State of the Science: An Update on Renal Cell Carcinoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Renal cell carcinomas (RCC) are emerging as a complex set of diseases that are having a major socioeconomic impact and showing a continued rise in incidence throughout the world. As the field of urologic oncology faces these trends, several major genomic and mechanistic discoveries are altering our core understanding of this multitude of cancers, including several new rare subtypes of renal cancers. In this review, these new findings are examined and placed in the context of the well-established association of clear cell RCC (ccRCC) with mutations in the von Hippel-Lindau (VHL) gene and resultant aberrant hypoxia inducible factor (HIF) signaling. The impact of novel ccRCC-associated genetic lesions on chromatin remodeling and epigenetic regulation is explored. The effects of VHL mutation on primary ciliary function, extracellular matrix homeostasis, and tumor metabolism are discussed. Studies of VHL proteostasis, with the goal of harnessing the proteostatic machinery to refunctionalize mutant VHL, are reviewed. Translational efforts using molecular tools to elucidate discriminating features of ccRCC tumors and develop improved prognostic and predictive algorithms are presented, and new therapeutics arising from the earliest molecular discoveries in ccRCC are summarized. By creating an integrated review of the key genomic and molecular biological disease characteristics of ccRCC and placing these data in the context of the evolving therapeutic landscape, we intend to facilitate interaction among basic, translational, and clinical researchers involved in the treatment of this devastating disease, and accelerate progress toward its ultimate eradication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it