Transcriptomics Studies Reveal Functions of Transglutaminase 2 in Breast Cancer Cells Using Membrane Permeable and Impermeable Inhibitors
Bibliographic record
Abstract
Transglutaminase 2 (TG2) performs many functions both under physiological and pathological conditions. In cancer, its expression is associated with aggressiveness, propensity to epithelial-mesenchymal transition, and metastasis. Since TG2 performs key functions both outside and inside the cell, using inhibitors with different membrane permeability we analyzed the changes in the transcriptome induced in two triple-negative cell lines (MDA-MB-436 and MDA-MB-231) with aggressive features. By characterizing pathways and gene networks, we were able to define the effects of TG2 inhibitors (AA9, membrane-permeable, and NCEG2, impermeable) in relation to the roles of the enzyme in the intra- and extracellular space within the context of breast cancer. The deregulated genes revealed p53 and integrin signaling to be the common pathways with some genes showing opposite changes in expression. In MDA-MB-436, AA9 induced apoptosis, modulated cadherin, Wnt, gastrin and cholecystokinin receptors (CCKR) mediated signaling, with RHOB and GNG2 playing significant roles, and affected the Warburg effect by decreasing glycolytic enzymes. In MDA-MB-231 cells, AA9 strongly impacted HIF-mediated hypoxia, including AKT and mTOR pathway. These effects suggest an anti-tumor activity by blocking intracellular TG2 functions. Conversely, the use of NCEG2 stimulated the expression of ATP synthase and proteins involved in DNA replication, indicating a potential promotion of cell proliferation through inhibition of extracellular TG2. To effectively utilize these molecules as an anti-tumor strategy, an appropriate delivery system should be evaluated to target specific functions and avoid adverse effects. Additionally, considering combinations with other pathway modulators is crucial.
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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) | 0.000 | 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) | 0.000 | 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".