Journal: Acta Neuropathologica Communications

Article Title: Metabolic and transcriptomic profiles of glioblastoma invasion revealed by comparisons between patients and corresponding orthotopic xenografts in mice

doi: 10.1186/s40478-021-01232-4

Figure Lengend Snippet: Baseline information of patients and PDOX

Article Snippet: Preprocessing of RNA sequencing (RNAseq) data was performed following the standard pipeline and recommendations from bcbio-nextgen (version 1.0.4, http://bcbio-nextgen.readthedocs.org/en/latest/ ).

Techniques:

Journal: Cell Reports Medicine

Article Title: Molecular taxonomy of pancreatic neuroendocrine tumors reveals BEND2 -fusions-driven transcriptional plasticity and therapeutic vulnerabilities

doi: 10.1016/j.xcrm.2026.102642

Figure Lengend Snippet: Association of BEND2 fusions with poor clinical outcomes (A) Diagram of sample composition for the pooled BEND2 cohort of pNET. (B) Kaplan-Meier curve of disease-specific survival rate regarding BEND2 rearrangement status. (C) Forest plot showing the hazard ratio (95% CI) in the univariate Cox regression and multivariate regression after adjusting for major clinicopathological features and the corresponding p values. The total number for the cohort, the number of cases per variable category, and the number of events (disease-specific deaths) for each level were also indicated.

Article Snippet: Pre-processed bulk RNA-seq data from pNET clinical samples and cell lines (this study) , Mendeley Data , https://data.mendeley.com/datasets/r9m66rjtxy/1.

Techniques:

Journal: Cell Reports Medicine

Article Title: Molecular taxonomy of pancreatic neuroendocrine tumors reveals BEND2 -fusions-driven transcriptional plasticity and therapeutic vulnerabilities

doi: 10.1016/j.xcrm.2026.102642

Figure Lengend Snippet: Inter-tumor heterogeneity at single-nuclei level (A) UMAP representation of 43,619 nuclei isolated from nine pNET samples with tumor purity annotated at the top left corner. (B) UMAP showing a separation between tumor cells and non-tumor cells. Tumor cells were grouped according to the five-subtype bulk classification, referred as pseudo-bulk sn-clusters. (C) Dot plot of canonical marker genes across all identified cell populations. Dot size indicates the proportion of cells expressing a gene, and color intensity reflects mean expression levels. (D) Heatmap of the Hallmark signaling pathways specific for each of the five pseudo-bulk sn-clusters based on GSVA enrichment scores. (E) Regulon specificity plot showing the top six regulons identified for each of the five pseudo-bulk sn-clusters. The x axis of the plot represents the genes within the regulon, while the y axis represents the specificity score. (F) Validation of bulk subtype-specific regulon on the bulk pNET cohort using GSVA based on a set of target genes within a regulon.

Article Snippet: Pre-processed bulk RNA-seq data from pNET clinical samples and cell lines (this study) , Mendeley Data , https://data.mendeley.com/datasets/r9m66rjtxy/1.

Techniques: Isolation, Marker, Expressing, Protein-Protein interactions, Biomarker Discovery

Journal: Cell Reports Medicine

Article Title: Molecular taxonomy of pancreatic neuroendocrine tumors reveals BEND2 -fusions-driven transcriptional plasticity and therapeutic vulnerabilities

doi: 10.1016/j.xcrm.2026.102642

Figure Lengend Snippet: Cell-cell communication network and in silico drug sensitivity prediction in pNET subtypes (A) Cell-cell communication network visualized in Cytoscape, depicting the number and strength of interactions between tumor and microenvironmental cell populations. Nodes represent cell types, and edges represent intercellular interactions, with edge width and color reflecting interaction strength and frequency. (B) Bubble plot of selected ligand-receptor pairs between tumor subtypes and non-tumor microenvironmental cell populations. (C) Correlation plots showing associations between gene expression and deconvoluted cell-type proportions in bulk pNET samples. (D) Kaplan-Meier survival curves showing different DSS rates between pNET patients with high and low expression of genes of interest, including NOTCH3 (left), CD74 (middle), and the geometric mean value of these two genes (right). Patients were categorized into different groups according to the optimal thresholding. (E) Mechanisms of action of the 10 compounds predicted by Connectivity Map (CMap) analysis to preferentially target the BEND2 fusion. (F) Predicted sensitivities to 12 HDAC inhibitors across pNET subtypes based on GDSC database analyses. Statistical comparisons were performed using the Kruskal-Wallis test. p < 0.1; ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001.

Article Snippet: Pre-processed bulk RNA-seq data from pNET clinical samples and cell lines (this study) , Mendeley Data , https://data.mendeley.com/datasets/r9m66rjtxy/1.

Techniques: In Silico, Gene Expression, Expressing

Journal: Cell Reports Medicine

Article Title: Molecular taxonomy of pancreatic neuroendocrine tumors reveals BEND2 -fusions-driven transcriptional plasticity and therapeutic vulnerabilities

doi: 10.1016/j.xcrm.2026.102642

Figure Lengend Snippet: BEND2 fusions induce transcriptional reprogramming and morphological plasticity in pNET tumor cells (A) Phase-contrast microscopy images of BON1 cells at 48 h post-induction showing morphological changes following overexpression of BEND2 -only, CHD7 - BEND2 , EWSR1 - BEND2 , or mCherry control. (B) Bar plot showing the number of differentially expressed genes at 12 and 48 h across all BON1 cell line models, including EWSR1 (E), BEND2 (B), CHD7 - BEND2 (CB), and EWSR1 - BEND2 (EB), compared to the mCherry (M) control. (C) Heatmap illustrating transcriptomic clustering of BON1 cell lines at 48 h (D) Venn diagram showing overlapping significantly upregulated transcription factors (TFs) in CHD7 - BEND2 and EWSR1 - BEND2 models compared to controls at 12 h (E) Bar plot of ASCL1 expression across BON1 cell line models at 12 and 48 h. Data are represented as mean ± SEM. (F) Heatmap showing transcriptional activation of neurodevelopmental, mesenchymal, and immune-related TFs in fusion-expressing BON1 cells at 48 h, accompanied by ASCL1 downregulation, activation of GAST-high subtype-specific regulons, and upregulation of immune checkpoint genes PDCD1 and CD274 . (G) Heatmap illustrating temporal transcriptomic shifts in BON1 fusion models using a 50-gene classifier (25 neuroendocrine and 25 non-neuroendocrine genes) derived from human SCLC lines. (H) GSEA results showing transcriptional reprogramming at 48 h in BEND2 fusion lines compared to 12 h (I) Bar plot showing GATA6 expression uniquely and robustly upregulated in BEND2 fusion lines at both 12 and 48 h. Data are represented as mean ± SEM. (J) Bar plot showing specific upregulation of POMC in BON1 cells expressing EWSR1 - BEND2 at 48 h. Data are represented as mean ± SEM. (K) Bar plot showing markedly higher POMC expression in the EWSR1 - BEND2 -positive tumor compared to the CHD7 - BEND2 -positive tumor in the clinical cohort.

Article Snippet: Pre-processed bulk RNA-seq data from pNET clinical samples and cell lines (this study) , Mendeley Data , https://data.mendeley.com/datasets/r9m66rjtxy/1.

Techniques: Microscopy, Over Expression, Control, Expressing, Activation Assay, Derivative Assay