Intratumoral genetic heterogeneity in metastatic melanoma is accompanied by variation in malignant behaviors
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
BACKGROUND: Intratumoral heterogeneity is a major obstacle for the treatment of cancer, as the presence of even minor populations that are insensitive to therapy can lead to disease relapse. Increased clonal diversity has been correlated with a poor prognosis for cancer patients, and we therefore examined genetic, transcriptional, and functional diversity in metastatic melanoma. METHODS: Amplicon sequencing and SNP microarrays were used to profile somatic mutations and DNA copy number changes in multiple regions from metastatic lesions. Clonal genetic and transcriptional heterogeneity was also assessed in single cell clones from early passage cell lines, which were then subjected to clonogenicity and drug sensitivity assays. RESULTS: MAPK pathway and tumor suppressor mutations were identified in all regions of the melanoma metastases analyzed. In contrast, we identified copy number abnormalities present in only some regions in addition to homogeneously present changes, suggesting ongoing genetic evolution following metastatic spread. Copy number heterogeneity from a tumor was represented in matched cell line clones, which also varied in their clonogenicity and drug sensitivity. Minor clones were identified based on dissimilarity to the parental cell line, and these clones were the most clonogenic and least sensitive to drugs. Finally, treatment of a polyclonal cell line with paclitaxel to enrich for drug-resistant cells resulted in the adoption of a gene expression profile with features of one of the minor clones, supporting the idea that these populations can mediate disease relapse. CONCLUSION: Our results support the hypothesis that minor clones might have major consequences for patient outcomes in melanoma.
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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 | 0.000 | 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) | 0.000 | 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