TGFβ1 Inhibition Increases the Radiosensitivity of Breast Cancer Cells<i>In Vitro</i>and Promotes Tumor Control by Radiation<i>In Vivo</i>
Bibliographic record
Abstract
PURPOSE: To determine whether inhibition of TGFβ signaling prior to irradiation sensitizes human and murine cancer cells in vitro and in vivo. EXPERIMENTAL DESIGN: TGFβ-mediated growth and Smad phosphorylation of MCF7, Hs578T, MDA-MB-231, and T47D human breast cancer cell lines were examined and correlated with clonogenic survival following graded radiation doses with and without pretreatment with LY364947, a small molecule inhibitor of the TGFβ type I receptor kinase. The DNA damage response was assessed in irradiated MDA-MB-231 cells pretreated with LY364947 in vitro and LY2109761, a pharmacokinetically stable inhibitor of TGFβ signaling, in vivo. The in vitro response of a syngeneic murine tumor, 4T1, was tested using a TGFβ neutralizing antibody, 1D11, with single or fractionated radiation doses in vivo. RESULTS: Human breast cancer cell lines pretreated with TGFβ small molecule inhibitor were radiosensitized, irrespective of sensitivity to TGFβ growth inhibition. Consistent with increased clonogenic cell death, radiation-induced phosphorylation of H2AX and p53 was significantly reduced in MDA-MB-231 triple-negative breast cancer cells when pretreated in vitro or in vivo with a TGFβ type I receptor kinase inhibitor. Moreover, TGFβ neutralizing antibodies increased radiation sensitivity, blocked γH2AX foci formation, and significantly increased tumor growth delay in 4T1 murine mammary tumors in response to single and fractionated radiation exposures. CONCLUSION: These results show that TGFβ inhibition prior to radiation attenuated DNA damage responses, increased clonogenic cell death, and promoted tumor growth delay, and thus may be an effective adjunct in cancer radiotherapy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".