Abstract 5402: Metabolic shift towards the <i>de novo</i> serine pathway in non-transformed breast cells drives epigenetic plasticity, oxidative DNA damage, and pro-tumorigenic cChanges associated with aging
Notice bibliographique
Résumé
Abstract Introduction: A lipid metabolism gene signature is enriched in breast tissue at risk for estrogen receptor negative (ERneg) breast cancer (BC). Fatty acid (FA) exposure alters histone methylation, gene expression and increases metabolic flux through serine, one-carbon, glycine (SOG) and methionine pathways. We hypothesize that FA exposure induces a metabolic shift towards the SOG, increasing S-adenosylmethionine (SAM), altering histone methylation, gene expression, and promoting ERneg BC. Methods: Proteomics, metabolomics, Reactive Oxygen Species (ROS) measurement, comet assay and H3K4me3 CUT&RUN were performed in MCF-10A cells exposed to octanoic acid (OA). Single-cell RNA-seq (scRNAseq) was performed in breast tissue derived microstructures exposed to OA. Intracellular communication was analyzed using CellChat, and metabolic flux with Compass. Results: OA increased SAM, glutathione (GSH) and 2-hydroxyglutarate (2-HG); blocking the serine pathway (SSP) prevented these increases. ScRNAseq revealed that OA increased expression of the SSP transcription factor ATF3 and genes PHGDH and PSAT1 in epithelial and stromal compartments. Metabolic flux analysis revealed a significant increase in flux through SSP in Basal BSL1, Luminal Progenitor LP3, and Hormone Sensing HS1 cells after OA exposure. Differential proteomics reveals PHGDH overexpression and downregulation of proteins involved in extracellular matrix (ECM)-receptor interaction and focal adhesion post-OA exposure, along with significant increase in mitochondrial and nuclear ROS (p < 0.01). OA exposure also induced DNA damage, likely due to elevated nuclear ROS. OA increased GSH metabolism and ROS detoxification in BSL1. CUT&RUN identified 661 peaks significantly enriched upon OA (FDR < 0.01) in regulatory regions of OA-induced genes involved in neural pathways and BC, including MDK, NGF, and NGFR. CellChat predicted a decrease in ECM-cell interactions, a reduction in cell-cell adhesions, and an increase of secreted signaling upon OA exposure. The strongest secreted signals in OA were AREG (linked to proliferation, growth, and invasiveness), GDF15 (involved in EMT, invasion, and aging), and MDK (linked to neurogenesis, and aging). Conclusions: We demonstrate an FA-induced shift towards the SOG and methionine pathways that promotes epigenetic plasticity, regulates ROS, and supports the survival of cells with 'inappropriate' phenotypes. These accumulate DNA damage, leading to age-related changes in the mammary gland (elevated ROS, disrupted junctions, altered ECM interactions, and increased MDK/GDF15 expression), all supporting carcinogenesis. Our findings also provide a metabolic explanation for the elevation of PHGDH in 70% of ERneg BCs, despite gene amplification in only 6%, and point to preventive strategies targeting the SSP. Citation Format: Mariana Bustamante Eduardo, Gannon Cottone, Curtis McCloskey, Flavio Palma, Shiyu Liu, Maria Paula Zappia, Abul B.M.M.K. Islam, Elizaveta Benevolenskaya, Maxim Frolov, Jason Locasale, Marcelo Bonini, Rama Khokha, Navdeep Chandel, Seema A. Khan, Susan E. Clare. Metabolic shift towards the de novo serine pathway in non-transformed breast cells drives epigenetic plasticity, oxidative DNA damage, and pro-tumorigenic cChanges associated with aging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5402.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».