Journal: bioRxiv

Article Title: Extra-lineage tissue programs define the transcription states of human pancreatic cancer

doi: 10.64898/2026.04.29.721655

Figure Lengend Snippet: (a) Workflow of analysis of human pancreatic ductal adenocarcinoma samples. Transcriptional data supported by genetic data is deconvoluted using NMF into signatures. Tumour programs derived from these signatures are validated with scRNA-seq and biological meaning is derived through pathway enrichment and comparison with the human single cell atlas. (b) UMAP of malignant cells scored with the tumour programs. Circled sections of the UMAP are shown below and highlight differences in expression of the tumour programs. (c) Heatmap showing expression of tumour program gene sets genes across all 490 bulk tumours. Expression is scaled by z-score. Tumours are annotated above the heatmap by stage and classification.

Article Snippet: Standard droplet-based scRNA-seq (10x Genomics) lack sufficient coverage at the 5’ end of KRAS , where hotspot mutations reside.

Techniques: Derivative Assay, Comparison, Single Cell, Expressing

Journal: bioRxiv

Article Title: Extra-lineage tissue programs define the transcription states of human pancreatic cancer

doi: 10.64898/2026.04.29.721655

Figure Lengend Snippet: (a) Classification proportions of malignant cells from each sample across the scRNA-seq cohort, separated into diversity groups. Each bar represents a sample and is annotated with the pseudobulk classification and tumour type as primary (pink) or metastatic (green). An asterisk (*) highlights the one lung metastasis. Samples with fewer than 50 malignant cells were omitted, as well as the neuroendocrine tumour. (b) Scatterplot of Basal and Classical program proportions across the malignant cells of the samples of the scRNA-seq cohort, coloured and labelled by k-means diversity grouping. Each dot represents a sample with at least 50 malignant cells as shown in (a). (c) UMAP plots of representative samples from each subgroup, cells coloured by cell classification. (d) Classical-1, Classical-2, Basal-1 and Basal-2 cell proportion between early and late clones in samples with at least 2 clones (n=27). Samples are connected by a line, and lines are coloured by direction of change in proportion, where “similar” in grey indicates a change of less than 10% of total proportion. Asterisks (*) highlight the one lung metastasis.

Article Snippet: Standard droplet-based scRNA-seq (10x Genomics) lack sufficient coverage at the 5’ end of KRAS , where hotspot mutations reside.

Techniques: Clone Assay

Journal: bioRxiv

Article Title: Extra-lineage tissue programs define the transcription states of human pancreatic cancer

doi: 10.64898/2026.04.29.721655

Figure Lengend Snippet: (a) UMAP plot of all cells in the scRNA-seq cohort coloured by KRAS mutation status, where red indicates at least one mutation read found (mut) and blue indicates only wildtype reads (wt only). Cells with unknown KRAS status due to lack of sequencing coverage are shown in light grey. (b) Bar plot of total KRAS mutation (mut, red) or wildtype (wt, blue) read count by cell type across all KRAS PCR amplified samples (top). Proportion of mutant vs wildtype KRAS reads found in selected cell types (bottom). Only cell types with at least 250 KRAS mutant or wildtype reads are included. (c) Comparison of mutation found between matched bulk RNA-seq and single cell KRAS PCR amplified reads from patient 96460 (PCSI1054) in IGV. (d) UMAP plots of all cells in samples from patients G9903 (left) and 97189 (right) coloured by KRAS mutation status (top) and cell type (bottom).

Article Snippet: Standard droplet-based scRNA-seq (10x Genomics) lack sufficient coverage at the 5’ end of KRAS , where hotspot mutations reside.

Techniques: Mutagenesis, Sequencing, Amplification, Comparison, RNA Sequencing, Single Cell