Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.223 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.
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.
The record
- Venue
- Cell
- Topic
- Renal cell carcinoma treatment
- Field
- Medicine
- Canadian institutions
- —
- Funders
- Biomedical Research CouncilSeventh Framework ProgrammeCRUK Lung Cancer Centre of ExcellenceNemzeti Kutatási Fejlesztési és Innovációs HivatalMinisterio de Economía y CompetitividadRosetrees TrustNational Institute for Health and Care ResearchMedical Research CouncilCelgeneInstitute of Cancer ResearchUCLH Biomedical Research CentreNovo Nordisk FondenCancer Research UKFrancis Crick InstituteWellcome TrustKræftens BekæmpelseAstraZenecaRoyal Marsden Cancer CharityNIHR Maudsley Biomedical Research CentreGlaxoSmithKlinePfizer
- Keywords
- BiologyClear cell renal cell carcinomaSomatic evolution in cancerEvolutionary biologyRenal cell carcinomaEvolutionary dynamicsGeneticsBioinformaticsGeneOncology
- Has abstract in OpenAlex
- yes