Dissecting macrophage heterogeneity and kaempferol in lung adenocarcinoma: a single-cell transcriptomic approach and network pharmacology

Abstract

Background: Lung adenocarcinoma (LUAD) is a leading form of non-small cell lung cancer characterized by a complex tumor microenvironment (TME) that influences disease progression and therapeutic response. Tumor-associated macrophages (TAMs) within the TME promote tumorigenesis and evasion of immune surveillance, though their heterogeneity poses challenges in understanding their roles and therapeutic targeting. Additionally, traditional Chinese medicine (TCM) offers potential anti-cancer agents that could modulate the immune landscape.

Methods: We conducted single-cell RNA sequencing (scRNA-seq) on LUAD samples, performing an in-depth analysis of macrophage populations and their expression signatures. Network pharmacology was used to identify TCM components with potential TAM-modulatory effects, focusing on Astragalus membranaceus. Pseudotime trajectory analysis, immunofluorescence staining, and in vitro assays examined the functional roles of TAMs and the effects of selected compounds on macrophage polarization.

Results: Our scRNA-seq analysis identified notable heterogeneity among macrophages, revealing predominant M2-like phenotypes within TAMs. Network pharmacology highlighted active TCM ingredients, including quercetin, isorhamnetin, and kaempferol, targeting genes related to macrophage function. Survival analysis implicated AHSA1, CYP1B1, SPP1, and STAT1 as prognostically significant factors. Further experiments demonstrated kaempferol's efficacy in inhibiting M2 polarization, underlining a selective influence on TAM functionality.

Conclusions: This study delineates the diverse macrophage landscape in LUAD and suggests a pivotal role for STAT1 in TAM-mediated immunosuppression. Kaempferol, identified from TCM, emerges as an influential agent capable of altering TAM polarization, potentially enhancing anti-tumoral immunity. These findings underscore the translational potential of integrating TCM-derived compounds into immunotherapeutic strategies for LUAD.

Keywords: Kaempferol; Lung adenocarcinoma; Macrophage heterogeneity; Single-cell transcriptomics; Tumor microenvironment.

Fig. 1

Lung adenocarcinoma single-cell panoramic map. A All cells are colored according to cell type, where dots of different colors represent different types of cells. B All cells are colored based on tissue origin, with dots of different colors representing cells from different tissues. C marker genes of the cells, red indicates high gene expression levels, blue indicates low gene expression levels, and the size of the bubbles represents the percentage of gene expression. D The bars of different colors represent the proportions of different types of cells in tumor tissue or normal lung tissue

Fig. 2

Macrophages’ single-cell panoramas. A All macrophages are colored according to subgroups, with dots of different colors representing macrophages from different subgroups. B All macrophages are colored according to the tissue of origin, with dots of different colors representing macrophages from different tissues. C Different colored bars represent different macrophage subgroups, and each stripe in the heatmap represents a cell. Yellow indicates increased expression, while purple indicates decreased expression. D Red indicates that the pathway is activated, while blue indicates that the pathway is not activated. E The bars of different colors represent the proportions of different macrophage subgroups in tumor tissue or normal lung tissue. F The inflammasome scores of macrophages originating from tumors and normal tissues. G The inflammasome scores of macrophages from different subgroups

Fig. 3

Network pharmacology and survival analysis. A The intersection between the target genes of the drug and the characteristic genes of macrophages. B A network graph of the intersecting genes and corresponding drug components, with blue representing genes and green representing drugs. C KM (Kaplan–Meier) survival curve of AHSA1. D KM survival curve of CTSD. E KM survival curve of CYP1B1. F KM survival curve of OLR1. G KM survival curve of PARP1. H KM survival curve of PSMD3. I KM survival curve of SPP1. J KM survival curve of STAT1. The dashed line represents the 95% confidence interval of the survival curve

Fig. 4

STAT1 plays an important role in TAMs. A Expression levels of prognostically relevant genes in different cell types in GSE117570. B Expression levels of prognostically relevant genes in macrophages of tumor tissue and normal tissue in GSE117570, with blue indicating increased expression and gray indicating decreased expression. C Expression levels of prognostically relevant genes in different cell types in GSE198099. D Expression levels of prognostically relevant genes in macrophages of tumor tissue and normal tissue in GSE198099, with red indicating increased expression and green indicating decreased expression. E GOBP (Gene Ontology Biological Process) enrichment of upregulated genes in macrophages expressing STAT1. F KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment of upregulated genes in macrophages expressing STAT1

Fig. 5

Pseudotime analysis of STAT1 and immunofluorescence validation. A All macrophages are colored according to their status and distributed along the pseudotime branches. B All macrophages are colored according to their tissue origin and distributed along the pseudotime branches. C Distribution of STAT1 expression along the pseudotime axis, with cells colored by status. D Distribution of STAT1 expression along the pseudotime axis, with cells colored by tissue origin. E Representative images of STAT1 and CD68 immunofluorescence staining and F statistical results of the immunofluorescence. **** means P < 0.001

Fig. 6

Kaempferol inhibits macrophage M2 polarization. A Flow cytometry strategy for screening M1 and M2 macrophages. B Representative flow cytometry graphs of kaempferol inhibiting macrophage M2 polarization and C flow cytometry statistical results (Each group n = 15). D Representative flow cytometry graphs showing that kaempferol has no significant effect on macrophage M1 polarization and E flow cytometry statistical results (Each group n = 15)