Abstract 6642: Exploring the x-ray psoralen activated cancer therapy mechanism of action in a genetically engineered mouse model of soft tissue sarcoma
Bibliographic record
Abstract
Abstract BACKGROUND: Psoralen is a natural ultraviolet activated compound that has been used for over 70 years to treat skin cancer, psoriasis, and vitiligo. Recently, to expand its use beyond external treatment, a novel therapeutic called X-PACT (X-ray psoralen activated cancer therapy) was created to treat internal tumors. A combination of 8-methoxypsoralen and phosphors that convert low doses of x-ray radiation to ultraviolet (UV) light are injected into solid tumors and subsequently activated by x-ray photons with considerable antineoplastic effect. Notably, canine clinical trials have observed significant abscopal effects of X-PACT therapy on metastatic lesions throughout patients, but the immunomodulatory mechanisms of action are unclear (Nolan et al, in submission). Here, we present preliminary data investigating the immune response to X-PACT therapy in a murine soft tissue sarcoma (STS) model. METHODS: Six mice of the inducible KrasG12D/+; p53flox/flox (KP) murine STS model with palpable, gastrocnemius tumors were used in this initial study. Four mice underwent treatment with X-PACT. In this group, psoralen was mixed with energy converters and injected into the tumor. The mice then received low-level radiation to activate the drug. Treatment was performed five times over a 15-day period and the animals were sacrificed within 48 hours of final treatment. The other two mice with induced tumors received no treatment prior to sacrifice. For both groups, a cardiac blood draw was performed at the time of sacrifice to obtain plasma serum for analysis. Luminex xMAP technology was used for multiplexed quantification of 45 mouse cytokines, chemokines and growth factors. RESULTS: There were five markers that showed significantly different levels between the treated and control groups. Results indicated significantly higher (p = 0.006) plasma concentrations of macrophage derived chemokine (MDC) following five rounds of treatment with X-PACT therapy. Additionally, the treated mice displayed significantly lower concentrations of granulocyte colony-stimulating factor (G-CSF, p = 0.003), eotaxin (p = 0.016), tissue inhibitor of matrix metalloproteinase 1 (TIMP1, p = 0.024), and interleukin-1β (IL-1β, p = 0.033) compared to untreated mice with STS. CONCLUSION: In humans, MDC levels are associated with longer survival and lower cancer severity. G-CSF, eotaxin, TIMP1, and IL-1β are upregulated in cancer patients and correlate with disease severity. Together, the lower concentrations of G-CSF, Eotaxin, TIMP1, and IL-1β suggest a softening of cancer severity following X-PACT treatment. Further studies and larger sample sizes are necessary to confirm and expand upon these preliminary findings. Citation Format: Beatrice Schleupner, Alexandra Hunter Aitchison, Elle MacAlpine, Nicole Cantor, Jason Somarelli, Brian Brigman, Julia Visgauss, Michael Monument, William Eward. Exploring the x-ray psoralen activated cancer therapy mechanism of action in a genetically engineered mouse model of soft tissue sarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6642.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".