Clusterin and IGFBPs as Antisense Targets in Prostate Cancer
Bibliographic record
Abstract
The primary hurdle to improved survival of advanced prostate cancer is our failure to prevent or treat the tumor's progression to its lethal and untreatable stage of androgen independence. Novel treatment modalities designed to prevent androgen-independent progression including prostate cancer metastasis are required. Accelerated identification and characterization of cancer-relevant molecular targets has sparked considerable interest in the development of new generations of anticancer agents that specifically inhibit a progression-relevant target. Antisense oligonucleotides, short synthetic stretches of chemically modified DNA capable of specifically hybridizing to the mRNA of a chosen cancer-relevant target gene, promise to show enhanced specificity for malignant cells with a favorable side-effect profile due to well-defined and tailored modes of action. Although not all of the challenges have been met to date, emerging clinical evidence supports the premise that antisense oligonucleotides stand a realistic chance of emerging as major partners of rationally designed anticancer regimens. The rationale and status of antisense targeting of the treatment resistance factor clusterin and of insulin-like growth factor binding protein (IGFBP) 2 and 5 are discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".