OR16-02 Single-cell dissection of Obesity Identifies Epithelial-Mesenchymal Transition to promote cancer progression in Triple-Negative Breast Cancer
Bibliographic record
Abstract
Abstract X. Xu: None. S. Bahl: None. M. Lupien: None. Overweight and obesity are known to have an adverse impact on the metastasis-free survival of individuals with triple-negative breast cancer (TNBC) (1). However, since the underlying mechanisms remain elusive, there is an unmet need for specific treatment regimens for obese patients with TNBC. Epithelial-Mesenchymal Transition (EMT) is a pathway that plays a pivotal role in tumorigenesis, spanning from tumor initiation to metastasis (2). Despite its significance, limited evidence exists regarding the relationship between obesity and EMT in TNBC.Obesity has been shown to expedite and exacerbate metastatic progression in breast cancer, as supported by animal models that induce cancer stem-like signatures (3). Moreover, EMT-associated transcription factors (TFs) are significantly enriched in breast cancer stem cells (4). These TFs induce EMT properties by binding to various components of the epigenetic and transcriptional machinery. However, conducting a comprehensive investigation of EMT-associated TFs, their correlations with activating pathways, downstream targets, and their effects on crucial cancer-related processes has been hindered by the heterogeneity of tumor samples. This heterogeneity is influenced by various cell types in the tumor microenvironment play a role in interacting with cancer cells(5).To explore EMT triggers and regulatory mechanisms influenced by obesity (6), we categorized TNBC patients (T2N0M0) without any neoadjuvant therapy before surgery samples as obese or BMI-matched lean counterparts and conducted single nucleus multiome analysis to address tumor heterogeneity. Our results indicate that obese patients harbor a cancer cell state enriched with EMT-related pathways, whereas lean patients exhibit lower activity in these pathways. Furthermore, in vitro models of TNBC induced to mimic obesity through fatty acid exposure demonstrated higher migration abilities than control groups, without altering proliferation. Three differentially expressed genes (ARID4B, SMURF1, CTNNB1) were identified from the hallmark TGF-BETA-SIGNALING pathway, a classical pathway involved in EMT. These genes were negatively associated with worse survival in TNBC patients (7). Ongoing efforts aim to elucidate the underlying regulatory mechanisms governing the overexpression of EMT-associated genes. This knowledge holds potential for the development of targeted therapeutic approaches tailored to obese TNBC patients for the precision therapy.(1) Picon-Ruiz, et al,2017,CA Cancer J. Clin (2) Marc P. Stemmler,et al,2019, Nature Cell Biology (3) Mélanie Bousquenaud,et al,2018, Breast Cancer Research (4) Dongre, A, and Weinberg, R.A,et al,2019, Nat. Rev. Mol. Cell Biol (5) Alison E. Ringel, et al,2020,Cell (6)Ayse Bassez,et al,2021,Nature Medicine (7) Yuna Landais,et al,2023,Nature Communication Monday, June 3, 2024
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".