BackgroundPlatinum-resistant ovarian cancer (PROC) is a major clinical challenge driven by profound intratumoral heterogeneity. Triptolide (TP) exhibits promising anti-tumor potential, yet its precise mechanisms within PROC remain elusive due to the limitations of traditional target-screening strategies.MethodsThis study developed a comprehensive strategy integrating computational predictions with in vitro experimental validations. First, scRNA-seq data were processed to evaluate TP target genes predicted by SwissTargetPrediction, alongside pseudotime trajectory and CellChat intercellular communication analyses. Subsequently, an ensemble of six machine learning (ML) algorithms (LASSO, Random Forest, Boruta, Decision Tree, XGBoost, and GBM) was utilized to pinpoint the core therapeutic target. To verify direct molecular engagement, molecular docking, molecular dynamics (MD) simulations, and Surface Plasmon Resonance (SPR) assays were performed. Finally, the functional mechanism of the identified target in CDDP resistance was validated in vitro using parental SKOV3 and resistant SKOV3/CDDP cell lines.ResultsscRNA-seq analysis revealed TP target genes are preferentially enriched in highly genomically unstable malignant epithelial cells. This subpopulation showed an aggressive intercellular communication profile, profound dependence on extracellular matrix (ECM) signals, and dominant secretion of the chemoresistance-related cytokine osteopontin (SPP1). Furthermore, the ML pipeline consistently pinpointed the proto-oncogene JUN as the core therapeutic target. Experiments confirmed TP efficiently suppressed aberrant c-Jun overexpression. Targeted JUN knockdown restored CDDP sensitivity, while its overexpression antagonized the synergistic cytotoxic and apoptotic effects of TP and CDDP. Ultimately, TP reverses CDDP resistance in PROC by downregulating JUN, dismantling intracellular pro-survival networks, and disrupting pro-tumorigenic crosstalk.ConclusionIn conclusion, TP reverses CDDP resistance in PROC by downregulating JUN, which dismantles intracellular pro-survival networks. Integrating scRNA-seq and ML provides an accurate paradigm for deciphering botanical pharmacology, laying a strong foundation for the future development of TP-based therapies tailored for PROC.

Abstract The modernization of natural medicines research is defined by a systemic paradigm shift. This evolution is prominently exemplified by traditional Chinese medicine (TCM), where the integration of advanced technologies enables a move from single‐marker analysis to holistic quality control through comprehensive chemical and biological profiling. The mechanistic study of natural medicines, particularly complex TCM formulas, now explores both discrete molecular targets and overarching systemic mechanisms, such as metabolic restoration and host–microbiota crosstalk. Artificial intelligence further accelerates the study of natural medicines by modeling complex pharmacological networks. Despite shared challenges in standardization and validation, this integrated approach is decisively advancing the field of natural medicines, with TCM at the forefront, into an era of precision and scientifically grounded innovation for future drug discovery.

The enhanced light–matter interaction provides a significant way to reveal information about the matter. Within a confining light in a small-sized microcavity is an important issue in both nonlinear optics and waveguides. Here, we present a symmetrical metal-cladding optical waveguide (SMCOW) with a high-quality factor [Formula: see text] which possesses numerous superior performances, such as high sensitivity and high power density, due to the excited ultrahigh-order modes oscillating between the top and bottom layer at a very small incident angle to standing wave field. The relationship between thickness, angle and [Formula: see text] is obtained from experimental detection and theoretical simulation, with a high-quality factor [Formula: see text]. Meanwhile, we have deduced the equation of an important parameter, the half-width [Formula: see text] of the attenuated total reflectance (ATR) peak, which is dependent on the imaginary part of the propagation constant Im[Formula: see text] and incident angle [Formula: see text].

In antitumor activities, baicalin and astragaloside IV inhibit tumor growth, induce cell death, and restrain metastasis in various cancers. Generally, a mixture of massive herbs like scutellaria or astragalus matches with other drugs to reach a curative effect in traditional Chinese prescription. Therefore, researchers aspire to an effective type of drug combination that shows promoted absorption and higher bioavailability in preclinical studies. Here, we report an optical method to detect chiral baicalin and astragaloside IV and also monitor the absorption of different chirals in ovarian cells. Eventually, R-Baicalin-Astragaloside IV dual drugs combination shows promoted absorption of each other compared with single chiral drugs or another. Based on the optical method results, we designed a series of in vitro and in vivo experiments to explain and analyze the mechanism of the curative effect. Therein, the result reveals that the tumor-associated neutrophils were reduced via the down-regulated TLR4/MYD88/NF-κB pathway to increased PD-1/PD-L1 immune response in epithelial ovarian cancer under the influence of R-Baicalin-Astragaloside IV. Thus, this work offers a comprehensive report on structure-activity relationships of chiral and dual drug strategies to improve its bioavailability in therapy of ovarian cancer.

OBJECTIVE:Buyi Xiaozheng decoction (BYXZD) is widely used as an adjunct therapy for ovarian cancer (OC) chemotherapy, effectively inhibiting OC progression. However, its targets and mechanisms remain unclear. This study aimed to identify the active components and clarify the molecular mechanisms of BYXZD in OC treatment using an integrated approach combining UHPLC-QE-MS, network pharmacology, molecular docking, dynamics simulations, and experimental validation METHODS: UHPLC-QE-MS was employed to identify the main components of BYXZD. Targets of BYXZD were predicted using PharmMapper and Swiss target prediction, while OC-related targets were retrieved from GeneCards, OMIM, TTD, and CTD databases. The intersection of these targets was analyzed to identify potential therapeutic targets of BYXZD. An "herb-compound-target" network was constructed using Cytoscape, and protein-protein interactions (PPI) were analyzed via the string database. Functional enrichment analysis (GO and KEGG) was performed using the DAVID database. Molecular docking and dynamics simulations were conducted to evaluate the binding affinity and stability of core components with key targets. In vitro experiments were performed to validate the effects of BYXZD on OC cell migration, invasion, and signaling pathways RESULTS: The main components of BYXZD were identified as atractylenolide II, lithospermic acid, baicalein, and scutellarein. PPI, GO, and KEGG analyses identified AKT1, MAPK1, MAPK3, and PIK3CA as key targets, with the PI3K/AKT and MAPK pathways serving as the primary mechanisms. Molecular docking showed high binding affinity between core components and key targets, and molecular dynamics simulations indicated stable interactions between baicalein/lithospermic acid and MAPK1/PI3CA. In vitro experiments confirmed that BYXZD dose-dependently inhibited OC cell migration and invasion by regulating the PI3K/AKT and MAPK pathways CONCLUSIONS: The integrative approach revealed that BYXZD exerts therapeutic effects on OC through multiple components, multiple targets, and multiple pathways, highlighting its potential as a valuable adjuvant therapy for OC.

This study introduces the synthesis and application of a novel metal-organic coordination polymer for photocatalytic cancer therapy. The material was prepared via coordination between Ru(dcbpy)3Cl2 and manganese ions, forming sheet-like nanostructures with strong visible-light absorption and high photostability. Upon light irradiation, Mn-Ru MOCPs not only produce singlet oxygen via a type II photodynamic pathway but also efficiently catalyze the oxidation of intracellular NADH with a high photocatalytic turnover frequency (TOF) of 175 h-1. Moreover, the material facilitates the photocatalytic reduction of cytochrome c in the presence of NADH, triggering multimodal therapeutic effects including ROS erupt, NADH and ATP depletion, loss of mitochondrial membrane potential, and ultimately apoptosis. Both intracorporeal and extracorporeal experiments exhibited significant light-induced anticancer activity against 4T1 breast cancer cells and xenograft tumor models, with good biocompatibility and tumor-targeting capability.

Diabetic wound healing represents a complex biological challenge, often impeded by disrupted cellular processes and dysregulated inflammation, which can lead to chronic and non-healing wounds. Given the significant burden on patients and the healthcare system, there is an urgent need for advanced therapeutic strategies. Hyaluronic acid (HA)-based hydrogels have emerged as a promising solution due to their biocompatibility, biodegradability, and unique physiological functions. This review aims to provide a comprehensive overview of recent advances in HA-based hydrogels, highlighting their potential in addressing diabetic wound complications. Specifically, it examines challenges such as hyperglycemia-induced oxidative stress and impaired cellular signaling within the intricate diabetic wound microenvironment. Moreover, the review explores the composition and properties of HA, including its adhesive capabilities and role in reducing surgical trauma. Various crosslinking strategies and functional modifications are also discussed to endow HA-based hydrogels with antioxidant, antimicrobial, and growth factor-releasing capabilities. By summarizing the latest research and identifying areas for further exploration, this review contributes to the development of more effective HA-based hydrogel formulations for diabetic wound healing.

While increasing evidence suggests that alterations in the gut microbiota and metabolites are associated with ovarian cancer (OC) risk, whether these associations imply causation remains to be identified. We conducted a two-sample Mendelian randomization (MR) study utilizing a large-scale genome-wide association study (GWAS) to explore the causal effects of the gut microbiota of 196/220 individuals and 1,400 plasma metabolites on OC and epithelial ovarian cancer (EOC) subtypes. Data on the gut microbiota were obtained from the MiBioGen consortium of 18,340 subjects and the Dutch Microbiome Project of 7,738 volunteers. Data on plasma metabolites were derived from a GWAS of plasma metabolites in 8,299 participants. Ovarian cancer (n = 25,509) and EOC subtypes were obtained from the Ovarian Cancer Association Consortium (OCAC). Metabolites and associated targets were analyzed via network pharmacology and molecular docking. At the genus and species levels, we identified seven risk factors for the gut microbiota: the genus Dialister (P = 0.024), genus Ruminiclostridium5 (P = 0.0004), genus Phascolarctobacterium (P = 0.0217), species Bacteroides massiliensis (P = 0.011), species Phascolarctobacterium succinatutens (P = 0.0212), species Paraprevotella clara (P = 0.0247) and species Bacteroides dorei (P = 0.0054). In addition, five gut microbes at the genus and species levels were found to be protective: genus Family XIII AD3011 group (P = 0.006), genus Butyrivibrio (P = 0.0095), genus Oscillibacter (P = 0.0206), species Roseburia hominis (P = 0.0241), and species Bifidobacterium bifidum (P = 0.0224). For plasma metabolites, we revealed five positive and four negative correlations with OC. Among these, caffeic acid and caffeine metabolites and sphingomyelin and ceramide metabolites were identified as risk factors, whereas phenylalanine metabolites, butyric acid metabolites, and some lipid metabolites were recognized as protective factors. A series of sensitivity analyses revealed no abnormalities, including pleiotropy and heterogeneity analyses. Our MR analysis demonstrated that the gut microbiota and metabolites are causally associated with OC, which has significant potential for the early detection and diagnosis of OC and EOC subtypes, providing valuable insights into this area of research.

BACKGROUND:Despite advances in ovarian cancer treatment, the tendency for cancer cells to metastasise to the peritoneum still results in poor prognosis. Studies have demonstrated that the integrin family plays a role in this metastasis; however, the underlying mechanism remains unclear. Triptolide (TP) has been confirmed to have a strong cytotoxic effect against ovarian cancer. However, its clinical application is limited by its severe systemic toxicity and low water solubility. METHODS:This study investigated the integrins involved in peritoneal metastasis and their associated mechanisms. Furthermore, Si/TP@Exos were constructed to counteract the metastatic potential of ovarian cancer cells. RESULTS:In vitro experiments showed that the construction of the ITGA4B2/AEP ternary complex contributed to the peritoneal metastasis of ovarian cancer by activating the IL-17 and NF-kappa B signalling pathways. Thus, whether the combined application of siRNA targeting ITGA4B2 and TP could further overcome peritoneal metastasis in ovarian cancer was investigated. In vitro results indicated that Si/TP@Exos were efficiently taken up by ovarian cancer cells, thus significantly enhancing the apoptosis of tumor cells. Similarly, Si/TP@Exos were effectively enriched in the tumor areas and exerted anti-tumor activity obviously in vivo. CONCLUSIONS:Together, these findings present a novel strategy to overcome the peritoneal metastasis tendency of ovarian cancer and offer a potential therapeutic solution for clinical treatment of ovarian cancer. The combination of traditional Chinese medicine nano drug delivery platforms provides a new perspective for cancer treatment.

Triptolide, the active compound of Tripterygium wilfordii, exhibits broad anti-tumor activity. This study explores PPP2CA dysregulation in ovarian cancer (OC) progression via lactate production and evaluates Triptolide’s potential to regulate this process. We used patient-derived xenograft (PDX) models, cell proliferation, and migration assays to assess lactate’s impact on OC progression. CRISPR-Cas9 was applied to knock out PPP2CA, examining its effect on lactate production and tumor progression. RNA-seq analyzed transcriptomic changes post-PPP2CA knockout. The PPP2CA-ITGA5 axis was validated using xenografts, immunofluorescence, immunohistochemistry staining and western blot. Exosome isolation and co-culture experiments with tumor cells and human peritoneal mesothelial cells (HPMCs) investigated ITGA5’s role in migration. Finally, patient-derived organoids, xenograft tumor model, and lactate assays assessed Triptolide’s reversal effect on PPP2CA dysregulation-driven OC progression. We found that PPP2CA dysregulation significantly promotes OC proliferation, migration, and tumorigenesis by enhancing YAP nuclear translocation and upregulating ITGA5/ITGB1. PPP2CA dysregulation led to ITGA5 upregulation, where ITGA5, as part of the integrin α5β1 heterodimer, plays a key role in driving OC migration. Exosomal ITGA5 facilitates OC metastasis to the HPMCs. Triptolide effectively inhibited patient-derived organoid growth and reduced lactate production in OC cells. By suppressing ITGA5, Triptolide reversed cancer progression and restored tumor-suppressive effects in a PPP2CA-knockout xenograft model. Our study reveals that Triptolide effectively inhibits OC progression by targeting the PPP2CA-ITGA5 axis, mitigating lactate-driven metabolic reprogramming.

Scutellarin, a natural compound extracted from Scutellaria barbata, has demonstrated antitumor activity in various cancers. However, its role in ovarian cancer has not been fully explored. This study aims to evaluate the therapeutic potential and underlying mechanisms of Scutellarin in ovarian cancer. The effects of Scutellarin on cell proliferation and migration were assessed in ovarian cancer cell lines including SKOV3, A2780, OVCAR3, and OVCAR8. Patient-derived ovarian cancer organoids were used to further validate the in vitro findings. Calcein-AM and PI staining were used to analyze cell viability, and ATP assays were performed to assess organoid activity. Western blot was used to evaluate the regulation of METTL5 protein by Scutellarin. The gene and protein expression levels of METTL5 and their association with ovarian cancer prognosis were assessed using the databases The Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), TNMplot, KM-plotter and The Cancer Genome Atlas (TCGA). The functional role of METTL5 was assessed by transwell migration and colony formation assays, and its involvement in Scutellarin's mechanism of action was confirmed by rescue experiments using wound healing and transwell assays. Scutellarin significantly inhibited the proliferation and migration of ovarian cancer cells. In organoid models, Scutellarin markedly reduced organoid growth, induced cell damage, and decreased ATP levels. Compared to normal ovarian tissue, ovarian cancer tissue exhibited elevated RNA and protein expression levels of METTL5. High METTL5 expression was associated with poorer prognosis in ovarian cancer patients and promoted the migration and clonogenicity of ovarian cancer cells. Scutellarin downregulated METTL5 expression, and rescue experiments demonstrated that Scutellarin inhibited ovarian cancer migration by targeting METTL5. Scutellarin demonstrates potent, broad-spectrum anti-tumor activity in ovarian cancer cell lines, potentially mediated through targeting METTL5. These findings suggest a novel and promising therapeutic strategy for ovarian cancer treatment.

Despite advances in cancer therapy, high mortality persists due to drug resistance and relapse. Developing selective anticancer agents with minimal toxicity and resistance remains crucial. Baicalin shows antitumor potential, but its mechanism against papillary thyroid carcinoma (PTC) remains unclear. We designed an optical resonator to monitor baicalin-membrane protein interactions, identifying NGFR as the key ATR-shifted target. Mechanistic studies revealed baicalin induces autophagy via the NGFR/MAPK/mTOR axis, validated through in vitro and in vivo models. These findings position baicalin as a promising PTC therapeutic with clinical translation potential.

LBA7074 Background: Relapsed/refractory diffuse large B-cell lymphoma (r/r DLBCL) has a poor prognosis. Double-expressor (DEL) or TP53 abnormal r/r DLBCL patients(pts) are associated with even worse outcomes. Class I and IIb histone deacetylases (HDACs) are overexpressed in DLBCL and have been identified as a therapy target. Purinostat Mesylate (PM) is a high selective HDAC I/IIb inhibitor. Phase I dose-escalation trial of PM (1.2, 2.4, 4.0, 6.0, 8.4, 11.2, 15 mg/m 2 ) by i.v was conducted in 29 hematologic malignancies at day 1, 4, 8, 11 of a 21-day cycle. PM was generally well tolerated with no DLTs. 61.1% (11/18) ORR was observed in r/r lymphoma pts. Based on these data, we conducted a phase 2a to further explore efficacy and safety of PM and mechanism of actions. Methods: This randomized, multicenter, open-label, phase 2a study was conducted from Nov.2022 to the present(NCT05563844). Key eligibility include r/r DLBCL pts with prior therapy including anti-CD20 antibody and anthracycline-based chemotherapy; ECOG≤2. Thirty pts were randomized 1:1 received PM at 8.4 and 11.2 mg/m 2 on Day 1, 4, 8, 11 of a 21-day cycle. Pts continued to receive PM until disease progression or unacceptable toxicity. Primary outcome was ORR and safety. Multiple cell lines and PDX mouse models were used to evaluate the PM activity and mechanism of action in vitro and in vivo. ATAC-seq, bulk RNA-seq, and scRNA-seq from both PDX models and pts were investigated for the activated immune response of PM. Results: Thirty patients were enrolled and 28 patients were evaluable. The ORR (20/28) was 71.4% (95%CI:51.3-86.8) with 5 CR and 15 PR. Fifteen pts at 8.4 mg/m 2 achieved an ORR of 66.7%(95%CI:38.4-88.2) with 1 CR and 9 PR. Thirteen pts at 11.2 mg/m 2 achieved ORR of 76.9%(95%CI:46.2-95.0) with 4 CR and 6 PR. As of the data cut off in Feb. 2024, 7 pts remained on treatment and the longest treatment has lasted 17 cycles. Median PFS was 4.3m (95%CI:2.8-8.5), OS were immature. In subgroup analyses, 7 DE DLBCL pts obtained 42.9%(3/7) ORR and 11 pts with TP53 abnormal by FISH or NGS test achieved 45.5%(5/11) ORR. Fifteen pts with non-DE or without TP53 abnormal achieved ORR of 86.7%(13/15). The most frequently reported Grade≥3 TRAE were thrombocytopenia, neutropenia, lymphocytopenia. No PM-related death was reported. PM monotherapy showed stronger and superior antitumor effects in DE DLBCL and TP53 mutations PDX models than selinexor and R-CHOP. PM significantly down-regulates the proteins c-MYC, EZH2, and mutated P53. ATAC-seq, bulk RNA-seq and scRNA-seq revealed that PM can stimulate the proliferation and activation of cytotoxic T cells and NKT cells, up-regulate the expression of B-cell tumor MHC I and II and inhibit tumor cell immune escape. Conclusions: This study further supports the recommended dose 11.2 mg/m 2 PM as the phase 2b for r/r DLBCL. Currently, the phase 2b, open-label, multicenter study has enrolled in 37 sites in China. Clinical trial information: NCT05563844 .

Breast cancer has become the most common form of cancer worldwide. Chemotherapy failure, primarily due to drug resistance, necessitates the development of new therapeutic strategies. In this study, ultrathin Ti3C2 nanosheets are utilized as photothermal agents and nanocarriers. We developed a multifunctional Ti3C2-based nanoplatform (214.7 nm) through layer-by-layer absorption of HSP90 antisense oligonucleotide (ASO) and doxorubicin (DOX), with surface modification using hyaluronic acid (HA). In a simulated acidic tumor microenvironment in vitro, 90 % of the drug was released within 36 hours. Additionally, Under 808 nm irradiation (2.0 W/cm(2)), MCF-7/ADM cell viability assays revealed the following results: HA-Ti3C2 (57 %), HA-Ti3C2@ASO (HT@A) (41 %), and HA-Ti3C2@ASO/DOX (HT@AD) (26 %), which shown the synergistic inhibitory effects of this multifunctional nanoplatform. Herein, this nanosystem exhibits enhanced biocompatibility, superior photothermal performance, and stimuli-responsive drug release behavior, making it a promising candidate for effective inhibition of cancer cell proliferation and migration.

Papillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer. Methylation of some genes plays a crucial role in the tendency to malignancy as well as poor prognosis of thyroid cancer, suggesting that methylation features can serve as complementary markers for molecular diagnosis. In this study, we aimed to develop and validate a diagnostic model for PTC based on DNA methylation markers. A total of 142 thyroid nodule tissue samples containing 84 cases of PTC and 58 cases of thyroid adenoma (TA) were collected for reduced representation bisulfite sequencing (RRBS) and subsequent analysis. The diagnostic model was constructed by the logistic regression (LR) method followed by 5-cross validation and based on 94 tissue methylation haplotype block (MHB) markers. The model achieved an area under the receiver operating characteristic curve (AUROC) of 0.974 (95% CI, 0.964-0.981) on 108 training samples and 0.917 (95% CI, 0.864-0.973) on 27 independent testing samples. The diagnostic model scores showed significantly high in males (P = 0.0016), age ≤ 45 years (P = 0.026), high body mass index (BMI) (P = 0.040), lymph node metastasis (P = 0.00052) and larger nodules (P = 0.0017) in the PTC group, and the risk score of this diagnostic model showed significantly high in recurrent PTC group (P = 0.0005). These results suggest that the diagnostic model can be expected to be a powerful tool for PTC diagnosis and there are more potential clinical applications of methylation markers to be excavated.

Chemical investigations on the culture of Penicillium oxalicum 2021CDF-3, a marine red alga-sourced endophytic fungus, revealed a new steroid, namely peniciloxatone A (1). With the aid of high-resolution electrospray ionization mass spectrometry (HRESIMS) and nuclear magnetic resonance (NMR) analyses, the structure of peniciloxatone A (1) was determined to be a polyoxygenated ergostane steroid. Cytotoxic activities of 1 were tested against A549, FADU, and HepG2 cells, and 1 was active against the FADU and HepG2 cells, with IC50 values of 9.5 +/- 0.1 and 18.1 +/- 0.3 mu M, respectively.

Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation. It also highlights multiomics integration, demonstrating machine learning's potential in elucidating biological phenomena and advancing disease diagnostics. This work contributes significantly to metabolomics by merging it with machine learning, offering innovative solutions to analytical challenges and setting new standards for omics data analysis.

Background: Ovarian cancer (OC) is a life-threatening pathological condition in women through the world. The treatment of ovarian cancer is limited to surgical resection, radiotherapy, and chemotherapy. Sea cucumbers are natural and a health food with a well-known potential for the development of anticancer pharmaceuticals. Sea cucumber glycosides are the anticancer substance in sea cucumbers. The present study was designed to evaluate the effect of sea cucumber glucosides on ovarian cancer in the cell line SKOV3. Methods: Comprehensive bioinformatic analysis were performed to predict the pharmacological effect of sea cucumber on OC. Dose screening, microarray analysis and cytological experiments were performed to investigate the detailed effects of sea cucumber glucosides on OC. Results: Sea cucumber glycosides were found to have apoptotic, anti-proliferated, anti-invading and migration effects on SKOV3 ovarian cells. By using microarray analysis, we speculate that the anti-cancer effect of sea cucumber glycosides on ovarian cancer might be related to the p38-MAPK pathway. Conclusion: In the present study, we showed that sea cucumber glycosides have anti-cancer effects by inducing the apoptosis rate, reducing cell proliferation and cell invasion, and we also identified the possible cellular pathway for the sea cucumber glycoside action by in silico study. Our study provides a new potential in the treatment of ovarian cancer by natural products.