Neoplastic Transformation of Human Mesenchymal Stromal Cells Mediated via LIN28B
Bibliographic record
Abstract
Bone marrow stromal (Mesenchymal) stem cells (MSCs) are multipotent bone cells capable of differentiating into mesoderm-type cells, such as osteoblasts and adipocytes. Existing evidence suggests that transformation of MSCs gives rise to sarcoma. In order to identify the molecular mechanism leading to spontaneous transformation of human bone marrow MSCs (hBMSCs), we performed comprehensive microRNA (miRNA) and mRNA profiling in the transformed hBMSC-Tum line compared to the parental clone. As a result, we identified multiple dysregulated molecular networks associated with the hBMSC transformed phenotype. LIN28B was upregulated 177.0-fold in hBMSC-Tum, which was associated with marked reduction in LET-7 expression and upregulated expression of its target HMGA2. Targeted depletion of LIN28B or exogenous expression of LET-7b suppressed hBMSC-Tum proliferation, colony formation, and migration. On the other hand, forced expression of LIN28B promoted malignant transformation of parental hBMSC cells as shown by enhanced in vitro colony formation, doxorubicin resistance, and in vivo tumor formation in immunocompromised mice. Analysis of LIN28B and HMGA2 expression levels in cohorts from The Cancer Genome Atlas sarcoma dataset revealed a strong inverse-relationship between elevated expression and overall survival (OS) in 260 patients (p = 0.005) and disease-free survival (DFS) in 231 patients (p = 0.02), suggesting LIN28B and HMGA2 are important regulators of sarcoma biology. Our results highlight an important role for the LIN28B/LET-7 axis in human sarcoma pathogenesis and suggest that the therapeutic targeting of LIN28B may be relevant for patients with sarcoma.
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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) | 0.002 | 0.001 |
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".