Journal: Nature Cancer

Article Title: Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

doi: 10.1038/s43018-025-01054-6

Figure Lengend Snippet: ( a ) SLAMF6 expression in immune cell populations based on the”Immune Cells” RNA sequencing dataset from the Human Protein Atlas. ( b ) Gene expression of SLAMF6 in major tissues based on the Human Protein Atlas RNA sequencing dataset. ( c ) SLAMF6 gene expression in major cell types in the”Single Cell Type” whole-body scRNAseq dataset from the Human Protein Atlas. ( d ) SLAMF6 protein expression in major tissues based on immunohistochemistry in the”Human Protein Atlas” dataset. ( e ) Protein expression of SLAMF6 in major tissues and cell types based on mass spectrometry in the”Human Proteome Map” dataset.

Article Snippet: Extended Data Fig. 2 SLAMF6 gene and protein expression in normal cells. ( a ) SLAMF6 expression in immune cell populations based on the”Immune Cells” RNA sequencing dataset from the Human Protein Atlas. ( b ) Gene expression of SLAMF6 in major tissues based on the Human Protein Atlas RNA sequencing dataset. ( c ) SLAMF6 gene expression in major cell types in the”Single Cell Type” whole-body scRNAseq dataset from the Human Protein Atlas. ( d ) SLAMF6 protein expression in major tissues based on immunohistochemistry in the”Human Protein Atlas” dataset. ( e ) Protein expression of SLAMF6 in major tissues and cell types based on mass spectrometry in the”Human Proteome Map” dataset.

Techniques: Expressing, RNA Sequencing, Gene Expression, Immunohistochemistry, Mass Spectrometry

Journal: Nature Cancer

Article Title: Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

doi: 10.1038/s43018-025-01054-6

Figure Lengend Snippet: Frequencies of CD4 + T cells, CD8 + T cells and regulatory T cells within the total T cell population for each AML patient and NBM donor based on ( a ) surface protein expression by flow cytometry (n = 39 cases; Kruskal-Wallis test with Dunn’s post hoc test) and ( b ) global gene expression by single cell RNA sequencing (n = 41 cases; Kruskal-Wallis test with Dunn’s post hoc test). Similarity of T cell populations in primary AML samples to ( c ) exhausted T cells , ( d ) exhausted T cells and ( e ) progenitor exhausted T cells , based on global gene expression profiles generated by single cell RNA sequencing. ( f ) Expression of the progenitor exhausted T cell marker GZMK in T cell populations in primary AML samples. ( g ) Expression of inhibitory receptors upregulated in CD8 + T cells in AML patients . Left: All T cell populations in all AML cases (n = 41 cases). Middle: The CD4 + naïve T cell population in AML cases classified as SLAMF6 High (red; n = 11 cases), SLAMF6 Int (yellow; n = 13 cases) and SLAMF6 Neg (blue; n = 17 cases) as well as CD4 + naïve T cells from normal bone marrow (grey). Right: The CD8 + naïve T cell population in AML cases and NBM. Violin plots with bars indicating median values. Y axis scales are consistent across left, middle and right panels.

Article Snippet: Extended Data Fig. 2 SLAMF6 gene and protein expression in normal cells. ( a ) SLAMF6 expression in immune cell populations based on the”Immune Cells” RNA sequencing dataset from the Human Protein Atlas. ( b ) Gene expression of SLAMF6 in major tissues based on the Human Protein Atlas RNA sequencing dataset. ( c ) SLAMF6 gene expression in major cell types in the”Single Cell Type” whole-body scRNAseq dataset from the Human Protein Atlas. ( d ) SLAMF6 protein expression in major tissues based on immunohistochemistry in the”Human Protein Atlas” dataset. ( e ) Protein expression of SLAMF6 in major tissues and cell types based on mass spectrometry in the”Human Proteome Map” dataset.

Techniques: Expressing, Flow Cytometry, Gene Expression, RNA Sequencing, Generated, Marker

Journal: Nature Cancer

Article Title: Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

doi: 10.1038/s43018-025-01054-6

Figure Lengend Snippet: ( a ) T cell activation in response to in vitro treatment with TNC-1 in co-cultures with primary T cells and HNT-34 cells (left; p = 0.041), KG-1 cells (middle; p = 0.314) and THP-1 cells (right; p = 0.364), as determined by surface marker expression of CD25 and CD69. Mean ± SEM of four (KG-1) or six (HNT-34, THP-1) T cell donors, normalized to isotype control (two-sided Mann-Whitney U test). ( b ) AML cell killing in response to treatment with TNC-1 in suspension cultures without T cells, containing only HNT-34 cells (left; p = 0.999), KG-1 cells (middle; p = 0.700) and THP-1 cells (right; p = 0.999). Mean ± SEM of four experiments, normalized to isotype control (two-sided Mann-Whitney U test). ( c ) T cell-mediated killing of AML cells over time in co-cultures with T cells expressing the NY-ESO T cell receptor and HNT-34 AML cells expressing the corresponding peptide-MHC complex. Mean ± SEM of four technical replicates for each time point and treatment condition for one T cell donor (two-sided Mann-Whitney U test; p = 0.029 for all time points). ( d ) T cell activation after 72 h in the NY-ESO co-culture model, as determined by surface expression of CD25. Mean ± SEM of three T cell donors (two-sided Mann-Whitney U test; p = 0.999). ( e ) UMAP projection and cell type classifications for co-cultures with T cells and HNT-34 AML cells after treatment with TNC-1 (left; n = 16254 cells) or an isotype control antibody (right; n = 15723 cells), based on single-cell RNA sequencing. Joint projection for co-cultures with two independent T cell donors. MAIT: mucosal-associated invariant T cell, Treg: regulatory T cell, gdT: gamma delta T cell, NK: natural killer cell. ( f ) Volcano plot of differentially expressed genes between HNT-34 cells treated with TNC-1 or an isotype control antibody in T cell co-cultures (n = 23886 genes). Y axis represents significance denoted as the negative logarithm of the p value (two-sided t test, without multiple testing correction). Grey: P value > 10 −5 . Blue: P value < 10 −5 . ( g ) The 15 most significantly downregulated (left) and upregulated (right) gene sets in HNT-34 cells treated with TNC-1 compared to treatment with an isotype control antibody, based on gene set enrichment analysis (GSEA) using the Reactome database (fgsea test with multiple testing correction and threshold p < 0.05). ( h ) Distribution of T cell populations in two independent donors after treatment with TNC-1 or an isotype control antibody, based on single-cell RNA sequencing analysis.

Article Snippet: Extended Data Fig. 2 SLAMF6 gene and protein expression in normal cells. ( a ) SLAMF6 expression in immune cell populations based on the”Immune Cells” RNA sequencing dataset from the Human Protein Atlas. ( b ) Gene expression of SLAMF6 in major tissues based on the Human Protein Atlas RNA sequencing dataset. ( c ) SLAMF6 gene expression in major cell types in the”Single Cell Type” whole-body scRNAseq dataset from the Human Protein Atlas. ( d ) SLAMF6 protein expression in major tissues based on immunohistochemistry in the”Human Protein Atlas” dataset. ( e ) Protein expression of SLAMF6 in major tissues and cell types based on mass spectrometry in the”Human Proteome Map” dataset.

Techniques: Activation Assay, In Vitro, Marker, Expressing, Control, MANN-WHITNEY, Suspension, Co-Culture Assay, RNA Sequencing

Journal: Nature Cancer

Article Title: Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

doi: 10.1038/s43018-025-01054-6

Figure Lengend Snippet: Similarity of T cell populations to ( a ) progenitor exhausted T cells and ( b ) exhausted T cells after treatment of T cell and AML cell co-cultures with TNC-1 or an isotype control antibody for 72 h, based on gene expression profiles determined by single-cell RNA sequencing. Violin plots with bars indicating median values. Red: Distributions of T cells treated with TNC-1. Blue: Distributions of T cells treated with an isotype control antibody. ( c ) Frequencies of CD4 + and CD8 + T cells after treatment with TNC-1 in co-culture experiments with primary T cells and HNT-34 AML cells. ( d ) Composition of the CD4 + T cell population in co-cultures, based on surface expression of CD45RA and CCR7. ( e ) Composition of the CD8 + T cell population in co-cultures, based on surface expression of CD45RA and CCR7. ( f ) Expression of T cell inhibitory receptors and exhaustion markers after treatment with TNC-1. All data is based on surface marker profiling by flow cytometry. Mean of four technical replicates for each donor and treatment condition.

Article Snippet: Extended Data Fig. 2 SLAMF6 gene and protein expression in normal cells. ( a ) SLAMF6 expression in immune cell populations based on the”Immune Cells” RNA sequencing dataset from the Human Protein Atlas. ( b ) Gene expression of SLAMF6 in major tissues based on the Human Protein Atlas RNA sequencing dataset. ( c ) SLAMF6 gene expression in major cell types in the”Single Cell Type” whole-body scRNAseq dataset from the Human Protein Atlas. ( d ) SLAMF6 protein expression in major tissues based on immunohistochemistry in the”Human Protein Atlas” dataset. ( e ) Protein expression of SLAMF6 in major tissues and cell types based on mass spectrometry in the”Human Proteome Map” dataset.

Techniques: Control, Gene Expression, RNA Sequencing, Co-Culture Assay, Expressing, Marker, Flow Cytometry

Journal: Nature Cancer

Article Title: Aberrant expression of SLAMF6 constitutes a targetable immune escape mechanism in acute myeloid leukemia

doi: 10.1038/s43018-025-01054-6

Figure Lengend Snippet: Increased expression of genes associated with T cell activation in T cell populations from ( a ) Donor U and ( b ) Donor W after treatment with TNC-1 compared to an isotype control antibody, based on gene set enrichment analysis of single-cell RNA sequencing data. ( c ) The 15 most significantly upregulated (left) and downregulated (right) gene sets in cells classified as CD8 + effector T cells after treatment of co-cultures containing primary T cells from Donor U and HNT-34 cells with TNC-1 compared to an isotype control antibody, based on gene set enrichment analysis (GSEA) of single-cell RNA sequencing data using the Reactome database. ( d ) Gene sets upregulated (left) and downregulated (right) in CD8 + effector T cells from Donor W after treatment of co-cultures with TNC-1. ( e ) Gene sets upregulated (left) and downregulated (right) in CD8 + memory T cells from Donor U after treatment of co-cultures with TNC-1. ( f ) Gene sets upregulated (left) and downregulated (right) in CD8 + memory T cells from Donor W after treatment of co-cultures with TNC-1. All p values are based on the fgsea test with correction for multiple testing. Gene sets are included with a significance threshold of p < 0.05.

Article Snippet: Extended Data Fig. 2 SLAMF6 gene and protein expression in normal cells. ( a ) SLAMF6 expression in immune cell populations based on the”Immune Cells” RNA sequencing dataset from the Human Protein Atlas. ( b ) Gene expression of SLAMF6 in major tissues based on the Human Protein Atlas RNA sequencing dataset. ( c ) SLAMF6 gene expression in major cell types in the”Single Cell Type” whole-body scRNAseq dataset from the Human Protein Atlas. ( d ) SLAMF6 protein expression in major tissues based on immunohistochemistry in the”Human Protein Atlas” dataset. ( e ) Protein expression of SLAMF6 in major tissues and cell types based on mass spectrometry in the”Human Proteome Map” dataset.

Techniques: Expressing, Activation Assay, Control, RNA Sequencing

Journal: iScience

Article Title: Fine-tuned KDM1A alternative splicing regulates human cardiomyogenesis through an enzymatic-independent mechanism

doi: 10.1016/j.isci.2022.104665

Figure Lengend Snippet:

Article Snippet: Artificial Intelligence RNA-Seq (AIR) Software , Sequentia Biotech , https://transcriptomics.cloud.

Techniques: Virus, Recombinant, Transfection, Protease Inhibitor, Magnetic Beads, cDNA Synthesis, Staining, Immunocytochemistry, Calcium Assay, Purification, Western Blot, Plasmid Preparation, Software, Electrophoresis, Microscopy, Imaging, Real-time Polymerase Chain Reaction, Mass Spectrometry

Journal: iScience

Article Title: Profiling of diverse tumor types establishes the broad utility of VHL-based ProTaCs and triages candidate ubiquitin ligases

doi: 10.1016/j.isci.2022.103985

Figure Lengend Snippet: Correlation of PROTAC activity with CRBN and VHL RNA expression, DNA copy number, and protein level (A and B) DC50 values from the cell line panel for each compound were used to group the cell lines into the bottom (low) and top (high) quartiles. Low and high quartiles were plotted against ligase mRNA expression or copy number, p values from unpaired two-samples, two-sided Wilcoxon rank sum tests of the groups were calculated. (A) dBET1 activity correlates significantly with CRBN copy number, p = 0.00058, and mRNA expression, p = 0.0048. Cell lines with non-synonymous mutations of CRBN were marked in red. (B) MZ1 activity correlates with VHL RNA expression, p = 0.028 but not VHL copy number, p = 0.059. Cell lines with non-synonymous mutations of VHL were marked in red. (C) Dose-response curves from representative kidney-derived cancer cell lines are shown; 786-O is devoid of both VHL and CRBN activity, 769P is lacking VHL activity. Dose titration curves are derived from n = 2 independent experiments, error bars represent standard error of the mean (SEM). (D) Lysates from untreated cells were separated by capillary electrophoresis, VHL and CRBN proteins were immune-detected. Each of the five kidney-derived cancer cell lines is lacking VHL protein, all of the cell lines express appreciable CRBN protein. (E) Dose-response curves from two representative lung cancer cell lines, H23 lacks dBET1-CRBN-associated activity. Dose titration curves are derived from n = 2 independent experiments, error bars represent standard error of the mean (SEM). (F) Lung-derived cancer cell lines with low CRBN activity have low or no CRBN protein, all lung cancer cell lines express VHL protein.

Article Snippet: For this analysis, we retrieved RNA-Seq expression and DNA alteration data from available OmicSoft TCGA data sets and graphed these by TCGA-designated tumor type ( B).

Techniques: Activity Assay, RNA Expression, Expressing, Derivative Assay, Titration, Electrophoresis

Journal: iScience

Article Title: Profiling of diverse tumor types establishes the broad utility of VHL-based ProTaCs and triages candidate ubiquitin ligases

doi: 10.1016/j.isci.2022.103985

Figure Lengend Snippet: Comparison of genomic features for seven PROTAC Ub-ligases (A) Boxplot showing the distribution of log transformed fold change of the expression of seven Ub-ligases in cancer tissue compared to its paired non-cancer control tissue. Only cancer types with at least 50 non-cancer control tissue samples were included. (B) DNA alternation landscape of seven Ub-ligases across cancer types in TCGA. Bar graph showing percentage of samples harboring each Ub-ligase mutations across tumor types, the number of samples altered are labeled in the right side of each bar. Different mutation types are color labeled, with red representing amplification, blue representing homozygous deletion, green representing non-synonymous mutations, and gray representing a mixture of the above type of mutations. (C) Genome-scale CRISPR-Cas9 essentiality screen results for genes in across different cancer cell lines performed by the Broad Institute were characterized by dependency score (CERES) to reflect the functional importance of genes in certain cancer types. Boxplots summarized the distribution of CERES score of each ligase receptor in cell lines of representative tumor types. A lower score means that a gene is more likely to be essential for the cancer cell line survival and proliferation. A score of −1 corresponds to the median of all common essential genes, used as a cutoff indicator here.

Article Snippet: For this analysis, we retrieved RNA-Seq expression and DNA alteration data from available OmicSoft TCGA data sets and graphed these by TCGA-designated tumor type ( B).

Techniques: Comparison, Transformation Assay, Expressing, Control, Labeling, Mutagenesis, Amplification, CRISPR, Functional Assay

Journal: Nature Communications

Article Title: Post-resolution macrophages shape long-term tissue immunity and integrity in a mouse model of pneumococcal pneumonia

doi: 10.1038/s41467-024-48138-y

Figure Lengend Snippet: WT C57BL6/J mice were administered intranasal S. pneumoniae with lungs digested and macrophage populations including ( A ) double negative interstitial macrophage, ( B ) LYVE-1 - /MHC-II + interstitial macrophages, ( C ) LYVE-1 + /MHC-II - interstitial macrophages as well as ( D ) alveolar macrophages sorted by FACS and subject to analysis by RNAseq followed by bioinformatic analysis using edgeR in RStudio as illustrated ( n = 5 mice/group). D qPCR validation ( n = 3 mice/group) was used in a separate independent experiment to confirm upregulation of Inhba and Ptgs2 in naïve versus day 14 alveolar macrophages. Students unpaired t -test was used to compare the means of two groups. A p value of <0.05 was taken as the threshold of significance with graphical representation as; p < 0.05 = *, p < 0.01 = ** and p < 0.001 = *** and presented as mean ± SEM. As alveolar macrophages showed the greatest changes post-resolution compared to the naive state these cells were further analysed by using ( E ) PANTHER to identify GoTerms from upregulated genes at day 14 compared to naïve, ( F , G ) normalised read counts of five replicates from naïve alveolar macrophages compared to day 14, ( H ) EdgeR results showing differential gene expression as logFC and p value for genes relating to migration, matrix remodelling, regulation of phenotype and interferon signalling.

Article Snippet: WT C57BL6/J mice were administered intranasal S. pneumoniae with lungs digested and macrophage populations including ( A ) double negative interstitial macrophage, ( B ) LYVE-1 - /MHC-II + interstitial macrophages, ( C ) LYVE-1 + /MHC-II - interstitial macrophages as well as ( D ) alveolar macrophages sorted by FACS and subject to analysis by RNAseq followed by bioinformatic analysis using edgeR in RStudio as illustrated ( n = 5 mice/group).

Techniques: Biomarker Discovery, Gene Expression, Migration