Frontiers_1591615_raw data.

This dataset originates from a comprehensive study investigating the functional role of the RGC32 gene in diffuse large B-cell lymphoma (DLBCL), integrating histological, molecular biological, and in vitro/in vivo experimental data.Figure 1: Expression Profiling and Prognostic Significance of RGC32 in DLBCLData Content:1A: RGC32 immunohistochemical (IHC) staining images of 80 DLBCL and 32 reactive hyperplasia lymph node (RHL) tissues (scale bar = 5 μm).1B: Kaplan-Meier survival analysis data tables for progression-free survival (PFS) and overall survival (OS) (unit: months) from 74 patient records, with groups stratified by RGC32 expression threshold (low-expression group ≤7, high-expression group ≥8).1C: Original Western blot images and grayscale quantification values of RGC32 expression in DLBCL cell lines (OCI-LY1, OCI-LY10, etc.) versus peripheral blood mononuclear cells (PBMCs) (internal control: GAPDH).1D: RGC32 mRNA expression table quantified by RT-PCR (values: 2<sup>−ΔΔCt</sup>; n=3 independent experiments).1E: Poly(A) tail length electrophoretograms and quantitative data (nucleotide counts for RGC32 mRNA in PBMCs and DLBCL cell lines). Figure 2: RGC32 Promotes DLBCL Growth In Vitro and In VivoData Content:2A: RGC32 Western blot images of shRGC32-transduced versus control vector-treated cell lines.2B: Cell proliferation kinetics measured by CCK-8 assay (OD<sub>450nm</sub> values at 0/24/48/72/96 hours; n=3 technical replicates).2C–D: Xenograft tumor volume records (unit: mm³) monitored at days 0/7/14/21/28 (n=6 mice per group).2E: H&E-stained and Ki-67-immunolabeled tumor tissue images (scale bar=5 μm). Figure 3: Transcriptomic Signatures of shRGC32-Treated CellsData Content:3A–B: Gene Ontology (GO) enrichment tables for biological processes (BP) and molecular functions (MF), including the top 10 significantly enriched terms (gene counts, padj values).3C: Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis table (top 20 pathways, enrichment factors, p-values, gene lists) derived from RNA-Seq data (shRGC32 vs. shControl; 3 biological replicates; DESeq2 pipeline with padj < 0.05). Figure 4: RGC32 Knockdown Induces Cell Cycle ArrestData Content:4A: Flow cytometry-based cell cycle distribution data (percentages of cells in G0/G1, S, and G2/M phases; n=3).4B: Quantitative Western blot data for cell cycle regulators (Cyclin D1, CDK4, p27). Figure 5: RGC32 Knockdown Enhances DNA Damage and Immune InfiltrationData Content:5A–B: Original Western blot images and quantification for DNA damage pathway proteins (p-ATM, p-ATR, p-CHK1, p-H2AX) and immunomodulators (IRF1, PD-L1).5C–E:Flow cytometry data (.fcs files and summary statistics) for CD3<sup>+</sup>CD8<sup>+</sup> T-cell infiltration in mouse tumors (% gated populations).IHC images (scale bar=5 μm) and scoring metrics (n=58 human DLBCL specimens) for localization of CD8 and RGC32.