Cancer Biotherapy and Radiopharmaceuticals最新文献

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.

Introduction: Epithelial cell adhesion molecule (EpCAM) is overexpressed in a wide range of epithelial malignancies, and thus is a potential target for antibody-based radiotherapy. This work describes the synthesis, labeling, and biological evaluation of an alpha-emitting radioconjugate, [²²⁵Ac]Ac-Macropa-PEG₄-HEA125, as a targeted alpha therapy candidate for EpCAM-positive tumors.

Materials and methods: The murine anti-EpCAM monoclonal antibody HEA125 was site-specifically conjugated to the chelator Macropa using a PEG₄-maleimide linker. The structural integrity and chelator-to-antibody (C/A) ratio of the conjugate were confirmed by SDS-PAGE and LC-MS. Radiolabeling with ²²⁵Ac was performed under mild conditions, and radiochemical purity was assessed using iTLC and radio-HPLC. In vitro studies included stability testing, immunoreactivity, and cytotoxicity assays using MCF-7 (EpCAM⁺) and CHO-K1 (EpCAM^-) cell lines. In vivo biodistribution and therapeutic efficacy were evaluated in MCF-7 xenograft-bearing female athymic nude mice (BALB/c nu/nu).

Results: Conjugation with HEA125 resulted in a C/A ratio of 4.2 ± 0.3, and SDS-PAGE proved integrity of antibodies to be preserved. Purity of radiolabeling was >98%, and >94% stability was retained for more than 120 h both in PBS and serum. Immunoreactive fraction was 86.2 ± 2.4%, and cytotoxicity assays showed, dose-dependent MCF-7 cell killing with minimal impact on EpCAM-negative controls. In vivo, [²²⁵Ac]Ac-Macropa-PEG₄-HEA125, exhibited significant tumor uptake (15.7 ± 2.3 %ID/g at 24 h), maintained retention (12.1 ± 1.9 %ID/g at 72 h), and minimal off-target accumulation. Therapeutic injection resulted in extensive tumor growth inhibition and long-term survival, with 60% of the mice surviving past day 30 with little overt toxicity.

Conclusions: [²²⁵Ac]Ac-Macropa-PEG₄-HEA125, establishes high radiochemical purity, in vitro stability, EpCAM specificity, and strong antitumor activity in preclinical models. These results warrant its advancement as a promising targeted alpha therapy candidate for EpCAM-expressing carcinomas.

Background: Dynamic characteristics such as cancer stemness and the epithelial-to-mesenchymal transition (EMT) cause the spread of colorectal cancer (CRC). Although there are now few pharmaceutical approaches, therapeutically correcting these conditions may improve prognosis. Acoustic radiation force and other mechanical ultrasonic forces have become new, noninvasive methods for modifying tumor biology. Nevertheless, little is known about their molecular influence on CRC EMT-stemness pathways.

Materials and methods: The authors created a simulation pipeline to predict the effects of ultrasound-induced mechanical stress on CRC samples enriched for tumor-infiltrating T cells using transcriptome datasets (GSE108989). Heatmap visualizations, differential expression, pathway enrichment, principal component analysis (PCA), and EMT and stemness scores were computed using bulk RNA-seq. To evaluate mechanistic suppression, signaling axes such as TGF-β, Wnt/β-catenin, Notch, and yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) were investigated. The potential ultrasonic sensitivity of key gene modules was assessed.

Results: Mesenchymal and stemness-associated transcriptional pathways were found to be downregulated in response to simulated acoustic modulation. Coherent clustering of decreased EMT/stemness genes was shown via heatmaps. Modified tumor groupings were identified by PCA. In the simulated postultrasound condition, canonical pathways associated with invasion, immunological evasion, and stemness maintenance were diminished. These results lend credence to the theory that CRC cellular plasticity may be reprogrammed by mechanical ultrasonic force.

Conclusions: Early mechanistic understanding of how acoustic force-based ultrasound may inhibit EMT and stemness in CRC is provided by this transcriptome simulation. This data-driven approach presents ultrasound as a promising supplement to immune-oncology and antimetastatic methods and encourages more in vitro validation.

Background: Focused ultrasound, low-intensity focused ultrasound, and microbubble-enhanced sonoporation are examples of ultrasound-based cancer therapies that have shown promise as biophysical modalities for enhancing drug penetration, immunogenic cell death, and targeted delivery of radiopharmaceuticals in solid tumors. The molecular factors controlling ultrasonic therapy receptivity, however, are still not well understood. Because of the significant variability of the tumor microenvironment (TME), colorectal cancer (CRC) necessitates biomarker-guided techniques to enhance ultrasound-based therapy regimens.

Methods: To investigate serotonylation-related and hallmark-pathway-related genes that might influence ultrasound-responsive cellular pathways, such as extracellular matrix (ECM) remodeling, mechanotransduction, and immune activation, the authors combined bulk RNA-sequencing (RNS-seq) (TCGA-COAD), single-cell RNA-seq (GSE132465), and spatial transcriptomics (GSE280313) datasets. Nine prognostic genes were found using survival analysis and differential expression screening. To create a prognostic classifier with translational relevance for ultrasonic therapies, the authors used non-negative matrix factorization clustering, single-cell functional scoring, spatial deconvolution, and 101 machine-learning models.

Results: Of the 2475 serotonylation-hallmark genes found, 784 exhibited differential expression in tumor and normal tissues. CRC was divided into six molecular subgroups with different TME symptoms and survival patterns by nine important prognostic genes (PCOLCE2, TIMP1, FJX1, FABP4, CALB2, NAT1, CDKN2A, FSTL3, and INHBB). Elevated stromal activation, epithelial-mesenchymal transition signals, macrophage infiltration, and ECM stiffness were seen in high-risk clusters; these variables are known to affect cavitation thresholds, ultrasonic energy absorption, and treatment response. Strong prognostic accuracy was demonstrated by the final RSF-SuperPC model (concordance index 0.72-0.85 across validation cohorts). Strong enrichment in mechanotransduction, oxygen metabolism, and immune chemotaxis pathways-pathways previously demonstrated to regulate ultrasound-triggered drug delivery and immune activation-was revealed by functional studies.

Conclusions: This multiomics integration reveals a serotonylation-hallmark gene signature that represents microenvironmental characteristics, such as matrix stiffness, stromal density, and immune infiltration, that are pertinent to ultrasound-based CRC therapy. These biomarkers could direct patient classification for radiopharmaceutical, immunotherapy, and ultrasound-enhanced medication delivery. This work supports future clinical trial stratification frameworks and offers a mechanistic basis for precision ultrasound oncology.

Malignant brain tumors remain a major therapeutic challenge due to poor intracellular delivery of therapeutics. Radiopharmaceuticals such as Technetium-99m (^^99mTc) are valuable for imaging and therapy but suffer from limited tumor uptake caused by cellular and membrane barriers. Focused ultrasound (FUS) offers a noninvasive strategy to transiently enhance membrane permeability through sonoporation. Unlike prior studies largely focused on blood-brain barrier disruption, this work specifically investigates direct tumor cell sonoporation as an independent uptake mechanism. This study evaluates FUS-mediated enhancement of ^^99mTc radiopharmaceutical uptake in brain tumor cells and determines optimal acoustic parameters balancing efficacy and safety. Human glioblastoma (U87-MG) and astrocytoma (A172) cells were cultured and exposed to FUS at intensities of 0.3, 0.5, and 0.7 W/cm² for 30-120 s. Radiopharmaceutical uptake was quantified using γ-scintillation counting. Membrane integrity was assessed by live/dead fluorescence microscopy and lactate dehydrogenase release, while cell viability was evaluated via medical training therapy (MTT) assays. U87-MG cells exhibited up to a 3.1-fold increase at 0.7 W/cm² for 120 s, with a 2.3-fold enhancement at the clinically relevant 0.5 W/cm² for 60 s while maintaining >92% viability. A172 cells showed similar trends with slightly lower magnitudes. Safety assays confirmed reversible membrane permeabilization at ≤0.5 W/cm². The temporal uptake kinetics aligned with established membrane pore resealing dynamics, supporting reversible sonoporation as the uptake mechanism. Importantly, while ^^99mTc complexes are primarily diagnostic, enhanced intracellular delivery achieved by optimized FUS may also support future theranostic strategies, including radionuclide therapy. These findings underscore the translational potential of FUS in neuro-oncology, where tumor heterogeneity necessitates parameter optimization to maximize radiopharmaceutical delivery, improve imaging contrast, and overcome therapeutic resistance.

Background: Early diagnosis and accurate prediction of treatment response in esophageal squamous cell carcinoma (ESCC) remain major clinical challenges due to the lack of reliable and noninvasive biomarkers. Recently, artificial intelligence-driven endoscopic ultrasound image analysis has shown great promise in revealing genomic features associated with imaging phenotypes.

Methods: A prospective study of 115 patients with ESCC was conducted. Deep features were extracted from endoscopic ultrasound using a ResNet50 convolutional neural network. Important features shared across three machine learning models (NN, GLM, DT) were used to construct an image-derived signature. Plasma levels of leukotriene B4 (LTB4) and other inflammatory markers were measured using enzyme-linked immunosorbent assay. Correlations between signature and inflammation markers were analyzed, followed by logistic regression and subgroup analyses.

Results: The endoscopic ultrasound image-derived signature, generated using deep learning algorithms, effectively distinguished esophageal cancer from normal esophageal tissue. Among all inflammatory markers, LTB4 exhibited the strongest negative correlation with the image signature and showed significantly higher expression in the healthy control group. Multivariate logistic regression analysis identified LTB4 as an independent risk factor for ESCC (odds ratio = 1.74, p = 0.037). Furthermore, LTB4 expression was significantly associated with patient sex, age, and chemotherapy response. Notably, higher LTB4 levels were linked to an increased likelihood of achieving a favorable therapeutic response.

Conclusions: This study demonstrates that deep learning-derived endoscopic ultrasound image features can effectively distinguish ESCC from normal esophageal tissue. By integrating image features with serological data, the authors identified LTB4 as a key inflammation-related biomarker with significant diagnostic and therapeutic predictive value.

Background: Colorectal cancer (CRC), the second leading cause of cancer-related deaths globally, continues to lack effective early diagnostic biomarkers and therapeutic strategies. Minichromosome maintenance protein 10 (MCM10), a replication initiation factor implicated as a pan-cancer marker, remains poorly characterized in CRC. Its role within the p53/p21/Cyclin D1 (CCND1) regulatory axis and its potential as a therapeutic target, particularly under ultrasound-based modulation, warrants investigation.

Methods: Integrated bioinformatic analyses were conducted using public databases to evaluate MCM10 expression and clinical significance. Clinical CRC specimens were analyzed via qPCR and immunohistochemistry to validate MCM10 expression. Functional assays, including colony formation, cell counting kit-8 (CCK-8), Transwell migration/invasion, and flow cytometry, assessed the biological effects of MCM10 knockdown on proliferation, apoptosis, and cell cycle. Western blotting and rescue experiments elucidated signaling pathways. A CRC mouse xenograft model was established to evaluate in vivo tumor growth. The therapeutic modulation of MCM10-related pathways using ultrasound-based interventions was preliminarily assessed.

Results: MCM10 expression was significantly upregulated in cell lines and CRC tissues, and correlated with poor prognosis. Silencing MCM10-impaired CRC cell proliferation, invasion, migration, and induced G1/S cell cycle arrest suppressed epithelial-mesenchymal transition and increased apoptosis. Mechanistically, MCM10 knockdown activated the p53/p21 axis and downregulated CCND1 expression. In vivo, MCM10 inhibition suppressed xenograft tumor growth. Ultrasound exposure exhibited the potential to enhance the therapeutic effects of MCM10 suppression by modulating the MCM10/p53/p21/CCND1 axis.

Conclusions: These findings reveal that MCM10 promotes CRC malignancy through inhibiting the tumor-suppressive p53/p21/CCND1 pathway. Targeting this axis, particularly through ultrasound-enhanced delivery or sensitization strategies, holds promise as a novel therapeutic approach in CRC.

Background: Accurate and noninvasive breast cancer grading and therapy monitoring remain critical challenges in oncology. Traditional methods often rely on invasive histopathological assessments or imaging-only techniques, which may not fully capture the molecular and morphological intricacies of tumor response.

Method: This article presents a novel, noninvasive framework for breast cancer analysis and therapy monitoring that combines two parallel mechanisms: (1) a dual-stream convolutional neural network (CNN) processing high-intensity ultrasound images, and (2) a biomarker-aware CNN stream utilizing patient-specific breast cancer biomarkers, including carbohydrate antigen 15-3, carcinoembryonic antigen, and human epidermal growth factor receptor 2 levels. The imaging stream extracts spatial and morphological features, while the biomarker stream encodes quantitative molecular indicators, enabling a multimodal understanding of tumor characteristics. The outputs from both streams are fused to predict the cancer grade (G1-G3) with high reliability.

Results: Experimental evaluation on a cohort of pre- and postchemotherapy patients demonstrated the effectiveness of the proposed approach, achieving an overall grading accuracy of 97.8%, with an area under the curve of 0.981 for malignancy classification. The model also enables quantitative post-therapy analysis, revealing an average tumor response improvement of 41.3% across the test set, as measured by predicted regression in grade and changes in biomarker-imaging correlation.

Conclusions: This dual-parallel artificial intelligence strategy offers a promising noninvasive alternative to traditional histopathological and imaging-alone methods, supporting real-time cancer monitoring and personalized treatment evaluation. The integration of high-resolution imaging with biomolecular data significantly enhances diagnostic depth, paving the way for intelligent, patient-specific breast cancer management.

Introduction: [⁶⁸Ga]Ga-prostate-specific membrane antigen (PSMA)-11 positron emission tomography (PET)/computed tomography (CT) imaging has demonstrated clinical value for individuals with prostate cancer (PC). In this phase 2 study, we measured the pharmacokinetics and dosimetry of [⁶⁸Ga]Ga-PSMA-11 in Chinese participants.

Methods: Adult Chinese participants with progressive metastatic castration-resistant PC (mCRPC) received a single intravenous [⁶⁸Ga]Ga-PSMA-11 dose of approximately 150 MBq. Blood samples were collected at 5, 15, 30, 45, 85, 175, and 245 min post injection for pharmacokinetics assessments. Whole-body PET scans and low/ultra-low-dose CT scans were acquired at 30, 60, 120, and 255 min post injection for dosimetry assessments.

Results: Pharmacokinetics and dosimetry assessments were completed in seven participants who received a [⁶⁸Ga]Ga-PSMA-11 dose (range: 108.3-236.7 MBq). In the blood, the geometric mean effective terminal half-life was 1.34 h (geometric coefficient of variation [geo-CV], 182%); geometric mean clearance was 9.80 L/h (geo-CV, 106%). The highest absorbed doses were seen in the kidneys, urinary bladder walls, and lacrimal glands. In the study population, the geometric mean (geo-CV) effective dose of [⁶⁸Ga]Ga-PSMA-11 was 4.2 mSv (32.9%).

Conclusions: The pharmacokinetic and dosimetry profiles of [⁶⁸Ga]Ga-PSMA-11, assessed using a validated method in participants with progressive mCRPC, make it very suitable as an imaging agent.

Background: Colorectal cancer (CRC) development and therapy resistance are heavily controlled by the tumor microenvironment (TME). Although anti-PD-1 immunotherapy has significant therapeutic advantages, resistance remains a key challenge. Recent research has identified the gut microbiota as a key regulator of host immunity and checkpoint inhibitor effectiveness. Ultrasound (US) has emerged as a viable biophysical technique for improving medication and microbial delivery and controlling immune activation within tumors.

Objectives: The purpose of this work was to assess the synergistic effects of US-assisted fecal microbiota transplantation (US-FMT) on TME remodeling and anti-PD-1 resistance in a CRC cell line-derived xenograft mouse model.

Materials and methods: Tumor-bearing mice were randomized into four treatment groups: vehicle control, anti-PD-1 alone, fecal microbiota transplantation (FMT) alone, and US-FMT plus anti-PD-1 therapy. Low-intensity focused US was utilized to promote microbial engraftment and intestinal permeability. Flow cytometry, ELISA, and transcriptome profiling were used to investigate tumor growth kinetics, immune cell infiltration, cytokine profiles, and TME-related gene expression.

Results: In comparison with the other groups, US-FMT reduced tumor development and restored sensitivity to anti-PD-1 treatment. US facilitated beneficial microbial colonization, boosted CD8 T cell infiltration, and decreased immunosuppressive cell populations. Furthermore, US-FMT modified cytokine release and reduced pro-tumorigenic inflammatory mediators, reprogramming the TME to be immune-active.

Conclusions: US-assisted microbiota manipulation is a unique and synergistic biotherapeutic method for reversing immunological resistance in CRC. The combination of US and FMT has translational promise for enhancing immunotherapy response and developing noninvasive cancer treatment techniques.