Immunotherapies such as immune checkpoint blockade and adoptive cell transfer have revolutionized cancer treatment, but further progress is hindered by our limited understanding of tumor resistance mechanisms. Emerging technologies now enable the study of tumors at the single-cell level, providing unprecedented high-resolution insights into the genetic makeup of the tumor microenvironment and immune system that bulk genomics cannot fully capture. Here, we highlight the recent key findings of the use of single-cell RNA sequencing to deconvolute heterogeneous tumors and immune populations during immunotherapy. Single-cell RNA sequencing has identified new crucial factors and cellular subpopulations that either promote tumor progression or leave tumors vulnerable to immunotherapy. We anticipate that the strategic use of single-cell analytics will promote the development of the next generation of successful, rationally designed immunotherapeutics.
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http://dx.doi.org/10.1084/jem.20201574 | DOI Listing |
Int J Mol Sci
January 2025
School of Chemistry and Life Science, Suzhou University of Science and Technology, Suzhou 215011, China.
Colorectal cancer (CRC) is one of the most common malignant tumors, characterized by a high incidence and mortality rate. Macrophages, as a key immune cell type within the tumor microenvironment (TME), play a key role in tumor immune evasion and the progression of CRC. Therefore, identifying macrophage biomarkers is of great significance for predicting the prognosis of CRC patients.
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January 2025
Cancer Research Center (CiC-IBMCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC), University of Salamanca (USAL) & Instituto de Investigación Biomédica de Salamanca (IBSAL), 37007 Salamanca, Spain.
There are many different cells that perform highly specialized functions in the human hematological and immune systems. Due to the relevance of their activity, in this work we investigated the cell types and subtypes that form this complex system, using single-cell RNA sequencing (scRNA-seq) to dissect and assess the markers that best define each cell population. We first developed an optimized computational workflow for analyzing large scRNA-seq datasets.
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January 2025
School of Environmental Science and Engineering, Hainan University, Haikou 570228, China.
Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factors. Cellular senescence, marked by permanent cell cycle arrest, plays a crucial role in cancer biology, but its markers and roles in the HCC immune microenvironment remain unclear. Three machine learning methods, namely k nearest neighbor (KNN), support vector machine (SVM), and random forest (RF), are utilized to identify eight key HCC cell senescence markers (HCC-CSMs).
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January 2025
Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198, USA.
Methamphetamine is a highly addictive stimulant known to cause neurotoxicity, cognitive deficits, and immune dysregulation in the brain. Despite significant research, the molecular mechanisms driving methamphetamine-induced neurotoxicity and glial cell dysfunction remain poorly understood. This study investigates how methamphetamine disrupts glial cell function and contributes to neurodevelopmental and neurodegenerative processes.
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January 2025
Department of General Practice, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron degeneration and α-synuclein (α-syn) aggregation. Lipid metabolism dysfunction may contribute to PD progression. This study aims to identify lipid metabolism-related genes (LMGs) associated with PD using an integrative transcriptomic analysis of microarray and single-cell RNA sequencing (scRNA-seq) datasets from patients with PD and healthy controls.
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