Abstract 849: Characterization and prevention of radiation-induced malignancies in Li-Fraumeni Syndrome
Bibliographic record
Abstract
Abstract PURPOSE: Li-Fraumeni Syndrome (LFS) is a genetic disorder associated with a significant risk of early-onset cancer. This condition is largely driven by germline mutations in the TP53 tumor suppressor, which has a broad spectrum of functions including the transcriptional regulation of radiation response. Termed the guardian of the genome, TP53 serves as a critical checkpoint which coordinates DNA repair, cell cycle progression and apoptosis following DNA damage, ultimately controlling the fate of the cell. Aberrant or deficient TP53 function, such as occurs in LFS, contributes to radiation vulnerability. As a result, there is particular caution in the use of radiotherapy to treat primary LFS tumors, in order to prevent the formation of secondary, radiation-induced malignancies. To this end, therapeutic options for LFS are often limited to surgery and chemotherapy, posing substantial constraints for the treatment of patients who may otherwise benefit from primary tumor radiation. Metformin, a commonly prescribed anti-diabetic drug, is associated with lower cancer incidence in populations worldwide. Recent studies have shed light on the potential utility of metformin as a pharmacopreventive agent for primary tumors in LFS; hence, we hypothesize that the utility of metformin can be extended to the prevention of secondary malignancies following radiotherapy in LFS. METHODS/RESULTS: To explore the chemopreventive potential of metformin in LFS, we completed tumor challenges using a p53R172H/+ LFS mouse model. Mice treated prophylactically with metformin showed slower xenograft tumor growth compared to vehicle-treated mice. Ongoing work in our lab aims to characterize the effects of metformin on tumor growth following the administration of localized ionizing radiation (IR) to LFS mice. Briefly, these mice are treated with either vehicle or metformin, and IR is administered to the left hindlimbs to induce tumor formation. The timing and rates of tumor growth are monitored using magnetic resonance imaging. At endpoint, excised tumors are subjected to global profiling via RNA sequencing, proteomic analysis, and single-cell sequencing of discrete cell populations to characterize the effects of metformin on the development of radiation-induced malignancies. Results of these studies will be presented. SIGNIFICANCE: Overall, this work will advance our understanding of the chemopreventive effects of metformin, with the potential to broaden the treatment options available to LFS patients. Citation Format: Pamela Psarianos, Nicholas Fischer, Camilla Giovino, Noel Ong, David Malkin. Characterization and prevention of radiation-induced malignancies in Li-Fraumeni Syndrome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 849.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".