Prostate cancer is the most common cancer in over 50% of the countries and the third most common malignancy worldwide. The tumor microenvironment denotes the non-cancerous cells and components present in the tumor, including the molecules they produce and release. Prostate cancer proliferation, angiogenesis, metastasis and drug resistance are closely associated with the tumor microenvironment. With the continuous development of in vitro tumor models, they have gradually become an important tool for recapitulating parental tumors in vivo and studying the reciprocal interactions between tumors and their microenvironment. In this review, we describe significant in vitro models of prostate cancer, analyze the research results on incorporating the tumor microenvironment into these models, and compare their advantages and disadvantages. Furthermore, we highlight the future developmental direction of prostate cancer in vitro model research according to the hotspots of in vitro model research in other cancer types to facilitate precision medicine in prostate cancer.

Background: In the context of precision diagnosis for various subtypes of melanoma, identifying biomarkers with clinical translational potential from a molecular standpoint is crucial for a more comprehensive characterization of the disease. MUC18 is highly expressed in both tumor cells and tumor vasculature in major melanoma subtypes and is restricted to normal tissues. Methods: A noninvasive imaging approach for MUC18 in melanoma utilizing an immune Positron Emission Tomography (PET) radionuclide-conjugated drug (RDC) with an 89Zr-labeled humanized anti-MUC18 monoclonal antibody (mAb) was developed. A375, Sk-Mel-28, HMVII, and A549 cells and tumor model mice were conducted. Immuno-PET was employed to assess the specificity and targeting of three distinct melanoma cell line-derived xenografts (CDXs) and patient-derived tumor xenografts (PDXs) in immunodeficient mice. Results: The developed RDC, named 89Zr-IP150, demonstrated robust in vitro stability and high binding affinity, ensuring reliable and specific PET imaging of small, medium, and large subcutaneous tumors in human melanoma mouse xenotransplantation models. Notably, for the first time, the clinical translational potential of 89Zr-IP150 was successfully validated using a PDX model. Conclusions: These findings present a noninvasive, real-time method for the early screening of MUC18 (+) melanoma patients and are important for studying the early-stage biological distribution of MUC18-targeted antibody‒drug conjugates (ADCs).

The efficacy and reliability of super-resolution (SR) imaging for evaluating urethral vasculature (UV) in females remains uncertain. This study evaluates the Super Resolution for Greater Accuracy and Resolution (SUGAR) method, an SR modality, for visualizing UV in female pigs within clinical ultrasound settings, aiming to establish its clinical feasibility and accuracy for potential human application. Female pigs (40-45 kg) were used to investigate UV blood flow dynamics, with data collected via a handheld ultrasound probe at 100 fps. The images were processed using SUGAR to achieve a resolution of 30 μm and validated against computed tomography angiography (CTA) and histopathological analyses. SUGAR demonstrated superior capability in visualizing urethral blood flow compared to CTA, allowing for detailed multiparametric analysis of UV, including fractal dimension, vessel density, tortuosity, diameter, and blood flow velocity. Strong correlations between SUGAR imaging and histopathological findings underscore its potential clinical applicability for diagnosing and managing urological conditions in humans.

Over the past century, the field of antibody discovery has undergone significant evolution, excluding the current exploration stage of AI-based antibody generation and the often overlooked non-animal sourced antibody discovery, which typically requires mature in vitro affinity and the selection of high-quality antigen formulations. This journey has traversed various stages, from methods involving serum-based antibody acquisition, the isolation of B cells capable of perpetual antibody production through hybridoma technology, to the in-depth exploration of genetic material using the phage display system, and the current stage involving diverse single B cell screening techniques. Additionally, the emergence of machine learning has brought impressive scientific and technological breakthroughs across research domains, proving to be a powerful application in the field of antibody discovery. However, each technique comes with its limitations, such as variability and control challenges in serum-based acquisition, lengthy and difficult hybridoma-derived antibody development, potential limitations in sequence and epitope diversity due to immunization biases in phage display techniques, and costly single B cell screening. Protein mass spectrometry sequencing, with shorter acquisition time and lower costs, is seen as a shortcut by diagnostic companies, impacting traditional antibody development. In diagnostic antibody development, methodological differences in downstream assays and the impact of constant regions outside the Fv core are often neglected. This paper deeply analyzes challenges, proposing innovative strategies for the next generation of diagnostic antibody development. Aimed at moving closer to the gold standard of antibody discovery, these strategies enhance the competitiveness of diagnostic reagent products.

Exosomes are nanoscale membrane vesicles identified by electron microscopy in 1946. They are approximately 30-150 nanometers in size. Originally, exosomes were thought to be used to eliminate excess components from cells to maintain their normal physiology. In recent years, studies have shown that the function and targeting of specific cellular components in exosomes have important implications for the regulation of cellular communication. In the last few years, exosomes have been implicated in oncology, infections and other diseases and have been shown to have an impact on cancer progression. New advances in cancer immunotherapy have occurred as a result of the identification of Exosomes of immune cell origin, expanding the existing anti-cancer immune response. This paper details exosomes derived from dendritic cells, T-lymphocytes (CD4+ T-cells, CD8+ T-cells, CAR-T-cells), natural killer cells and their promising applications in tumor therapy.

Gliomas are highly heterogenous diseases with poor prognosis. Precise survival prediction could benefit further clinical decision-making, clinical trial incursion and health economics. Recent research has emphasized the prognostic value of magnetic resonance imaging, pathological specimens and circulating biomarkers. However, the integrative potential and efficacy of these modalities require to be further validated. After incorporating 218 patients of TCGA glioma datasets of and 54 patients of Huashan cohort with complementary prognostic information, we established Squeeze-and-excitation deep learning feature extractor (SE-DLFE) for T1-contrast enhanced images and histological slides, and explored to screen significant circulating 5-hydroxymethylcytosines (5hmC) profiles for glioma survival by LASSO-Cox regression. Therefore, a prognostication predictive model with high efficiency was obtained through survival support vector machine (SVM) multimodal integration of radiologic imaging, histopathologic imaging features, genome-wide 5hmC in circulating cell-free DNA (cf-DNA) and clinical variables, suggesting a valid strategy (C-index = 0.897; Brier score = 0.118) for improved survival risk stratification of glioma patients.

Surface-enhanced Raman scattering (SERS) has become an essential bio-detection technique. Due to its high sensitivity, good signal specificity, and resistance to photobleaching, SERS has been widely used in biomedical research fields such as molecular imaging, tumor diagnosis, and drug monitoring. This review focuses on the progress of SERS in biomedical applications. We first introduce the basic principle of SERS and the progress of substrate research. Then we summarize the latest research progress of SERS in drug monitoring, cell and exosome detection, tumor imaging, and detection platforms combining microfluidic and lateral flow technologies. Subsequently, the applied research of SERS in early diagnosis of pancreatic cancer and drug efficacy monitoring is described. Finally, the future development direction and possible challenges of SERS in tumor diagnosis and treatment are proposed.

DNA logic programming, based on the principles of base complementarity and Boolean operations, exhibits organizational structures and computational rules similar to machine language. Consequently, DNA logic programming enables programming, decision-making, and output capabilities consistent with machine language in real-world applications. In recent years, the thinking behind DNA logic programming has synergized with life sciences, medicine, and various interdisciplinary fields, establishing an intelligent and digitized research framework. It has paved the way for cutting-edge interdisciplinary research and facilitated the transition of DNA logic programming from concept to construction. This article provides an overview of recent research achievements in the field of DNA logic programming in biomedical applications, focusing on the design and implementation of DNA logic programming and further exploring its advantages and challenges in frontier research areas.

The cellular uptake of drug carriers to the cytosol of a specific cell remains challenging, and a non-classical supramolecular strategy is motivated. Here, we select a model host-guest complex in which a diamino-viologen (VG) fluorescent tag was engulfed by cucurbit[8]uril (CB8) and covalently linked to alginate polysaccharides (ALG) as the modified drug vehicle. When adsorbed on the ALG surface, the encapsulation of VG was first confirmed utilizing FTIR and NMR spectroscopic methods. Solid optical measurements (DRS, PL, and TRPL) revealed emissive materials at around 650 nm and that CB8 enhanced the rigidity of the modified hydrogel. The molar composition of 2 to 1 for the complexation of VG to CB8 on the alginate surface and the thermal stabilities were also confirmed using TGA and DSC techniques. CB8 induced a dramatic decrease in the average size of the VGALG polysaccharides from 485 to 165 nm and a turnover in their charge from -19.8 to +14.4 mV. Flow cytometry with inhibitors of various endocytosis pathways was employed to track the cellular uptake across different blood cell types: human T-cell leukemia 1301 and peripheral blood mononuclear cells. Noticeably, complexation of VG to CB8 host on top of the sugar platform dramatically enhanced the internalization to 1301 cells (viz. from 1 to 99%) at a concentration of 1.8 mg/mL via caveolae-mediated endocytosis (CvME) because of the size reduction, turnover in the charge from negative to positive, and rigidity induction. These observations reveal a more profound understanding of the macrocyclic effects on drug delivery

Alzheimers disease (AD) is a common neurodegenerative disease. The histopathological changes of AD include amyloid β-protein (Aβ) deposition, tau tangles, neuroinflammation and neurodegeneration. Some of the pathological changes could be shown in vivo by positron emission tomography (PET) and magnetic resonance imaging (MRI) biomarkers which play a key role in diagnosing AD. Fluorodeoxyglucose positron emission tomography (FDG-PET) can reflect and predict dysfunction. Aβ-PET was sensitive for the diagnosis of early AD but cannot distinguish the severity of AD. Tau-PET can compensate for the deficiency of Aβ-PET. Tau tangles were positively correlated with the severity of AD, and also associated with cognitive impairment. Probes targeting neuroinflammation of AD have been developed, but further study is needed to validate its effectiveness. Conventional MRI performs high tissue contrast that can show structural changes and has been routinely applied in clinical practice, such as evaluation of cerebral atrophy. Advanced MRI sequences (such as DTI、ASL、MRS、BOLD and QSM) that can provide additional information beyond structure that includes brain microstructure, blood perfusion, metabolite concentration, brain activity, connections and networks between brain regions, iron deposition, etc. The integrated PET and MR may improve the diagnostic efficiency of AD.

Organoids are three-dimensional cell aggregates with near-physiologic cell behaviors and can undergo long-term expansion in vitro. They are amenable to high-throughput drug screening processes, which renders them a viable preclinical model for drug development. The procedure of organoid-based high-throughput screening has been extensively employed to discover small molecule drugs, encompassing the steps of generating organoids, examining efficient drugs in organoid cultures, and data assessment. Compared to small molecules, peptides are more straightforward to synthesize, can be modified chemically, and demonstrate a high degree of target specificity and low cytotoxicity. Therefore, they have emerged as promising carriers to deliver drugs to disease-associated targets, and could be efficient therapeutic drugs for various diseases. To date, organoids have been used to evaluate the efficacy of certain peptide agents; however, no organoid-based high-throughput screening of peptide drugs has been reported. Given the advantages of peptide drugs, there is an urgent need to establish organoid-based peptide high-throughput screening platforms. In this review, we discuss the typical approach of screening small-molecular drugs with the use of organoid cultures, as well as provide an overview of the studies that have incorporated organoids in peptide research. Drawing on the knowledge gained from small molecular screens, we explore the difficulties and potential avenues for creating new platforms to identify peptide agents using organoid models.

Biosafe wearable healthcare monitor has attracted significant attention owing to their applicability to wearable electronics. However, the narrow sensing range and poor response limit the application of flexible devices for comprehensive monitoring of human health-related physiological signals (i.e. pulse diagnosis). Critical challenges remain in the development of biocompatible materials and the design of flexible bio-integrated platforms for these purposes, targeting performance approaching those of conventional wafer-based technologies and long-term operational stability. In this context, this work presents a robust and flexible MXene/polydopamine (PDA)-composite-film-based pressure sensor in a portable/wearable fashion, which establishes a unique intercalated spherical-like PDA molecules structure, thereby resulting in excellent sensing performance. The MXene/PDA-based pressure sensor has sensitivity of up to 138.8 kPa-1 in the pressure range of 0.18-6.20 kPa with fast response and recovery speed (t1<100 ms; t2<50 ms). Associated embodiment involves real-time precise measurements of a variety of health-related physiological signals, ranging from wrist pulse, to finger motions, to vocalization and to facial expressions, with high sensitivity and accuracy. Studies on human subjects establish the clinical significance of these devices for future opportunities of health monitoring and intelligent control to predict and diagnose diseases.

Cuproptosis, the current form of regulated cell death characterized by copper overload, oligomerization of lipoacylated proteins, and loss of the Fe-S cluster proteins, has been proposed to function closely with human diseases including cancer. Since the first identification in 2022, a wide range of strategies have been developed to induce cuproptosis for cancer therapy, such as small-molecule drugs and nanomaterials. Although many reviews related to cuproptosis have been reported, they remain at a basic mechanism level and a summary covering recent progress in the field of nanotechnologies in cuproptosis-based cancer therapy has not yet been presented. Therefore, it is time to fill the gap and shed light on future directions for the application of this promising tool to fight against cancer. In this minireview, we first expounded the mechanism of action of cuproptosis and emphasized the feasibility of triggering cuproptosis for cancer therapy. The recent progress of cancer treatments based on nanoparticle-induced cuproptosis was then described. Finally, the challenges and future development directions of the emerging field of cuproptosis were also discussed.