A Unique Approach: Biomimetic Graphdiyne-Based Nanoplatform to Treat Prostate Cancer by Combining Cuproptosis and Enhanced Chemodynamic Therapy.

Purpose: Current treatment approaches for Prostate cancer (PCa) often come with debilitating side effects and limited therapeutic outcomes. There is urgent need for an alternative effective and safe treatment for PCa. Methods: We developed a nanoplatform to target prostate cancer cells based on graphdiyne (GDY) and a copper-based metal-organic framework (GDY-CuMOF), that carries the chemotherapy drug doxorubicin (DOX) for cancer treatment. Moreover, to provide GDY-CuMOF@DOX with homotypic targeting capability, we coated the PCa cell membrane (DU145 cell membrane, DCM) onto the surface of GDY-CuMOF@DOX, thus obtaining a biomimetic nanoplatform (DCM@GDY-CuMOF@DOX). The nanoplatform was characterized by using transmission electron microscope, atomic force microscope, X-ray diffraction, etc. Drug release behavior, antitumor effects in vivo and in vitro, and biosafety of the nanoplatform were evaluated. Results: We found that GDY-CuMOF exhibited a remarkable capability to load DOX mainly through π-conjugation and pore adsorption, and it responsively released DOX and generated Cu+ in the presence of glutathione (GSH). In vivo experiments demonstrated that this nanoplatform exhibits remarkable cell-killing efficiency by generating lethal reactive oxygen species (ROS) and mediating cuproptosis. In addition, DCM@GDY-CuMOF@DOX effectively suppresses tumor growth in vivo without causing any apparent side effects. Conclusion: The constructed DCM@GDY-CuMOF@DOX nanoplatform integrates tumor targeting, drug-responsive release and combination with cuproptosis and chemodynamic therapy, offering insights for further biomedical research on efficient PCa treatment.

FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to the HIF2α blockade by facilitating LDHA phosphorylation.

Renal cell carcinoma (RCC) is one of the three major malignant tumors of the urinary system and originates from proximal tubular epithelial cells. Clear cell renal cell carcinoma (ccRCC) accounts for approximately 80% of RCC cases and is recognized as a metabolic disease driven by genetic mutations and epigenetic alterations. Through bioinformatic analysis, we found that FK506 binding protein 10 (FKBP10) may play an essential role in hypoxia and glycolysis pathways in ccRCC progression. Functionally, FKBP10 promotes the proliferation and metastasis of ccRCC in vivo and in vitro depending on its peptidyl-prolyl cis-trans isomerase (PPIase) domains. Mechanistically, FKBP10 binds directly to lactate dehydrogenase A (LDHA) through its C-terminal region, the key regulator of glycolysis, and enhances the LDHA-Y10 phosphorylation, which results in a hyperactive Warburg effect and the accumulation of histone lactylation. Moreover, HIFα negatively regulates the expression of FKBP10, and inhibition of FKBP10 enhances the antitumor effect of the HIF2α inhibitor PT2385. Therefore, our study demonstrates that FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to HIF2α blockade by facilitating LDHA phosphorylation, which may be exploited for anticancer therapy.

Molecular predictors of metastasis in patients with prostate cancer.

INTRODUCTION: Prostate cancer is a serious threat to the health of older adults worldwide. The quality of life and survival time of patients sharply decline once metastasis occurs. Thus, early screening for prostate cancer is very advanced in developed countries. The detection methods used include Prostate-specific antigen (PSA) detection and digital rectal examination. However, the lack of universal access to early screening in some developing countries has resulted in an increased number of patients presenting with metastatic prostate cancer. In addition, the treatment methods for metastatic and localized prostate cancer are considerably different. In many patients, early-stage prostate cancer cells often metastasize due to delayed observation, negative PSA results, and delay in treatment time. Therefore, the identification of patients who are prone to metastasis is important for future clinical studies. AREAS COVERED: this review introduced a large number of predictive molecules related to prostate cancer metastasis. These molecules involve the mutation and regulation of tumor cell genes, changes in the tumor microenvironment, and the liquid biopsy. EXPERT OPINION: In next decade, PSMA PET/CT and liquid biopsy will be the excellent predicting tools, while 177 Lu- PSMA-RLT will be showed excellent anti-tumor efficacy in mPCa patients.

Ferrocene-Based Polymeric Nanoparticles Carrying Doxorubicin for Oncotherapeutic Combination of Chemotherapy and Ferroptosis.

Mono-chemotherapy has significant side effects and unsatisfactory efficacy, limiting its clinical application. Therefore, a combination of multiple treatments is becoming more common in oncotherapy. Chemotherapy combined with the induction of ferroptosis is a potential new oncotherapy. Furthermore, polymeric nanoparticles (NPs) can improve the antitumor efficacy and decrease the toxicity of drugs. Herein, a polymeric NP, mPEG-b-PPLGFc@Dox, is synthesized to decrease the toxicity of doxorubicin (Dox) and enhance the efficacy of chemotherapy by combining it with the induction of ferroptosis. First, mPEG-b-PPLGFc@Dox is oxidized by endogenous H2 O2 and releases Dox, which leads to an increase of H2 O2 by breaking the redox balance. The Fe(II) group of ferrocene converts H2 O2 into ·OH, inducing subsequent ferroptosis. Furthermore, glutathione peroxidase 4, a biomarker of ferroptosis, is suppressed and the lipid peroxidation level is elevated in cells incubated with mPEG-b-PPLGFc@Dox compared to those treated with Dox alone, indicating ferroptosis induction by mPEG-b-PPLGFc@Dox. In vivo, the antitumor efficacy of mPEG-b-PPLGFc@Dox is higher than that of free Dox. Moreover, the loss of body weight in mice treated mPEG-b-PPLGFc@Dox is lower than in those treated with free Dox, indicating that mPEG-b-PPLGFc@Dox is less toxic than free Dox. In conclusion, mPEG-b-PPLGFc@Dox not only has higher antitumor efficacy but it reduces the damage to normal tissue.

Untargeted metabolomics reveals alterations in the metabolic reprogramming of prostate cancer cells by double-stranded DNA-modified gold nanoparticles.

Metabolic reprogramming plays an important role in the development of prostate cancer (PCa). However, there are few reports on the effects of nanomaterials as vectors on cancer metabolic reprogramming. Herein, a type of nanoparticle with good biocompatibility was synthesized by modifying the double-stranded of DNA containing a sulfhydryl group on the surface of gold nanoparticles (AuNPs-dsDNA) through salt-aging conjugation methods. The resultant AuNPs-dsDNA complexes possessed low toxicity to PC3 and DU145 cells in vitro. There was also no obvious hepatorenal toxicity after intravenous injection of AuNPs-dsDNA complexes in vivo, which indicated that these nanoparticles had good biological compatibilities. We investigated their biological functions using prostate cancer cells. Seahorse assay showed that AuNPs-dsDNA complexes could increase glycolysis and glycolysis capacity both in PC3 and DU145 cells. We further detected the expression of glycolysis-related genes by qPCR assay, and found that PKM2, PDHA, and LDHA were significantly upregulated. Furthermore, untargeted metabolomics revealed that PC (18:2(9Z,12Z)/18:2(9Z,12Z)) and PC (18:0/18:2 (9Z,12Z)) levels were decreased and inosinic acid level was increased in PC3 cells. Whereas (3S,6E,10E)-1,6,10,14-Phytatetraen-3-ol, Plasmenyl-PE 36:5 and Cer (d18:2/18:2) were decreased, PE 21:3 and 1-pyrrolidinecarboxaldehyde were increased in DU145 cells after co-culturing with AuNPs-dsDNA. In summary, we found that AuNPs and AuNPs-dsDNA complexes possibly regulate the metabolic reprogramming of cancer cells mainly through the lipid metabolic pathways, which could compensate for the previously mentioned phenomenon of enhanced glycolysis and glycolysis capacity. This will provide an important theoretical basis for our future research on the characteristic targeted design of nanomaterials for cancer metabolism.

Identification and Validation of a PPP1R12A-Related Five-Gene Signature Associated With Metabolism to Predict the Prognosis of Patients With Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is the most common malignant male neoplasm in the American male population. Our prior studies have demonstrated that protein phosphatase 1 regulatory subunit 12A (PPP1R12A) could be an efficient prognostic factor in patients with PCa, promoting further investigation. The present study attempted to construct a gene signature based on PPP1R12A and metabolism-related genes to predict the prognosis of PCa patients. METHODS: The mRNA expression profiles of 499 tumor and 52 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. We selected differentially expressed PPP1R12A-related genes among these mRNAs. Tandem affinity purification-mass spectrometry was used to identify the proteins that directly interact with PPP1R12A. Gene set enrichment analysis (GSEA) was used to extract metabolism-related genes. Univariate Cox regression analysis and a random survival forest algorithm were used to confirm optimal genes to build a prognostic risk model. RESULTS: We identified a five-gene signature (PPP1R12A, PTGS2, GGCT, AOX1, and NT5E) that was associated with PPP1R12A and metabolism in PCa, which effectively predicted disease-free survival (DFS) and biochemical relapse-free survival (BRFS). Moreover, the signature was validated by two internal datasets from TCGA and one external dataset from the Gene Expression Omnibus (GEO). CONCLUSION: The five-gene signature is an effective potential factor to predict the prognosis of PCa, classifying PCa patients into high- and low-risk groups, which might provide potential novel treatment strategies for these patients.

The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries.

Several pilot experiments have indicated that improvements in older NMR structures can be expected by applying modern software and new protocols (Nabuurs et al. in Proteins 55:483-186, 2004; Nederveen et al. in Proteins 59:662-672, 2005; Saccenti and Rosato in J Biomol NMR 40:251-261, 2008). A recent large scale X-ray study also has shown that modern software can significantly improve the quality of X-ray structures that were deposited more than a few years ago (Joosten et al. in J. Appl Crystallogr 42:376-384, 2009; Sanderson in Nature 459:1038-1039, 2009). Recalculation of three-dimensional coordinates requires that the original experimental data are available and complete, and are semantically and syntactically correct, or are at least correct enough to be reconstructed. For multiple reasons, including a lack of standards, the heterogeneity of the experimental data and the many NMR experiment types, it has not been practical to parse a large proportion of the originally deposited NMR experimental data files related to protein NMR structures. This has made impractical the automatic recalculation, and thus improvement, of the three dimensional coordinates of these structures. We here describe a large-scale international collaborative effort to make all deposited experimental NMR data semantically and syntactically homogeneous, and thus useful for further research. A total of 4,014 out of 5,266 entries were 'cleaned' in this process. For 1,387 entries, human intervention was needed. Continuous efforts in automating the parsing of both old, and newly deposited files is steadily decreasing this fraction. The cleaned data files are available from the NMR restraints grid at http://restraintsgrid.bmrb.wisc.edu .

BioMagResBank.

The BioMagResBank (BMRB: www.bmrb.wisc.edu) is a repository for experimental and derived data gathered from nuclear magnetic resonance (NMR) spectroscopic studies of biological molecules. BMRB is a partner in the Worldwide Protein Data Bank (wwPDB). The BMRB archive consists of four main data depositories: (i) quantitative NMR spectral parameters for proteins, peptides, nucleic acids, carbohydrates and ligands or cofactors (assigned chemical shifts, coupling constants and peak lists) and derived data (relaxation parameters, residual dipolar couplings, hydrogen exchange rates, pK(a) values, etc.), (ii) databases for NMR restraints processed from original author depositions available from the Protein Data Bank, (iii) time-domain (raw) spectral data from NMR experiments used to assign spectral resonances and determine the structures of biological macromolecules and (iv) a database of one- and two-dimensional (1)H and (13)C one- and two-dimensional NMR spectra for over 250 metabolites. The BMRB website provides free access to all of these data. BMRB has tools for querying the archive and retrieving information and an ftp site (ftp.bmrb.wisc.edu) where data in the archive can be downloaded in bulk. Two BMRB mirror sites exist: one at the PDBj, Protein Research Institute, Osaka University, Osaka, Japan (bmrb.protein.osaka-u.ac.jp) and the other at CERM, University of Florence, Florence, Italy (bmrb.postgenomicnmr.net/). The site at Osaka also accepts and processes data depositions.

BioMagResBank databases DOCR and FRED containing converted and filtered sets of experimental NMR restraints and coordinates from over 500 protein PDB structures.

We present two new databases of NMR-derived distance and dihedral angle restraints: the Database Of Converted Restraints (DOCR) and the Filtered Restraints Database (FRED). These databases currently correspond to 545 proteins with NMR structures deposited in the Protein Databank (PDB). The criteria for inclusion were that these should be unique, monomeric proteins with author-provided experimental NMR data and coordinates available from the PDB capable of being parsed and prepared in a consistent manner. The Wattos program was used to parse the files, and the CcpNmr FormatConverter program was used to prepare them semi-automatically. New modules, including a new implementation of Aqua in the BioMagResBank (BMRB) software Wattos were used to analyze the sets of distance restraints (DRs) for inconsistencies, redundancies, NOE completeness, classification and violations with respect to the original coordinates. Restraints that could not be associated with a known nomenclature were flagged. The coordinates of hydrogen atoms were recalculated from the positions of heavy atoms to allow for a full restraint analysis. The DOCR database contains restraint and coordinate data that is made consistent with each other and with IUPAC conventions. The FRED database is based on the DOCR data but is filtered for use by test calculation protocols and longitudinal analyses and validations. These two databases are available from websites of the BMRB and the Macromolecular Structure Database (MSD) in various formats: NMR-STAR, CCPN XML, and in formats suitable for direct use in the software packages CNS and CYANA.