Abstract C034: Obesity-Linked Leptin Signaling Promotes Immune Checkpoint Expression and Tumor Cell Survival
Bibliographic record
Abstract
Abstract Background: Obesity promotes cancer progression and immune evasion. B7-H3 (CD276), an immune checkpoint protein, is overexpressed in cancers and linked to tumor growth and therapy resistance. This study investigates whether leptin, an adipokine elevated in obesity, regulates B7-H3 expression and contributes to tumor progression and immune escape. Methods: HeLa and T47D cell lines were used to model tumor cells in the early phase of this study. Cells were treated with different concentrations of leptin to evaluate changes in B7-H3, phosphorylated STAT3 (pSTAT3), and PD-L1 expression. Quantitative real-time PCR (qRT-PCR) and Western blotting were employed to assess mRNA and protein expression, respectively. Leptin receptor (OBRb) knockdown was achieved using siRNA to investigate the involvement of leptin signaling. Apoptosis following OBRb knockdown was measured by flow cytometry using Annexin V/Propidium Iodide staining. Results: Leptin treatment led to significant upregulation of B7-H3, pSTAT3, and PD-L1 at both mRNA and protein levels. Silencing of OBRb reduced their expression and increased apoptotic cell populations, indicating a role for leptin in promoting tumor survival and immune evasion. Conclusion: These preliminary findings suggest leptin contributes to obesity-driven tumor progression via the B7-H3–pSTAT3–PD-L1 axis. Further in-depth studies are needed to validate these mechanisms and explore their potential as therapeutic targets in obesity-associated cancers. References: 1. Getu AA, Tigabu A, Zhou M, Lu J, Fodstad Ø, Tan M. New frontiers in immune checkpoint B7-H3 (CD276) research and drug development. Molecular Cancer. 2023 Mar 2;22(1):43. 2. Picarda E, Galbo Jr PM, Zong H, Rajan MR, Wallenius V, Zheng D, Börgeson E, Singh R, Pessin J, Zang X. The immune checkpoint B7-H3 (CD276) regulates adipocyte progenitor metabolism and obesity development. Science advances. 2022 Apr 27;8(17):eabm7012. Acknowledgements: This research is in part funded by China Medical University Ying-Tsai Scholar Fund CMU109-YT-04 (to M.T.) Citation Format: Iqra Kousar. Obesity-Linked Leptin Signaling Promotes Immune Checkpoint Expression and Tumor Cell Survival [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr C034.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".