Investigation of ferroptosis and mTOR signaling in chromophobe renal cell carcinoma (ChRCC).
Notice bibliographique
Résumé
583 Background: ChRCC is a rare form of kidney cancer that has shown limited response to immune checkpoint inhibitors currently used as the standard-of-care for other RCC histologies. mTOR inhibition is a therapeutic strategy for advanced ChRCC, but the mechanistic basis for response remains poorly understood. We investigated clinical responses to mTOR inhibitors in patients with ChRCC and explored the underlying mechanism of therapeutic response at single-cell resolution. Methods: Clinical data from the International Metastatic RCC Database Consortium (IMDC) was used to evaluate survival outcomes, including progression-free survival (PFS) and overall survival (OS), in patients with metastatic ChRCC compared to metastatic clear cell RCC (mccRCC) treated with first-line mTOR inhibitors. To uncover the mechanisms underlying ChRCC’s clinical response and identify future therapeutic targets, we compared gene expression in ChRCC tumor cells against their cell-of-origin via scRNA-seq analysis. Epithelial cells from matched normal kidney samples were clustered and annotated into distinct known cellular types of the healthy human kidney. A logistic regression model (Young M.D. et al., 2018) was trained on normal epithelial clusters, using a set of 74 marker genes. The model was tested on ChRCC tumors to identify their cellular origin by finding the highest predicted probabilities of similarity between normal epithelial cellular types and tumor cells. Validation analysis was conducted using a separate training set (KPMP Atlas). Differential gene expression and pathway analyses between ChRCC and its cell-of-origin were then conducted. Results: Patients with metastatic ChRCC exhibited higher overall survival (OS) compared to those with metastatic clear cell RCC when treated with first-line mTOR inhibitors (median OS: 41.3 months [95% CI: 14.4-NR] vs. 13.4 months [95% CI: 10.9-15.3], respectively). After quality control, 7,425 cells from ChRCC tumors and 784 epithelial cells from adjacent normal kidney tissue were isolated for scRNA-seq analysis. Normal epithelial cells were classified into proximal tubule, loop of Henle – distal tubule, principal cells, α-intercalated cells (ICA), and β-intercalated cells (ICB). The ChRCC tumor cells showed the highest similarity to ICA cells (0.60 probability), which was confirmed in the validation analysis. Among the most upregulated genes in ChRCC compared to ICA were NUPR1, FTL, and FTH1, all associated with the inhibition of ferroptosis. The top enriched pathways included NFE2L2 signaling, ferroptosis, and mTORC1 signaling. Conclusions: Metastatic ChRCC patients demonstrate improved overall survival compared to mccRCC patients when treated with mTOR inhibitors as first-line therapy. ChRCC appears to originate from ICA cells of the normal kidney. Potential therapeutic targets in ChRCC include ferroptosis and mTOR signaling pathways.
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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 | 0,001 | 0,001 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».