Abstract A005: An Iron-regulated Signalling Pathway Controls Adipose Browning and Cancer Cachexia
Bibliographic record
Abstract
Abstract Browning and atrophy of white adipose tissue (WAT) are early events of cachexia, a lethal metabolic disorder affecting nearly half of cancer patients, including those with pancreatic ductal adenocarcinoma (PDA). Using patient-derived specimens and PDA mouse models, we identified an iron-dependent signalling pathway that initiates adipose browning in both physiological and cachectic settings. Upon sympathetic stimulation of adipocytes, an influx of iron induces the activity of methionine sulfoxide reductase A (MSRA), an enzyme that reverses the oxidation of proteinaceous methionine residues. Mechanistically, iron coordination by the conserved iron-binding EXXH motif of two MSRA polypeptides serves to dimerize, stabilize, and elevate its reductase activity. Iron-bound MSRA in turn promotes adipose browning by maintaining the reduced state of select substrates, including a conserved methionine (Met71) in the ATP-binding site of Protein Kinase A (PKA). Remarkably, in mouse models of PDA, MsrA deletion impairs WAT browning, significantly mitigates cachexia, and improves the overall survival of tumour-bearing animals. By establishing the b3AR-iron-MSRA-PKA axis as a key nexus of cancer-associated cachexia, this study opens new perspectives for clinical intervention. Citation Format: JungSeung Nam, Sung Shin Ahn, Yeonoh Shin, Ariana Vargas-Castillo, Maya Dixon, Pardis Ahmadi, Kathrin Schilling, Fereshteh Zandkarimi, Alex Chen, Nal Ae Yoon, Harrison Cullen, Yanping Sun, Thomas Caffrey, Kelsey Klute, Benjamin Swanson, Jordan Lu, Samuel Pan, Yuxuan Chen, Shu Ichimiya, Geena Kim, Jeanine Genkinger, Kazuki Sugahara, Michael Kluger, Paul Grandgenett, Michael Hollingsworth, Luke Berchowitz, Anthony Ferrante Jr., Sabrina Diano, Christine Chio. {Abstract title} [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr A005.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".