Acta Biochimica et Biophysica Sinica•2024•DOI: 10.3724/abbs.2024106
Acquired resistance to EGFR tyrosine kinase inhibitors (EGFR-TKIs) represents a primary cause of treatment failure in non-small cell lung cancer (NSCLC) patients. Chemokine (C-C motif) ligand 2 (CCL2) is recently found to play a pivotal role in determining anti-cancer treatment response. However, the role and mechanism of CCL2 in the development of EGFR-TKIs resistance have not been fully elucidated. In the present study, we focus on the function of CCL2 in the development of acquired resistance to EGFR-TKIs in NSCLC cells. Our results show that CCL2 is aberrantly upregulated in EGFR-TKIs-resistant NSCLC cells and that CCL2 overexpression significantly diminishes sensitivity to EGFR-TKIs. Conversely, CCL2 suppression by CCL2 synthesis inhibitor, bindarit, or CCL2 knockdown can reverse this resistance. CCL2 upregulation can also lead to enhanced migration and increased expressions of epithelial-mesenchymal transition (EMT) markers in EGFR-TKI-resistant NSCLC cells, which could also be rescued by CCL2 knockdown or inhibition. Furthermore, our findings suggest that CCL2-dependent EGFR-TKIs resistance involves the AKT-EMT signaling pathway; inhibition of this pathway effectively attenuates CCL2-induced cell migration and EMT marker expression. In summary, CCL2 promotes the development of acquired EGFR-TKIs resistance and EMT while activating AKT signaling in NSCLC. These insights suggest a promising avenue for the development of CCL2-targeted therapies that prevent EGFR-TKIs resistance in NSCLC.
Acta Biochimica et Biophysica Sinica•2025•DOI: 10.3724/abbs.2024147
The subcellular localization of RNA is critical to a variety of physiological and pathological processes. Dissecting the spatiotemporal regulation of the transcriptome is key to understanding cell function and fate. However, it remains challenging to effectively enrich and catalogue RNAs from various subcellular structures using traditional approaches. In recent years, proximity labeling has emerged as an alternative strategy for efficient isolation and purification of RNA from these intricate subcellular compartments. This review focuses on examining RNA-related proximity labeling tools and exploring their application in elucidating the spatiotemporal regulation of RNA at the subcellular level.
Chinese Traditional and Herbal Drugs•2026•DOI: 10.7501/j.issn.0253-2670.2026.16.20261629
Arthritis incidence has risen steadily, with complex and protracted pathological progression; it remains among the leading causes of disability worldwide. Existing therapeutic approaches, including traditional Chinese medicine (TCM) hot compress and acupuncture, provide symptomatic relief but rarely achieve disease modification, and some carry adverse effects. TCM's multi-component, multi-target, multi-pathway characteristics are mechanistically compatible with arthritis heterogeneity, yet its pharmacodynamic basis remains poorly resolved at the cellular level. Bulk RNA sequencing averages transcriptional signals across cell populations, obscuring rare pathogenic subpopulations and cell-state transitions. Single-cell RNA sequencing (scRNA-seq) resolves gene expression heterogeneity at single-cell resolution, enabling construction of joint tissue cellular atlases and identification of key subpopulations and molecular targets driving disease progression. This review systematically summarizes the technical advantages of scRNA-seq relative to bulk RNA-seq, including platforms such as 10× Genomics and BD, and examines its application to rheumatoid arthritis, osteoarthritis, and gouty arthritis. It further discusses prospects and challenges for integrating scRNA-seq into TCM-based arthritis research, including cell-cell communication inference, macrophage M1/M2 polarization analysis, and SPP1+ chondrocyte identification, providing a reference for mechanistic studies and development of novel Chinese herbal therapeutics.
Chinese Journal of Tissue Engineering Research•2026•DOI: 10.12307/2026.21368
BACKGROUND: In the process of applying artificial intelligence to orthopedic imaging, the technical system exhibits a clear hierarchical structure: machine learning is the primary pathway to achieving artificial intelligence, while convolutional neural networks, a branch of deep learning, have become the core model for image analysis. Clarifying this technical lineage helps to systematically review the research evolution and trends in this field through bibliometric methods. OBJECTIVE: To comprehensively analyze the research status and development trends of artificial intelligence in the field of orthopedic imaging based on bibliometric methods, providing ideas and methods for future research. METHODS: By searching the Web of Science Core Collection database, with keywords including artificial intelligence, deep learning, convolutional neural network, and orthopedic imaging, a total of 460 relevant English articles published between 2015 and 2025 were included. CiteSpace 6.4.R1, VOSviewer 1.6.20, and Bibliometrix software were used to conduct visual analysis from dimensions such as annual publication volume, country and institution distribution, author collaboration network, keyword co-occurrence, clustering, and burst word evolution. RESULTS AND CONCLUSION: (1) The number of publications in this field has steadily increased over the past 10 years. (2) China and the United States are the main publishing countries, with the United States showing outstanding performance in citation frequency and international collaboration influence; Sichuan University, the University of California, and Harvard University constitute a core collaborative institutional network. (3) Research hotspots mainly focus on bone age assessment, automated image segmentation, and the application of deep learning in fracture detection and osteoarthritis diagnosis. Related keywords such as bone age assessment, automated segmentation, and deep learning have continued to burst, indicating the evolutionary trajectory of research focus. (4) The research enthusiasm for artificial intelligence in orthopedic imaging continues to rise, with intelligent segmentation, disease grading, and multimodal data fusion being important future research directions. (5) This paper systematically reviews the field from a macro perspective, providing a reference for promoting the deep integration of artificial intelligence technology in orthopedic clinical practice; through bibliometric analysis, it constructs a knowledge map of the application of artificial intelligence in orthopedic imaging, systematically summarizes the research status and hotspots in this field, and aims to provide reference and guidance for future related research.
Chinese Journal of Tissue Engineering Research•2026•DOI: 10.12307/2026.21363
OBJECTIVE: To conduct a meta-analysis concerning the effects of human umbilical cord blood mesenchymal stem cells on pain and function in patients with knee osteoarthritis. METHODS: Using the Chinese search terms “human umbilical cord blood, mesenchymal stem cells, knee joint-related diseases” and the English search terms “human cord blood, mesenchymal stem cell, MSC, knee osteoarthritis, knee joint disease, knee joint disorders, knee OA,” we conducted searches in the CNKI, WanFang, VIP, PubMed, Elsevier, and Web of Science databases. The search timeframe spanned from the establishment of each database until June 13, 2024. The quality of the included literature was assessed using the Cochrane Risk of Bias tool and the ROBINS-I tool. For meta-analysis, the Revman software was utilized, calculating mean differences for continuous variables and relative risks for dichotomous variables, along with 95% confidence intervals. RESULTS: Three randomized controlled trials and three case-control studies were included, totaling 248 subjects, with moderate quality. Meta-analysis showed: (1) The visual analog scale score in the experimental group was lower than that in the control group, with a significant difference (χ²=44.98, P < 0.001, I²=91%); (2) The Western Ontario and McMaster Universities Osteoarthritis Index in the experimental group was lower than that in the control group, with a significant difference (χ²=16.84, P < 0.001, I²=88%); (3) The Lysholm knee function score in the experimental group was higher than that in the control group, with a significant difference (χ²=0.12, P=0.73, I²=0%); (4) The incidence of adverse reactions in the experimental group was higher than that in the control group, with a significant difference (χ²=4.99, P < 0.001, I²=20%), with a combined risk difference of 0.21, translating to a number needed to treat of 5. CONCLUSION: Human umbilical cord blood mesenchymal stem cells can reduce pain and improve knee function in patients with knee osteoarthritis, achieving a good balance between safety and efficacy.
Chinese Journal of Tissue Engineering Research•2026•DOI: 10.12307/2026.21333
BACKGROUND: Periprostatic adipose tissue is the white visceral adipose tissue that is closest to the prostate, which is part of the prostate cancer tumor microenvironment and plays a key role in the occurrence and progression of prostate cancer. OBJECTIVE: To investigate the ability of adipose-derived stem cells derived from periprostatic adipose tissue to form three-dimensional cell sheets. METHODS: Periprostatic adipose tissue was harvested from patients undergoing radical prostatectomy. Adipose-derived stem cell suspensions were prepared using a combination of enzymatic digestion and mechanical dissection. Adipose-derived stem cell proliferation was assessed using a CCK-8 assay. Expression of stem cell-associated antigens CD34/CD44/CD45/CD90/CD105 was determined by flow cytometry. Multidirectional differentiation potential of the stem cells was assessed using osteogenic/adipogenic/chondrogenic differentiation assays. Adipose-derived stem cells were cultured for three weeks in low-glucose DMEM containing 100 μg/mL vitamin C and 10% fetal bovine serum to construct cell sheets, followed by histological analysis and scanning electron microscopy. RESULTS AND CONCLUSION: Adipose-derived stem cells from periprostatic adipose tissue exhibited a long spindle or fusiform shape, aligned growth, and consistent morphology. Primary culture reached 95% confluence at 9-10 days with good cell viability, and no obvious senescence was observed up to passage 15. Flow cytometry showed expression rates of CD44, CD90, and CD105 at 98.24%, 84.99%, and 89.14%, respectively, while CD34 and CD45 were expressed at 0.64% and 1.02%. After 3 weeks of osteogenic, adipogenic, and chondrogenic induction, the cells could differentiate into osteoblasts, adipocytes, and chondrocytes. After continuous culture for 3 weeks, the cells formed a three-dimensional cell sheet with a smooth surface and uniform texture, rich in extracellular matrix components such as fibronectin and type I collagen. Scanning electron microscopy revealed a flat surface with aligned long spindle-shaped cells and abundant extracellular matrix deposition between cells. This study successfully isolated adipose-derived stem cells from periprostatic adipose tissue of prostate cancer patients and constructed a three-dimensional cell sheet by stimulating extracellular matrix secretion with vitamin C over 3 weeks of continuous culture.
Stem Cell Research & Therapy•2026•DOI: 10.1186/s13287-026-04918-5
Intervertebral disc (IVD) degenerative disease is a prevalent and debilitating spinal condition. Current treatments provide only symptomatic relief and fail to halt disease progression or restore native biomechanical function. Regenerative medicine strategies, particularly those harnessing endogenous progenitor cells, offer a promising avenue for biological repair and functional homeostasis. The identification of intervertebral disc progenitor cells (IVD-PCs) has revealed a potential cellular reservoir for self-repair, given their demonstrated stemness attributes, including clonogenicity and multipotent differentiation. However, clinical translation of IVD-PCs is significantly hampered by an incomplete understanding of their inherent heterogeneity, hierarchical organization, and, most critically, the dynamic interplay with their unique microenvironment, which dictates their fate decisions. This review synthesizes recent advances in deciphering the molecular signatures and functional plasticity of IVD-PCs. We emphasize how key physicochemical, mechanical, and cellular cues within the IVD niche orchestrate progenitor cell behavior—ranging from maintenance and activation to aberrant differentiation—during both homeostasis and degeneration. Furthermore, we propose forward-looking insights to bridge critical knowledge gaps, aiming to propel the development of novel progenitor cell-based therapeutics for IVD degeneration.