Single-Cell Transcriptome Analysis Reveals Mesenchymal Stem Cells in Cavernous Hemangioma
Bibliographic record
Abstract
A cavernous hemangioma, well-known as vascular malformation, is present at birth, grows proportionately with the child, and does not undergo regression. Although a cavernous hemangioma has well-defined histopathological characteristics, its origin remains controversial. In the present study, we characterized the cellular heterogeneity of a cavernous hemangioma using single-cell RNA sequencing (scRNA-seq). The main contribution of the present study is that we discovered a large number of embryonic mesenchymal stem cells (MSCs) in a cavernous hemangioma and proposed that cavernous hemangiomas may originate from embryonic MSCs. Further analysis of the embryonic MSCs revealed that: 1) proinflammatory cytokines and related genes TNF , TNFSF13B , TNFRSF12A , TNFAIP6 , and C1QTNF6 are significantly involved in the MSC-induced immune responses in cavernous hemangiomas; 2) UCHL1 is up-regulated in the embryonic MSC apoptosis induced by proinflammatory cytokines; 3) the UCHL1-induced apoptosis of MSCs may play an important role in the MSC-induced immune responses in cavernous hemangiomas; and 4) UCHL1 can be used as a marker gene to detect embryonic MSCs at different apoptosis stages. In addition to MSCs, ECs, macrophages, T lymphocytes and NKCs were intensively investigated, revealing the genes and pathways featured in cavernous hemangiomas. The present study revealed the origin of cavernous hemangiomas and reported the marker genes, cell types and molecular mechanisms, which are associated with the origin, formation, progression, diagnosis and therapy of cavernous hemangiomas. The better understanding of the MSC-induced immune responses in benign tumours helps to guide future investigation and treatment of embryonic MSC-caused tumours. Our findings initiated future research for the rediscovery of MSCs, cancers/tumours and the UCHL1-induced apoptosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".