siPC group were digested and counted. A total of 5×10⁵ cells were transferred into a centrifuge tube, centrifuged, and washed once with pre-chilled PBS. After another round of centrifugation, 300μL of 80% aqueous methanol solution was added, followed by quick-freezing in liquid nitrogen for 5 minutes. The mixture was thawed on ice, vortexed for 30s, and sonicated for 6 minutes. Subsequently, it was centrifuged at 5000rpm and 4℃ for 1 minute. The supernatant was collected into a new centrifuge tube, lyophilized to a dry powder, and then reconstituted in 300μL of 10% aqueous methanol solution. Metabolite detection was conducted using the SCIEX QTRAP® 6500+ mass spectrometer in multiple reaction monitoring mode, supported by Novogene's proprietary metabolomics database (novoDB). Quantification was based on Q3 (product ion) signals, while qualitative analysis integrated three-dimensional identification: 1) retention time alignment, 2) Q1/Q3 (precursor/product ion) pair matching, and 3) verification through MS/MS spectral library comparison. Three biological replicates were performed, and quality control (QC) samples were prepared by equal-volume mixing of all experimental samples. Data normalization was conducted using the total peak area normalization method. R software and MetaboAnalyst were utilized for bioinformatics analysis of metabolomics data, including principal component analysis (PCA), differential metabolite analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.
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Pyruvate carboxylase promotes glycolysis and progression of endometriosis by activating the AKT pathway
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Description
Quasi-targeted metabolomics was employed to investigate the effects of PC knockdown (si#1) on cellular metabolite profiles, with experimental analysis performed by Novogene. The workflow consisted of four main phases: sample collection, metabolite extraction, mass spectrometry analysis, and bioinformatics processing. IhESCs in NC or siPC group were digested and counted. A total of 5×10⁵ cells were transferred into a centrifuge tube, centrifuged, and washed once with pre-chilled PBS. After another round of centrifugation, 300μL of 80% aqueous methanol solution was added, followed by quick-freezing in liquid nitrogen for 5 minutes. The mixture was thawed on ice, vortexed for 30s, and sonicated for 6 minutes. Subsequently, it was centrifuged at 5000rpm and 4℃ for 1 minute. The supernatant was collected into a new centrifuge tube, lyophilized to a dry powder, and then reconstituted in 300μL of 10% aqueous methanol solution.
Metabolite detection was conducted using the SCIEX QTRAP® 6500+ mass spectrometer in multiple reaction monitoring mode, supported by Novogene's proprietary metabolomics database (novoDB). Quantification was based on Q3 (product ion) signals, while qualitative analysis integrated three-dimensional identification: 1) retention time alignment, 2) Q1/Q3 (precursor/product ion) pair matching, and 3) verification through MS/MS spectral library comparison. Three biological replicates were performed, and quality control (QC) samples were prepared by equal-volume mixing of all experimental samples. Data normalization was conducted using the total peak area normalization method. R software and MetaboAnalyst were utilized for bioinformatics analysis of metabolomics data, including principal component analysis (PCA), differential metabolite analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.
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