Abstract B13: Utilizing metabolic reprogramming to regulate fibroblast phenotype and reduce radiation fibrosis
Bibliographic record
Abstract
Abstract Introduction: Radiation fibrosis affects up to half of all patients undergoing radiotherapy for head and neck cancer treatment. It is characterized by excess extracellular matrix deposition, leading to tissue dysfunction, distortion, hardening, and pain. There are currently no effective treatments for radiation fibrosis. A fundamental challenge has been to understand and modulate the function of fibroblasts, a key mediator in extracellular matrix production and degradation. Recent evidence has demonstrated that metabolic regulation plays an important role in altering cell behavior in cancer biology and immunology. However, little is known about how metabolic changes affect fibroblast phenotype. Hypothesis: We propose that metabolic reprogramming may be an effective strategy to modulate fibroblast function and reduce radiation fibrosis. Results: An interplay between fatty acid oxidation and glycolysis was found to be a convergence point directly governing fibroblast behavior. It was demonstrated that manipulating the balance between FAO and glycolysis in fibroblasts induced either an extracellular matrix anabolic or catabolic phenotype. Specifically, anabolic fibroblasts relied on a fatty acid oxidation to glycolysis shift to produce extracellular matrix components. Reversal of this metabolic shift generated a catabolic fibroblast, which downregulated extracellular matrix synthesis and upregulated extracellular matrix lysosomal degradation. We further uncovered that CD36, a multifunctional fatty acid transporter, was a crucial link connecting fibroblast metabolism with extracellular matrix regulation, as its depletion completely inhibited collagen-1 internalization and degradation. Finally, through metabolic reprogramming using fibroblasts expressing high levels of CD36, but not CD36 knockout fibroblasts, metabolic balance could be restored, and in turn extracellular matrix accumulation was reduced in murine radiation fibrosis. Conclusions: We have uncovered that a fibroblast’s phenotype can be differentiated and regulated based on its metabolic signature. These findings have significant implications for drug development and for future cellular therapies to reduce radiation fibrosis. Citation Format: Xiao Zhao, Pamela Psarianos, David Goldstein, Ralph Gilbert, Ian Witterick, Laurie Ailles, Benjamin Haibe-Kains, Fei-Fei Liu. Utilizing metabolic reprogramming to regulate fibroblast phenotype and reduce radiation fibrosis [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; 2019 Apr 29-30; Austin, TX. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_2):Abstract nr B13.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".