Related Experiment Video
Updated: Jan 20, 2026

A Mouse Model to Investigate the Role of Cancer-Associated Fibroblasts in Tumor Growth
Published on: December 22, 2020
Integrating Proteomics and Predictive Model: Elucidating the Role of Aminated Nanodiamonds in Suppressing Prostate
Wenjie Xie1, Qianfeng Xu1, Zeheng Tan1
1Department of Urology, the Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou 510180, China.
Abstract:
Prostate cancer (PCa) presents a formidable therapeutic challenge owing to the limited efficacy of existing treatments. In this study, a series of comparative experiments demonstrated that nanodiamonds (NDs) with different functional groups exhibit inhibitory effects on the growth, replication, and migration of prostate cancer cells without directly killing the cells. Among them, aminated nanodiamonds (aNDs) showed the most pronounced inhibitory activity. Subsequently, a combination of proteomics analysis and machine learning was employed to elucidate the molecular mechanisms by which these aNDs exerted their inhibitory effects on PCa progression. Data-independent acquisition proteomics identified the key proteins affected by the aNDs, and the Kyoto Encyclopedia of Genes and Genomes analysis revealed ribosome pathway enrichment. Bioinformatics analysis focused on ten crucial genes, thus incorporating a novel prognostic model that categorized patients based on gene expression and emphasized the significance of mitochondrial ribosomal protein L22 (MRPL22). In vivo experiments confirmed the antitumor effects and biocompatibility of the aNDs. In addition, an analysis of the response of MRPL22 to anticancer drugs in public databases revealed its relevance to a range of drugs and compounds. In summary, this study integrated diverse interdisciplinary methodologies, thereby offering insights into the mechanism of the inhibition of PCa by the aNDs and the regulatory role of MRPL22 in the ribosomal pathway.
Insights
Aminated nanodiamonds (aNDs) inhibit prostate cancer (PCa) cell growth and migration by affecting the ribosome pathway. A novel prognostic model highlights mitochondrial ribosomal protein L22 (MRPL22) as a key factor in PCa progression.
Area of Science:
- Nanomedicine
- Cancer Biology
- Proteomics
Background:
- Prostate cancer (PCa) poses significant treatment challenges due to limited therapeutic options.
- Nanodiamonds (NDs) are explored for their potential in cancer therapy.
- Understanding the molecular mechanisms of NDs in PCa is crucial for therapeutic development.
Purpose of the Study:
- To investigate the inhibitory effects of functionalized nanodiamonds on prostate cancer cells.
- To elucidate the molecular mechanisms underlying the anti-prostate cancer effects of aminated nanodiamonds (aNDs).
- To develop a novel prognostic model for PCa based on gene expression.
Main Methods:
- Comparative experiments with nanodiamonds (NDs) bearing different functional groups.
- Proteomics analysis (data-independent acquisition) to identify proteins affected by aNDs.
- Bioinformatics analysis, including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and machine learning for prognostic model development.
- In vivo studies to evaluate antitumor effects and biocompatibility of aNDs.
Main Results:
- Aminated nanodiamonds (aNDs) demonstrated the most significant inhibition of PCa cell growth, replication, and migration without direct cytotoxicity.
- Proteomics and KEGG analysis revealed enrichment in the ribosome pathway.
- A novel prognostic model identified mitochondrial ribosomal protein L22 (MRPL22) as a key gene, with its expression correlating with patient prognosis.
- In vivo studies confirmed the antitumor efficacy and biocompatibility of aNDs.
Conclusions:
- Aminated nanodiamonds (aNDs) represent a promising therapeutic strategy for inhibiting prostate cancer progression.
- The study elucidates the mechanism involving the ribosome pathway and highlights MRPL22 as a critical regulator and potential therapeutic target in PCa.
- Integrated multi-omics and machine learning approaches provide valuable insights into PCa mechanisms and drug response.
Related Concept Videos
06:35A Mouse Model to Investigate the Role of Cancer-Associated Fibroblasts in Tumor Growth
06:48An Orthotopic Murine Model of Human Prostate Cancer Metastasis
05:07Intra-prostatic Injection of Cancer Cells: A Technique to Deliver Cancer Cells for Establishing Orthotopic Prostate Cancer Mouse Model
07:01Pre-clinical Orthotopic Murine Model of Human Prostate Cancer
08:03Generation of Prostate Cancer Patient Derived Xenograft Models from Circulating Tumor Cells
04:20Knockdown of FAM83A to Verify Its Role in Cervical Cancer Cell Growth and Cisplatin Sensitivity

