Abstract C122: Effects of standard-of-care therapies on tumor growth, tumor-induced bone loss and bone pain in preclinical models of breast and prostate cancer bone metastasis and multiple myeloma bone disease
Bibliographic record
Abstract
Abstract Bone metastases are a significant clinical problem in many major cancers, especially in breast and prostate cancer where 70-90% of advanced patients develop bone metastases. Myeloma bone disease is associated with similar clinical problems than bone metastases, including increased risk of fractures and bone pain that decrease the quality of life. The standard-of-care therapy (SOC) to prevent tumor growth depends on the tumor type. In this study, we demonstrated the effects of SOCs in triple-negative breast cancer (TNBC) and castration-resistant prostate cancer (CRPC) bone metastasis models, and in a multiple myeloma (MM) bone disease model. The TNBC model included 4T1 mouse triple-negative breast cancer cells in female BALB/c mice, the CRPC model included RM-1 mouse androgen-insensitive prostate cancer cells in castrated male C57BL/6 mice, and the MM model included human RPMI 8226 cells in immunodeficient female NPG mice. In all models, luciferase-labelled cancer cells were inoculated intratibially into the bone marrow to model tumor growth in bone, mimicking growth of bone metastases in patients. Tumor growth was monitored by bioluminescence imaging (BLI) and cancer-induced bone changes by X-ray imaging. The study lengths were 21, 25 and 56 days in the TNBC, CRPC and MM models, respectively. In the TNBC and CRPC models, bone pain was assessed by Von Frey filaments (mechanical allodynia). Doxorubicin (4 mg/kg, ip, BIW), docetaxel (10 mg/kg, ip, BIW) or bortezomib (0.5 mg/kg, ip, BIW) were used as SOCs in the TNBC, CRPC and MM models, respectively. In the TNBC model, doxorubicin reduced both tumor growth and cancer-induced bone loss at the endpoint, and reduction in bone pain was observed at day 14. In the CRPC model, docetaxel decreased tumor burden at day 18 but the effect was lost at day 25, and no effects were observed on cancer-induces bone loss or bone pain. In the MM model, bortezomib decreased tumor growth at days 28 and 56, but no effects were observed in cancer-induced bone loss. The SOCs decreased tumor growth in all three preclinical models. Doxorubicin also decreased cancer-induced bone loss and bone pain in the TNBC model. In conclusion, different SOCs have varying effects in preclinical bone metastasis models and performance of each SOC needs to be validated separately before they are included as reference compounds or used as combination partners in preclinical studies. Citation Format: Tiina E. Kähkönen, Jie Wen, Ru Yang, Jussi Halleen. Effects of standard-of-care therapies on tumor growth, tumor-induced bone loss and bone pain in preclinical models of breast and prostate cancer bone metastasis and multiple myeloma bone disease [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C122.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".