A clinical-radiomic-pathomic model for prognosis prediction in patients with hepatocellular carcinoma after radical resection.

PURPOSE: Radical surgery, the first-line treatment for patients with hepatocellular cancer (HCC), faces the dilemma of high early recurrence rates and the inability to predict effectively. We aim to develop and validate a multimodal model combining clinical, radiomics, and pathomics features to predict the risk of early recurrence. MATERIALS AND METHODS: We recruited HCC patients who underwent radical surgery and collected their preoperative clinical information, enhanced computed tomography (CT) images, and whole slide images (WSI) of hematoxylin and eosin (H & E) stained biopsy sections. After feature screening analysis, independent clinical, radiomics, and pathomics features closely associated with early recurrence were identified. Next, we built 16 models using four combination data composed of three type features, four machine learning algorithms, and 5-fold cross-validation to assess the performance and predictive power of the comparative models. RESULTS: Between January 2016 and December 2020, we recruited 107 HCC patients, of whom 45.8% (49/107) experienced early recurrence. After analysis, we identified two clinical features, two radiomics features, and three pathomics features associated with early recurrence. Multimodal machine learning models showed better predictive performance than bimodal models. Moreover, the SVM algorithm showed the best prediction results among the multimodal models. The average area under the curve (AUC), accuracy (ACC), sensitivity, and specificity were 0.863, 0.784, 0.731, and 0.826, respectively. Finally, we constructed a comprehensive nomogram using clinical features, a radiomics score and a pathomics score to provide a reference for predicting the risk of early recurrence. CONCLUSIONS: The multimodal models can be used as a primary tool for oncologists to predict the risk of early recurrence after radical HCC surgery, which will help optimize and personalize treatment strategies.

Enhancing Specific Fluorescence In Situ Hybridization with Quantum Dots for Single-Molecule RNA Imaging in Formalin-Fixed Paraffin-Embedded Tumor Tissues.

Single-molecule fluorescence in situ hybridization (smFISH) represents a promising approach for the quantitative analysis of nucleic acid biomarkers in clinical tissue samples. However, low signal intensity and high background noise are complications that arise from diagnostic pathology when performed with smFISH-based RNA imaging in formalin-fixed paraffin-embedded (FFPE) tissue specimens. Moreover, the associated complex procedures can produce uncertain results and poor image quality. Herein, by combining the high specificity of split DNA probes with the high signal readout of ZnCdSe/ZnS quantum dot (QD) labeling, we introduce QD split-FISH, a high-brightness smFISH technology, to quantify the expression of mRNA in both cell lines and clinical FFPE tissue samples of breast cancer and lung squamous carcinoma. Owing to its high signal-to-noise ratio, QD split-FISH is a fast, inexpensive, and sensitive method for quantifying mRNA expression in FFPE tumor tissues, making it suitable for biomarker imaging and diagnostic pathology.

Aptamer-based expansion microscopy platform enables signal-amplified imaging of dendritic spines.

Super-resolution imaging of dendritic spines (DS) can provide valuable information for mechanistic studies related to synaptic physiology and neural plasticity, but challenged by their small dimension (50-200 nm) below the spatial resolution of conventional optical microscopes. In this work, by combining the molecular recognition specificity of aptamer with high programmability of DNA nanotechnology, we developed an expansion microscopy (ExM) platform for imaging DS with enhanced spatial resolution and amplified signal output. Our results demonstrated that the aptamer probe could specifically bind to DS of primary hippocampal neurons. With physical expansion, the DS structure could be effectively enlarged by 4-5 folds, leading to the generation of more structural information. Meantime, the aptamer binding signal could be readily amplified by the introduction of DNA signal amplification strategy, overcoming the drawback of fluorescence dilution during the ExM treatment. This platform enabled evaluation of ischemia-induced early stroke based on the morphological change of DS, highlighting a promising avenue for studying nanoscale structures in biological systems.

Multi-parameter Inputted Logic-Gating on Aptamer-Encoded Extracellular Vesicles for Colorectal Cancer Diagnosis.

Extracellular vesicles (EVs) have emerged as a potential biomarker in liquid biopsy. However, cancer heterogeneity poses significant challenge to precise molecular diagnosis based on single-parameter input. Hence, strategies for analyzing multiple inputs with molecular computing were developed with the aim of improving diagnostic accuracy in liquid biopsy. In the present study, based on the surface of aptamer-encoded EVs, three toe-hold extended DNA aptamers served as specific inputs to perform AND-logic-gating to distinguish between healthy and cancerous EVs. In addition, this strategy has been successfully employed to analyze circulating EVs in clinical samples from colorectal cancer patients and healthy donors. The developed method has a promising future in the analysis of multiplex EV membrane proteins and the identification of early cancer.

Manipulation of Multiple Cell-Cell Interactions by Tunable DNA Scaffold Networks.

Manipulation of cell-cell interactions via cell surface engineering has potential biomedical applications in tissue engineering and cell therapy. However, manipulation of the comprehensive and multiple intercellular interactions remains a challenge and missing elements. Herein, utilizing a DNA triangular prism (TP) and a branched polymer (BP) as functional modules, we fabricate tunable DNA scaffold networks on the cell surface. The responsiveness of cell-cell recognition, aggregation and dissociation could be modulated by aptamer-functionalized DNA scaffold networks with high accuracy and specificity. By regulating the DNA scaffold networks coated on the cell surface, controlled intercellular molecular transportation is achieved. Our tunable network provides a simple and extendible strategy which addresses a current need in cell surface engineering to precisely manipulate cell-cell interactions and shows promise as a general tool for controllable cell behavior.

AGMB-Transformer: Anatomy-Guided Multi-Branch Transformer Network for Automated Evaluation of Root Canal Therapy.

Accurate evaluation of the treatment result on X-ray images is a significant and challenging step in root canal therapy since the incorrect interpretation of the therapy results will hamper timely follow-up which is crucial to the patients' treatment outcome. Nowadays, the evaluation is performed in a manual manner, which is time-consuming, subjective, and error-prone. In this article, we aim to automate this process by leveraging the advances in computer vision and artificial intelligence, to provide an objective and accurate method for root canal therapy result assessment. A novel anatomy-guided multi-branch Transformer (AGMB-Transformer) network is proposed, which first extracts a set of anatomy features and then uses them to guide a multi-branch Transformer network for evaluation. Specifically, we design a polynomial curve fitting segmentation strategy with the help of landmark detection to extract the anatomy features. Moreover, a branch fusion module and a multi-branch structure including our progressive Transformer and Group Multi-Head Self-Attention (GMHSA) are designed to focus on both global and local features for an accurate diagnosis. To facilitate the research, we have collected a large-scale root canal therapy evaluation dataset with 245 root canal therapy X-ray images, and the experiment results show that our AGMB-Transformer can improve the diagnosis accuracy from 57.96% to 90.20% compared with the baseline network. The proposed AGMB-Transformer can achieve a highly accurate evaluation of root canal therapy. To our best knowledge, our work is the first to perform automatic root canal therapy evaluation and has important clinical value to reduce the workload of endodontists.

Engineering DNA on the Surface of Upconversion Nanoparticles for Bioanalysis and Therapeutics.

Surface modification of inorganic nanomaterials with biomolecules has enabled the development of composites integrated with extensive properties. Lanthanide ion-doped upconversion nanoparticles (UCNPs) are one class of inorganic nanomaterials showing optical properties that convert photons of lower energy into higher energy. Additionally, DNA oligonucleotides have exhibited powerful capabilities for organizing various nanomaterials with versatile topological configurations. Through rational design and nanotechnology, DNA-based UCNPs offer predesigned functionality and potential. To fully harness the capabilities of UCNPs integrated with DNA, various DNA-UCNP composites have been developed for diagnosis and therapeutics. In this review, beginning with the introduction of the UCNPs and the conjugation of DNA strands on the surface of UCNPs, we present an overview of the recent progress of DNA-UCNP composites while focusing on their applications for bioanalysis and therapeutics.

G-Quadruplex-Induced Liquid-Liquid Phase Separation in Biomimetic Protocells.

Biomolecular condensates comprised of specific proteins and nucleic acids are now recognized as one of the key organizing mechanisms in eukaryotic cells. However, the specific roles played by the nucleic acid secondary structure and sequence in biomolecular phase separation are still not clear. Here, utilizing giant membrane vesicles (GMVs) as a protocell model, we found that single-stranded DNA (ssDNA) with a parallel G-quadruplex structure could functionally cooperate with a G-quadruplex-binding protein to form speckle-like puncta inside the GMVs. The clustering behavior is dependent on the structural diversity of G-quadruplexes, and the reversible clustering behavior implicated a new pathway in dynamically regulating the formation of biomolecular condensates. This finding represents a potential link between G-quadruplex-binding proteins and the resulting G-quadruplex-mediated biomolecular phase separation, which would gain insight into a wide range of biological processes associated with nucleic acid-modulated phase separation inside living cells.

Multicolor Two-Photon Nanosystem for Multiplexed Intracellular Imaging and Targeted Cancer Therapy.

The novel theranostic nanosystems based on two-photon fluorescence can achieve higher spatial resolution of deep tissue imaging for simultaneous diagnosis and therapy of a variety of cancers. Herein, we have designed and prepared FRET-based two-photon mesoporous silica nanoparticles (MTP-MSNs) for single-excitation multiplexed intracellular imaging and targeted cancer therapy for the first time. This nanosystem includes two constituents, containing (1) multicolor two-photon mesoporous silica nanoparticles and (2) cancer cell-targeting aptamers that act as gatekeepers for MTP-MSNs. After incubation with cancer cells, the Dox-loaded and aptamer-capped MTP-MSNs could be internalized into the cells, opening the pores and releasing the drug. Furthermore, using two-photon multicolor fluorescence, MTP-MSNs could serve as good contrast agents for multicolor two-photon intracellular imaging with increased imaging depth and improved spatial localization of tissue. In sum, these multicolor MTP-MSNs provide a promising system for traceable targeted cancer therapy with further applications in multiplex intracellular imaging and the screening of drug.

A Cascade Signaling Network between Artificial Cells Switching Activity of Synthetic Transmembrane Channels.

Cell-cell communication plays a vital role in biological activities; in particular, membrane-protein interactions are profoundly significant. In order to explore the underlying mechanism of intercellular signaling pathways, a full range of artificial systems have been explored. However, many of them are complicated and uncontrollable. Herein we designed an artificial signal transduction system able to control the influx of environmental ions by triggering the activation of synthetic transmembrane channels immobilized on giant membrane vesicles (GMVs). A membrane protein-like stimulator from one GMV community (GMVB) stimulates a receptor on another GMV community (GMVA) to release ssDNA messengers, resulting in the activation of synthetic transmembrane channels to enable the influx of ions. This event, in turn, triggers signal responses encapsulated in the GMVA protocell model. By mimicking natural signal transduction pathways, this novel prototype provides a workable tool for investigating cell-cell communication and expands biological signaling systems in general as well as explores useful platforms for addressing scientific problems which involve materials science, chemistry, and medicine.

A minireview on multiparameter-activated nanodevices for cancer imaging and therapy.

Tumor microenvironment (TME)-responsive nanodevices are essential tools for cancer imaging and therapy. Exploiting the advantages of molecular engineering, nanodevices are emerging for biomedical applications. In order to reach targeted cancer areas, activated nanodevices first respond to the TME and then serve as an actuator for sensing, imaging and therapy. Most nanodevices depend on a single parameter as an input for their downstream activation, potentially leading to inaccurate diagnostic results and poor therapeutic outcomes. However, in the TME, some biomarkers are cross-linked, and such correlated biomarkers are potentially useful for cancer imaging and theranostic applications. Based on this phenomenon, researchers have developed approaches for the construction of multiparameter-activated nanodevices (MANs) to improve accuracy. This minireview summarizes the recent advances in the development of MANs for cancer imaging including fluorescence imaging, photoacoustic (PA) imaging, magnetic resonance imaging (MRI) and computed tomography (CT) imaging, as well as cancer therapy including radiotherapy, chemotherapy, photoinduced therapy and immunotherapy. We highlight different approaches for improving the specificity and precision of cancer imaging and therapy. In the future, MANs will show promise for clinical work in multimodal diagnosis and therapeutics.

DNA-based artificial molecular signaling system that mimics basic elements of reception and response.

In order to maintain tissue homeostasis, cells communicate with the outside environment by receiving molecular signals, transmitting them, and responding accordingly with signaling pathways. Thus, one key challenge in engineering molecular signaling systems involves the design and construction of different modules into a rationally integrated system that mimics the cascade of molecular events. Herein, we rationally design a DNA-based artificial molecular signaling system that uses the confined microenvironment of a giant vesicle, derived from a living cell. This system consists of two main components. First, we build an adenosine triphosphate (ATP)-driven DNA nanogatekeeper. Second, we encapsulate a signaling network in the biomimetic vesicle, consisting of distinct modules, able to sequentially initiate a series of downstream reactions playing the roles of reception, transduction and response. Operationally, in the presence of ATP, nanogatekeeper switches from the closed to open state. The open state then triggers the sequential activation of confined downstream signaling modules.

Hierarchical Fabrication of DNA Wireframe Nanoarchitectures for Efficient Cancer Imaging and Targeted Therapy.

Though small-molecule drugs play a crucial role in cancer treatment, intrinsic issues such as poor solubility and systematic toxicity have considerably mitigated their anticancer functions and caused unwanted side effects. To achieve satisfying therapeutic efficiency, it is essential to develop innovative targeting systems for precise and efficient delivery of anticancer drugs. In this work, a hierarchical self-assembly strategy was applied to fabricate a core-shell nanoarchitecture composed of a DNA octahedral wireframe and chemodrug-functionalized Sgc8c aptamer. The integrated enhanced permeability and retention effect of the DNA nanostructure and active targeting ability of the Sgc8c aptamer allowed the highly selective chemodrug delivery and in vivo efficient imaging and treatment. The advantage of our multifunctional nanostructure was further highlighted by its impressive serum stability, excellent accumulation ability, deep penetration capability, significantly improved therapeutic efficacy, and favorable biosafety. This study showed promising potential of such a core-shell DNA nanoarchitecture in precise drug loading control, drug delivery, and personal medicine.

Programming DNA Tube Circumference by Tile Offset Connection.

DNA tubes with prescribed circumferences are appealing for numerous multidisciplinary applications. The DNA single-stranded tiles (SSTs) assembly method has demonstrated an unprecedented capability for programming the circumferences of DNA tubes in a modular fashion. Nevertheless, a distinct set of SSTs is typically required to assemble DNA tube of a specific circumference, with wider tubes requiring higher numbers of tiles of unique sequences, which not only increases the expense and design complexity but also hampers the assembly yield. Herein, we introduce "offset connection" to circumvent such challenges in conventional SST tube assembly. In this new connection scheme, the boundary SST tiles in an SST array are designed to connect in an offset manner. To compensate for the offset, the SST array has to grow wider until the array can close to form a wide tube with a tolerable degree of twist. Using this strategy, we have successfully assembled DNA tubes with prescribed circumferences consisting of 8, 12, 14, 16, 20, 24, 28, 32, 36, 42, 56, or 70 helices from two distinct sets of SSTs composed of 19×4 or 19×14 tiles.

Biomimetic Carriers Based on Giant Membrane Vesicles for Targeted Drug Delivery and Photodynamic/Photothermal Synergistic Therapy.

Membrane vesicles derived from live cells show great potential in biological applications due to their preserved cell membrane properties. Here, we demonstrate that cell-derived giant membrane vesicles can be used as vectors to deliver multiple therapeutic drugs and carry out combinational phototherapy for targeted cancer treatment. We show that therapeutic drugs can be efficiently encapsulated into giant membrane vesicles and delivered to target cells by membrane fusion, resulting in synergistic photodynamic/photothermal therapy under light irradiation. This study highlights biomimetic giant membrane vesicles for drug delivery with potential biomedical application in cancer therapeutics.

Generating Giant Membrane Vesicles from Live Cells with Preserved Cellular Properties.

Biomimetic giant membrane vesicles, with size and lipid compositions comparable to cells, have been recognized as an attractive experimental alternative to living systems. Due to the similarity of their membrane structure to that of body cells, cell-derived giant plasma membrane vesicles have been used as a membrane model for studying lipid/protein behavior of plasma membranes. However, further application of biomimetic giant membrane vesicles has been hampered by the side-effects of chemical vesiculants and the utilization of osmotic buffer. We herein develop a facile strategy to derive giant membrane vesicles (GMVs) from mammalian cells in biofriendly medium with high yields. These GMVs preserve membrane properties and adaptability for surface modification and encapsulation of exogenous molecules, which would facilitate their potential biological applications. Moreover, by loading GMVs with therapeutic drugs, GMVs could be employed for drug transport to tumor cells, which represents another step forward in the biomedical application of giant membrane vesicles. This study highlights biocompatible GMVs with biomimicking membrane surface properties and adaptability as an ideal platform for drug delivery strategies with potential clinical applications.

Hierarchical Self-Assembly of Cholesterol-DNA Nanorods.

Amphiphilic DNA block copolymers have been utilized in preparing self-assembled amphiphilic structures in aqueous solution. These block copolymers usually contain specifically designed hydrophobic regions, and typically assemble under near-physiological conditions. Here, we report self-assembly of spherical micelles and one-dimensional nanorods under acidic conditions from cholesterol-conjugated DNA strands (Cholesterol-DNA). Further study also revealed that the nanorods were hierarchically assembled from the micelle nanostructures. The morphology of the nanorod assemblies can be tuned by altering solution condition and the design of Cholesterol-DNA. The self-assembly of Cholesterol-DNA nanostructures under acidic conditions and the discovery of the relationship between the nanorods and the micelles can provide new insights for future design of self-assemblies of amphiphilic DNA block copolymers.

Artificial Signal Feedback Network Mimicking Cellular Adaptivity.

Inspired by this elegant system of cellular adaptivity, we herein report the rational design of a dynamic artificial adaptive system able to sense and respond to environmental stresses in a unique sense-and-respond mode. Utilizing DNA nanotechnology, we constructed an artificial signal feedback network and anchored it to the surface membrane of a model giant membrane vesicle (GMV) protocell. Such a system would need to both senses incoming stimuli and emit a feedback response to eliminate the stimuli. To accomplish this mechanistically, our DNA-based artificial signal system, hereinafter termed DASsys, was equipped with a DNA trigger-induced DNA polymer formation and dissociation machinery. Thus, through a sequential cascade of stimulus-induced DNA strand displacement, DASsys could effectively sense and respond to incoming stimuli. Then, by eliminating the stimulus, the membrane surface would return to its initial state, realizing the formation of a cyclical feedback mechanism. Overall, our strategy opens up a route to the construction of artificial signaling system capable of maintaining homeostasis in the cellular micromilieu, and addresses important emerging challenges in bioinspired engineering.

Protocells programmed through artificial reaction networks.

As the smallest unit of life, cells attract interest due to their structural complexity and functional reliability. Protocells assembled by inanimate components are created as an artificial entity to mimic the structure and some essential properties of a natural cell, and artificial reaction networks are used to program the functions of protocells. Although the bottom-up construction of a protocell that can be considered truly 'alive' is still an ambitious goal, these man-made constructs with a certain degree of 'liveness' can offer effective tools to understand fundamental processes of cellular life, and have paved the new way for bionic applications. In this review, we highlight both the milestones and recent progress of protocells programmed by artificial reaction networks, including genetic circuits, enzyme-assisted non-genetic circuits, prebiotic mimicking reaction networks, and DNA dynamic circuits. Challenges and opportunities have also been discussed.

Engineering a 3D DNA-Logic Gate Nanomachine for Bispecific Recognition and Computing on Target Cell Surfaces.

Among the vast number of recognition molecules, DNA aptamers generated from cell-SELEX exhibit unique properties for identifying cell membrane biomarkers, in particular protein receptors on cancer cells. To integrate all recognition and computing modules within a single structure, a three-dimensional (3D) DNA-based logic gate nanomachine was constructed to target overexpressed cancer cell biomarkers with bispecific recognition. Thus, when the Boolean operator "AND" returns a true value, it is followed by an "ON" signal when the specific cell type is presented. Compared with freely dispersed double-stranded DNA (dsDNA)-based molecular circuits, this 3D DNA nanostructure, termed DNA-logic gate triangular prism (TP), showed better identification performance, enabling, in turn, better molecular targeting and fabrication of recognition nanorobotics.