<i>SLC13A5</i> plays an essential role in the energy shift to oxidative phosphorylation in cisplatin‐resistant mesothelioma stem cells
Bibliographic record
Abstract
Mesothelioma is a highly aggressive tumor affecting an increasing number of patients worldwide. Owing to the poor clinical outcomes associated with current therapies, the development of novel therapies that target cancer stem cells (CSCs) is desirable. Here, we examined the applicability of our previously established hydrogel-based rapid CSC generation method to human mesothelioma cell lines and further analyzed the characteristics of the induced mesothelioma stem cell (MesoSC) -like cells. Human mesothelioma cell lines cultured on hydrogels presented increased expression of pan-stem cell markers and acquired spheroid formation and early tumorigenicity, suggesting that MesoSC-like cells are highly malignant. Microarray analysis demonstrated that the expression of SLC13A5, a citrate transporter involved in TCA cycle, was significantly induced in the resulting MesoSC-like cells. The overexpression of SLC13A5 resulted in a metabolic shift toward oxidative phosphorylation, increased phosphorylation of ERK and YAP, and increased SOX2 expression, leading to increased cisplatin resistance. scRNA-seq database analysis revealed that clinical mesothelioma samples contained a small number of SLC13A5-expressing cells. Our findings suggest that the hydrogel-based CSC generation method is also effective for human mesothelioma cells and that SLC13A5 may contribute to MesoSC survival. The new properties of MesoSCs revealed in this study may provide clues for establishing future treatments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".