Empowering chemotherapy-induced antitumor immunity by multi-targeted synergistic combination nanomedicine for triple-negative breast cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Triple negative breast cancer (TNBC) is an aggressive malignancy characterized by early recurrence, high metastatic burden, and resistance to conventional therapies, largely due to the absence of targetable receptors and an immunosuppressive tumor microenvironment. To address these limitations, our lab has engineered a multifunctional nanotherapeutic system iRGD-DOX-oHA-PLN comprising polymer-lipid nanoparticles co-loaded with doxorubicin (DOX) and oligomeric hyaluronic acid (oHA) and functionalized with the tumor-penetrating integrin-targeting iRGD peptide. This rationally designed platform capitalizes on the sequential targeting mechanism: integrin-mediated tumor penetration and endocytosis via iRGD, followed by CD44 engagement through oHA to enhance intracellular drug delivery and suppresses cell motility. iRGD-DOX-oHA-PLN significantly improved cellular uptake, intratumoral accumulation, and cytotoxic efficacy in TNBC cells and tumor. Notably, it enhanced immunogenic cell death, characterized by increased calreticulin exposure, ATP and HMGB1 levels, triggering potent anti-tumor immune responses. Intravenous treatment led to elevated CD8 + T-cell infiltration, granzyme B expression, and secretion of pro-inflammatory cytokines (TNF-α, IFN-γ), while concurrently suppressing immunosuppressive mediators including IL-6, regulatory T cells, and tumor-associated macrophages. Over a four-week treatment period, iRGD-DOX-oHA-PLN effectively inhibited primary tumor growth and systemic pulmonary metastases in a syngeneic orthotopic TNBC mouse model. These findings demonstrate the therapeutic potential of simultaneously targeting integrin-CD44 signaling and the immunosuppressive niche using a dual-functional nanomedicine to overcome drug resistance and immune evasion in TNBC, offering a promising strategy for metastatic cancer intervention.
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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 | 0.000 | 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 | 0.000 |
| 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