News from China
Updates every hour. Last Updated: 21-Oct-2025 19:11 ET (21-Oct-2025 23:11 GMT/UTC)
Spatial and single-cell omics propel precision biomarker discovery in tumor immunotherapy, review finds
Shanghai Jiao Tong University Journal CenterPeer-Reviewed Publication
Recent advances in spatial omics and single-cell omics have significantly reshaped biomarker discovery in tumor immunotherapy by addressing critical challenges posed such as tumor heterogeneity, immune evasion, and variability within the tumor microenvironment (TME).
While immunotherapeutic strategies—such as immune checkpoint inhibitors and adoptive T-cell transfer—have demonstrated promising clinical outcomes, their effectiveness is hindered by low response rates and immune-related adverse events (irAEs). Thus, identifying reliable biomarkers is essential for predicting treatment efficacy, minimizing irAEs, and facilitating patient stratification. Spatial omics integrates molecular profiling with spatial localization, providing comprehensive insights into the cellular organization and functional states of the TME. By revealing spatial patterns of immune cell infiltration and tumor heterogeneity, this approach enhances our predictive capacity for therapeutic response. Similarly, single-cell omics yields high-resolution analysis of cellular heterogeneity, capturing transcriptomic, epigenomic, and metabolic signatures at the single-cell level. The combined application of spatial and single-cell omics has led to the identification of previously undetected biomarkers, including rare immune cell subsets implicated in resistance mechanisms. Beyond spatial transcriptomics (ST), this technological landscape also includes spatial proteomics and metabolomics, which further facilitate the study of dynamic tumor–immune interactions. Multi-omics integration offers a comprehensive overview of biomarker landscapes, while the rapid evolution artificial intelligence approaches enhances the analysis of complex, multidimensional datasets—ultimately enhancing predictive power and clinical utility. Despite substantial progress, challenges remain in standardization, data integration, and real-time monitoring. Nevertheless, incorporating spatial omics and single-cell omics into biomarker research holds transformative potential for personalized cancer immunotherapy. These emerging strategies pave the way for innovative diagnostic and therapeutic interventions, enabling precision oncology and elevating treatment outcomes for patients a wide range of tumor profiles.
This review aims to provide a comprehensive summary of the integration of spatial omics and single-cell omics in tumor immunotherapy biomarker discovery. Specifically, it focuses on how these emerging technologies address challenges related to tumor heterogeneity, immune evasion, and the dynamic TME. By elaborating on the principles, applications, and clinical potential of these technologies, the review will also critically evaluate their limitations, challenges, and the current gaps in their translational applications.
- Journal
- LabMed Discovery
Congratulations to Professor Qian Kun, editorial board member of LabMed Discovery, for winning the "Ruiyuan Youth Science and Technology Award" of Shanghai Jiao Tong University
Shanghai Jiao Tong University Journal CenterOn April 6, the 129th anniversary commemoration meeting of Shanghai Jiao Tong University was held at the Minhang campus. President (Principal) Ding Kuiling announced the list of the third "Ruiyuan Science and Technology Award" and the second "Ruiyuan Youth Science and Technology Award" at the meeting. Professor Qian Kun, editor of LabMed Discovery and professor at the School of Biomedical Engineering of Shanghai Jiao Tong University, won the Life and Medical Science and Technology Award of the second "Ruiyuan Youth Science and Technology Award".
Novel model optimization algorithm developed to improve robustness of near-infrared spectroscopy models
Hefei Institutes of Physical Science, Chinese Academy of SciencesPeer-Reviewed Publication
- Journal
- Analytica Chimica Acta
New fluorescent probe enables rapid, visible detection of harmful pesticide residues
Hefei Institutes of Physical Science, Chinese Academy of SciencesPeer-Reviewed Publication
- Journal
- Analytical Chemistry
New Martian meteorite unveils secrets of Mars’ ancient volcanic systems
Higher Education PressPeer-Reviewed Publication
- Journal
- Planet
Engineered composite materials offer broad-spectrum synergistic radiation shielding
Hefei Institutes of Physical Science, Chinese Academy of SciencesPeer-Reviewed Publication
Recently, Dr. HUO Zhipeng and his student CHEN Zuoyang from Hefei Institutes of Physical Science of Chinese Academy of Sciences developed novel PbWO4 filler-reinforced B4C/HDPE composites with tunable microstructures.
By precisely regulate the microstructure of PbWO4 fillers, they achieved enhanced synergistic radiation shielding performance against both neutron and gamma radiation, while elucidating the correlation mechanisms between the microstructure and thermal, mechanical, radiation shielding properties, and service durability of the shielding composites.
- Journal
- Composites Part A Applied Science and Manufacturing
Step-wise organization of genomic nuclear speckle-associated domains during mammalian embryonic development
Higher Education PressThis study reveals the step-wise establishment of nuclear speckle-associated domains (SPADs) during mouse embryogenesis. Using optimized CUT&Tag, researchers found paternal SPADs dominate pre-ZGA stages, coordinating sequential gene expression and 3D genome reorganization. SPADs form two classes (primary and ZGA-dependent secondary), regulated by factors like Nipbl and Gata6, linking chromatin dynamics to developmental programming.
- Journal
- Protein & Cell
- Funder
- Biological Breeding-National Science and Technology Major Project, National Key Research and Development Program of China, National Natural Science Foundation of China, 2115 Talent Development Program of China Agricultural University
AI language models show promise in predicting liver cancer treatment outcomes
Hefei Institutes of Physical Science, Chinese Academy of SciencesPeer-Reviewed Publication
- Journal
- Journal of Medical Systems
New AI-powered model accurately predicts lung motion with minimal radiation
Hefei Institutes of Physical Science, Chinese Academy of SciencesPeer-Reviewed Publication
- Journal
- Computerized Medical Imaging and Graphics