Journal: bioRxiv

Article Title: CRlSPR/Cas9 screening revealed BlRC6-AS1 /BlRC6 mediates abiraterone resistance via NHEJ pathway-dependent A20 degradation in prostate cancer

doi: 10.1101/2025.10.01.679907

Figure Lengend Snippet: ( A ) Schematic of CRISPR-Cas9 screens: A lentiviral sgRNA library was transduced into PC3-Cas9 cells, which were then treated with DMSO or Abiraterone, respectively. After 28 days, sgRNAs were extracted for NGS. ( B ) Box plots displaying sgRNA distribution in the experimental groups from lncRNA CRISPR-Cas9 library: D0-DMSO (baseline), D28-DMSO (vehicle control), and D28-Abiraterone (treatment). ( C and D ) Volcano plots showing depleted (red; RRA Score ≤ 0.05, -log□FC ≥ 2) and enriched (blue; RRA Score ≤ 0.05, log□FC ≥ 2) genes. Screening analysis was performed with MaGeCK RRA. ( C ) Negative selection identified 523 abiraterone resistance-associated LncRNAs and 553 essential LncRNAs. ( D ) Positive selection revealed 717 LncRNAs associated with abiraterone sensitivity and 169 essential LncRNAs. ( E ) Venn diagram showed negatively selected genes from two comparisons: Abiraterone vs Control and Control vs D0. ( F ) MAGeCK analysis results displayed a ranking of genes based on their RRA scores. ( G ) Frequency distribution of log2 fold change for all sgRNAs (top) and log2 fold change of individual sgRNAs for representative candidates (bottom). Enriched and depleted sgRNA hits were indicated by red and blue vertical bars, respectively. ( H ) The RRA score distribution plot revealed the top 10 candidate LncRNAs associated with abiraterone resistance. ( I-N ) Cell viability assays in PC3 ( I-K ) and DU145 ( L-N ) cells treated with 0-70 μM abiraterone for 48h, following transduction with either control sgRNAs or sgRNAs targeting candidate lncRNAs: RP11-1079K10.3 ( I and L ), WWTR1-AS1 ( J and M ), and RP11-49K24.4 ( K and N ). Data are shown as the mean ± SD (n = 4 biological replicates). Data were analyzed by two-way analysis of variance (ANOVA) with Dunnett’s multiple comparisons test ( I-N ).

Article Snippet: PC3-Cas9 cells (4×10 ) were transduced with either the Splicing-targeting CRISPR-Cas9 library for human lncRNAs (Addgene, Cat# 119977) or the Human genome-wide lentiviral CRISPR gRNA library version 1 (Addgene, Cat# 67989) at a multiplicity of infection (MOI) of 0.3, ensuring single gRNA integration per cell.

Techniques: CRISPR, Control, Selection, Transduction

Journal: Oncology Letters

Article Title: Integrated analysis of transcriptome profiling predicts potential lncRNA and circRNA targets in human nasopharyngeal carcinoma

doi: 10.3892/ol.2020.11412

Figure Lengend Snippet: Differentially expressed circRNAs and their miRNA binding sites.

Article Snippet: First, the circRNA-miRNA interaction was predicted with Arraystar's proprietary miRNA target prediction software (version 1.0) using datasets retrieved from the TargetScan and miRanda databases, and the DE circRNAs within all the comparisons were annotated in detail using the circRNA-miRNA interaction information.

Techniques: Binding Assay

Journal: Oncology Letters

Article Title: Integrated analysis of transcriptome profiling predicts potential lncRNA and circRNA targets in human nasopharyngeal carcinoma

doi: 10.3892/ol.2020.11412

Figure Lengend Snippet: circRNA-miRNA-mRNA regulatory network in nasopharyngeal carcinoma. Green circle, miRNA; pink circle, circRNA; light-blue circle, mRNA. circRNA, circular RNA; miRNA, micro RNA.

Article Snippet: First, the circRNA-miRNA interaction was predicted with Arraystar's proprietary miRNA target prediction software (version 1.0) using datasets retrieved from the TargetScan and miRanda databases, and the DE circRNAs within all the comparisons were annotated in detail using the circRNA-miRNA interaction information.

Techniques:

Journal: Oncology Letters

Article Title: Integrated analysis of transcriptome profiling predicts potential lncRNA and circRNA targets in human nasopharyngeal carcinoma

doi: 10.3892/ol.2020.11412

Figure Lengend Snippet: circRNA-miRNA-mRNA regulatory modules in nasopharyngeal carcinoma. Green rectangle, miRNA; pink rectangle, circRNA; light-blue rectangle, mRNA. circRNA, circular RNA; miRNA, micro RNA.

Article Snippet: First, the circRNA-miRNA interaction was predicted with Arraystar's proprietary miRNA target prediction software (version 1.0) using datasets retrieved from the TargetScan and miRanda databases, and the DE circRNAs within all the comparisons were annotated in detail using the circRNA-miRNA interaction information.

Techniques:

Journal: bioRxiv

Article Title: Cross-species single-cell atlases chart progression, therapy-driven remodelling and immune evasion in pancreatic cancer

doi: 10.64898/2026.03.19.712924

Figure Lengend Snippet: a) Schematic overview of the experimental design. Mouse PDAC cell lines were clonally barcoded using a lentiviral library (1), expanded and orthotopically transplanted into syngeneic immunocompetent mice (2–3), followed by scRNA-seq profiling of resultant tumours (4). Expressed barcode tracing enabled unambiguous separation of malignant (TAG⁺) from host-derived non-malignant cells (right panel, UMAPs depicting barcoded (TAG + ) (top) and malignant (bottom) cells). b-e) UMAPs of the integrated Mouse PDAC Atlas coloured by dataset (b), sex (c), treatment type (d), and model (orthotopic syngeneic immunocompetent allografts vs. autochthonous GEMMs (e). f) Sample-wise cell-type composition across treatment types, datasets, and models. Autochthonous tumours were dominated by classical epithelial-like malignant states, whereas orthotopic allografts displayed greater heterogeneity with an enrichment of EMT, hypoxic, and mesenchymal programs. g ) Level 3 hierarchical annotation of the Mouse Atlas using the same multi-tiered scheme as the Human Atlas, resolving lymphoid, myeloid, stromal, endocrine, exocrine, endothelial, and malignant compartments. h-j) Substate resolution of major immune and stromal lineages: CD4⁺ T cells (h), CD8⁺ T cells (i), and macrophages (j), showing distinct regulatory, effector, angiogenic, and lipid-processing programs. k) Validation of double-positive (DP) CD4⁺CD8⁺ T cells at the transcriptomics level (transcription density plots, left panel) and at the protein level by flow cytometry (right panel). l) UMAP showing DP T cells coloured by species (left) and Pearson correlation of mouse DP T cell gene expression against the human DP T cell archetype (right).

Article Snippet: For clonal and state-fate analysis by single-cell RNA-seq, primary mouse PDAC cells were clonally tagged with expressed DNA barcodes using the LARRY Barcode Library (Addgene #140024; RRID: Addgene 140024) .

Techniques: Derivative Assay, Biomarker Discovery, Transcriptomics, Flow Cytometry, Gene Expression