Cancer stem cells: implications for the progression and treatment of metastatic disease
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
Metastasis is the major cause of death for cancer patients with solid tumours, due mainly to the ineffectiveness of current therapies once metastases begin to form. Further insight into the biology of metastasis is therefore essential in order to gain a greater understanding of this process and ultimately to develop better cancer therapies. Metastasis is an inefficient process, such that very few cells that leave a tumour successfully form macrometastases in distant sites. This suggests that only a small subset of cells can successfully navigate the metastatic cascade and eventually re-initiate tumour growth to form life-threatening metastases. Recently, there has been growing support for the cancer stem cell (CSC) hypothesis which stipulates that primary tumours are initiated and maintained by a small subpopulation of cancer cells that possess "stem-like" characteristics. Classical properties of normal stem cells are strikingly reminiscent of the observed experimental and clinical behaviour of metastatic cancer cells, including an unlimited capacity for self renewal; the requirement for a specific 'niche' or microenvironment to grow; use of the stromal cell-derived factor 1 (SDF-1)/chemokine receptor 4 (CXCR4) axis for migration; enhanced resistance to apoptosis and an increased capacity for drug resistance. Therefore, in addition to playing a role in primary tumour formation, we believe that CSCs are also key players in the metastatic process. We will review the current evidence supporting this idea and discuss the potential implications of the CSC hypothesis with regards to experimental investigation and treatment of metastatic disease.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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