Abstract B74: Identifying conserved properties of the epithelial-mesenchymal transition in cancer using highly multiplexed single-cell RNA sequencing
Notice bibliographique
Résumé
Abstract Epithelial-mesenchymal heterogeneity is ubiquitous among epithelial tissues and the reversible transition (EMT) between these two states provides ovarian cancer cells with plasticity to promote metastasis and resistance to chemotherapy. While extensively studied, no common, EMT-defining expression program has been identified. Leveraging multiplexed single-cell RNA sequencing (scRNA-seq), we compared transcriptional dynamics of the EMT from twelve distinct time course experiments comprising four different human cancer cell types and three different EMT inducers. From this, we identified many context-specific changes, cell type-specific patterns, and a core set of genes whose dynamics are largely conserved, including activation of the canonical EMT genes vimentin and fibronectin, and other less-documented genes, such as the immunoregulatory factors IL32 and CXCL1. Integrating scRNA-seq data from a variety of tumors and healthy epithelium revealed consistent patterns. In general, progression through the EMT was associated with increased expression of cytokines and growth factors. To assess the dependence of the EMT on this paracrine signaling, we perturbed each time course experiment with 22 kinase inhibitors and used scRNA-seq to assess the dependence of the transition on a variety of signaling pathways. This revealed multiple pathways whose perturbation affects the EMT, e.g., inhibition of RIPK1 or triple inhibition of VEGFR, FGFR, and PDGFR strikingly blocks cells at an intermediate state along the EMT continuum. Interestingly, the human ovarian cancer cell line OVCA420 had the strongest association between cytokine expression and EMT progression. While the EMT has been loosely associated with immunoregulation in several cancers, this has yet to be studied in ovarian cancer. To determine if the EMT signature exists in tumors, we generated scRNA-seq data from tumors derived from the syngeneic STOSE and ID8 mouse ovarian cancer cells. Both tumors exhibited significant intratumoral heterogeneity of the EMT signature we had identified, and expression of this signature correlated with many of the same secreted factors, including several chemokines and interleukins. Further, myeloid and lymphocyte populations within the same tumors expressed receptors for several of these factors, suggesting EMT-associated cytokines are not only important for paracrine coordination of the EMT, but they may also modulate immune cell activity within the microenvironment. These results highlight the complexity and diversity of the EMT, but also reveal core genes whose dynamics are conserved across contexts. Coordinated progression through the EMT depends on paracrine signaling from EMT-associated cytokines that likely also affect many cell types in the tumor microenvironment. Targeting their signaling networks may present opportunities to not only reduce metastasis and chemoresistance, but also to reprogram the tumor microenvironment to promote immune cell activation and tumor clearance. Citation Format: Barbara C. Vanderhyden, David P. Cook. Identifying conserved properties of the epithelial-mesenchymal transition in cancer using highly multiplexed single-cell RNA sequencing [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B74.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».