Molecular and metabolomic characterization of hiPSC-derived cardiac fibroblasts transitioning to myofibroblasts
Bibliographic record
Abstract
Background: Mechanical stress and pathological signaling trigger the activation of fibroblasts to myofibroblasts, which impacts extracellular matrix composition, disrupts normal wound healing, and can generate deleterious fibrosis. Myocardial fibrosis independently promotes cardiac arrhythmias, sudden cardiac arrest, and contributes to the severity of heart failure. Fibrosis can also alter cell-to-cell communication and increase myocardial stiffness which eventually may lead to lusitropic and inotropic cardiac dysfunction. Human induced pluripotent stem cell derived cardiac fibroblasts (hiPSC-CFs) have the potential to enhance clinical relevance in precision disease modeling by facilitating the study of patient-specific phenotypes. However, it is unclear whether hiPSC-CFs can be activated to become myofibroblasts akin to primary cells, and the key signaling mechanisms in this process remain unidentified. Objective: We aim to explore the notable changes in fibroblast phenotype upon passage-mediated activation of hiPSC-CFs with increased mitochondrial metabolism, like primary cardiac fibroblasts. Methods: We activated the hiPSC-CFs with serial passaging from passage 0 to 3 (P0 to P3) and treatment of P0 with TGFβ1. Results: Passage-mediated activation of hiPSC-CFs was associated with a gradual induction of genes to initiate the activation of these cells to myofibroblasts, including collagen, periostin, fibronectin, and collagen fiber processing enzymes with concomitant downregulation of cellular proliferation markers. Most importantly, canonical TGFβ1 and Hippo signaling component genes including TAZ were influenced by passaging hiPSC-CFs. Seahorse assay revealed that passaging and TGFβ1 treatment increased mitochondrial respiration, consistent with fibroblast activation requiring increased energy production, whereas treatment with the glutaminolysis inhibitor BPTES completely attenuated this process. Conclusion: preclinical model for the cardiac fibrotic condition, which may facilitate the identification of putative anti-fibrotic therapies, including patient-specific approaches.
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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".