ObjectiveTo understand the single-cell RNA sequencing (scRNA-seq) and its research progress in the tumor microenvironment (TME) of breast cancer, in order to provide new ideas and directions for the research and treatment of breast cancer. MethodThe development of scRNA-seq technology and its related research literature in breast cancer TME at home and abroad in recent years was reviewed. ResultsThe scRNA-seq was a quantum technology in high-throughput sequencing of mRNA at the cellular level, and had become a powerful tool for studying cellular heterogeneity when tissue samples were fewer. While capturing rare cell types, it was expected to accurately describe the complex structure of the TME of breast cancer. ConclusionsAfter decades of development, scRNA-seq has been widely used in tumor research. Breast cancer is a malignant tumor with high heterogeneity. The application of scRNA-seq in breast cancer research can better understand its tumor heterogeneity and TME, and then promote development of personalized diagnosis and treatment.
The emergence of single-cell sequencing technology enables people to observe cells with unprecedented precision. However, it is difficult to capture the information on all cells and genes in one single-cell RNA sequencing (scRNA-seq) experiment. Single-cell data of a single modality cannot explain cell state and system changes in detail. The integrative analysis of single-cell data aims to address these two types of problems. Integrating multiple scRNA-seq data can collect complete cell types and provide a powerful boost for the construction of cell atlases. Integrating single-cell multimodal data can be used to study the causal relationship and gene regulation mechanism across modalities. The development and application of data integration methods helps fully explore the richness and relevance of single-cell data and discover meaningful biological changes. Based on this, this article reviews the basic principles, methods and applications of multiple scRNA-seq data integration and single-cell multimodal data integration. Moreover, the advantages and disadvantages of existing methods are discussed. Finally, the future development is prospected.
Non-small cell lung cancer (NSCLC) is one of the most common types of cancer in the world and is an important cause for cancer death. Although the application of immunotherapy in recent years has greatly improved the prognosis of NSCLC, there are still huge challenges in the treatment of NSCLC. The immune microenvironment plays an important role in the process of NSCLC development, infiltration and metastasis, and they can interact and influence each other, forming a vicious circle. Notably, single-cell RNA sequencing enables high-resolution analysis of individual cells and is of great value in revealing cell types, cell evolution trajectories, molecular mechanisms of cell differentiation, and intercellular regulation within the immune microenvironment. Single-cell RNA sequencing is expected to uncover more promising immunotherapies. This article reviews the important researches and latest achievements of single-cell RNA sequencing in the immune microenvironment of NSCLC, and aims to explore the significance of applying single-cell RNA sequencing to analyze the immune microenvironment of NSCLC.
Objective To investigate the heterogeneity of lung epithelial cells, particularly alveolar type II (AT2) cells, in chronic obstructive pulmonary disease (COPD), and to explore their potential interactions with immune cells.Methods Single-cell RNA sequencing (scRNA-seq) was performed to systematically analyze 57,879 lung-derived cells obtained from patients with mild to moderate COPD and age-matched control individuals. Major cell types were identified through cell clustering and annotation. AT2 cells were further subdivided into distinct subpopulations, and differential gene expression analysis, functional enrichment analysis, pseudotime trajectory analysis, and cell–cell communication analysis were conducted to characterize their transcriptional features, differentiation trajectories, and interaction patterns with immune cells.Results Single-cell analysis identified major cell populations, including epithelial, immune, stromal, and endothelial cells. Compared with controls, AT2 cells from COPD patients exhibited pronounced heterogeneity, with a significantly increased proportion of an inflammation-associated AT2 subpopulation characterized by high expression of complement component C3. Functional enrichment analysis revealed that this subpopulation was significantly enriched in complement activation and inflammatory response–related pathways. Cell–cell communication analysis suggested that this inflammatory AT2 subpopulation may aberrantly interact with macrophages via the C3–ITGAX/ITGB2 signaling axis, potentially contributing to the formation and maintenance of the chronic inflammatory microenvironment in COPD.Conclusions At the single-cell transcriptomic level, this study identifies a novel inflammation-associated AT2 cell subpopulation in COPD lung tissue and suggests its potential involvement in immune regulation through complement-mediated AT2–macrophage interactions. These findings provide new insights into the pathogenesis of COPD and offer a theoretical basis for the exploration of potential targeted therapeutic strategies.
ObjectiveTo investigate the expression of neutrophil extracellular traps (NETs) marker proteins citrullinated histone H3 (CitH3) and myeloperoxidase (MPO) in early-stage lung adenocarcinoma, and to analyze the dynamics of neutrophil infiltration, subpopulation heterogeneity, and the relationship between NET activity and tumor progression. MethodsPaired tumor and adjacent normal tissue specimens were collected from patients with pathologically confirmed early-stage lung adenocarcinoma after surgical resection at the Second Affiliated Hospital of Hainan Medical University between October and December 2024. Immunofluorescence staining was performed to detect CitH3 and MPO expression. Image J software was used for quantitative analysis of fluorescence intensity and density of double-positive cells. Single-cell RNA sequencing data of cancerous and matched normal tissues were obtained from patients with early-stage lung adenocarcinoma at the same hospital from October 2024 to April 2025. Patients were stratified into groups with versus without high-grade components, and well-differentiated versus moderately/poorly differentiated groups according to pathological subtypes. Unsupervised clustering was applied to identify cell populations. The ratio of observed to expected values was used to analyze tissue distribution preference. Subset clustering was performed based on neutrophil marker genes, and a NETs gene set score was calculated to assess activity signatures. ResultsPaired tumor and normal tissues from 3 patients with early-stage lung adenocarcinoma (2 males and 1 female; median age 68.0 years, range 60.0-70.0 years) were included for immunofluorescence staining. Another 14 patients with early-stage lung adenocarcinoma were enrolled, including 6 males and 8 females, with a median age of 62.5 years (range 41.0-73.0 years). Three of these 14 patients also provided paired normal tissues. Single-cell RNA sequencing was conducted on tumor tissues from all 14 patients and paired normal tissues from the 3 patients. Among the 14 invasive non-mucinous adenocarcinomas, 7 samples were well-differentiated and 7 were moderately/poorly differentiated; 10 samples had no high-grade components and 4 had high-grade components. Immunofluorescence showed that NETs expression was significantly higher in tumor tissues than in normal tissues (P<0.001). Single-cell sequencing revealed an immunosuppressive tumor microenvironment in early lung adenocarcinoma, characterized by an early depletion of neutrophils followed by a sharp increase in neutrophil abundance as disease progressed. Two neutrophil categories were identified: resident subsets (c0/c4) and tumor-associated subsets (c1/c2/c3/c5). Resident subsets decreased while tumor-associated subsets accumulated with increasing malignancy. Among them, c3-Neut-LGALS3 and c2-Neut-CKLF were associated with progression in the high-grade group. The c0-Neut-AZIN1-AS1 subset was the major source of high NETs expression, and its activity was negatively correlated with tumor malignancy. ConclusionNETs-related proteins (CitH3 and MPO) are highly expressed in early-stage lung adenocarcinoma tissues. The microenvironment of early-stage lung adenocarcinoma exhibits immunosuppressive characteristics, and neutrophil subpopulation composition is remodeled with tumor progression, with the c0-Neut-AZIN1-AS1 subpopulation serving as a key source of high NETs expression.