CCN3/NOV as a functional driver and prognostic biomarker of prostate cancer bone metastasis.
Bibliographic record
Abstract
182 Background: Prostate cancer commonly metastasizes to the bone, resulting in pathological fractures and poor prognosis. CCN3/NOV (Nephroblastoma overexpressed) has been implicated in promoting the formation of osteolytic prostate cancer (PC) bone metastases. The C-terminal domain of CCN3 binds growth factors, heparin sulfate proteoglycans, activates Notch signaling and promotes dimerization of CCN family members. We hypothesize that the CCN3 CT domain is required to promote osteolytic PC bone metastasis and that CCN3 represents a prognostic biomarker in primary PC tumors to predict recurrence to bone. Methods: CCN3WT and CCN3∆CT were overexpressed in LNCaP C4-2 cells. The role of CCN3 was assessed with in vitro proliferation, migration and invasion assays, and in vivo through intracardiac injection in male Nude mice (Nu/Nu). Ex vivo µCT scans were performed on bone specimens. CCN3 expression was assessed in two unique tissue microarrays (TMA) comprising over 1,500 primary prostate tumor using different anti-CCN3 antibodies with immunohistochemistry and immunohistofluorescnece, respectively. Results: While CCN3WT and CCN3∆CT had little effect in vitro on cell proliferation, migration or invasion, intracardiac injection of CCN3WT resulted in increased incidence of bone metastasis compared to empty vector control and CCN3∆CT. Ex vivo µCT revealed decreased bone mineral density in bones from mice injected with CCN3WT cells compared to control and CCN3∆CT expressing cells. In both TMAs studied, high CCN3 expression in tumor epithelium correlated with increased risk of biochemical relapse and bone metastasis at 5 years and 15 years post-resection, respectively. Conclusions: CCN3 requires its C-terminal domain for its bone metastatic function, and CCN3 is correlated with aggressive disease biology in prostate cancer. These findings point to CCN3 as a biomarker that can be useful to predict prostate cancer aggressiveness, while providing clarity on its role as a functional mediator of prostate cancer bone metastasis.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".