Enhanced anti-tumor efficacy of electroporation (EP)-mediated DNA vaccine boosted by allogeneic lymphocytes in pre-established tumor models.

BACKGROUND: Tumor-reactive T cells play a crucial role in anti-tumor responses, but T cells induced by DNA vaccination are time-consuming processes and exhibit limited anti-tumor efficacy. Therefore, we evaluated the anti-tumor effectiveness of reactive T cells elicited by electroporation (EP)-mediated DNA vaccine targeting epidermal growth factor receptor variant III (pEGFRvIII plasmid), in conjunction with adoptive cell therapy (ACT), involving the transfer of lymphocytes from a pEGFRvIII EP-vaccinated healthy donor. METHODS: The validation of the established pEGFRvIII plasmid and EGFRvIII-positive cell model was confirmed through immunofluorescence and western blot analysis. Flow cytometry and cytotoxicity assays were performed to evaluate the functionality of antigen-specific reactive T cells induced by EP-mediated pEGFRvIII vaccines, ACT, or their combination. The anti-tumor effectiveness of EP-mediated pEGFRvIII vaccines alone or combined with ACT was evaluated in the B16F10-EGFRvIII tumor model. RESULTS: EP-mediated pEGFRvIII vaccines elicited serum antibodies and a robust cellular immune response in both healthy and tumor-bearing mice. However, this response only marginally inhibited early-stage tumor growth in established tumor models. EP-mediated pEGFRvIII vaccination followed by adoptive transfer of lymphocytes from vaccinated healthy donors led to notable anti-tumor efficacy, attributed to the synergistic action of antigen-specific CD4+ Th1 cells supplemented by ACT and antigen-specific CD8+ T cells elicited by the EP-mediated DNA vaccination. CONCLUSIONS: Our preclinical studies results demonstrate an enhanced anti-tumor efficacy of EP-mediated DNA vaccination boosted with adoptively transferred, vaccinated healthy donor-derived allogeneic lymphocytes.

Trends in research on nanomedicine in urologic cancer: a bibliometric and visualized analysis.

Increasing research efforts are focused on studying the synthesis and mechanisms of nanomedicine in urologic cancer. We performed a bibliometric study of the literature on nanomedicine in urologic cancer over the last 23 years, focusing on aspects such as researchers, institutions, nations, and keywords. We searched for papers in the Web of Science Core Collection from January 1, 2001, to December 29, 2023. Only reviews and original articles written in English were considered. A total of 2386 papers satisfied the given criteria for inclusion. The publications included in the study originated from 90 nations. The United States had the largest number of published papers, accounting for more than 31.01% of the total. The leading institution in this field is the Chinese Academy of Sciences, with a publishing output of 2.35%. Farokhzad, Omid C., is the most prolific author, with 21 articles, and has garnered the most citations, totaling 6271. The latest phrase to enter the top ten most common lists was "gold nanoparticles." We searched for papers in the Web of Science Core Collection from January 1, 2000, to November 28, 2023. Only reviews and original articles written in English were considered. This is the first bibliometric study of nanomedicine in urologic cancer. This article provides a comprehensive analysis of the current state of research on nanomedicine in urologic cancer over the last 23 years. On the basis of this study, future researchers can identify noteworthy publications, journals, and potential collaborators and explore cutting-edge research directions.

Machine Learning Prediction of On/Off Target-driven Clinical Adverse Events.

OBJECTIVE: Currently, 90% of clinical drug development fails, where 30% of these failures are due to clinical toxicity. The current extensive animal toxicity studies are not predictive of clinical adverse events (AEs) at clinical doses, while current computation models only consider very few factors with limited success in clinical toxicity prediction. We aimed to address these issues by developing a machine learning (ML) model to directly predict clinical AEs. METHODS: Using a dataset with 759 FDA-approved drugs with known AEs, we first adapted the ConPLex ML model to predict IC 50 values of these FDA-approved drugs against their on-target and off-target binding among 477 protein targets. Subsequently, we constructed a new ML model to predict clinical AEs using IC 50 values of 759 drugs' primary on-target and off-target effects along with tissue-specific protein expression profiles. RESULTS: The adapted ConPLex model predicted drug-target interactions for both on- and off-target effects, as shown by co-localization of the 6 small molecule kinase inhibitors with their respective kinases. The coupled ML models demonstrated good predictive capability of clinical AEs, with accuracy over 75%. CONCLUSIONS: Our approach provides a new insight into the mechanistic understanding of in vivo drug toxicity in relationship with drug on-/off-target interactions. The coupled ML models, once validated with larger datasets, may offer advantages to directly predict clinical AEs using in vitro/ex vivo and preclinical data, which will help to reduce drug development failure due to clinical toxicity.

A 23-year bibliometric analysis of the development of global research on hereditary renal carcinoma.

Objectives: Medical research continues to be extensively devoted to investigating the pathogenesis and treatment approaches of hereditary renal cancer. By aspect including researchers, institutions, countries, journals, and keywords, we conduct a bibliometric analysis of the literature pertaining to hereditary renal cancer over the last 23 years. Methods: From the Web of Science Core Collection, we conducted a search for publications published between January 1, 2000 and November 28, 2023. Reviews and original articles were included. Results: A cumulative count of 2,194 publications met the specified criteria for inclusion. The studies of the included articles involved a collective of 2,402 institutions representing 80 countries. Notably, the United States exhibited the highest number of published documents, constituting approximately 45.49% of the total. The preeminent institution in this discipline is the National Cancer Institute (NCI), which maintains a publication volume of 8.98%. In addition to being the most prolific author (125 publications), Linehan WM's works received the highest number of citations (11,985). In a comprehensive count, 803 journals have published related articles. In the top 10 most recent occurrences were the terms "hereditary leiomyomatosis" and "fumarate hydratase." Conclusion: This is the first bibliometric analysis of the literature on hereditary renal cancer. This article offers a thorough examination of the present status of investigations concerning hereditary renal cancer during the previous 23 years.

Ascorbyl palmitate ameliorates inflammatory diseases by inhibition of NLRP3 inflammasome.

The aberrant activation of NLRP3 inflammasome contributes to pathogenesis of multiple inflammation-driven human diseases. However, the medications targeting NLRP3 inflammasome are not approved for clinic use to date. Here, we show that ascorbyl palmitate (AP), a lipophilic derivative of ascorbic acid (AA) and a safe food additive, is a potent inhibitor of NLRP3 inflammasome. Compared with AA, AP inhibited the activation of NLRP3 inflammasome with increased potency and specificity. Mechanistically, AP directly scavenged mitochondrial reactive oxygen species (mitoROS) by its antioxidant activity and blocked NLRP3-NEK7 interaction and NLRP3 inflammasome assembly. Moreover, AP showed more significant preventive effects than AA in LPS-induced systemic inflammation, dextran sulfate sodium (DSS)-induced colitis and experimental autoimmune encephalomyelitis (EAE). Thus, our results suggest that AP is a potential therapeutic combating NLRP3-driven diseases.

A gastrointestinal locally activating Janus kinase inhibitor to treat ulcerative colitis.

In this study, we integrated machine learning (ML), structure-tissue selectivity-activity-relationship (STAR), and wet lab synthesis/testing to design a gastrointestinal (GI) locally activating JAK inhibitor for ulcerative colitis treatment. The JAK inhibitor achieves site-specific efficacy through high local GI tissue selectivity while minimizing the requirement for JAK isoform specificity to reduce systemic toxicity. We used the ML model (CoGT) to classify whether the designed compounds were inhibitors or noninhibitors. Then we used the regression ML model (MTATFP) to predict their IC50 against related JAK isoforms of predicted JAK inhibitors. The ML model predicted MMT3-72, which was retained in the GI tract, to be a weak JAK1 inhibitor, while MMT3-72-M2, which accumulated in only GI tissues, was predicted to be an inhibitor of JAK1/2 and TYK2. ML docking methods were applied to simulate their docking poses in JAK isoforms. Application of these ML models enabled us to limit our synthetic efforts to MMT3-72 and MMT3-72-M2 for subsequent wet lab testing. The kinase assay confirmed MMT3-72 weakly inhibited JAK1, and MMT3-72-M2 inhibited JAK1/2 and TYK2. We found that MMT3-72 accumulated in the GI lumen, but not in GI tissue or plasma, but released MMT3-72-M2 accumulated in colon tissue with minimal exposure in the plasma. MMT3-72 achieved superior efficacy and reduced p-STAT3 in DSS-induced colitis. Overall, the integration of ML, the structure-tissue selectivity-activity-relationship system, and wet lab synthesis/testing could minimize the effort in the optimization of a JAK inhibitor to treat colitis. This site-specific inhibitor reduces systemic toxicity by minimizing the need for JAK isoform specificity.

CoGT: Ensemble Machine Learning Method and Its Application on JAK Inhibitor Discovery.

The discovery of new drug candidates to inhibit an intended target is a complex and resource-consuming process. A machine learning (ML) method for predicting drug-target interactions (DTI) is a potential solution to improve the efficiency. However, traditional ML approaches have limitations in accuracy. In this study, we developed a novel ensemble model CoGT for DTI prediction using multilayer perceptron (MLP), which integrated graph-based models to extract non-Euclidean molecular structures and large pretrained models, specifically chemBERTa, to process simplified molecular input line entry systems (SMILES). The performance of CoGT was evaluated using compounds inhibiting four Janus kinases (JAKs). Results showed that the large pretrained model, chemBERTa, was better than other conventional ML models in predicting DTI across multiple evaluation metrics, while the graph neural network (GNN) was effective for prediction on imbalanced data sets. To take full advantage of the strengths of these different models, we developed an ensemble model, CoGT, which outperformed other individual ML models in predicting compounds' inhibition on different isoforms of JAKs. Our data suggest that the ensemble model CoGT has the potential to accelerate the process of drug discovery.

Liposomal T cell engager and re-director for tumor cell eradication in cancer immunotherapy.

T cells are one of the most important effector cells in cancer immunotherapy. Various T cell-dependent bispecific antibody (TDB) drugs that engage T cells for targeted cancer cell lysis are being developed. Here, we describe supra-molecular T-cell redirecting antibody fragment-anchored liposomes (TRAFsomes) and report their immune modulation and anti-cancer effects. We found that TRAFsomes containing different copies of anti-CD3 fragments displayed different T cell modulation profiles, showing that optimization of surface density is needed to define the therapeutic window for potentiating cancer cell-specific immune reactions while minimizing nonspecific side effects. Moreover, small molecular immunomodulators may also be incorporated by liposomal encapsulation to drive CD8 + T cell biased immune responses. In vivo studies using human peripheral blood mononuclear cell reconstituted mouse models showed that TRAFsomes remained bounded to human T cells and persisted for more than 48 hours after injection. However, only TRAFsomes containing a few anti-CD3 (n = 9) demonstrated significant T cell-mediated anti-cancer activities to reverse tumor growth. Those with more anti-CD3s (n = 70) caused tumor growth and depletion of human T cells at the end of treatments. These data suggested that TRAFsomes can be as potent as traditional TDBs and the liposomal structure offers great potential for immunomodulation and improvement of the therapeutic index.Abbreviation: Chimeric antigen receptor T cells (CAR-T cells), Cytokine release syndrome (CRS) Cytotoxic T cell (CTL) Effector: target ratios (E:T ratios), Heavy chain (HC) Immune-related adverse events (irAE), Large unilamellar vesicle (LUV), Peripheral blood mononuclear cells (PBMCs, Single-chain variable fragment (scFv), T cell-dependent bispecific antibody (TDB), T cell redirecting antibody fragment-anchored liposomes (TRAFsomes), Methoxy poly-(ethylene glycol) (mPEG).

Chelerythrine ameliorates rheumatoid arthritis by modulating the AMPK/mTOR/ULK-1 signaling pathway.

BACKGROUND: Rheumatoid arthritis (RA) is a long-term, progressive, and disabling autoimmune disease. It causes inflammation, swelling and pain in and around the joints and other body organs. Currently, no cure is available for RA. Clinical interventions can only relieve the condition, and at least 30% of RA patients do not respond to first­line therapy. This means that the development of more effective therapies against RA is urgently needed. OBJECTIVE: This study aimed to assess the anti-rheumatoid arthritis effect of chelerythrine (CLT) and explore its mechanism of action. METHODS: The cytotoxic effect of CLT on human rheumatoid arthritis fibroblast-like synoviocyte (HFLS-RA) cells and HFLS-normal cells were measured by MTT assay. The growth and migration of HFLS-RA cells were determined by colony-formation and wound-healing assay. The level of intracellular reactive oxygen species (ROS) was detected using the DCFH-DA reagent. Cell apoptosis was measured by flow cytometry, TUNEL staining, caspase 3 activity, as well as the activation of apoptosis related proteins. In addition, the levels of autophagy related markers such as LC3B and P62 were determined by immunocytochemistry and western blotting. Lastly, the anti-RA effect of CLT was evaluated in an Adjuvant-Induced Arthritis(AIA) rat model and the severity of arthritis was detected and quantified using macroscopic inspection and X­ray imaging. RESULTS: We discovered that treatment with CLT effectively inhibited the migration and colony-formation of the HFLS-RA cells and resulted in cell death. Moreover, CLT increased the intracellular level of ROS and the apoptotic rate of HFLS-RA by activating the AMPK/mTOR/ULK-1 signaling pathways. In vivo study showed CLT effectively ameliorated AIA in rats, protecting them from inflammation and bone damage. CONCLUSION: Our study shows CLT is an effective agent for ameliorating RA in vitro and in vivo by modulation of the AMPK/mTOR/ULK-1 signaling pathway. These findings indicate that CLT is a great potential candidate for development as a therapeutic agent for the prevention and treatment of RA.

Albumin nanoparticle containing a PI3Kγ inhibitor and paclitaxel in combination with α-PD1 induces tumor remission of breast cancer in mice.

Immunomodulators that remodel the tumor immunosuppressive microenvironment have been combined with anti-programmed death 1 (α-PD1) or anti-programmed death ligand 1 (α-PDL1) immunotherapy but have shown limited success in clinical trials. However, therapeutic strategies to modulate the immunosuppressive microenvironment of lymph nodes have been largely overlooked. Here, we designed an albumin nanoparticle, Nano-PI, containing the immunomodulators PI3Kγ inhibitor (IPI-549) and paclitaxel (PTX). We treated two breast cancer mouse models with Nano-PI in combination with α-PD1, which remodeled the tumor microenvironment in both lymph nodes and tumors. This combination achieved long-term tumor remission in mouse models and eliminated lung metastases. PTX combined with IPI-549 enabled the formation of a stable nanoparticle and enhanced the repolarization of M2 to M1 macrophages. Nano-PI not only enhanced the delivery of both immunomodulators to lymph nodes and tumors but also improved the drug accumulation in the macrophages of these two tissues. Immune cell profiling revealed that the combination of Nano-PI with α-PD1 remodeled the immune microenvironment by polarizing M2 to M1 macrophages, increasing CD4+ and CD8+ T cells, B cells, and dendritic cells, decreasing regulatory T cells, and preventing T cell exhaustion. Our data suggest that Nano-PI in combination with α-PD1 modulates the immune microenvironment in both lymph nodes and tumors to achieve long-term remission in mice with metastatic breast cancer, and represents a promising candidate for future clinical trials.

Hepatic Carcinoma Selective Nucleic Acid Nanovector Assembled by Endogenous Molecules Based on Modular Strategy.

We rationally formulated a nucleic acid nanovector platform utilizing endogenous molecules in the following steps: nucleic acids are initially packed by a multifunctional peptide and a cationic liposome to form positively charged ternary complexes through electrostatic interaction; then the ternary complexes were coated with hyaluronic acid (HA) to form negatively charged quaternary nanocomplexes (Q-complexes). Among the components of Q-complexes, the multifunctional peptide was composed of a poly-16-arginine (R16) and a hepatic tumor-targeted cell penetrating peptide (KRPTMRFRYTWNPMK); the cationic lipid component included DOTAP and fusogenic lipid DOPE; the HA component shielded the cationic ternary complexes and actively targeted the CD44 overexpressed on the surface of tumor cells. Q-complexes have showed a relatively high stability in the medium, and HA component partially separated from the nanocomplexes after the Q-complexes bound to the cancer cells. The Q-complexes showed significantly enhanced nucleic acid delivery activity than the corresponding quaternary complexes containing R16 and nonvisible cytotoxicity in SCMM-7721 cells. In vivo, a selected Q-complex HLP1R specifically targeted and entered tumor cells without affecting normal tissues. Furthermore, HLP1R wrapped survivin siRNA efficiently and silenced the targeting gene in the liver orthotropic transplantation tumor models and showed nontoxic in vivo. This study reveals that Q-complexes are reasonable and feasible gene therapeutic carriers.

Effect of inserted spacer in hepatic cell-penetrating multifunctional peptide component on the DNA intracellular delivery of quaternary complexes based on modular design.

A safe and efficient quaternary gene delivery system (named Q-complexes) was constructed based on self-assembly of molecules through noncovalent bonds. This system was formulated through the cooperation and competing interactions of cationic liposomes, multifunctional peptides, and DNA, followed by coating hyaluronic acid on the surface of the ternary complexes. The multifunctional peptide was composed of two functional domains: penetrating hepatic tumor-targeted cell moiety (KRPTMRFRYTWNPMK) and a wrapping gene sequence (polyarginine 16). The effect of spacer insertion between the two domains of multifunctional peptide on the intracellular transfection of Q-complexes was further studied. Experimental results showed that the formulations assembled with various peptides in the spacer elements possessed different intercellular pathways and transfection efficiencies. The Q-complexes containing peptide in the absence of spacer element (Pa) showed the highest gene expression among all samples. The Q-complexes containing peptides with a noncleavable spacer GA (Pc) had no ability of intracellular nucleic acid delivery, whereas those with a cleavable spacer RVRR (Pd) showed moderate transfection activity. These results demonstrated that the different spacers inserted in the multifunctional peptide played an important role in in vitro DNA transfection efficiency. Atomic force microscopy images showed that the morphologies of ternary complexes (LPcD) and Q-complexes (HLcPD) were crystal lamellas, whereas those of other nanocomplexes were spheres. Circular dichroism showed the changed configuration of peptide with spacer GA in nanocomplexes compared with that of its free state, whereas the Pa configuration without spacer in nanocomplexes was consistent with that of its free state. The present study contributed to the structural understanding of Q-complexes, and further effective modification is in progress.