Dynamic regulation of drug biodistribution by turning tumors into decoys for biomimetic nanoplatform to enhance the chemotherapeutic efficacy of breast cancer with bone metastasis

Breast cancer with bone metastasis accounts for serious cancer-associated pain which significantly reduces the quality of life of affected patients and promotes cancer progression. However, effective treatment using nanomedicine remains a formidable challenge owing to poor drug delivery efficiency to multiple cancer lesions and inappropriate management of cancer-associated pain. In this study, using engineered macrophage membrane (EMM) and drugs loaded nanoparticle, we constructed a biomimetic nanoplatform (EMM@DJHAD) for the concurrent therapy of bone metastatic breast cancer and associated pain. Tumor tropism inherited from EMM provided the targeting ability for both primary and metastatic lesions. Subsequently, the synergistic combination of decitabine and JTC801 boosted the lytic and inflammatory responses accompanied by a tumoricidal effect, which transformed the tumor into an ideal decoy for EMM, resulting in prolonged troop migration toward tumors. EMM@DJHAD exerted significant effects on tumor suppression and a pronounced analgesic effect by inhibiting µ-opioid receptors in bone metastasis mouse models. Moreover, the nanoplatform significantly reduced the severe toxicity induced by chemotherapy agents. Overall, this biomimetic nanoplatform with good biocompatibility may be used for the effective treatment of breast cancer with bone metastasis.

Identification of hub genes for early detection of bone metastasis in breast cancer

BACKGROUND

Globally, among all women, the most frequently detected and diagnosed and the most lethal type of cancer is breast cancer (BC). In particular, bone is one of the most frequent distant metastases 24in breast cancer patients and bone metastasis arises in approximately 80% of advanced patients. Thus, we need to identify and validate early detection markers that can differentiate metastasis from non-metastasis breast cancers.

METHODS

GSE55715, GSE103357, and GSE146661 gene expression profiling data were downloaded from the GEO database. There was 14 breast cancer with bone metastasis samples and 8 breast cancer tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). The volcano plots, Venn diagrams, and annular heatmap were generated by using the ggplot2 package. By using the cluster Profiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, K-M survival and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 143 DEGs were enriched in the following GO terms: extracellular structure organization, extracellular matrix organization, leukocyte migration class II protein complex, collagen tridermic protein complex, extracellular matrix structural constituent, growth factor binding, and platelet-derived growth factor binding. In the KEGG pathway enrichment analysis, DEGs were enriched in Staphylococcus aureus infection, Complement and coagulation cascades, and Asthma. By PPI network analysis, we selected the top 10 genes, including SLCO2B1, STAB1, SERPING1, HLA-DOA, AIF1, GIMAP4, C1orf162, HLA-DMB, ADAP2, and HAVCR2. By using TCGA and THPA databases, we validated 2 genes, SERPING1 and GIMAP4, that were related to the early detection of bone metastasis in BC.

CONCLUSIONS

2 abnormally expressed hub genes could play a pivotal role in the breast cancer with bone metastasis by affecting bone homeostasis imbalance in the bone microenvironment.