Metabolomics has proven to be a sensitive tool for monitoring biochemical processes in cell culture. It enables multi-analysis, clarifying the correlation between numerous metabolic pathways. Together with other analysis, it thus provides a global view of a cell’s physiological state. A comprehensive analysis of molecular changes is also required in the case of mesenchymal stem cells (MSCs), which currently represent an essential portion of cells used in regenerative medicine. Reproducibility and correct measurement are closely connected to careful metabolite extraction, and sample preparation is always a critical point. Our study aimed to compare the efficiencies of four harvesting and six extraction methods. Several organic reagents (methanol, ethanol, acetonitrile, methanol–chloroform, MTBE) and harvesting approaches (trypsinization vs. scraping) were tested. We used untargeted nuclear magnetic resonance spectroscopy (NMR) to determine the most efficient method for the extraction of metabolites from human adherent cells, specifically human dermal fibroblasts adult (HDFa) and dental pulp stem cells (DPSCs). A comprehensive dataset of 29 identified and quantified metabolites were determined to possess statistically significant differences in the abundances of several metabolites when the cells were detached mechanically to organic solvent compared to when applying enzymes mainly in the classes of amino acids and peptides for both types of cells. Direct scraping to organic solvent is a method that yields higher abundances of determined metabolites. Extraction with the use of different polar reagents, 50% and 80% methanol, or acetonitrile, mostly showed the same quality. For both HDFa and DPSC cells, the MTBE method, methanol–chloroform, and 80% ethanol extractions showed higher extraction efficiency for the most identified and quantified metabolites Thus, preparation procedures provided a cell sample processing protocol that focuses on maximizing extraction yield. Our approach may be useful for large-scale comparative metabolomic studies of human mesenchymal stem cell samples.

Pancreatic ductal adenocarcinoma (PDAC) has limited effective therapeutic strategies. Statins inhibit 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase and may affect tumor cell fitness via the mevalonate pathway, mitochondrial function, and redox homeostasis. We systematically compared seven statins in patient-derived PDAC cell lines and related viability effects to mitochondrial, redox, cell-cycle, apoptotic, and metabolic responses. Statins were tested in three PDAC cell lines (PDAC-1/2/3) using MTT assays (5–20 µM; 24–120 h). Based on MTT responses, mechanistic profiling was performed after 72 h at 20 µM concentration using lipophilic statins, including apoptosis (Annexin V/7-AAD), cell-cycle distribution, mitochondrial membrane potential (Δψm), intracellular ROS, and ¹H-NMR quantification of intracellular and extracellular metabolites. Statins reduced viability in a concentration- and time-dependent manner, with lipophilic statins more active than hydrophilic. PDAC-1 was highly sensitive, PDAC-3 intermediate, and PDAC-2 comparatively resistant. PDAC-1 and PDAC-3 showed G0/G1 accumulation, Δψm depolarization, reactive oxygen species (ROS) elevation, and Annexin V–positive apoptosis, whereas PDAC-2 (high basal ROS) showed ROS reduction and limited apoptosis despite Δψm loss. Metabolomics indicated reduced glucose and amino-acid utilization and lactate secretion while preserving line-specific metabolic fingerprints. PDAC cell lines display marked inter-tumoral heterogeneity in statin responses, supporting evaluation of statins as chemosensitizing adjuvants in functionally guided PDAC treatment strategies.

Background: Glioblastoma (GBM) is the most aggressive primary brain tumour in adults and is characterised by poor prognosis and frequent resistance to temozolomide (TMZ)-based chemotherapy. Increasing evidence suggests that long non-coding RNAs (lncRNAs) contribute to GBM progression, therapeutic adaptation, and chemoresistance. This study investigated the relationship between TMZ responsiveness and the expression of selected lncRNAs in GBM cell lines exhibiting distinct sensitivity profiles. Methods: Human GBM cell lines (A172, U87, and T98G) and normal human astrocytes (NHA) were exposed to TMZ for 24–72 h. Cell viability, cell cycle distribution, MGMT protein expression, and expression levels of nine selected lncRNAs were analysed using MTT assay, flow cytometry, Western blot, and quantitative RT-PCR, respectively. Results: TMZ induced dose- and time-dependent reductions in cell viability in all analysed cell lines. A172 cells exhibited the greatest TMZ sensitivity, whereas T98G cells displayed the highest resistance. TMZ-sensitive GBM cells demonstrated pronounced G2/M cell cycle arrest, while T98G cells showed minimal cell cycle perturbation. MGMT protein expression was markedly elevated in T98G cells and decreased following exposure to higher TMZ concentrations. Distinct lncRNA expression profiles were identified among GBM cell lines. MALAT1 expression was consistently reduced, whereas NCK1-AS1 was strongly upregulated, particularly in T98G cells. TMZ exposure induced significant alterations in H19, PVT1, OIP5-AS1, and NCK1-AS1 expression, suggesting their potential involvement in adaptive resistance mechanisms. Conclusions: Collectively, these findings indicate that selected lncRNAs, particularly H19, MALAT1, NCK1-AS1, and PVT1, may contribute to TMZ resistance in GBM and could be promising biomarkers and therapeutic targets for precision oncology approaches.