Abstract B005: Characterizing the role of fibroadipogenic progenitors in pancreatic cancer cachexia: the role of miR-27a-3p
Bibliographic record
Abstract
Abstract Introduction: Approximately 80% of patients with pancreatic cancer suffer from cachexia- a debilitating condition characterized by involuntary loss of muscle and fat. While muscle wasting has mostly been investigated from a whole tissue level, the impact of how different cell types contribute to muscle wasting remains elusive. The current study focuses on characterizing the role of muscle resident fibroadipogenic progenitors (FAPs) in pancreatic cancer cachexia. Dysregulation of FAPs produces sustained fibrogenic and/or adipogenic signals, which may lead to fibrofatty infiltration- a condition often observed in patients with cachexia. Using an experimental model of pancreatic cancer cachexia, we aim to understand (i) the overall contribution of FAPs to muscle wasting, (ii) the role of microRNAs (miRNAs- a class of small RNAs considered as global modulators of gene expression) in FAPs dysregulation and (iii) if modulating miRNAs in cancer improves muscle micro and macroenvironment. Methods: A male pancreatic cancer cell line was utilized to investigate the cachexia progression over time where day 14 (D14), 21 (D21), and day 26 (D26) were considered early, intermediate, and late time points, respectively. Mice were orthotopically implanted with 2 million pancreatic cancer cells (referred to as the KPC) and control mice received sham surgery (referred to as the control). Single nucleus RNA seq (snRNA seq) from quadriceps muscle, RNA seq, and miRNA profiling from sorted FAPs were performed. miR-27a-3p was knocked down in pancreatic cancer cells using a lentiviral system. Results: snRNA seq identified 13 clusters in quadriceps muscle including FAPs. Further, 4 subpopulations of FAPs with predominantly distinct transcriptional profiles were identified indicating that FAPs may be functionally heterogeneous. Further, muscle wasting genes such as Bmp4 and Osmr were present predominantly in FAPs suggesting that dysregulation of FAPs may contribute to muscle wasting. Time-resolved RNA seq analysis from sorted FAPs showed that alterations in adipogenesis (observed on day 14) preceded fibrosis (observed on d21), suggesting that dysregulation of FAPs is an early event in the muscle wasting trajectory, potentially contributing to fibrofatty infiltration. miR-27a-3p was chosen as a candidate molecule that was downregulated in FAPs and upregulated in the tumor when compared to controls. Inhibiting miR-27a-3p on FAPs increased adipogenesis and treatment with mimic reduced adipogenesis. Knocking down miR-27a in cancer prevented muscle wasting in vivo, and reduced FAPs dysregulation, suggesting that miR-27a-3p plays a dual role in tumor and muscle microenvironment. Conclusions: The study shows for the first time that dysregulation of FAPs significantly contributes to muscle wasting, potentially mediated through miR-27a-3p which when modulated in tumor reduces tumor progression and improves the muscle micro and macroenvironment. Citation Format: Ashok Narasimhan, Chun Wai Cheung, Nasim Kajabadi, Bruce Lin, Lin Wei Tung, Chihkai Chang, Fabio MV Rossi. Characterizing the role of fibroadipogenic progenitors in pancreatic cancer cachexia: the role of miR-27a-3p [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B005.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".