Abstract A037: Prostate Specific Membrane Antigen Targeted Photodynamic Therapy Agent for the Treatment of Breast Cancer
Bibliographic record
Abstract
Abstract Introduction: Breast cancer (BCa) is a solid cancer where 65% of all BCa cases, women with stages 1-3 of BCa undergoing Breast Conserving Surgery (BCS) as the primary form of treatment with incomplete resections occurring in 20-60% of BCS leading to repeat procedures[1]. Local recurrence, an indication of “surgically missed” cancerous tissues, occurs in 5-16% of patients with clean margins [1], indicating regions of tumor not resected during analysis of excised tissues. This demonstrates an unmet clinical need for technologies to identify and destroy cancerous tissues in the margins of BCa specimens. Prostate Specific Membrane Antigen (PSMA) is known to be overexpressed in prostate cancer and on the neovasculature of many solid human tumors, including breast tumors [2]. Photodynamic therapy (PDT) is a minimally invasive phototherapy used in the treatment of cancers and other diseases. Previously, we combined a potent Photodynamic Therapy (PDT) agent and highly selective PSMA ligand invented in our lab, to develop a theranostic agent to selectively identify and destroy prostate cancer (PCa) [3]. We have characterized PSMA expression in BCa tumor neovascualture in our novel syngeneic mouse model and show how PSMA-1-Pc413 is an effective strategy in visualizing and treating BCa tumors. Methods: 20 female BALB/c mice were inoculated with 10,000 4T1 – i.e., metastatic mouse cancer cell line – via injection into the mammary pads to create a syngeneic mouse model. We allowed the tumors to grow till an average of 50mm3. Mice were randomly separated into 3 treatment groups based on PSMA-1-Pc413 and PDT irradiation dose, a combination of 0.75mg/kg or 1.0mg/kg at 100Jcm−2 or 150Jcm−2. A 4th control group that received PBS irradiated with 150jcm−2 of light. PSMA-1-Pc413 was injected via tail vein and fluorescence images were taken till 24hr. 24hours post-injection, we irradiated the tumors at the given dose with a 672 nm laser. Tumor growth was tracked via calipers. The endpoint was 28days after treatment. Mice were euthanized, and their lung nodules quantified through counting. Results: Fluorescence images of a representative mouse from the group show positive accumulation of probe within the tumor which was subsequently bleached after PDT treatment, signified by a dark area. Compared to our control group, we see a significant reduction in tumor growth rate with all 5 mice in each of the treatment groups surviving longer than the control group. Groups that received a higher dose of agent and irradiation showed further improved response. Additionally, after euthanizing animals 4 weeks after PDT treatment and quantifying lung nodules we can see a significant decrease in lung metastases which contributes to improved survival outcomes. Conclusions: From the results provided that PSMA can be used as an in vivo target for treating Breast Cancer and that our PSMA-1-Pc413 agent is effective in non-prostatic cancer models. Even a single dose of PDT with our agent has significant impact in reducing tumor growth rate and lung metastases formation. Citation Format: Aditi A Shirke, Xinning Wang, James P Basilion. Prostate Specific Membrane Antigen Targeted Photodynamic Therapy Agent for the Treatment of Breast Cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A037.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".