Renal organoid modeling of tuberous sclerosis complex reveals lesion features arise from diverse developmental processes
Bibliographic record
Abstract
Tuberous sclerosis complex (TSC) is a multisystem tumor-forming disorder caused by loss of TSC1 or TSC2 . Renal manifestations predominately include cysts and angiomyolipomas. Despite a well-described monogenic etiology, the cellular pathogenesis remains elusive. We report a genetically engineered human renal organoid model that recapitulates pleiotropic features of TSC kidney disease in vitro and upon orthotopic xenotransplantation. Time course single-cell RNA sequencing demonstrates that loss of TSC1 or TSC2 affects multiple developmental processes in the renal epithelial, stromal, and glial compartments. First, TSC1 or TSC2 ablation induces transitional upregulation of stromal-associated genes. Second, epithelial cells in the TSC1 −/− and TSC2 −/− organoids exhibit a rapamycin-insensitive epithelial-to-mesenchymal transition. Third, a melanocytic population forms exclusively in TSC1 −/− and TSC2 −/− organoids, branching from MITF + Schwann cell precursors. Together, these results illustrate the pleiotropic developmental consequences of biallelic inactivation of TSC1 or TSC2 and offer insight into TSC kidney lesion pathogenesis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".