Cell Membrane‐Camouflaged Chitosan‐Polypyrrole Nanogels Co‐Deliver Drug and Gene for Targeted Chemotherapy and Bone Metastasis Inhibition of Prostate Cancer

Yu, Qiuyu; Gao, Yue; Dai, Waicong; Li, Danni; Zhang, Lu; Hameed, Meera Moydeen Abdul; Guo, Rui; Liu, Min; Shi, Xiangyang; Cao, Xueyan

doi:10.1002/adhm.202400114

Cited by 3 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PRAD is a highly aggressive tumor with a poor prognosis, often being detected in advanced stages with metastasis ( 33 ). Biomarkers are essential in evaluating the therapeutic efficacy and prognosis of tumors and can be an essential component of precision medicine ( 34 ).…”

Section: Discussionmentioning

confidence: 99%

Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy

Wang,

Li,

et al. 2024

Front. Immunol.

View full text Add to dashboard Cite

BackgroundMonocytes play a critical role in tumor initiation and progression, with their impact on prostate adenocarcinoma (PRAD) not yet fully understood. This study aimed to identify key monocyte-related genes and elucidate their mechanisms in PRAD.MethodUtilizing the TCGA-PRAD dataset, immune cell infiltration levels were assessed using CIBERSORT, and their correlation with patient prognosis was analyzed. The WGCNA method pinpointed 14 crucial monocyte-related genes. A diagnostic model focused on monocytes was developed using a combination of machine learning algorithms, while a prognostic model was created using the LASSO algorithm, both of which were validated. Random forest and gradient boosting machine singled out CCNA2 as the most significant gene related to prognosis in monocytes, with its function further investigated through gene enrichment analysis. Mendelian randomization analysis of the association of HLA-DR high-expressing monocytes with PRAD. Molecular docking was employed to assess the binding affinity of CCNA2 with targeted drugs for PRAD, and experimental validation confirmed the expression and prognostic value of CCNA2 in PRAD.ResultBased on the identification of 14 monocyte-related genes by WGCNA, we developed a diagnostic model for PRAD using a combination of multiple machine learning algorithms. Additionally, we constructed a prognostic model using the LASSO algorithm, both of which demonstrated excellent predictive capabilities. Analysis with random forest and gradient boosting machine algorithms further supported the potential prognostic value of CCNA2 in PRAD. Gene enrichment analysis revealed the association of CCNA2 with the regulation of cell cycle and cellular senescence in PRAD. Mendelian randomization analysis confirmed that monocytes expressing high levels of HLA-DR may promote PRAD. Molecular docking results suggested a strong affinity of CCNA2 for drugs targeting PRAD. Furthermore, immunohistochemistry experiments validated the upregulation of CCNA2 expression in PRAD and its correlation with patient prognosis.ConclusionOur findings offer new insights into monocyte heterogeneity and its role in PRAD. Furthermore, CCNA2 holds potential as a novel targeted drug for PRAD.

show abstract

Section: Discussionmentioning

confidence: 99%

Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy

Wang,

Li,

et al. 2024

Front. Immunol.

View full text Add to dashboard Cite

show abstract

Docetaxel‐Encapsulated Catalytic Pt/Au Nanotubes for Synergistic Chemo‐Photothermal Therapy of Triple‐Negative Breast Cancer

Yang,

Zhang,

Dai

et al. 2024

Adv Healthcare Materials

View full text Add to dashboard Cite

The combination of photothermal therapy with chemotherapy has emerged as a promising therapeutic modality for addressing triple‐negative breast cancer (TNBC). This manuscript describes a novel hybrid nanoplatform comprising ultrathin catalytic platinum/gold (Pt/Au) nanotubes encapsulated with docetaxel and phase‐change materials (PCMs) for the photoacoustic imaging‐guided synergistic chemo‐photothermal therapy of TNBC. Upon irradiation of near‐infrared laser, the photothermal heating of nanotubes converts solid‐state PCM into liquid, triggering the controlled release of the encapsulated docetaxel. The thin Pt layer within nanotubes enhances the nanotube's thermal stability, thus prolonging the photothermal ablation of tumors. Furthermore, platinum effectively mitigates tumor hypoxia by catalyzing the decomposition of hydrogen peroxides to generate oxygen in the tumor microenvironment, thus improving the efficiency of chemotherapy. It is demonstrated that the drug‐loaded nanotubes achieve significant tumor inhibition rates of 75.4% in vivo on 4T1 tumor‐bearing mice, significantly surpassing control groups. These nanotubes also notably extend survival, attributable to the synergistic effects of prolonged photothermal therapy facilitated by platinum and oxygenation‐enhanced chemotherapy. This combination leverages the unique properties of the Pt/Au NTs‐DTX/PCM nanoplatform, optimizing therapeutic outcomes. It is envisioned that this nanoplatform may find important applications in managing superficial malignant solid tumors in general.

show abstract

Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy

Wang,

Ma,

et al. 2024

Front. Immunol.

View full text Add to dashboard Cite

BackgroundCancer stem cells (CSCs) are a subset of cells within tumors that possess the unique ability to self-renew and give rise to diverse tumor cells. These cells are crucial in driving tumor metastasis, recurrence, and resistance to treatment. The objective of this study was to pinpoint the essential regulatory genes associated with CSCs in prostate adenocarcinoma (PRAD) and assess their potential significance in the diagnosis, prognosis, and immunotherapy of patients with PRAD.MethodThe study utilized single-cell analysis techniques to identify stem cell-related genes and evaluate their significance in relation to patient prognosis and immunotherapy in PRAD through cluster analysis. By utilizing diverse datasets and employing various machine learning methods for clustering, diagnostic models for PRAD were developed and validated. The random forest algorithm pinpointed HSPE1 as the most crucial prognostic gene among the stem cell-related genes. Furthermore, the study delved into the association between HSPE1 and immune infiltration, and employed molecular docking to investigate the relationship between HSPE1 and its associated compounds. Immunofluorescence staining analysis of 60 PRAD tissue samples confirmed the expression of HSPE1 and its correlation with patient prognosis in PRAD.ResultThis study identified 15 crucial stem cell-related genes through single-cell analysis, highlighting their importance in diagnosing, prognosticating, and potentially treating PRAD patients. HSPE1 was specifically linked to PRAD prognosis and response to immunotherapy, with experimental data supporting its upregulation in PRAD and association with poorer prognosis.ConclusionOverall, our findings underscore the significant role of stem cell-related genes in PRAD and unveil HSPE1 as a novel target related to stem cell.

show abstract

Cell Membrane‐Camouflaged Chitosan‐Polypyrrole Nanogels Co‐Deliver Drug and Gene for Targeted Chemotherapy and Bone Metastasis Inhibition of Prostate Cancer

Cited by 3 publications

References 36 publications

Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy

Multi-omics analysis and experimental validation of the value of monocyte-associated features in prostate cancer prognosis and immunotherapy

Docetaxel‐Encapsulated Catalytic Pt/Au Nanotubes for Synergistic Chemo‐Photothermal Therapy of Triple‐Negative Breast Cancer

Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy

Contact Info

Product

Resources

About