Oncogenic and Therapeutic Targeting of PTEN Loss in Bone Malignancies
Bibliographic record
Abstract
Being a tumor suppressor, PTEN functions as a dual-specificity protein and phospholipid phosphatase and regulates a variety of cellular processes and signal transduction pathways. Loss of PTEN function has been detected frequently in different forms of cancers, such as breast, prostate and lung cancer, gastric and colon cancer, skin cancer, as well as endometrial carcinoma. In this review, we provide a summary of PTEN and its role in bone malignancies including bone metastases, multiple myeloma, and osteosarcoma, etc. We highlight the importance of PTEN loss leading to activation of the oncogenic PI3K/Akt/mTOR pathway in tumorigenesis and progression, which can be attributed to both genetic and non-genetic alterations involving gene mutation, loss of heterozygosity, promoter hypermethylation, and microRNA mediated negative regulation. We also discuss the emerging therapeutic applications targeting PTEN loss for the treatment of these bone malignant diseases.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".