Investigation of ferroptosis and mTOR signaling in chromophobe renal cell carcinoma (ChRCC).
Bibliographic record
Abstract
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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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".