β1-Integrin: A Potential Therapeutic Target in the Battle against Cancer Recurrence
Bibliographic record
Abstract
Primary cancer treatment, involving both local and often systemic adjuvant therapy, is often successful, especially if the cancer is detected at an early stage of progression. However, for some patients, the cancer may recur either locally or as distant metastases, in some cases many years after apparently successful primary treatment. Significant tumor dormancy has been documented in several cancers, such as breast, melanoma, and renal cancer. Tumor dormancy has long been recognized as an important problem in management of cancer patients. Recent work has clarified biologic aspects of tumor dormancy and has shown that dormant tumor cells may be resistant to cytotoxic chemotherapy and radiation. This work has led to recognition of a key role for β1-integrin in regulating the switch from a dormant state to active proliferation and metastasis. Here we discuss the role of β1-integrin and its signaling partners in regulating the dormant phenotype. We also consider possible therapeutic approaches, such as small molecules or antibodies (ATN-161, volociximab, and JSM6427), directed against β1-integrin signaling to target dormant cancer cells and to prevent metastatic recurrence.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".