High levels of serum cholesterol positively correlate with the risk of the development of vessel co-opting tumours in colorectal cancer liver metastases
Bibliographic record
Abstract
Abstract Colorectal cancer liver metastatic (CRCLM) tumours present as two main histopathological growth patterns (HGPs) including desmoplastic HGP (DHGP) and replacement HGP (RHGP). The DHGP tumours obtain their blood supply by sprouting angiogenesis, whereas the RHGP tumours utilize an alternative vascularisation known as vessel co-option. In vessel co-option, the cancer cells hijack the mature sinusoidal vessels to obtain blood supply. Vessel co-option has been reported as an acquired mechanism of resistance to anti-angiogenic treatment in CRCLM. Here, we show the connection between the concentration of serum cholesterol and the development of vessel co-option in CRCLM. Our clinical data suggested that the elevation of serum cholesterol levels correlates with the risk of developing vessel co-opting tumours. Moreover, inhibition of the key modulators of cholesterol metabolism including HMGCR or PCSK9 attenuated the development of CRCLM tumours, as well as vessel co-option in vivo. Altogether, our data uncovered the importance of cholesterol in the development of vessel co-option tumours and demonstrated PCSK9 and HMGCR inhibitors as promising strategies to mitigate the development of vessel co-option tumours in CRCLM.
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.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".