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Calinescu, A.

Publications and source records attributed to Calinescu, A..

2 recordsLinked to original sources

Systemic delivery of a CXCR4-CXCL12 signaling inhibitor encapsulated in synthetic protein nanoparticles for glioma immunotherapy

Glioblastoma multiforme (GBM) is an aggressive primary brain tumor, with poor prognosis. Major obstacles hampering effective therapeutic response in GBM are tumor heterogeneity, high infiltration of immunosuppressive myeloid cells, and the presence of the blood-brain barrier. The C-X-C Motif Chemokine Ligand 12/ C-X-C Motif Chemokine Receptor 4 (CXCL12/ CXCR4) signaling pathway is implicated in GBM invasion and cell cycle progression. While the CXCR4 antagonists (AMD3100) has a potential anti-GBM effects, its poor pharmacokinetic and systemic toxicity had precluded its clinical application. Moreover, the role of CXCL12/ CXCR4 signaling pathway in anti-GBM immunity, particularly in GBM-mediated immunosuppression has not been elucidated. Here, we developed a synthetic protein nanoparticle (SPNPs) coated with the cell-penetrating peptide iRGD (AMD3100 SPNPs) to target the CXCR4/CXCL12 signaling axis in GBM. We showed that AMD3100 SPNPs effectively blocked CXCR4 signaling in mouse and human GBM cells in vitro as well as in GBM model in vivo. This results in inhibition of GBM proliferation and induction of immunogenic tumor cell death (ICD) leading to inhibition of GBM progression. Our data also demonstrate that blocking CXCR4 sensitizes GBM cells to radiation, eliciting enhanced release of ICD ligands. Combining AMD3100 SPNPs with radiotherapy inhibited GBM progression and led to long-term survival; with 60% of mice remaining tumor-free. This was accompanied by an anti-GBM immune response and sustained immunological memory that prevented tumor recurrence without further treatment. Finally, we showed that systemic delivery of AMD3100 SPNPs decreased the infiltration of CXCR4+ monocytic myeloid-derived suppressor cells to the tumor microenvironment. With the potent ICD induction and reprogrammed immune microenvironment, this strategy has significant potential for future clinical translation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/457953v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@17c9377org.highwire.dtl.DTLVardef@1b5a4dcorg.highwire.dtl.DTLVardef@5aa4eaorg.highwire.dtl.DTLVardef@1011a86_HPS_FORMAT_FIGEXP M_FIG Immunological mechanism targeting Glioblastoma (GBM) upon blocking CXCR4 signaling pathway with AMD3100-conjugated nanoparticles (SPNPs). (1) Radiotherapy induces glioma cell death, followed by Damage-associated molecular patterns (DAMPs) release. Dendritic cells (DC) are activated by DAMPs and migrate to the regional lymph node where they prime cytotoxic T lymphocyte immune response. Tumor-specific cytotoxic T cells infiltrate the tumor and attack glioma cells. (2) Glioma cells express CXCR4, as well its ligand CXCL12. CXCL12 induces glioma cell proliferation and, (3) as well as mobilization in the bone marrow of CXCR4 expressing myeloid MDSC, which will infiltrate the tumor, and inhibit tumor-specific cytotoxic T cells activity. GEMM of glioma when treated systemically with SPNPs AMD3100 SPNPs plus radiation, nanoparticles block the interaction between CXCR4 and CXCL12, thus (4) inhibiting glioma cell proliferation and (5) reducing mobilization in the bone marrow of CXCR4 expressing myeloid MDSC, (6) generating a reduced MDSC tumor infiltration, as well as releasing MDSC inhibition over tumor specific cytotoxic T cell response. C_FIG

cell biology

feamiR: Feature selection based on Genetic Algorithms for predicting miRNA-mRNA interactions

microRNAs play a key role in RNA interference, the sequence-driven targeting of mRNAs that regulates their translation to proteins, through translation inhibition or the degradation of the mRNA. Around ~ 30% of animal genes may be tuned by microRNAs. The prediction of miRNA/mRNA interactions is hindered by the short length of the interaction (seed) region (~7- 8nt). We collate several large datasets overviewing validated interactions and propose feamiR, a novel pipeline comprising optimised classification approaches (Decision Trees/Random Forests and an efficient feature selection based on embryonic Genetic Algorithms used in conjunction with Support Vector Machines) aimed at identifying discriminative nucleotide features, on the seed, compensatory and flanking regions, that increase the prediction accuracy for interactions. Common and specific combinations of features illustrate differences between reference organisms, validation techniques or tissue/cell localisation. feamiR revealed new key positions that drive the miRNA/mRNA interactions, leading to novel questions on the mode-of-action of miRNAs.

bioinformatics