Single-cell RNA sequencing (scRNA-seq) is a powerful method in investigating single-cell heterogeneity to reveal rare cells, identify cell subpopulations, and construct a cell atlas. Conventional benchtop methods for scRNA-seq, including multistep operations, are labor intensive, reaction inefficient, contamination prone, and reagent consuming. Here we report a digital microfluidics-based single-cell RNA sequencing (digital-RNA-seq) for simple, efficient, and low-cost single-cell mRNA measurements. Digital-RNA-seq automates fluid handling as discrete droplets to sequentially perform protocols of scRNA-seq. To overcome the current problems of single-cell isolation in efficiency, integrity, selectivity, and flexibility, we propose a new strategy, passive dispensing method, relying on well-designed hydrophilic-hydrophobic microfeatures to rapidly generate single-cell subdroplets when a droplet of cell suspension is encountered. For sufficient cDNA generation and amplification, digital-RNA-seq uses nanoliter reaction volumes and hydrophobic reaction interfaces, achieving high sensitivity in gene detection. Additionally, the stable droplet handling and oil-closed reaction space featured in digital-RNA-seq ensure highly accurate measurement. We demonstrate the functionality of digital-RNA-seq by quantifying heterogeneity among single cells, where digital-RNA-seq shows excellent performance in rare transcript detection, cell type differentiation, and essential gene identification. With the advantages of automation, sensitivity, and accuracy, digital-RNA-seq represents a promising scRNA-seq platform for a wide variety of biological applications.
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http://dx.doi.org/10.1021/acs.analchem.0c01613 | DOI Listing |
Cancer Immunol Res
January 2025
University of Chicago, Chicago, IL, United States.
Based on the notion that hypomorphic germline genetic variants are linked to autoimmune diseases, we reasoned that novel targets for cancer immunotherapy might be identified through germline variants associated with greater T-cell infiltration into tumors. Here, we report that while investigating germline polymorphisms associated with a tumor immune gene signature, we identified PKCδ as a candidate. Genetic deletion of PKCδ in mice resulted in improved endogenous antitumor immunity and increased efficacy of anti-PD-L1.
View Article and Find Full Text PDFDiscov Oncol
January 2025
The Department of Experimental Medicine, Meishan City People's Hospital, No. 288, South Fourth Section, Dongpo Avenue, Meishan, 620000, Sichuan, China.
Background: Thyroid carcinoma (THCA) is the most common cancer of the endocrine system. Natural killer (NK) cell play an important role in tumor immune surveillance. The aim of this study was to explore the possible molecular mechanisms involved in NK cell in THCA to help the management and treatment of the disease.
View Article and Find Full Text PDFNano Lett
January 2025
Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing 100853, P. R. China.
Portal vein tumor thrombus (PVTT) is a poor prognostic factor for hepatocellular carcinoma (HCC) patients, highlighting the need for an oral drug delivery system that combines convenience, simplicity, biosafety, and improved patient compliance. Leveraging the unique anatomy of the portal vein and insights from single-cell RNA sequencing of the PVTT tumor microenvironment, we developed oral pellets using CaCO@PDA nanoparticles (NPs) encapsulating both doxorubicin hydrochloride and low molecular weight heparin. These NPs target the tumor thrombus microenvironment, aiming to break down the thrombus barrier and turn the challenge of portal vein blockage into an advantage by enhancing drug delivery efficiency through oral administration.
View Article and Find Full Text PDFCancer Res
January 2025
Karolinska Institutet, Stockholm, Stockholm, Sweden.
Transgenic mice and organoid models, such as three-dimensional tumoroid cultures, have emerged as powerful tools for investigating cancer development and targeted therapies. Yet, the extent to which these preclinical models recapitulate the cellular identity of heterogeneous malignancies, like neuroblastoma (NB), remains to be validated. Here, we characterized the transcriptional landscape of TH-MYCN tumors by single-cell RNA sequencing (scRNA-seq) and developed ex vivo tumoroids.
View Article and Find Full Text PDFAnim Cells Syst (Seoul)
January 2025
Department of Genome Medicine and Science, Gachon University College of Medicine, Incheon, Republic of Korea.
Dynamic modeling of cellular states has emerged as a pivotal approach for understanding complex biological processes such as cell differentiation, disease progression, and tissue development. This review provides a comprehensive overview of current approaches for modeling cellular state dynamics, focusing on techniques ranging from dynamic or static biomolecular network models to deep learning models. We highlight how these approaches integrated with various omics data such as transcriptomics, and single-cell RNA sequencing could be used to capture and predict cellular behavior and transitions.
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