Immunotherapy has revolutionized cancer treatment in recent years, yet non-responsiveness of immunotherapy remains a challenge for cancer treatment. Therefore, the prediction method for potential clinical benefits of patients from immunotherapy is urgently needed. This study aims to develop an effective clinical practice assistance tool to evaluate the potential clinical benefits and therapy responsiveness of patients undergoing immunotherapy. We developed an immunotherapy resistance score (IRS), which performed well compared with conventional immunotherapy response indicators across different immunotherapy cohorts. Tumor microenvironment (TME) analysis showed that both immune and nonimmune features collectively impact immunotherapy responsiveness. Thus, IRS was constructed based on the TME features using machine learning approaches. The clinical application potential of IRS has been demonstrated in our in-house Harbin Medical University (HMU) cohort and an external validation cohort. Furthermore, we analyzed the correlation between IRS and pathways related to cancer therapy targets to explore the application potential of IRS in comprehensive cancer therapy. In conclusion, IRS is a robust tool for predicting patient immunotherapy prognosis, which has great potential to promote precise clinical therapy.

Coronary artery disease (CAD), the most common panvascular disease, can progress to chronic total occlusion (CTO). Drug-eluting stent (DES) is one of standard CAD treatments, but in-stent restenosis leading to CTO is challenging, with unclear optimal management. The efficacy of drug-coated balloons (DCB) for treating DES-related in-stent chronic total occlusion (IS-CTO) is undetermined. In this single-center retrospective cohort study of 198 patients with IS-CTO post-DES, 3-year outcomes of DCB, DES, and plain old balloon angioplasty (POBA) were compared, focusing on target vessel failure (TVF). DES showed the lowest TVF rate (DCB vs. DES vs. POBA: 31.8% vs. 17.1% vs. 51.6%, p < 0.01), mainly due to fewer revascularizations. Notably, the difference in TVF between DCB and DES became more apparent after the first year. DCB was an independent risk factor for late TVF (HR_adj = 6.51, 95% confidence interval [CI] = 2.45–18.84, p < 0.01), whereas POBA for early TVF compared to DCB (HR_adj = 5.01, 95% CI = 1.36–18.42, p = 0.02). While POBA-treated patients exhibited a higher target vessel myocardial infarction rate, the death rates were comparable across all cohorts. In conclusion, DES showed the lowest 3-year TVF rate, making it the most effective treatment for IS-CTO compared to DCB and POBA.

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer, characterized by poor prognosis and limited therapeutic options. Although neoadjuvant chemotherapy (NACT) remains the established treatment approach, its suboptimal efficacy associated with TNBC highlight the urgent need for optimized treatment strategies to improve pathological complete response (pCR) rates. This review provides a comprehensive overview of recent advancements in neoadjuvant treatment for TNBC, emphasizing pivotal breakthroughs in therapeutic strategies and the ongoing pursuit of innovative approaches to enhance precision medicine. It emphasizes the clinical value of platinum-based agents, such as carboplatin and cisplatin, which have shown significant improvements in pCR rates, particularly in TNBC patients with BRCA mutations. Additionally, the review explores progress in targeted therapies, including PARP inhibitors, AKT inhibitors, and Antiangiogenic agents, showcasing their potential for personalized treatment approaches. The integration of immunotherapy, particularly immune checkpoint inhibitor like pembrolizumab and atezolizumab, with chemotherapy has demonstrated substantial efficacy in high-risk TNBC cases. Future research priorities include refining biomarker-driven strategies, optimizing therapeutic combinations, developing antibody-drug conjugates (ADCs) targeting TROP2 and other biomarkers, and reducing treatment-related toxicity to develop safer and highly personalized neoadjuvant therapies. Furthermore, artificial intelligence has also emerged as a transformative tool in predicting treatment response and optimizing therapeutic decision-making in TNBC. These advancements aim to improve long-term outcomes and quality of life for patients with TNBC.

Glioma, characterized by significant heterogeneity and aggressiveness, poses a formidable therapeutic challenge. Cuproptosis, a newly identified form of regulated cell death driven by copper imbalance, has recently emerged as a pivotal factor in tumor biology. However, its role in IDH1-mutant gliomas remains poorly understood. Through comprehensive bioinformatics analysis of publicly available datasets, we identified two distinct subtypes of IDH1-mutant gliomas based on cuproptosis regulator expression profiles. Subtype G1 exhibited elevated PD-L1 expression, increased pro-tumor immune infiltration, and worse clinical outcomes, whereas subtype G2 was enriched in antitumor immune cells and associated with improved prognosis. We identified FDX1 and SLC31A1 as critical prognostic markers, with their upregulation linked to PD-L1 expression. Mechanistically, we delineated a ceRNA regulatory axis involving COX10-AS1/miR-1-3p/FDX1 and SLC31A1 that drives glioma progression. Building on these insights, we developed a prognostic risk model integrating FDX1 and SLC31A1 expression, demonstrating robust predictive accuracy for patient outcomes and potential utility in guiding individualized treatment strategies. These findings advance our understanding of the molecular landscape in IDH1-mutant gliomas and underscore the potential of cuproptosis regulators as novel therapeutic targets and biomarkers for precision oncology.

Inflammation, as a complex biological response, can lead to tissue damage and pathological physiological changes, forming the basis for many chronic diseases. Stem cell-derived exosomes (SC-Exos), a type of nanoscale extracellular vesicle, possess advantages such as small volume, low immunogenicity, and drug-carrying capacity, demonstrating immense potential in the field of disease diagnostics and therapeutics. Current studies indicate that SC-Exos can not only alleviate inflammatory diseases by suppressing inflammatory cytokines and modulating the activation of macrophages through their immunomodulatory and regenerative properties but also show significant potential as carriers for anti-inflammatory drugs, presenting a promising therapeutic approach for inflammatory conditions. However, the current lack of systematic summaries of SC-Exos in the treatment of inflammatory diseases has impeded the development of standardized therapies and clinical applications. This review elucidates the methods of SC-Exo sourcing, isolation, characterization, and engineering, as well as their application, mechanisms of action, and efficacy in the treatment of inflammatory diseases such as periodontitis, osteoarthritis (OA), and inflammatory bowel disease. Integrating these findings, this review highlights that SC-Exos can attenuate a variety of inflammatory diseases by transporting a diverse range of molecules to modulate immune responses, thereby providing foundations for subsequent standardization of production and clinical trials.