Abstract IA018: Linking obesity-associated inflammation with cancer metastasis
Bibliographic record
Abstract
Abstract Obesity is associated with increased incidence and mortality of multiple tumor types, and competes with smoking tobacco as the leading preventable risk factor for all cancer-related deaths. In breast cancer, epidemiological studies have shown that obesity is linked to enhanced metastasis to lung and liver. However, it is not known how to improve cancer outcomes in the obese patient population as the mechanistic link between obesity and cancer progression is currently lacking. Using genetic and diet-induced obesity mouse models, it was previously shown that obesity promotes pulmonary metastasis of breast cancer by inducing lung neutrophilia via a IL5–GM-CSF signaling axis. We have now determined that neutrophils are reprogrammed by obesity within the lung to produce elevated levels of reactive oxygen species (ROS) and release neutrophil extracellular traps (NETs). This in turn weakens endothelial barrier integrity, leading to enhanced microvascular permeability and tumor cell extravasation into the lung parenchyma. This effect can be reversed by targeting ROS via pharmacological or genetic approaches, or by preventing NETosis using PAD4 inhibitors. To confirm the translational relevance of our findings, we performed imaging mass cytometry on lung metastasis samples from cancer patients, and observed a significant correlation between body mass index and NETosis, neutrophil oxidative burst, and ROS status. Given the high prevalence of obesity on an international scale, our data provide insight into mechanisms of cancer progression for a significant proportion of the adult population, including (potentially) those who are metabolically obese but normal weight. Citation Format: Sheri A. McDowell, Robin Luo, Jonathan D. Spicer, Andrew J. Dannenberg, Logan A. Walsh, Daniela F. Quail. Linking obesity-associated inflammation with cancer metastasis [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr IA018.
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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 | 0.001 | 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) | 0.012 | 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".