Metastatic Spread Emerging From Liver Metastases of Colorectal Cancer
Bibliographic record
Abstract
OBJECTIVE: To investigate whether liver metastases contribute to metastatic spread of colorectal cancer (CRC) by shedding intact tumor cells. BACKGROUND: Metastases represent the primary cause of death in CRC. Understanding the metastatic activity of metastases and which patients are at high risk for tumor cell dissemination may, therefore, have significant influence on cancer care in the future. METHODS: Circulating tumor cells (CTCs) were detected in the hepatic inflow (portal venous blood [PVB]) and outflow compartment (hepatic venous blood [HVB]) of a training (n = 55) and validation (n = 50) set using the CellSearch system. Isolated CTC from the HVB were subjected to gene expression analyses by quantitative polymerase chain reaction. RESULTS: CTC detection rate (37.2% vs 19.6%; P = 0.04) and count (mean: 12.7, SEM: ± 5.9 vs 1.9; ± 1.2; P = 0.01) were significantly higher in HVB compared to PVB. The increased CTC detection rate (54% vs 11.4%; P < 0.001) and CTC count (14.7 ± 5.1 vs 1.1 ± 0.6; P < 0.001) in the HVB compared to the PVB compartment was confirmed in the validation cohort. Expression of epithelial markers and genes involved in cell-to-cell and cell-to-matrix adhesion was reduced in CTC compared to tumor cells in liver metastases. Metastasis size greater than 5 cm was associated with CTC shedding from established liver metastases in the training and validation cohorts. CONCLUSIONS: Colorectal liver metastases shed intact tumor cells with an invasive phenotype. Metastasis size serves as a surrogate marker for metastatic activity of colorectal liver metastases.
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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 | 0.001 |
| 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".