Both high intratumoral microvessel density determined using CD105 antibody and elevated plasma levels of CD105 in colorectal cancer patients correlate with poor prognosis
Bibliographic record
Abstract
CD105 and its ligand transforming growth factor beta (TGFbeta) are modulators of angiogenesis, which drives tumour growth and metastasis. Tumour microvessel density (MVD) has proven to be an important determinant of prognosis. In this study, we have examined the prognostic value of MVD identified using Mabs to the pan-endothelial marker CD34 and to CD105 in 111 patients with colorectal cancer. The Mab to CD105 preferentially reacts with angiogenic endothelial cells. Of the 111 patients studied, 38 were alive and 73 had died of the disease. The median MVD values counted using anti-CD34 and anti-CD105 were 5 (range 1.40-9.00) and 3.10 (range 0.90-8.00), respectively. Kaplan-Meier survival analysis revealed that only MVD values obtained using CD105 Mab correlated with survival. Patients with a high MVD, above the median (3.10), showed the worst prognosis. A similar outcome was observed when MVD was divided into quartiles. In order to ascertain if this strong expression of CD105 in the tumour vasculature is reflected in patients' plasma, circulating levels of CD105, TGFbeta1 and TGFbeta3 together with the receptor-ligand complexes were quantified in patients with colorectal carcinoma and normal controls. Results showed that except for TGFbeta1, the levels of all other molecules were significantly elevated compared with controls. The levels of CD105 were positively correlated with Dukes' stages. A lower TGFbeta1 level was noted in patients with carcinoma over the controls. Furthermore, TGFbeta3 and CD105/TGFbeta3 complexes were markedly lowered in postoperative compared with preoperative plasma samples. Immunostaining revealed that TGFbeta1 was expressed in cancer cells but TGFbeta3 in the stromal cells, whereas CD105 was exclusively expressed in vascular endothelial cells of tumour blood vessels. In conclusion, this study demonstrates that MVD quantified using a Mab to CD105 is an independent prognostic parameter for survival of patients with colorectal cancer, and that plasma levels of CD105, TGFbeta1, TGFbeta3 and CD105/TGFbeta complexes may be useful markers for assessing disease progression. These data have led us to propose that quantification of these determinants may prove useful to monitor therapeutic efficacy in patients with colorectal cancer, especially those who are being treated with antiangiogenic therapies.
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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 | 0.000 | 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 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".