Cancer Biotherapy and Radiopharmaceuticals最新文献

Recently, exosomes, or "natural nanoparticles," have been considered as potential drug delivery methods. Due to exosome carriers' natural properties, exosome-mediated drug delivery systems (DDSs) are efficient cancer treatments. Exosomes, small membrane vesicles from many cell types, can transfer phytoconstituents, proteins, nucleic acids, and small molecule medicines across biological boundaries. Recent DDS advances have improved this potential using plant-derived exosomes (PDEs), which are biocompatible and low toxic. PDEs have anticancer effects, especially in the context of conventional treatment resistance, untargeted toxicity, and response variability. This review fills a gap by discussing the latest findings and offering new perspectives on exosome drug delivery in cancer. The study summarizes isolation and loading approaches such as ultracentrifugation and immunological isolation and the characterization parameters for the formulation of exosomes. The exosome-based DDSs are discussed in depth, along with the emphasis on PDEs. The article highlights emerging trends and challenges, including molecular targets and ongoing clinical trials, during the past decade that are critically relevant to the current scenario. Nanotechnology and personalized medicine could improve and lower the cost of exosome-mediated cancer treatment. While the preclinical data have been encouraging, clinical applications of exosome-based therapies are continuing to evolve in its early stages, and some of the problems include scalability, purification, and regulatory compliance. [Figure: see text].

Alkylating agents, characterized by their ability to bind to and modify DNA, have shown promising impacts on breast cancer patients in clinical trials across various stages and phases. This review, utilizing data from the National Library of Medicine's clinicaltrials.gov, investigates the efficacy of these drugs in breast cancer treatment. The report focuses on cyclophosphamide, an alkylating agent that prevents cancer cell DNA replication, and its synergistic effects when combined with other medications such as docetaxel, a taxane that suppresses cell division. Results indicate that these combination therapies may enhance treatment efficacy and improve outcomes. This survey highlights the widespread use of alkylating agents in clinical studies for breast cancer, a disease affecting over a million people annually in India alone. Commonly used alkylating drugs for breast cancer treatment include carmustine, chlorambucil, and cyclophosphamide. These agents have shown effectiveness in treating metastatic breast cancer and reducing the risk of recurrence, underscoring their significant role in breast cancer therapy.

Creation of a virtual avatar of a patient with cancer has the potential to transform theranostics into a truly individualized precision treatment of specific cancers, which express targetable receptors. Each patient is unique. Their cancer molecular biology has its own inherent relationship to their genomic phenotype and the metabolomic and immunological milieu of their tumor. This singularity can be captured and simulated through generation of an avatar, incarnated by means of artificial intelligence collection, collation and analysis of personal radio-genomics, tumor pathology, and molecular biology data, in the form of a digital twin. The capacity to replicate these idiosyncratic individual interactions within a digital twin construct of such a virtual avatar allows contemplation of ex vivo prototypical design and testing of N-of-1 theranostic strategies in real time. Continuing follow-up and analysis of evolving data confers the opportunity to adapt treatments to predict tumor response of the cancer in the avatar in order to optimize clinical outcomes in the actual patient.

Background: Neoadjuvant immunotherapy has become a standard treatment for locally advanced esophageal squamous cell carcinoma (ESCC), but predictive biomarkers for treatment efficacy remain limited. This study investigates the role of serum interleukin-6 (IL-6) levels as a prognostic biomarker in patients receiving neoadjuvant immunotherapy for ESCC. Methods: A retrospective cohort study was conducted in 47 patients with locally advanced ESCC who underwent neoadjuvant immunochemotherapy followed by esophagectomy. Pretreatment serum levels of IL-6 and the combined positive score were analyzed. Pathological responses were evaluated using the College of American Pathologists Tumor Regression Grade system, and survival outcomes were assessed by Kaplan-Meier analysis. IL-6 knockout mice models were used to validate the impact of IL-6 on anti-PD-1 therapy efficacy. Results: Lower pretreatment serum IL-6 levels were significantly associated with better pathological response compared with higher IL-6 levels. Elevated IL-6 levels (>61.495 pg/mL) were identified as an independent risk factor for poorer disease-free survival and overall survival. IL-6 deficiency enhanced the efficacy of anti-PD-1 therapy in mice, reducing tumor burden compared with wild-type controls. Conversely, exogenous IL-6 administration attenuated anti-PD-1 effects. Mechanistically, lower serum IL-6 levels increased CD8⁺ T cell activation and decreased the regulatory T cell proportion during immunotherapy. Conclusions: Low serum IL-6 levels enhance the efficacy of neoadjuvant immunotherapy in locally advanced ESCC.

Background: Breast disease, particularly breast cancer, ranks among the most prevalent malignancies affecting women globally. Accurate clinicopathological diagnosis is critical for early detection and prognostication of breast cancer. This study aimed to establish an ultrasensitive diagnostic model utilizing machine learning to assist in breast cancer pathology. Methods: By integrating bioinformatics, we identified four targets-DPP3, KIF4A, TK1, and UBE2C-with significantly higher expression levels in breast cancer tissues compared to adjacent normal tissues, supported by corresponding immunohistochemical staining images obtained from the HPA database. Using machine learning, we developed a pathological image recognition algorithm for breast cancer. Results: Our findings revealed that the diagnostic accuracy for DPP3 and KIF4A was significantly superior, achieving 93% and 92%, respectively, while TK1 and UBE2C attained accuracies of only 76% and 62%. However, the combined diagnostic efficacy of TK1 and UBE2C increased to 99%. Conclusion: This study highlights the potential of machine learning algorithms in the classification and diagnosis of breast cancer pathology images, emphasizing the importance of integrating bioinformatics with machine learning to enhance early diagnosis and facilitate personalized treatment strategies for breast cancer.

Background: Temozolomide (TMZ), an alkylating drug used for the treatment of gliomas, has to date not been exploited for its potential role as a radionuclide-imaging probe. This study reports the radiosynthesis of [^99mTc]Tc-TMZ and evaluates its specificity for glioma using C6 cell lines. Methods: TMZ was labeled with ^99mTc, optimized for reaction conditions and radiochemical purity. Physicochemical characterization was performed by evaluating plasma protein binding, stability in saline and serum, and partition coefficient. Furthermore, the cellular uptake and internalization mechanism of [^99mTc]Tc-TMZ were determined in C6 cells. The toxicity of the radiotracer was determined by performing the MTT and hemolysis assays. Results: The radiocomplex was synthesized with >90% radiochemical purity. The radiocomplex exhibited neutral charge, high lipophilicity, low plasma protein binding, and physiological stability in in vitro conditions. Cell binding studies exhibited [^99mTc]Tc-TMZ specificity for C6 cells in a concentration- and time-dependent manner, with maximum uptake at 12.5 μg and passive diffusion as the primary mode of transport. Toxicity studies revealed more than 50% damage to the cells with minimal hemolytic activity at 50 μg concentration of TMZ in radiocomplex. Conclusions:These preliminary findings suggest the specificity of [^99mTc]Tc-TMZ for C6 cells and warrant further exploration as a SPECT radiotracer for glioma imaging.

In cancer immunotherapy, the stimulator of interferon genes (STING) pathway regulation has become a promising new approach, offering potential solutions to overcome limitations of current treatments. Recent advances have revealed intricate mechanisms of STING activation and regulation, leading to the development of novel small-molecule agonists with improved properties. Preclinical studies have shown that STING agonists can convert "cold" tumors to "hot" ones, enhancing immune cell infiltration and overcoming resistance to checkpoint inhibitors. Combination strategies, particularly with existing immunotherapies and conventional treatments, have demonstrated synergistic effects. Early clinical trials evaluating STING agonists, both as monotherapies and in combination with checkpoint inhibitors, have yielded promising results. More specific methods have been made possible by biomarker investigations, which have revealed light on mechanisms of action and possible response predictors. Indirect STING activation through ENPP1 inhibition has emerged as a novel strategy, offering more controlled antitumor immunity enhancement while minimizing systemic toxicity. Innovative delivery systems, including nanoparticles and exosome-based therapies, improve STING modulators' therapeutic index. While challenges remain, including precise regulation of STING activation and managing immune-related adverse events, rapid progress suggests that STING-targeted therapies could become cornerstone treatments. By harnessing innate immunity and enhancing its interplay with adaptive responses, STING modulators offer a potentially more accessible, cost-effective, and broadly applicable approach to cancer immunotherapy, addressing many current treatment limitations.

Background: Hepatocellular carcinoma (HCC) is still the largest cause of cancer-related death globally, with alcohol-related HCC (AR-HCC) being a particularly difficult subtype with poor clinical results. Noninvasive biomarkers, such as the fibrosis-4 (FIB-4) index, may provide significant prognostic information that might aid in guiding new interventional techniques, such as ultrasound-based treatments. Methods: The authors did a retrospective cohort analysis on male AR-HCC patients diagnosed between January 2008 and December 2018. Clinical data and survival outcomes were obtained from electronic medical records, with HCC diagnosed as the baseline. The major endpoint was 12-month mortality. Multivariate logistic regression and limited cubic spline analysis were used to assess the relationship between FIB-4 and mortality risk. Results: Among 786 AR-HCC patients (mean age 57 years), 90.1% reported a history of alcohol usage for more than 10 years. The Barcelona Clinic Liver Cancer staging showed 42.8% in stage 0/A, 45.9% in stage B/C, and 11.3% in stage D. Deceased individuals had substantially higher FIB-4 levels (p < 0.05). Logistic regression demonstrated that higher FIB-4 was independently related with increased mortality, and spline analysis revealed a linear risk increase with a threshold of 5.61. Conclusion: Elevated FIB-4 (≥5.61) predicts worse mortality in AR-HCC, indicating its potential relevance in stratifying patients for ultrasound-based cancer therapy. The level of fibrosis may impact both therapeutic response and procedural risk. Routine incorporation of FIB-4 into clinical processes may aid precision decision-making in choosing AR-HCC patients most likely to benefit from ultrasound-guided or ultrasound-enhanced biotherapeutic. Keywords: alcohol, hepatocellular carcinoma, FIB-4, multivariate logistic regression analyses, mortality.

β-glucans are structurally diverse polysaccharides from fungi, yeasts, bacteria, and cereals, exhibiting variable branching and molecular weights that shape their biological activity. Emerging preclinical and clinical evidence highlights their ability to modulate innate and adaptive immunity, exerting direct and adjunct antitumor effects via dectin-1, toll-like receptors, and complement receptor 3. Although well known as nutraceuticals, their integration into advanced cancer biotherapeutics, such as monoclonal antibody regimens, cytokine modulation, and nanoparticle delivery, remains in early translation. This review examines the molecular basis of β-glucan-induced immunostimulation, emphasizing how linkage type, branching frequency, triple-helical structure, and source influence receptor engagement and downstream immune responses. Emerging evidence is presented on β-glucan formulation engineering, including β-glucan-coated polymeric nanoparticles and micelles, β-glucan-complexed lipid nanoparticles for nucleic acid delivery, polymersomes with splenic/myeloid avidity, and β-glucan-stabilized nanosuspensions, several of which show enhanced lymphatic targeting, improved drug bioavailability, or reduced tumor growth in preclinical cancer models. Clinical translation is analyzed with attention to dosing protocols, administration routes (oral, intravenous, topical), and the impact of β-glucan adjuvancy in therapeutic antibodies, immunotoxins, and vascular disrupting agents. The review further addresses essential safety and toxicology data, regulatory compliance challenges, and the imperative for rigorous physicochemical standardization to ensure clinical reproducibility and patient safety. β-glucans have emerged as multifunctional immunomodulators and drug delivery enhancers, driving progress toward personalized cancer immunotherapy and innovative combinatorial regimens. Continued interdisciplinary research and harmonization of extraction, characterization, and delivery protocols are paramount for success in precision oncology.