Development of a Poly(<scp>d</scp>,<scp>l</scp>-lactic-<i>co</i>-glycolic acid) Nanoparticle Formulation of STAT3 Inhibitor JSI-124: Implication for Cancer Immunotherapy
Why this work is in the frame
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Bibliographic record
Abstract
Constitutively activated signal transducer and activator of transcription-3 (STAT3) in tumor and dendritic cells (DCs) plays a critical role in tumor-induced immunosuppression. This is considered a major challenge in effective immunotherapy of cancer. Herein we describe the development of a polymeric nanocarrier for the delivery of JSI-124 (a small molecule inhibitor of STAT3) to tumor and immunosuppressed DCs using poly(d,l-lactic-co-glycolic acid) nanoparticles (PLGA NPs). For this purpose, JSI-124 was chemically conjugated to PLGA and the PLGA-JSI-124 conjugate was formulated into nanoparticles using the emulsification solvent evaporation method. The attachment of JSI-124 to PLGA was confirmed by a combination of thin layer chromatography and (1)H NMR. The level of JSI-124 in NPs, determined by liquid chromatography-mass spectrometry, was found to be 1.7 +/- 0.3 microg per mg of PLGA. The PLGA-JSI-124 NPs demonstrated a controlled drug release profile over a 1-month period and exhibited potent anticancer and STAT3 inhibitory activity comparable to the soluble JSI-124 after 24 h incubation with B16 melanoma cells, in vitro. Moreover, PLGA-JSI-124 NPs efficiently suppressed the level of p-STAT3 in p-STAT3(high) DCs, generated from mouse bone marrow cells in the presence of conditioned media of B16 cells (B16CM-DCs), and improved their function as assessed by mixed lymphocyte reaction (MLR). Specifically cotreatment of B16CM-DCs with PLGA-JSI-124 NPs and PLGA NPs containing the DC adjuvant CpG resulted in higher levels of T cell proliferation in the MLR assay compared with B16CM-DCs untreated or treated with either CpG NPs or JSI-124 NPs alone. Our results indicate that PLGA NPs containing conjugated JSI-124 can potentially provide a useful platform for sustained JSI-124 release in tumor and its targeted delivery to DCs leading to the modulation of anticancer response by JSI-124 in tumor cells and immunosuppressed DCs, in vitro.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it