Aptamer-RIBOTAC Strategy Enabling Tumor-Specific Targeted Degradation of MicroRNA for Precise Cancer Therapy.

MicroRNA (miRNA) molecules play crucial roles in a variety of diseases, making miRNA targeting a burgeoning field in medicinal chemistry. Ribonuclease targeting chimeras (RIBOTACs) present a compelling approach for RNA degradation. However, small molecule-based RIBOTAC requires an expensive and time-consuming screening process, and is difficult to directly target miRNA due to its short length lacking secondary structure. Antisense oligonucleotide (ASO)-based RIBOTAC is easy to design but with poor cell permeability. While both of them lack the specificity for tumor targeting. In this study, the first Aptamer-RIBOTAC (ARIBOTAC) chimera is designed based on ASO to achieve precise degradation of miRNA in a tumor cell-specific manner for precise cancer therapy. This chimera exhibits a remarkable ability to specifically identify and enter cancer cells, trigger localized activation of endogenous RNase L, and selectively cleave miRNAs that are complementary to ASO. The efficacy and universality of the ARIBOTAC strategy both in vitro and in vivo by degrading oncogenic miR-210-3p and miR-155-5p are validated. These findings underscore the potential of the ARIBOTAC strategy as a promising avenue for cancer therapy by precisely targeting cancer-associated miRNAs.

Next-Generation Sequencing-Based Spatial Transcriptomics: A Perspective from Barcoding Chemistry.

Gene expression profiling of tissue cells with spatial context is in high demand to reveal cell types, locations, and intercellular or molecular interactions for physiological and pathological studies. With rapid advances in barcoding chemistry and sequencing chemistry, spatially resolved transcriptome (SRT) techniques have emerged to quantify spatial gene expression in tissue samples by correlating transcripts with their spatial locations using diverse strategies. These techniques provide both physical tissue structure and molecular characteristics and are poised to revolutionize many fields, such as developmental biology, neuroscience, oncology, and histopathology. In this context, this Perspective focuses on next-generation sequencing-based SRT methods, particularly highlighting spatial barcoding chemistry. It delves into optically manipulated spatial indexing methods and DNA array-barcoded spatial indexing methods by exploring current advances, challenges, and future development directions in this nascent field.

Well-Paired-Seq2: High-Throughput and High-Sensitivity Strategy for Characterizing Low RNA-Content Cell/Nucleus Transcriptomes.

Single-cell RNA sequencing (scRNA-seq) is a transformative technology that unravels the intricate cellular state heterogeneity. However, the Poisson-dependent cell capture and low sensitivity in scRNA-seq methods pose challenges for throughput and samples with a low RNA-content. Herein, to address these challenges, we present Well-Paired-Seq2 (WPS2), harnessing size-exclusion and quasi-static hydrodynamics for efficient cell capture. WPS2 exploits molecular crowding effect, tailing activity enhancement in reverse transcription, and homogeneous enzymatic reaction in the initial bead-based amplification to achieve 3116 genes and 8447 transcripts with an average of ∼20000 reads per cell. WPS2 detected 1420 more genes and 4864 more transcripts than our previous Well-Paired-Seq. It sensitively characterizes transcriptomes of low RNA-content single cells and nuclei, overcoming the Poisson limit for cell and barcoded bead capture. WPS2 also profiles transcriptomes from frozen clinical samples, revealing heterogeneous tumor copy number variations and intercellular crosstalk in clear cell renal cell carcinomas. Additionally, we provide the first single-cell-level characterization of rare metanephric adenoma (MA) and uncover potential specific markers. With the advantages of high sensitivity and high throughput, WPS2 holds promise for diverse basic and clinical research.

Tumor Exosomal ENPP1 Hydrolyzes cGAMP to Inhibit cGAS-STING Signaling.

To evade immune surveillance, tumor cells express ectonucleotide pyrophosphatase phosphodiesterase 1 (ENPP1) on the surface of their membrane, which degrades extracellular cyclic GMP-AMP (cGAMP), thereby inhibiting the cyclic GMP-AMP synthase (cGAS) stimulator of interferon gene (STING) DNA-sensing pathway. To fully understand this tumor stealth mechanism, it is essential to determine whether other forms of ENPP1 with hydrolytic cGAMP activity also are present in the tumor microenvironment to regulate this innate immune pathway. Herein, it is reported that various tumor-derived exosomes carry ENPP1, and can hydrolyze synthetic 2'3'-cGAMP and endogenous 2'3'-cGAMP produced by cells to inhibit cGAS-STING pathway in immune cells. Moreover, tumor exosomal ENPP1 also can hydrolyze 2'3'-cGAMP bound to LL-37 (an effective transporter of 2'3'-cGAMP) to inhibit STING signaling. Furthermore, high expression of ENPP1 in exosomes is observed isolated from human breast and lung cancer tissue, and tumor exosomal ENPP1 inhibited the immune infiltration of CD8+ T cells and CD4+ T cells. The results elucidate the essential function of tumor exosomal ENPP1 in the cGAS-STING pathway, furthering understanding of the crosstalk between the tumor cells and immune system.

Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics.

Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.

Decoder-seq enhances mRNA capture efficiency in spatial RNA sequencing.

Spatial transcriptomics technologies with high resolution often lack high sensitivity in mRNA detection. Here we report a dendrimeric DNA coordinate barcoding design for spatial RNA sequencing (Decoder-seq), which offers both high sensitivity and high resolution. Decoder-seq combines dendrimeric nanosubstrates with microfluidic coordinate barcoding to generate spatial arrays with a DNA density approximately ten times higher than previously reported methods while maintaining flexibility in resolution. We show that the high RNA capture efficiency of Decoder-seq improved the detection of lowly expressed olfactory receptor (Olfr) genes in mouse olfactory bulbs and contributed to the discovery of a unique layer enrichment pattern for two Olfr genes. The near-cellular resolution provided by Decoder-seq has enabled the construction of a spatial single-cell atlas of the mouse hippocampus, revealing dendrite-enriched mRNAs in neurons. When applying Decoder-seq to human renal cell carcinomas, we dissected the heterogeneous tumor microenvironment across different cancer subtypes and identified spatial gradient-expressed genes related to epithelial-mesenchymal transition with the potential to predict tumor prognosis and progression.

Aptamer-Assisted Blockade of the Immune Suppressor Sialic Acid-Binding Immunoglobulin-Like Lectin-15 for Cancer Immunotherapy.

The percentage of low response and adaptive resistance to current antibody-based immune checkpoint blockade (ICB) therapy requires the development of novel immunotherapy strategies. Here, we developed an aptamer-assisted immune checkpoint blockade (Ap-ICB) against sialic acid-binding immunoglobulin-like lectin-15 (Siglec-15), a novel immune suppressor broadly upregulated on cancer cells and tumor infiltrating myeloid cells, which is mutually exclusive of programmed cell death ligand 1 (PD-L1). Using protein aptamer selection, we identified WXY3 aptamer with high affinity against Siglec-15 protein/Siglec-15 positive cells. We demonstrated that WXY3 aptamer rescued antigen-specific T cell responses in vitro and in vivo. Importantly, the WXY3 Ap-ICB against Siglec-15 amplified anti-tumor immunity in the tumor microenvironment and inhibited tumor growth/metastasis in syngeneic mouse model, which may result from enhanced macrophage and T cell functionality. In addition, by using aptamer-based spherical nucleic acids, we developed a synergetic ICB strategy of multivalent binding and steric hindrance, which further improves the in vivo anti-tumor effect. Taken together, our results support Ap-ICB targeted Siglec-15 as a potential strategy for normalization cancer immunotherapy.

A Magnetically Driven Tandem Chip Enables Rapid Isolation and Multiplexed Profiling of Extracellular Vesicles.

The protein phenotypes of extracellular vesicles (EVs) have emerged as promising biomarkers for cancer diagnosis and treatment monitoring. However, the technical challenges in rapid isolation and multiplexed molecular detection of EVs have limited their clinical practice. Herein, we developed a magnetically driven tandem chip to achieve streamlined rapid isolation and multiplexed profiling of surface protein biomarkers of EVs. Driven by magnetic force, the magnetic nanomixers not only act as tiny stir bars to promote mass transfer and enhance reaction efficiency of EVs, but also transport on communicating vessels of the tandem chip continuously and expedite the assay workflow. We designed cyclic surface enhancement of Raman scattering (SERS) tags to bind with target EVs and then release them by exonuclease I, eliminating steric hindrance and amplifying the SERS signal of multiple protein biomarkers on EVs. Due to the excellent assay performance, six breast cancer biomarkers were detected simultaneously on EVs using only 10 µL plasma within 1.5 h. The unweighted SUM signature offers great accuracy in discriminating breast cancer patients from healthy donors. Overall, the dynamic magnetic driving tandem chip offers a new avenue to advance the clinical application of EV-based liquid biopsy.

Hierarchical Fluid Interface Enables Spatiotemporal Regulation of Ligand Distribution to Increase Kinetics and Thermodynamics of Interfacial Binding Reaction.

In nature, regulation of the spatiotemporal distribution of interfacial receptors and ligands leads to optimum binding kinetics and thermodynamics of receptor-ligand binding reactions within interfaces. Inspired by this, we report a hierarchical fluid interface (HieFluidFace) to regulate the spatiotemporal distribution of interfacial ligands to increase the rate and thermodynamic favorability of interfacial binding reactions. Each aptamer-functionalized gold nanoparticle, termed spherical aptamer (SAPT), is anchored on a supported lipid bilayer without fluidity, like an "island", and is surrounded by many fluorescent aptamers (FAPTs) with free fluidity, like "rafts". Such ligand "island-rafts" model provides a large reactive cross-section for rapid binding to cellular receptors. The synergistic multivalency of SAPTs and FAPTs improves interfacial affinity for tight capture. Moreover, FAPTs accumulate at binding sites to bind to cellular receptors with clustered fluorescence to "lighten" cells for direct identification. Thus, HieFluidFace in a microfluidic chip achieves high-performance capture and identification of circulating tumor cells from clinical samples, providing a new paradigm to optimize the kinetics and thermodynamics of interfacial binding reactions.

Capturing nascent extracellular vesicles by metabolic glycan labeling-assisted microfluidics.

Extracellular vesicle (EV) secretion is a dynamic process crucial to cellular communication. Temporally sorting EVs, i.e., separating the newly-produced ones from the pre-existing, can allow not only deep understanding of EV dynamics, but also the discovery of potential EV biomarkers that are related to disease progression or responsible to drug intervention. However, the high similarity between the nascent and pre-existing EVs makes temporal separation extremely challenging. Here, by co-translational introduction of azido groups to act as a timestamp for click chemistry labelling, we develop a microfluidic-based strategy to enable selective isolation of nascent EVs stimulated by an external cue. In two mouse models of anti-PD-L1 immunotherapy, we demonstrate the strategy's feasibility and reveal the high positive correlation of nascent PD-L1+ EV level to tumor volume, suggesting an important role of nascent EVs in response to immunotherapy in cancer treatment.

Simultaneous subset tracing and miRNA profiling of tumor-derived exosomes via dual-surface-protein orthogonal barcoding.

The clinical potential of miRNA-based liquid biopsy has been largely limited by the heterogeneous sources in plasma and tedious assay processes. Here, we develop a precise and robust one-pot assay called dual-surface-protein-guided orthogonal recognition of tumor-derived exosomes and in situ profiling of microRNAs (SORTER) to detect tumor-derived exosomal miRNAs and enhance the diagnostic accuracy of prostate cancer (PCa). The SORTER uses two allosteric aptamers against exosomal marker CD63 and tumor marker EpCAM to create an orthogonal labeling barcode and achieve selective sorting of tumor-specific exosome subtypes. Furthermore, the labeled barcode on tumor-derived exosomes initiated targeted membrane fusion with liposome probes to import miRNA detection reagents, enabling in situ sensitive profiling of tumor-derived exosomal miRNAs. With a signature of six miRNAs, SORTER differentiated PCa and benign prostatic hyperplasia with an accuracy of 100%. Notably, the diagnostic accuracy reached 90.6% in the classification of metastatic and nonmetastatic PCa. We envision that the SORTER will promote the clinical adaptability of miRNA-based liquid biopsy.

mitoSplitter: A mitochondrial variants-based method for efficient demultiplexing of pooled single-cell RNA-seq.

Single-cell RNA-seq (scRNA-seq) analysis of multiple samples separately can be costly and lead to batch effects. Exogenous barcodes or genome-wide RNA mutations can be used to demultiplex pooled scRNA-seq data, but they are experimentally or computationally challenging and limited in scope. Mitochondrial genomes are small but diverse, providing concise genotype information. We developed "mitoSplitter," an algorithm that demultiplexes samples using mitochondrial RNA (mtRNA) variants, and demonstrated that mtRNA variants can be used to demultiplex large-scale scRNA-seq data. Using affordable computational resources, mitoSplitter can accurately analyze 10 samples and 60,000 cells in 6 h. To avoid the batch effects from separated experiments, we applied mitoSplitter to analyze the responses of five non-small cell lung cancer cell lines to BET (Bromodomain and extraterminal) chemical degradation in a multiplexed fashion. We found the synthetic lethality of TOP2A inhibition and BET chemical degradation in BET inhibitor-resistant cells. The result indicates that mitoSplitter can accelerate the application of scRNA-seq assays in biomedical research.

Simultaneous quantification of exosomal MMP14 expression and proteolysis activity on a spherical dual-probe-based fluorescent nanosensor.

Among various exosomal proteins, matrix metalloproteinases (MMPs) are a family of membrane associated endopeptidases and have been considered as potential biomarkers in liquid biopsy owing to their multiple roles in pathological processes. However, the potential of MMP14 expression (MMP14-E) and MMP14 proteolytic activity (MMP14-A) in clinical diagnosis is still not clear due to the lack of sensitive and simultaneous detection techniques. Herein, we propose a fluorescent nanosensor for the simultaneous detection of MMP14-E and MMP14-A using a spherical aptamer/peptide dual-probe strategy. The aptamer and peptide probes were sequentially immobilized on Fe3O4 magnetic nanoparticles coated with gold nanoparticles (m-AuNPs) using a disulfide linker. MMP14 can be specifically recognized by the aptamer, while the proteolytic-active MMP14 can cleave the peptide probe. While achieving simultaneous detection, the proposed sensor provides better analytical performances than traditional MMP14 sensors owing to the m-AuNP-based spherical dual-probe strategy. This sensor has been successfully applied for the detection of exosomal MMP14 from cell culture media and real serum samples. Levels of both MMP14-E and MMP14-A increase in serum from cancer patients, indicating their potential applications as biomarkers in liquid biopsy for disease diagnosis and real-time surveillance.

Reliable Detection of Extracellular PD-L1 by DNA Computation-Mediated Microfluidics.

Extracellular vesicle PD-L1 (programmed death-1 ligand 1) is of greater value in tumor diagnosis, prognosis, and efficacy monitoring of anti-PD-1/PD-L1 immunotherapy. However, soluble PD-L1 interferes with the accurate detection of extracellular vesicle (EV) PD-L1. Here, we developed a microfluidic differentiation method for the detection of extracellular PD-L1, without the interference of soluble, by DNA computation with lipid probes and PD-L1 aptamer as inputs (DECLA). For the developed DECLA method, a cholesterol-DNA probe was designed that efficiently embeds into the EV membrane, and an aptamer-based PD-L1 probe was used for PD-L1 recognition. Due to the stable secondary structure of the designed connector, only cobinding of cholesterol-DNA and PD-L1 affinity probe induced biotin-labeled connector activation, while soluble PD-L1 cannot hybridize. As a result, PD-L1 EVs can be efficiently captured by streptavidin-functioned herringbone chip and quantified by anti-CD63-induced fluorescence signal. The high specificity of dual-input DNA computation allied to the high sensitivity of microfluidic-based detection was suitable for distinguishing lung cancer patients from healthy donors, highlighting its potential translation to clinical diagnosis and therapy monitoring.

Isolation of PD-L1 Extracellular Vesicle Subpopulations Using DNA Computation Mediated Microfluidic Tandem Separation.

Accurate isolation of targeted extracellular vesicle (EV) is challenging due to the antigenic heterogeneity of EV subpopulations which are from different cell origins. Most EV subpopulations lack a single marker whose expression cleanly distinguishes them from mixed populations of closely related EVs. Here, a modular platform capable of taking multiple binding events as input, performing logic computations, and producing two independent outputs for tandem microchips for EV subpopulation isolation, is developed. Taking advantages of the excellent selectivity of dual-aptamer recognition and the sensitivity of tandem microchips, this method achieves, for the first time, sequential isolation of tumor PD-L1 EVs and non-tumor PD-L1 EVs. As a result, the developed platform can not only effectively distinguish cancer patients from healthy donors but also provides new clues for assessing immune heterogeneity. Moreover, the captured EVs can be released through a DNA hydrolysis reaction with high efficiency, which is compatible with downstream mass spectrometry for EV proteome profiling. Overall, this strategy is expected to isolate different EV subpopulations, translate EVs into reliable clinical biomarkers, and accurately investigate the biological functions of different EV subsets.

Encoded Fusion-Mediated MicroRNA Signature Profiling of Tumor-Derived Extracellular Vesicles for Pancreatic Cancer Diagnosis.

MicroRNAs (miRNAs) in tumor-derived extracellular vesicles (tEVs) are important cancer biomarkers for cancer screening and early diagnosis. Multiplex detection of miRNAs in tEVs facilitates accurate diagnosis but remains a challenge. Herein, we propose an encoded fusion strategy to profile the miRNA signature in tEVs for pancreatic cancer diagnosis. A panel of encoded-targeted-fusion beads was fabricated for the selective recognition and fusion of tEVs, with the turn-on fluorescence signals of molecule beacons for miRNA quantification and barcode signals for miRNA identification using readily accessible flow cytometers. Using this strategy, six types of pancreatic-cancer-associated miRNAs can be profiled in tEVs from 2 µL plasma samples (n = 36) in an isolation-free and lysis-free manner with only 2 h of processing, offering a high accuracy (98%) to discriminate pancreatic cancer, pancreatitis, and healthy donors. This encoded fusion strategy exhibits great potential for multiplex profiling of miRNA in tEVs, offering new avenues for cancer diagnosis and screening.

De Novo Evolution of an Antibody-Mimicking Multivalent Aptamer via a DNA Framework.

Multivalent interactions can often endow ligands with more efficient binding performance toward target molecules. Generally speaking, a multivalent aptamer can be constructed via post-assembly based on chemical structural information of target molecules and pre-identified monovalent aptamers derived from traditional systematic evolution of ligands by exponential enrichment (SELEX) technology. However, many target molecules may not have known matched aptamer partners, thus a de novo evolution will be highly desired as an alternative strategy for directed selection of a high-avidity, multivalent aptamer. Here, inspired by the superiority of multivalent interactions between antibodies and antigens, a direct SELEX strategy with a preorganized DNA framework library for an "Antibody-mimicking multivalent aptamer" (Amap) selection to epithelial cell adhesion molecule (EpCAM), a model target protein is reported. The Amap presents a relatively good binding affinity through both aptamer moieties concurrently binding to EpCAM, which has been confirmed by affinity analysis and molecular modeling. Furthermore, dynamic interactions between Amap and EpCAM are directly visualized by magnetic tweezers at the single-molecule level. A nice binding affinity of Amap to EpCAM-positive cancer cells has also been verified, which hints that their Amap-SELEX strategy has the potential to be a new route for de novo evolution of multivalent aptamers.

Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics.

Single-cell RNA sequencing (scRNA-seq) reveals the transcriptional heterogeneity of cells, but the static snapshots fail to reveal the time-resolved dynamics of transcription. Herein, we develop Well-TEMP-seq, a high-throughput, cost-effective, accurate, and efficient method for massively parallel profiling the temporal dynamics of single-cell gene expression. Well-TEMP-seq combines metabolic RNA labeling with scRNA-seq method Well-paired-seq to distinguish newly transcribed RNAs marked by T-to-C substitutions from pre-existing RNAs in each of thousands of single cells. The Well-paired-seq chip ensures a high single cell/barcoded bead pairing rate (~80%) and the improved alkylation chemistry on beads greatly alleviates chemical conversion-induced cell loss (~67.5% recovery). We further apply Well-TEMP-seq to profile the transcriptional dynamics of colorectal cancer cells exposed to 5-AZA-CdR, a DNA-demethylating drug. Well-TEMP-seq unbiasedly captures the RNA dynamics and outperforms the splicing-based RNA velocity method. We anticipate that Well-TEMP-seq will be broadly applicable to unveil the dynamics of single-cell gene expression in diverse biological processes.

Logic-Gates of Gas Pressure for Portable, Intelligent and Multiple Analysis of Metal Ions.

DNA logic gates have shown outstanding magic in intelligent biology applications, but it remains challenging to construct a portable, affordable and convenient DNA logic gate. Herein, logic gates of gas pressure were innovatively developed for multiplex analysis of metal ions. Hg2+ and Ag+ were input to interact specifically with the respective mismatched base pairs, which activated DNA extension reaction by polymerase and led to the enrichment of platinum nanoparticles for catalyzing the decomposition of peroxide hydrogen. Thus, the gas pressure obtained from a sealed well was used as output for detecting or identifying metal ions. Hg2+ and Ag+ were sensitively and selectively detected, and the assay of the real samples was also satisfactory. Based on this, DNA logic gates, including YES, NOT, AND, OR, NAND, NOR, INHIBIT, and XOR were successfully established using a portable and hand-held gas pressure meter as detector. So, the interactions between DNA and metal ions were intelligently transferred into the output of gas pressure, which made metal ions to be detected portably and identified intelligently. Given the remarkable merits of simplicity, logic operation, and portable output, the metal ion-driven DNA logic gate of gas pressure provides a promising way for intelligent and portable biosensing.

Dual-Mode Logic Gate for Intelligent and Portable Detection of MicroRNA Based on Gas Pressure and Lateral Flow Assay.

Molecular logic gate provides an intelligent option for simultaneous detection of biomarkers. Herein, a dual-mode DNA logic gate was proposed to portably and intelligently detect multiple microRNAs (miRNAs) by gas pressure biosensing and lateral flow assay (LFA). A platinum-coated gold nanoparticle (Au@PtNP) with catalase-like activity was used as a signal reporter to achieve a dual-signal readout. MiRNAs as the input initiated the cyclic strand displacement reaction (SDR) to enrich a large amount of Au@PtNPs. Thus, miRNA can be visually detected by a lateral flow strip (LFS) using the grayish-brown color of Au@PtNPs as output 1. Furthermore, Au@PtNP-catalyzed decomposition of H2O2 resulted in gas pressure as output 2, which was measured by a digital and handheld gas pressure meter. As a consequence, microRNA 21 (miR-21) was sensitively and reliably detected with the limit of detection (LOD) of 7.2 pM. The selectivity and real sample analysis were both satisfactory. Significantly, two-input and three-input AND logic gates were successfully developed to realize multiple detection of two miRNAs and three miRNAs, which provide a promising way for intelligent multi-input analysis. Predictably, with the advantages of portability, simplicity, and affordability, the dual-mode logic gate based on gas pressure biosensing and LFA offers a new perspective on the field of intelligent and portable biosensing and bioanalysis.