Review




Structured Review

Human Protein Atlas single cell clustering
RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells <t>from</t> <t>single-cell</t> samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.
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1) Product Images from "Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer"

Article Title: Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer

Journal: Frontiers in Immunology

doi: 10.3389/fimmu.2026.1782545

RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells from single-cell samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.
Figure Legend Snippet: RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells from single-cell samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.

Techniques Used: Single Cell, Marker, Expressing, Gene Expression, Spatial Transcriptomics

The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box line plots comparing scaled ssGSEA scores for gene sets between CC1, CC2, CC3 and CC5 ecotypes. Gene set construction from single-cell samples. Use the Wilcoxon rank-sum test to compare component differences across the four groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001 (B) Dotplot shows cell communication in CC4. (C) Cnetplot shows cell communication in CC4. (D) Spatial feature plot shows spatial ecotypes and malignant in T_I_2, Arrow indicates spatial trajectories. (E) GSVA scores of the HALLMARK gene sets along the spatial trajectory in T_I_2. Different colors of the trajectories indicate the different ecological niches they occupy. (F) The expression levels of key genes involved in CC6 communication in ST samples, with arrows representing the spatial trajectories. (G) Trends in gene expression of the key genes involved in CC6 communication.
Figure Legend Snippet: The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box line plots comparing scaled ssGSEA scores for gene sets between CC1, CC2, CC3 and CC5 ecotypes. Gene set construction from single-cell samples. Use the Wilcoxon rank-sum test to compare component differences across the four groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001 (B) Dotplot shows cell communication in CC4. (C) Cnetplot shows cell communication in CC4. (D) Spatial feature plot shows spatial ecotypes and malignant in T_I_2, Arrow indicates spatial trajectories. (E) GSVA scores of the HALLMARK gene sets along the spatial trajectory in T_I_2. Different colors of the trajectories indicate the different ecological niches they occupy. (F) The expression levels of key genes involved in CC6 communication in ST samples, with arrows representing the spatial trajectories. (G) Trends in gene expression of the key genes involved in CC6 communication.

Techniques Used: Single Cell, Expressing, Gene Expression

The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box plots illustrating the proportions of various macrophage subtypes in single-cell samples before and after immunochemotherapy, as well as under different pathological response conditions. (Wilcoxon test) (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages. (C) . In the TCGA_LUAD dataset, patients were divided into high and low CYP27A1 expression groups based on the median expression level. The OS of patients in these two groups was then compared. OS, overall survival (D) The difference in the overall survival rates between patients with high and low CYP27A1 + TAMs scores (log-rank test). (E) Display the distribution of different macrophage cell states among pCR patients using Monocle 2. (F) In pCR patients, macrophage state calculated by monocle2. (G) Heatmap showing gene expression changes across two clusters during pseudotime progression, with clusters annotated on the left. (H) Gene Ontology (GO) enrichment analysis of differentially expressed genes across clusters.
Figure Legend Snippet: The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box plots illustrating the proportions of various macrophage subtypes in single-cell samples before and after immunochemotherapy, as well as under different pathological response conditions. (Wilcoxon test) (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages. (C) . In the TCGA_LUAD dataset, patients were divided into high and low CYP27A1 expression groups based on the median expression level. The OS of patients in these two groups was then compared. OS, overall survival (D) The difference in the overall survival rates between patients with high and low CYP27A1 + TAMs scores (log-rank test). (E) Display the distribution of different macrophage cell states among pCR patients using Monocle 2. (F) In pCR patients, macrophage state calculated by monocle2. (G) Heatmap showing gene expression changes across two clusters during pseudotime progression, with clusters annotated on the left. (H) Gene Ontology (GO) enrichment analysis of differentially expressed genes across clusters.

Techniques Used: Single Cell, Expressing, Gene Expression

Immunotherapy enhances the function of CYP27A1 + TAMs through LXR upregulation (A) . Heatmap of genesets from KEGG for scaled GSVA across macrophages, with samples grouped into pre-treatment and post-treatment conditions. (B) Volcano plot displaying differentially expressed genes in CYP27A1 + TAMs between non-treatment (NT) and post-treatment (PT) conditions. (C, D) Spatial distribution of CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (E, F) Distribution of tumor cells and CYP27A1 + TAMs with high vs. low LXR expression in T_C and T_I samples. (G) Distribution of CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (H) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in single-cell samples (Pearson’s correlation test). (I) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in TCGA LUAD cohort (Pearson’s correlation test). (J) Heatmap showing co-localization intensity of different cell types within spots (intra view); darker colors indicate higher co-localization intensity.
Figure Legend Snippet: Immunotherapy enhances the function of CYP27A1 + TAMs through LXR upregulation (A) . Heatmap of genesets from KEGG for scaled GSVA across macrophages, with samples grouped into pre-treatment and post-treatment conditions. (B) Volcano plot displaying differentially expressed genes in CYP27A1 + TAMs between non-treatment (NT) and post-treatment (PT) conditions. (C, D) Spatial distribution of CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (E, F) Distribution of tumor cells and CYP27A1 + TAMs with high vs. low LXR expression in T_C and T_I samples. (G) Distribution of CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (H) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in single-cell samples (Pearson’s correlation test). (I) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in TCGA LUAD cohort (Pearson’s correlation test). (J) Heatmap showing co-localization intensity of different cell types within spots (intra view); darker colors indicate higher co-localization intensity.

Techniques Used: Expressing, Single Cell

External Cohort Validation of CYP27A1 + TAMs Function (A) . UMAP plot of 201,003 cells from the single-cell cohort GSE131907 . (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE131907 . (C) Spatial feature plot showing the spatial localization of CD8A, CD8B, and CYP27A1 genes in an E-MTAB-13530 sample. Gene expression values were normalized using SCTransform. (D) Schematic of co-localization strength for Misty cell types from an intra-perspective in E-MTAB-13530, with a cutoff threshold set at 1.5. (E) UMAP plot displaying major cell types and treatment response for 33,443 cells from GSE233203 . R: responder, NR: non-responder. (F) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE223203 . (G) Spatial feature plot illustrating the spatial distribution of different cell types in a sample from GSE267960 . (H) Bubble plot showing the distribution of CYP27A1 gene expression across various tissues and cell types based on data from the Human Protein Atlas. (I) Dendrogram displaying GO pathways enriched with specific genes from cluster 58.
Figure Legend Snippet: External Cohort Validation of CYP27A1 + TAMs Function (A) . UMAP plot of 201,003 cells from the single-cell cohort GSE131907 . (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE131907 . (C) Spatial feature plot showing the spatial localization of CD8A, CD8B, and CYP27A1 genes in an E-MTAB-13530 sample. Gene expression values were normalized using SCTransform. (D) Schematic of co-localization strength for Misty cell types from an intra-perspective in E-MTAB-13530, with a cutoff threshold set at 1.5. (E) UMAP plot displaying major cell types and treatment response for 33,443 cells from GSE233203 . R: responder, NR: non-responder. (F) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE223203 . (G) Spatial feature plot illustrating the spatial distribution of different cell types in a sample from GSE267960 . (H) Bubble plot showing the distribution of CYP27A1 gene expression across various tissues and cell types based on data from the Human Protein Atlas. (I) Dendrogram displaying GO pathways enriched with specific genes from cluster 58.

Techniques Used: Biomarker Discovery, Single Cell, Expressing, Gene Expression

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RNA Sequencing:

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other:

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Mouse Assay:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
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Western Blot:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Mice ○ Cell lines • METHOD DETAILS ○ DepMap data analysis ○ Generation of genetically edited lines ○ Western blotting ○ Viability assay ○ MitoTracker and TMRE assays ○ L-HPG nascent protein synthesis assay ○ OP-puro assay ○ EdU incorporation flow cytometry assay ○ Flow-based competition assay ○ Proliferation analyses ○ Oxygen consumption and extracellular acidification rates ○ Isotope tracing and steady-state metabolite measurement ○ Citrate uptake assays ○ GC-MS analysis ○ Pathology ○ Immunohistochemistry ○ RNA isolation and qPCR ○ RNA-sequencing and analysis ○ Single cell transcriptomics (Human Protein Atlas) ○ Statistics and reproducibility SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.cell. ..

Viability Assay:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
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Flow Cytometry:

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Competitive Binding Assay:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
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Gas Chromatography-Mass Spectrometry:

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Immunohistochemistry:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Mice ○ Cell lines • METHOD DETAILS ○ DepMap data analysis ○ Generation of genetically edited lines ○ Western blotting ○ Viability assay ○ MitoTracker and TMRE assays ○ L-HPG nascent protein synthesis assay ○ OP-puro assay ○ EdU incorporation flow cytometry assay ○ Flow-based competition assay ○ Proliferation analyses ○ Oxygen consumption and extracellular acidification rates ○ Isotope tracing and steady-state metabolite measurement ○ Citrate uptake assays ○ GC-MS analysis ○ Pathology ○ Immunohistochemistry ○ RNA isolation and qPCR ○ RNA-sequencing and analysis ○ Single cell transcriptomics (Human Protein Atlas) ○ Statistics and reproducibility SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.cell. ..

Isolation:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Mice ○ Cell lines • METHOD DETAILS ○ DepMap data analysis ○ Generation of genetically edited lines ○ Western blotting ○ Viability assay ○ MitoTracker and TMRE assays ○ L-HPG nascent protein synthesis assay ○ OP-puro assay ○ EdU incorporation flow cytometry assay ○ Flow-based competition assay ○ Proliferation analyses ○ Oxygen consumption and extracellular acidification rates ○ Isotope tracing and steady-state metabolite measurement ○ Citrate uptake assays ○ GC-MS analysis ○ Pathology ○ Immunohistochemistry ○ RNA isolation and qPCR ○ RNA-sequencing and analysis ○ Single cell transcriptomics (Human Protein Atlas) ○ Statistics and reproducibility SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.cell. ..

Real-time Polymerase Chain Reaction:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Mice ○ Cell lines • METHOD DETAILS ○ DepMap data analysis ○ Generation of genetically edited lines ○ Western blotting ○ Viability assay ○ MitoTracker and TMRE assays ○ L-HPG nascent protein synthesis assay ○ OP-puro assay ○ EdU incorporation flow cytometry assay ○ Flow-based competition assay ○ Proliferation analyses ○ Oxygen consumption and extracellular acidification rates ○ Isotope tracing and steady-state metabolite measurement ○ Citrate uptake assays ○ GC-MS analysis ○ Pathology ○ Immunohistochemistry ○ RNA isolation and qPCR ○ RNA-sequencing and analysis ○ Single cell transcriptomics (Human Protein Atlas) ○ Statistics and reproducibility SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.cell. ..

RNA sequencing:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Mice ○ Cell lines • METHOD DETAILS ○ DepMap data analysis ○ Generation of genetically edited lines ○ Western blotting ○ Viability assay ○ MitoTracker and TMRE assays ○ L-HPG nascent protein synthesis assay ○ OP-puro assay ○ EdU incorporation flow cytometry assay ○ Flow-based competition assay ○ Proliferation analyses ○ Oxygen consumption and extracellular acidification rates ○ Isotope tracing and steady-state metabolite measurement ○ Citrate uptake assays ○ GC-MS analysis ○ Pathology ○ Immunohistochemistry ○ RNA isolation and qPCR ○ RNA-sequencing and analysis ○ Single cell transcriptomics (Human Protein Atlas) ○ Statistics and reproducibility SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.cell. ..

Single-cell Transcriptomics:

Article Title: Citrate clearance is a major function of aconitase 2 in the canonical TCA cycle.
Article Snippet: .. STAR★METHODS Detailed methods are provided in the online version of this paper and include the following: • KEY RESOURCES TABLE • EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS ○ Mice ○ Cell lines • METHOD DETAILS ○ DepMap data analysis ○ Generation of genetically edited lines ○ Western blotting ○ Viability assay ○ MitoTracker and TMRE assays ○ L-HPG nascent protein synthesis assay ○ OP-puro assay ○ EdU incorporation flow cytometry assay ○ Flow-based competition assay ○ Proliferation analyses ○ Oxygen consumption and extracellular acidification rates ○ Isotope tracing and steady-state metabolite measurement ○ Citrate uptake assays ○ GC-MS analysis ○ Pathology ○ Immunohistochemistry ○ RNA isolation and qPCR ○ RNA-sequencing and analysis ○ Single cell transcriptomics (Human Protein Atlas) ○ Statistics and reproducibility SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.org/10.1016/j.cell. ..



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RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells <t>from</t> <t>single-cell</t> samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.
Single Cell Clustering, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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single cell clustering - by Bioz Stars, 2026-10
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86
Human Protein Atlas single cell clustering data
RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells <t>from</t> <t>single-cell</t> samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.
Single Cell Clustering Data, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cell+clusters/data+rna+seq/pm41687532-287-1-6
Average 86 stars, based on 1 article reviews
single cell clustering data - by Bioz Stars, 2026-10
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86
Human Protein Atlas dxriii targets hepatic stard4 single cell clustering data
RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells <t>from</t> <t>single-cell</t> samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.
Dxriii Targets Hepatic Stard4 Single Cell Clustering Data, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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dxriii targets hepatic stard4 single cell clustering data - by Bioz Stars, 2026-10
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96
Guangzhou JET Bio-Filtration well cell culture clusters
RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells <t>from</t> <t>single-cell</t> samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.
Well Cell Culture Clusters, supplied by Guangzhou JET Bio-Filtration, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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well cell culture clusters - by Bioz Stars, 2026-10
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Image Search Results


RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells from single-cell samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.

Journal: Frontiers in Immunology

Article Title: Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer

doi: 10.3389/fimmu.2026.1782545

Figure Lengend Snippet: RCTD integrates results of SC and ST (A) . UMAP plot of 127943 cells from single-cell samples. (B, C) Dotplot showing the marker genes for clusters. The color gradient represents the scaled expression level, and the diameter represents the percentage of cells. (B) markers of major clusters, (C) markers of macrophages. (D) H&E micrographs of infiltrative tumor (T_I), tumor core (T_C), Stroma of non-major pathologic response (S_NMPR) and Stroma of major pathologic response (MPR). (E) Cell marker gene expression levels in T_I, T_C, S_NMPR and S_MPR samples. (F, G) RCTD deconvolution results of T_I, T_C, S_NMPR and S_MPR samples. RCTD, Robust Cell Type Decomposition; SC, single-cell; ST, spatial transcriptomics.

Article Snippet: In the Human Protein Atlas single-cell clustering, CYP27A1 is part of cluster 58 (Macrophages - Innate immune response) with a confidence score of 1 ( ). (Confidence is the fraction of times a gene was assigned to the cluster in repeated clustering, and therefore reflects how strongly associated it is to the cluster.

Techniques: Single Cell, Marker, Expressing, Gene Expression, Spatial Transcriptomics

The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box line plots comparing scaled ssGSEA scores for gene sets between CC1, CC2, CC3 and CC5 ecotypes. Gene set construction from single-cell samples. Use the Wilcoxon rank-sum test to compare component differences across the four groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001 (B) Dotplot shows cell communication in CC4. (C) Cnetplot shows cell communication in CC4. (D) Spatial feature plot shows spatial ecotypes and malignant in T_I_2, Arrow indicates spatial trajectories. (E) GSVA scores of the HALLMARK gene sets along the spatial trajectory in T_I_2. Different colors of the trajectories indicate the different ecological niches they occupy. (F) The expression levels of key genes involved in CC6 communication in ST samples, with arrows representing the spatial trajectories. (G) Trends in gene expression of the key genes involved in CC6 communication.

Journal: Frontiers in Immunology

Article Title: Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer

doi: 10.3389/fimmu.2026.1782545

Figure Lengend Snippet: The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box line plots comparing scaled ssGSEA scores for gene sets between CC1, CC2, CC3 and CC5 ecotypes. Gene set construction from single-cell samples. Use the Wilcoxon rank-sum test to compare component differences across the four groups. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001 (B) Dotplot shows cell communication in CC4. (C) Cnetplot shows cell communication in CC4. (D) Spatial feature plot shows spatial ecotypes and malignant in T_I_2, Arrow indicates spatial trajectories. (E) GSVA scores of the HALLMARK gene sets along the spatial trajectory in T_I_2. Different colors of the trajectories indicate the different ecological niches they occupy. (F) The expression levels of key genes involved in CC6 communication in ST samples, with arrows representing the spatial trajectories. (G) Trends in gene expression of the key genes involved in CC6 communication.

Article Snippet: In the Human Protein Atlas single-cell clustering, CYP27A1 is part of cluster 58 (Macrophages - Innate immune response) with a confidence score of 1 ( ). (Confidence is the fraction of times a gene was assigned to the cluster in repeated clustering, and therefore reflects how strongly associated it is to the cluster.

Techniques: Single Cell, Expressing, Gene Expression

The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box plots illustrating the proportions of various macrophage subtypes in single-cell samples before and after immunochemotherapy, as well as under different pathological response conditions. (Wilcoxon test) (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages. (C) . In the TCGA_LUAD dataset, patients were divided into high and low CYP27A1 expression groups based on the median expression level. The OS of patients in these two groups was then compared. OS, overall survival (D) The difference in the overall survival rates between patients with high and low CYP27A1 + TAMs scores (log-rank test). (E) Display the distribution of different macrophage cell states among pCR patients using Monocle 2. (F) In pCR patients, macrophage state calculated by monocle2. (G) Heatmap showing gene expression changes across two clusters during pseudotime progression, with clusters annotated on the left. (H) Gene Ontology (GO) enrichment analysis of differentially expressed genes across clusters.

Journal: Frontiers in Immunology

Article Title: Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer

doi: 10.3389/fimmu.2026.1782545

Figure Lengend Snippet: The tumor niche uncovers key cells and genes involved in tumor progression (A) . Box plots illustrating the proportions of various macrophage subtypes in single-cell samples before and after immunochemotherapy, as well as under different pathological response conditions. (Wilcoxon test) (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages. (C) . In the TCGA_LUAD dataset, patients were divided into high and low CYP27A1 expression groups based on the median expression level. The OS of patients in these two groups was then compared. OS, overall survival (D) The difference in the overall survival rates between patients with high and low CYP27A1 + TAMs scores (log-rank test). (E) Display the distribution of different macrophage cell states among pCR patients using Monocle 2. (F) In pCR patients, macrophage state calculated by monocle2. (G) Heatmap showing gene expression changes across two clusters during pseudotime progression, with clusters annotated on the left. (H) Gene Ontology (GO) enrichment analysis of differentially expressed genes across clusters.

Article Snippet: In the Human Protein Atlas single-cell clustering, CYP27A1 is part of cluster 58 (Macrophages - Innate immune response) with a confidence score of 1 ( ). (Confidence is the fraction of times a gene was assigned to the cluster in repeated clustering, and therefore reflects how strongly associated it is to the cluster.

Techniques: Single Cell, Expressing, Gene Expression

Immunotherapy enhances the function of CYP27A1 + TAMs through LXR upregulation (A) . Heatmap of genesets from KEGG for scaled GSVA across macrophages, with samples grouped into pre-treatment and post-treatment conditions. (B) Volcano plot displaying differentially expressed genes in CYP27A1 + TAMs between non-treatment (NT) and post-treatment (PT) conditions. (C, D) Spatial distribution of CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (E, F) Distribution of tumor cells and CYP27A1 + TAMs with high vs. low LXR expression in T_C and T_I samples. (G) Distribution of CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (H) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in single-cell samples (Pearson’s correlation test). (I) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in TCGA LUAD cohort (Pearson’s correlation test). (J) Heatmap showing co-localization intensity of different cell types within spots (intra view); darker colors indicate higher co-localization intensity.

Journal: Frontiers in Immunology

Article Title: Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer

doi: 10.3389/fimmu.2026.1782545

Figure Lengend Snippet: Immunotherapy enhances the function of CYP27A1 + TAMs through LXR upregulation (A) . Heatmap of genesets from KEGG for scaled GSVA across macrophages, with samples grouped into pre-treatment and post-treatment conditions. (B) Volcano plot displaying differentially expressed genes in CYP27A1 + TAMs between non-treatment (NT) and post-treatment (PT) conditions. (C, D) Spatial distribution of CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (E, F) Distribution of tumor cells and CYP27A1 + TAMs with high vs. low LXR expression in T_C and T_I samples. (G) Distribution of CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in stromal samples. (H) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in single-cell samples (Pearson’s correlation test). (I) Correlation between CD8 + T cells and CYP27A1 + TAMs with high vs. low LXR expression in TCGA LUAD cohort (Pearson’s correlation test). (J) Heatmap showing co-localization intensity of different cell types within spots (intra view); darker colors indicate higher co-localization intensity.

Article Snippet: In the Human Protein Atlas single-cell clustering, CYP27A1 is part of cluster 58 (Macrophages - Innate immune response) with a confidence score of 1 ( ). (Confidence is the fraction of times a gene was assigned to the cluster in repeated clustering, and therefore reflects how strongly associated it is to the cluster.

Techniques: Expressing, Single Cell

External Cohort Validation of CYP27A1 + TAMs Function (A) . UMAP plot of 201,003 cells from the single-cell cohort GSE131907 . (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE131907 . (C) Spatial feature plot showing the spatial localization of CD8A, CD8B, and CYP27A1 genes in an E-MTAB-13530 sample. Gene expression values were normalized using SCTransform. (D) Schematic of co-localization strength for Misty cell types from an intra-perspective in E-MTAB-13530, with a cutoff threshold set at 1.5. (E) UMAP plot displaying major cell types and treatment response for 33,443 cells from GSE233203 . R: responder, NR: non-responder. (F) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE223203 . (G) Spatial feature plot illustrating the spatial distribution of different cell types in a sample from GSE267960 . (H) Bubble plot showing the distribution of CYP27A1 gene expression across various tissues and cell types based on data from the Human Protein Atlas. (I) Dendrogram displaying GO pathways enriched with specific genes from cluster 58.

Journal: Frontiers in Immunology

Article Title: Integrative multi-omics and machine learning reveals the spatial niche distribution and role of CYP27A1 + TAMs in immunotherapy response in non-small cell lung cancer

doi: 10.3389/fimmu.2026.1782545

Figure Lengend Snippet: External Cohort Validation of CYP27A1 + TAMs Function (A) . UMAP plot of 201,003 cells from the single-cell cohort GSE131907 . (B) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE131907 . (C) Spatial feature plot showing the spatial localization of CD8A, CD8B, and CYP27A1 genes in an E-MTAB-13530 sample. Gene expression values were normalized using SCTransform. (D) Schematic of co-localization strength for Misty cell types from an intra-perspective in E-MTAB-13530, with a cutoff threshold set at 1.5. (E) UMAP plot displaying major cell types and treatment response for 33,443 cells from GSE233203 . R: responder, NR: non-responder. (F) Heatmap of genesets from KEGG for scaled GSVA across macrophages ranked by CYP27A1 expression in GSE223203 . (G) Spatial feature plot illustrating the spatial distribution of different cell types in a sample from GSE267960 . (H) Bubble plot showing the distribution of CYP27A1 gene expression across various tissues and cell types based on data from the Human Protein Atlas. (I) Dendrogram displaying GO pathways enriched with specific genes from cluster 58.

Article Snippet: In the Human Protein Atlas single-cell clustering, CYP27A1 is part of cluster 58 (Macrophages - Innate immune response) with a confidence score of 1 ( ). (Confidence is the fraction of times a gene was assigned to the cluster in repeated clustering, and therefore reflects how strongly associated it is to the cluster.

Techniques: Biomarker Discovery, Single Cell, Expressing, Gene Expression