Interplay between Leptin and Stearoyl-CoA Desaturase 1 in Estrogen Receptor–Positive Breast Cancer Cells
Bibliographic record
Abstract
Obesity, a global health challenge, contributes to various cancers, including breast cancer. Complex metabolic dysregulation marks the development of both breast cancer and obesity. Here, the interplay between the obesity-derived adipokine leptin (LEP) and stearoyl-CoA desaturase 1 (SCD), a critical enzyme in fatty acid (FA) metabolism, was explored. While Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database analysis reported a significant protein-protein interaction between LEP and SCD, functional processing of the differentially expressed genes in LEP-treated breast cancer cells revealed a critical involvement of SCD in the interactome of deregulated proteins. Kaplan-Meier analyses linked LEP/SCD expression to poorer recurrence-free survival in patients with estrogen receptor α luminal A-like breast cancer. Functional studies demonstrated that LEP up-regulated SCD expression in luminal A-like breast cancer cells through LEP receptor-mediated signaling. Lipidomic profiling showed that SCD inhibition using MF-438 reduced LEP-induced FA desaturation, characterized by a shift from saturated to monounsaturated FAs. SCD inhibition also abolished the LEP-mediated mitochondrial respiration and ATP production. Additionally, LEP-induced oncogenic features, including enhanced growth and motility, were counteracted by pharmacologic/genetic SCD blockade, confirming SCD's role in leptin's protumorigenic effects. This study highlights the LEP-SCD axis as a driver of metabolic/functional alterations in estrogen receptor α-positive breast cancer, providing insights into the obesity-breast cancer link and identifying potential therapeutic targets (ie, SCD) to counter obesity-driven cancer progression.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".