Transcriptional Analysis Reveals Evidence of Chronically Impeded ECM Turnover and Epithelium-to-Mesenchyme Transition in Scar Tissue Giving Rise to Marjolin’s Ulcer
Bibliographic record
Abstract
Marjolin's ulcer (MU) is an aggressive malignancy arising within chronic wounds. A major cause is unhealed burn injuries. This results in well-differentiated squamous cell carcinoma (SCC). This study aimed to elucidate transcriptional changes leading to malignancy by investigating differentially expressed genes in squamous cells present in a SCC compared with MU. MU tumor cells were isolated from histologically confirmed biopsy of SCC within an unhealed burn scar. Epithelial cells (ECs) adjacent to the tumor were co-isolated and a SCC cell line was commercially purchased. mRNA from all three samples was isolated and its expression was quantified using RNASeq. A threshold of log2fold change >2-fold in either direction was considered "differentially expressed." Gene expression analysis revealed distinct differences in gene expression in MU cells compared with EC (665 genes), EC and SCC (1673 genes). Enrichment analysis confirmed that pathways most affected included 1) elevation of genes associated with extracellular matrix organization/degradation, 2) activation of DNA damage, and 3) activation of cytokine signaling. Our analysis revealed two key insights about chronic wound microenvironment conducive to ulceration. First, in EC vs. MU comparison, downregulation of Collagen and Matrix metalloproteinase families suggests chronically impaired extracellular matrix turnover giving rise to a fibrotic microenvironment. Second, in SCC vs. MU comparison, dysregulation of cadherin-mediated cell-cell adhesions is suggestive of epithelial-to-mesenchymal transitions, similar to those during development. Acquisition of epithelial-to-mesenchymal transition may underlie the high metastatic rate in MU tumors. Taken together, this sheds light on mechanisms that underlie the divergent clinical features of these cutaneous 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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".