rabbit anti p63α  (Cell Signaling Technology Inc)

Journal: Communications Biology

Article Title: Single-cell insights into trophoblast heterogeneity and adaptive dysfunction in selective fetal growth restriction

doi: 10.1038/s42003-026-09798-2

Figure Lengend Snippet: A UMAP visualization of all trophoblast lineage cells, showing further subclustering into VCT subsets (VCT_TP63, VCT_LDHA), VCT_Cycling, VCT_Fusing, and EVT and syncytiotrophoblast (SCT) clusters. B UMAP colored by sFGR_Larger and sFGR_Smaller samples, illustrating the distribution of trophoblast subsets across the two groups. C Feature plots depicting the expression of TP63 and LDHA, demonstrating distinct spatial segregation of structural (TP63-high) and metabolic (LDHA-high) VCT subpopulations. D Gene Ontology (GO) enrichment analysis of marker genes defining VCT_TP63 (blue) and VCT_LDHA (orange) subclusters, highlighting differences in cytoskeletal organization, signal transduction, and mitochondrial metabolic processes. E GO enrichment analysis of marker genes in the VCT_Cycling subpopulation. F GO enrichment analysis of marker genes in the VCT_Fusing subpopulation. G Venn diagrams showing the overlap of differentially expressed genes (DEGs) identified in the three paired samples for VCT_TP63 upregulated DEGs (left), VCT_TP63 downregulated DEGs (second), VCT_LDHA upregulated DEGs (third), and VCT_LDHA downregulated DEGs (right). H KEGG pathway enrichment analysis of DEGs in VCT_TP63 between sFGR_Smaller and sFGR_Larger samples, with top panel representing upregulated DEGs and bottom panel representing downregulated DEGs. I KEGG pathway enrichment analysis of DEGs in VCT_LDHA between sFGR_Smaller and sFGR_Larger samples, with top panel representing upregulated DEGs and bottom panel representing downregulated DEGs.

Article Snippet: After blocking with 5% bovine serum albumin, slides were incubated overnight at 4 °C with primary antibodies against TP63 (CST, #39692, 1:500), SEMA6D (abcam, ab198745, 1:100), LDHA (CST, #3582S, 1:200), S100A9 (CST, #73425, 1:100), and CDH1 (CST, #14472S, 1:200).

Techniques: Expressing, Marker, Transduction

Journal: Communications Biology

Article Title: Single-cell insights into trophoblast heterogeneity and adaptive dysfunction in selective fetal growth restriction

doi: 10.1038/s42003-026-09798-2

Figure Lengend Snippet: A UMAP visualization of VCT_TP63 and VCT_LDHA clusters further subdivided into ten transcriptionally distinct subclusters (five for each main cluster). Each subcluster is labeled (VCT_TP63_1–5 and VCT_LDHA_1–5) and colored separately. B Dot plot displaying selected marker gene expression for each VCT subcluster. Dot size represents the percentage of cells expressing the gene; color intensity reflects average scaled expression. C GO enrichment analysis of marker genes for each VCT_TP63 subcluster, highlighting subcluster-specific functional features such as chromatin organization, RNA splicing, and epithelial development. D GO enrichment analysis of marker genes for each VCT_LDHA subcluster, demonstrating enrichment of mitochondrial translation, oxidative phosphorylation, and stress response pathways in distinct subsets. E Diffusion pseudotime trajectory reconstruction for all VCT subclusters (Monocle 2). Cells are colored by pseudotime progression, suggesting a continuous differentiation continuum from VCT_TP63 subclusters toward VCT_LDHA and VCT_fusing states. F State assignment of individual cells along the inferred trajectory. Five discrete states are inferred, with VCT_TP63 subclusters predominantly occupying early states and VCT_fusing occupying the terminal state. G Trajectory overlaid with subcluster labels to illustrate branch allocation. Notably, VCT_TP63 subclusters distribute along early pseudotime, while VCT_LDHA subclusters align with later pseudotime and bifurcation toward fusing trophoblast. H Trajectory visualization for each subcluster individually, showing the spatial distribution of each subset along the differentiation manifold. I Trajectory visualization of individual samples (SC01, SC03, SC06) and their respective sFGR_Larger/sFGR_Smaller components to confirm consistency across biological replicates and paired twin samples.

Article Snippet: After blocking with 5% bovine serum albumin, slides were incubated overnight at 4 °C with primary antibodies against TP63 (CST, #39692, 1:500), SEMA6D (abcam, ab198745, 1:100), LDHA (CST, #3582S, 1:200), S100A9 (CST, #73425, 1:100), and CDH1 (CST, #14472S, 1:200).

Techniques: Labeling, Marker, Gene Expression, Expressing, Functional Assay, Phospho-proteomics, Diffusion-based Assay

Journal: Communications Biology

Article Title: Single-cell insights into trophoblast heterogeneity and adaptive dysfunction in selective fetal growth restriction

doi: 10.1038/s42003-026-09798-2

Figure Lengend Snippet: A Heatmap showing the relative activity of transcription factor (TF) regulons across the refined VCT_TP63 and VCT_LDHA subclusters. Regulon activity was inferred by SCENIC analysis, with key TFs including SOX6, TEAD1, TCF7L2, YY1, RELA, and HCFC1 demonstrating distinct subcluster-specific activation patterns. B Regulatory network reconstruction of representative TFs enriched in VCT_TP63 subclusters. Nodes denote TFs and predicted target genes, with edge color intensity reflecting regulatory confidence scores. UMAP feature plots depict the spatial expression distribution of representative TFs including SOX6, TEAD1, and TCF7L2 across the VCT subsets. C Regulatory network reconstruction of representative TFs enriched in VCT_LDHA subclusters. Notably, YY1, RELA, and HCFC1 regulons were prominent in VCT_LDHA clusters. UMAP feature plots demonstrate their specific enrichment patterns within the metabolic-stress-oriented VCT_LDHA subpopulations.

Article Snippet: After blocking with 5% bovine serum albumin, slides were incubated overnight at 4 °C with primary antibodies against TP63 (CST, #39692, 1:500), SEMA6D (abcam, ab198745, 1:100), LDHA (CST, #3582S, 1:200), S100A9 (CST, #73425, 1:100), and CDH1 (CST, #14472S, 1:200).

Techniques: Activity Assay, Activation Assay, Expressing

Journal: Communications Biology

Article Title: Single-cell insights into trophoblast heterogeneity and adaptive dysfunction in selective fetal growth restriction

doi: 10.1038/s42003-026-09798-2

Figure Lengend Snippet: A Network visualization of differential interaction strength between villous cytotrophoblast (VCT) subtypes (VCT_TP63, VCT_LDHA) and stromal (smooth muscle cells (SMC), fibroblasts, endothelial), myeloid (Hofbauer cells, monocytes, neutrophils), and lymphoid (T, NK) cell populations in sFGR_Smaller compared with sFGR_Larger placental samples. Edges represent ligand–receptor interactions; red indicates increased interaction strength and blue indicates decreased interaction strength in sFGR_Smaller. B – D Bubble plots of representative ligand–receptor pairs mediating the interactions between VCT_TP63 and stromal cell subtypes. B SMC-derived ligands interacting with VCT_TP63 receptors. C Fibroblast-derived ligands interacting with VCT_TP63 receptors. D Endothelial-derived ligands interacting with VCT_TP63 receptors. Dot size represents the statistical significance of each interaction (–log10 P value), and color scale indicates the mean expression level. Notable reductions in adhesion-related and Wnt/Notch signaling interactions were observed in sFGR_Smaller. E Bubble plot of representative ligand–receptor pairs mediating the interactions between immune cells (Hofbauer macrophages, monocytes, NK cells) and VCT_LDHA. sFGR_Smaller placentas demonstrated enhanced pro-inflammatory, including increased HLA-E–NKG2A/NKG2C and VEGFA–FLT1 signaling. SMC smooth muscle cell, NK natural killer cell, NRP1/2 neuropilin 1/2, FLT1 VEGF receptor 1.

Article Snippet: After blocking with 5% bovine serum albumin, slides were incubated overnight at 4 °C with primary antibodies against TP63 (CST, #39692, 1:500), SEMA6D (abcam, ab198745, 1:100), LDHA (CST, #3582S, 1:200), S100A9 (CST, #73425, 1:100), and CDH1 (CST, #14472S, 1:200).

Techniques: Derivative Assay, Expressing

Journal: Communications Biology

Article Title: Single-cell insights into trophoblast heterogeneity and adaptive dysfunction in selective fetal growth restriction

doi: 10.1038/s42003-026-09798-2

Figure Lengend Snippet: Representative multiplex immunofluorescence staining of placental villi from sFGR_Larger ( A ) and sFGR_Smaller ( B ) cotwins. TP63 and SEMA6D were used as principal markers of the VCT_TP63 subpopulation; LDHA and S100A9 as key markers of the VCT_LDHA subpopulation; CDH1 as a general VCT marker. Nuclei were counterstained with DAPI (blue). C Quantitative RT-PCR validation of representative transcription factors and subpopulation markers in paired placental samples ( n = 7 twin pairs; each dot represents one pregnancy). Data are presented as mean ± s.d. and were analyzed using two-tailed paired Student’s t tests. The results demonstrate downregulation of SOX6 and NR3C1 and upregulation of YY1, RELA and HCFC1 in sFGR_Smaller placentas. * P < 0.05.

Article Snippet: After blocking with 5% bovine serum albumin, slides were incubated overnight at 4 °C with primary antibodies against TP63 (CST, #39692, 1:500), SEMA6D (abcam, ab198745, 1:100), LDHA (CST, #3582S, 1:200), S100A9 (CST, #73425, 1:100), and CDH1 (CST, #14472S, 1:200).

Techniques: Multiplex Assay, Immunofluorescence, Staining, Marker, Quantitative RT-PCR, Biomarker Discovery, Two Tailed Test

Journal: Communications Biology

Article Title: Single-cell insights into trophoblast heterogeneity and adaptive dysfunction in selective fetal growth restriction

doi: 10.1038/s42003-026-09798-2

Figure Lengend Snippet: Schematic summary of three interconnected axes of placental dysfunction in sFGR: structural dysfunction (depletion of structurally supportive VCT_TP63 cells and loss of barrier integrity), metabolic disorder (expansion of VCT_LDHA metabolic-stress cells with upregulated oxidative phosphorylation, ROS metabolism and glycolysis), and immune imbalance (immune microenvironment remodeling and formation of a pro-inflammatory milieu). These processes reinforce each other, resulting in placental insufficiency and ultimately sFGR.

Article Snippet: After blocking with 5% bovine serum albumin, slides were incubated overnight at 4 °C with primary antibodies against TP63 (CST, #39692, 1:500), SEMA6D (abcam, ab198745, 1:100), LDHA (CST, #3582S, 1:200), S100A9 (CST, #73425, 1:100), and CDH1 (CST, #14472S, 1:200).

Techniques: Phospho-proteomics

Journal: bioRxiv

Article Title: FDXR Upregulation by p63/p73 is a Prognostic and Therapeutic Marker of HTLV-1-Associated Adult T Cell Leukemia/Lymphoma

doi: 10.64898/2026.02.25.707207

Figure Lengend Snippet: (A,B) RNA-Seq data retrieved from Protein Atlas were stratified by FDXR expression (≥75 nTPM = Mid-high_FDXR, <75 nTPM = Mid-low_FDXR). Differential transcription factor (TF) activity between groups was inferred using VIPER , based on regulatory networks constructed with DoRothEA and ARACNe. The bubble plot in (B) ranks TFs based on their differential activity in the two groups. The colour of the dots reflects relative TF activity, while the size of the dots represent -Log10 adjusted p values (FDR) calculated with the limma package. (C–F) Expression of TAp63 mRNA (C), p63α protein (D), TAp73 mRNA (E) and p73 protein (F) in HTLV-1 + , ATL, and uninfected cell lines and primary cells. Relative mRNA expression was quantified by qPCR; protein expression was assessed by western blot. In panels (C,E), each dot represents an independent qPCR assay (n = 3), and data are presented as mean ± SD. Relative mRNA levels were calculated by ΔΔCq using TBP expression as reference. Data were analyzed by non-parametric Wilcoxon rank-sum test. (G,H) Relative expression of TAp63 (G) and TAp73 (H) mRNA in primary CD4 T cells from PLHTLV stratified by disease condition and healthy controls. Relative mRNA expression was quantified by qPCR using the ΔΔCq method and TBP expression as reference. Each dot represents a donor and data are depicted as median ± IQR. Data were analyzed by non-parametric Kruskal–Wallis test followed by Dunn’s post hoc test with Benjamini–Hochberg correction for multiple comparisons. (I,N) Effect of TP63 and TP73 knockout on FDXR expression. The HTLV-1–infected MT-4 cell line (I-K) and the ATL-derived ATL-55T cell line (L-N) were stably transfected with Cas9 and subsequently transduced with lentiviruses expressing either a non-targeting (NT) sgRNA or sgRNAs targeting TP63 or TP73. Stable knockout cell lines were lysed and used to assess protein expression by Western blot. Panels I, L show p63 and FDXR expression in MT-4 and ATL-55T cells, respectively. Panels J, M show p73 and FDXR expression in MT-4 and ATL-55T cells, respectively. Wild-type and non-transduced Cas9-expressing cells served as additional controls. Panels K, N show relative FDXR protein levels normalized using actin as a loading control and the NT sgRNA condition as reference level. Barplots in K, N show mean ± SD for each condition. N = 2. **** p <0.0001; ** p <0.01; *p <0.05.

Article Snippet: For immunoprecipitation, 5–10 μg of chromatin was incubated with anti-p63α Rabbit mAb (Cell Signaling #13109), anti-ΔNp63 (Cell Signaling #67825S), anti-Histone H3 Rabbit mAb (Cell Signaling #4620), or rabbit IgG control (Cell Signaling #8726) overnight at 4 °C with rotation.

Techniques: RNA Sequencing, Expressing, Activity Assay, Construct, Western Blot, Knock-Out, Infection, Derivative Assay, Stable Transfection, Transfection, Transduction, Control