Human Bone Marrow Stromal Cells Lose Immunosuppressive and Anti-inflammatory Properties upon Oncogenic Transformation
Bibliographic record
Abstract
Because of their immunomodulatory properties, human bone marrow stromal cells (hBMSCs) represent promising stem cells for treatment of immune disorders. hBMSCs expansion precedes their clinical use, so the possibility that hBMSCs undergo spontaneous transformation upon long-term culture should be addressed. Whether hBMSCs retain immunosuppressive and anti-inflammatory properties upon oncogenic transformation remains unknown. Using sequentially mutated hBMSCs and spontaneously transformed hBMSCs, we report that, upon oncogenic transformation, hBMSCs lose immunosuppressive and anti-inflammatory properties in vitro and in vivo. Transcriptome profiling and functional assays reveal immune effectors underlying the loss of immunomodulation in transformed hBMSCs. They display a proinflammatory transcriptomic signature, with deregulation of immune and inflammatory modulators and regulators of the prostaglandin synthesis. Transformed hBMSCs lose their capacity to secrete the immunosuppressive prostacyclins prostaglandin E2 (PGE2) and PGI2 but produce proinflammatory thromboxanes. Together, the immunoregulatory profile adopted by hBMSCs largely depends on intrinsic genetic-molecular determinants triggered by genomic instability/oncogenic transformation.
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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".