<i>VHL</i>-mutant renal cell carcinomas contain cancer cells with mesenchymal phenotypes.
Bibliographic record
Abstract
4568 Background: To study “cancer stem cells” it is imperative to account for all stromal cell populations within the tumour. The existence of “cancer stem cells” in clear cell renal cell carcinoma (ccRCC) has not been examined in ex vivo patient samples. Methods: We established a multiplex flow cytometry (FC) antibody panel in ccRCC, which reliably identified stromal lineages including CD45+ immune, CD31+/CD144+ endothelial and fibroblast-marker-positive subpopulations, thus allowing isolation of "lineage-negative" tumor cells. To verify the identity of tumour-derived populations as either cancer cells or normal stromal cells, we took advantage of the fact that mutations in VHL occur early during ccRCC tumorigenesis and are found in two-thirds of patients. Results: We sequenced 18 patient tumor samples, 12 of which had VHL exome mutations. Targeted re-sequencing of FC sorted subpopulations from these patients’ samples revealed that while CD45+ immune cells and CD31+/CD144+ endothelial cells were genetically normal, a population of VHL-mutant fibroblast-marker positive cells was consistently identified in every patient’s tumour. Immunohistochemistry showed that fibroblast marker-positive VHL-mutant cells do not have the large “clear cell” morphology typical of the majority of the cancer cells in these tumours. When purified and cultured, these fibroblast marker-positive VHL-mutant cells proliferate extensively under mesenchymal culture conditions, but displayed different morphologies to lineage-negative VHL-mutant tumor cells. Functional characterization of these FC sorted cell subpopulations is ongoing, including proliferation, migration, invasion, differentiation and treatment resistance. Conclusions: The phenotype and preliminary functional characterization of these VHL-mutant fibroblast-marker positive cells suggests a mesenchymal differentiation program in ccRCC, with implications for the ontogeny, biology and clinical management of VHL-mutant renal cancer.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".