表1.

单细胞测序技术在肺癌免疫微环境研究中的临床发现

Author	Research technique	Type of lung cancer	Cell type	Main finding
Tian et al.[5]	10x Genomics ®scRNA-seq	SCLC	Tumor cell, T cell, Mac	In SCLC, patients with low immune features are more likely to benefit from ICB therapies than those with strong immune features. The study established a detailed immune atlas for SCLC and classified T cells, revealing patterns of dysfunction and exhaustion markers like PDCD1, CTLA4, HAVCR2, LAG3, TIGIT and LAYN. These markers are potential targets for immunotherapy. Additionally, non-neuroendocrine SCLC subtypes show increased interactions with other cells, including immune and stromal cells, which may correlate with clinical outcomes of immunotherapy.
Lavin et al.[35]	10x Genomics ®scRNA-seq, CyTOF	LUAD	Tumor cell, T cell, Mac	The study identified characteristic genes of tumor-infiltrating macrophages such as TREM2, CD81, MARCO and APOE. It also detailed the immune cell landscape in early-stage LUAD, highlighting a significant increase in Tregs and enhanced PD-1 expression in CD4+ and CD8+ T cells during early tumor stages. These findings deepen the understanding of the immune microenvironment in LUAD and suggest potential targets for future immunotherapy strategies.
Sun et al.[56]	VITApilote® snRandom-seq, IMC	LUAD	B cell, plasma cell, T cell	An extensive single-cell analysis revealed distinctive immune niches in different organ-specific environments. Notably, primary LUAD and adrenal gland metastases exhibited a significant presence of B cells, plasma cells, and various T cell subtypes (including activated, exhausted, and memory T cells), suggesting a robust immune environment conducive to immunotherapy effectiveness. Conversely, immunosuppressive environments characterized by the presence of collagen I and high expression of the T cell exhaustion marker TIM-3 were identified in brain and liver metastases, indicating a potential challenge for immunotherapy in these sites.
Sorin et al.[57]	10x Genomics ®scRNA-seq, IMC	NSCLC	Tumor cell, T cell, monocyte	The study found that CXCL13 expression is associated with the efficacy of ICIs. Recombinant CXCL13 can enhance the in vivo response to anti-PD-1 therapy, possibly due to the increase in antigen-stimulated T cell subgroups and the reduction in CCR2+ monocytes.
Leader et al.[58]	10x Genomics ®scRNA-seq, CITE-seq, TCR-seq	NSCLC	Tumor cell, T cell, Plasma cell, Mac	The study developed a detailed immunological profile of early-stage lung cancer and introduced the LCAM module consisting of PDCD1+ CXCL13+ activated T cells, IgG+ plasma cells, and SPP1+ macrophages, which serves as a direct indicator of antigen-specific anti-tumor immune activation. This framework assists in understanding and enhancing immunotherapeutic strategies.
Zhu et al.[59]	10x Genomics ®scRNA-seq, ST	LUAD	Tumor cell, Treg cell	The study identified a UBE2C+ subpopulation in LUAD crucial for tumor invasiveness. In the LUAD TME, NK cells and MALT+ B cells increased significantly in early stages, whereas Treg cells and secretory B cells decreased as LUAD progressed to advanced stages. These findings support the development of personalized treatment strategies for aggressive LUAD.
Sinjab et al.[60]	10x Genomics ®scRNA-seq, ST	LUAD	Tumor cell, Dendritic cell, Mac	This study identified distinct immune checkpoint receptor and cytokine receptor interactions within different regions of LUAD. Decreased overlap of L-R interactions was observed in distant tumor regions compared to proximal areas. Additionally, increased interactions involving immune checkpoint proteins CD24 with LGALS9 in tumor epithelial cells, and SIGLEC10 in dendritic and macrophage cells, as well as HAVCR2, suggest that regional differences in these interactions could affect the tumor's immune microenvironment and impact the effectiveness of immunotherapy.
Zhang et al.[61]	10x Genomics ®scRNA-seq	LUAD	Tumor cell, CD4+/ CD8+ T cell, NK cell, Treg cell, M2- Mac	Malignant cells with low R-loop scores exhibit glycolysis and epithelial-mesenchymal transition pathway activation and immune escape promotion. R-loop score correlates with T cell exhaustion and immune evasion, predicting therapeutic response to targeted therapy, chemotherapy, or immunotherapy. FANCI-mediated R-loop changes affect Ras signaling, inhibiting tumor proliferation and dissemination.

SCLC: small cell lung cancer; LUAD: lung adenocarcinoma; ICB: immune checkpoint blockade; Mac: Macrophage; snRandom-seq: nucleus RNA sequencing technology; IMC: imaging mass cytometry; CyTOF: cytometry by time-of-flight; Treg cell: T regulatory cell; ICIs: immune checkpoint inhibitors; NSCLC: non-small cell lung cancer; CITE-seq: cellular indexing of transcriptomes and epitopes sequencing; TCR-seq: T cell receptor sequencing; ST: spatial transcriptomics; TME: tumor microenvironment.