Antisense therapy: Current status in prostate cancer and other malignancies
Bibliographic record
Abstract
Recent technological advances now allowing both large scale data generation and its in-depth analysis have opened new avenues to identify and target genes involved in neoplastic transformation and tumor progression. This accelerated identification and characterization of cancer-relevant molecular targets has sparked considerable interest in the development of new generations of anti-cancer agents. It is anticipated, that these agents will show enhanced specificity for malignant cells and a more favorable side-effect profile due to well-defined and tailored modes of action. Antisense oligonucleotides (ASOs) are short synthetic stretches of chemically modified DNA capable of specifically hybridizing to the mRNA of a chosen cancer-relevant target gene are close, after decades of challenges, close to fulfilling their promise in the clinical setting. Emerging clinical evidence supports the notion that ASOs stand a realistic chance of developing into one of the main players of rationally designed anti-cancer agents, although certainly not all of the challenges have been met to date. The status of antisense targeting of genes relevant to prostate cancer, including bcl-2, bcl-xL, clusterin, androgen receptor (AR) and IGFBPs, are reviewed.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".