Gene expression analysis reveals marked differences in the transcriptome of infantile hemangioma endothelial cells compared to normal dermal microvascular endothelial cells
Bibliographic record
Abstract
BACKGROUND: Infantile hemangiomas are benign vascular tumors primarily found on the skin in 10% of the pediatric population. The etiology of this disease is largely unknown and while large scale genomic studies have examined the transcriptomes of infantile hemangioma tumors as a whole, no study to date has compared the global gene expression profiles of pure infantile hemangioma endothelial cells (HEMECs) to that of normal human dermal microvascular endothelial cells (HDMVECs). METHODS: To shed light on the molecular differences between these normal and aberrant dermal endothelial cell types, we performed whole genome microarray analysis on purified cultures of HEMECs and HDMVECs. We then utilized qPCR and immunohistochemistry to confirm our microarray results. RESULTS: Our array analysis identified 125 genes whose expression was upregulated and 104 genes whose expression was downregulated by greater than two fold in HEMECs compared to HDMVECs. Bioinformatics analysis revealed three major classifications of gene functions that were altered in HEMECs including cell adhesion, cell cycle, and arachidonic acid production. Several of these genes have been reported to be critical regulators and/or mutated in cancer, vascular tumors, and vascular malformations. We confirmed the expression of a subset of these differentially expressed genes (ANGPT2, ANTXR1, SMARCE1, RGS5, CTAG2, LTBP2, CLDN11, and KISS1) using qPCR and utilized immunohistochemistry on a panel of paraffin embedded infantile hemangioma tumor tissues to demonstrate that the cancer/testis antigen CTAG2 is highly abundant in vessel-dense proliferating infantile hemangiomas and with significantly reduced levels during tumor involution as vascular density decreases. CONCLUSION: Our data reveal that the transcriptome of HEMECs is reflective of a pro-proliferative cell type with altered adhesive characteristics. Moveover, HEMECs show altered expression of many genes that are important in the progression and prognosis of metastatic cancers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".