Genetics and Tumor Microenvironment of Renal Cell Carcinoma
Bibliographic record
Abstract
Renal cell carcinoma is a diverse group of diseases that can be distinguished by distinct histopathologic and genomic features. In this comprehensive review, we highlight recent advancements in our understanding of the genetic and microenvironmental hallmarks of kidney cancer. We begin with clear cell renal cell carcinoma (ccRCC), the most common subtype of this disease. We review the chromosomal and genetic alterations that drive initiation and progression of ccRCC, which has recently been shown to follow multiple highly conserved evolutionary trajectories that in turn impact disease progression and prognosis. We also review the diverse genetic events that define the many recently recognized rare subtypes within non-clear cell RCC. Finally, we discuss our evolving understanding of the ccRCC microenvironment, which has been revolutionized by recent bulk and single-cell transcriptomic analyses, suggesting potential biomarkers for guiding systemic therapy in the management of advanced ccRCC.
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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 | 0.001 | 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".